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Dynamic contrast-enhanced MRI for monitoring response to neoadjuvant chemotherapy inbreast cancer

Loo, C.E.

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Citation for published version (APA):Loo, C. E. (2016). Dynamic contrast-enhanced MRI for monitoring response to neoadjuvant chemotherapy inbreast cancer.

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Dynamic contrast-enhanced MRI

for monitoring responseto neoadjuvant chemotherapy

in breast cancerClaudette Loo

Dynam

ic contrast-enhanced MRI for m

onitoring response to neoadjuvant chemotherapy in breast cancer - Claudette Loo

Dynamic contrast-enhanced

MRI

for monitoring response

to neoadjuvant chemotherapy

in breast cancer

Claudette Loo

The work in this thesis was performed at the Netherlands Cancer Institute in Amsterdam, and was

partly funded by the Center for Translational Molecular Medicine (CTMM), grant 03O-104

The author gratefully acknowledges the financial support provided by: Teleconsult Europe

Het Nederlands Kanker Instituut - Antoni van Leeuwenhoek Ziekenhuis ISBN-13: 978-90-75575-45-3 ©2016 Claudette Loo, Amsterdam, the Netherlands Art work: Maria Roosen, Bunch of Breasts, 2010, glass & copper, 175 x 500 x 150 cm, Ajeto Glassworks, Lindava, Czech Republic, collection Museum Arnhem, Netherlands. Photography: Marc Pluim Cover design & Lay out: Belmondo Books Printed by: Belmondo Books

Dynamic contrast-enhanced MRI for monitoring response to neoadjuvant chemotherapy in breast cancer

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor

aan de Universiteit van Amsterdam

op gezag van de Rector Magnificus

prof. dr. ir. K.I.J. Maex

ten overstaan van een door het College voor Promoties ingestelde commissie,

in het openbaar te verdedigen in de Aula der Universiteit

op woensdag 28 september 2016, te 11:00 uur

door Claudette Elisabeth Loo

geboren te Amsterdam

Promotiecommissie:

Promotores: Prof. dr. S. Rodenhuis Universiteit van Amsterdam

Prof. dr. R.G.H. Beets-Tan Universiteit Maastricht

Copromotor: Dr. K.G.A. Gilhuijs Universiteit Utrecht

Overige leden: Prof. dr. M.J. van de Vijver Universiteit van Amsterdam

Dr. H.M. Zonderland Universiteit van Amsterdam

Prof. dr. E.J.T. Rutgers Universiteit van Amsterdam

Prof. dr. S.C. Linn Universiteit Utrecht

Prof. dr. R.M. Pijnappel Universiteit Utrecht

Faculteit der Geneeskunde

Voor Tiny

Contents Abbreviations .......................................................................................................................7

CHAPTER 1. ..........................................................................................................................9

Introduction and thesis outline

PART 1 ................................................................................................................................ 19

During Neoadjuvant Chemotherapy

CHAPTER 2. ........................................................................................................................ 21

Dynamic contrast-enhanced MRI for prediction of breast cancer response to

neoadjuvant chemotherapy: Initial Results

CHAPTER 3. ........................................................................................................................ 43

Magnetic resonance imaging response monitoring of breast cancer during

neoadjuvant chemotherapy: Relevance of breast cancer subtype

CHAPTER 4. ........................................................................................................................ 63

Neoadjuvant chemotherapy adaption and serial MRI response monitoring in ER-

positive HER2-negative breast cancer

PART 2 ................................................................................................................................ 83

After Neoadjuvant Chemotherapy

CHAPTER 5. ........................................................................................................................ 85

MRI-model to guide the surgical treatment in breast cancer patients after neoadjuvant

chemotherapy

CHAPTER 6. ...................................................................................................................... 103

Survival is associated with complete response on MRI after neoadjuvant

chemotherapy in ER-positive HER2-negative breast cancer

CHAPTER 7. ...................................................................................................................... 129

Summary, general discussion and conclusions

CHAPTER 8. ...................................................................................................................... 141

Samenvatting

LIST OF PUBLICATIONS .................................................................................................. 148

CONTRIBUTION AUTHORS ............................................................................................. 153

PHD PORTFOLIO .............................................................................................................. 154

DANKWOORD ................................................................................................................... 156

Curriculum Vitae ............................................................................................................... 159

7

Abbreviations

BCS: breast conserving surgery

CE: contrast-enhanced

CR: complete remission

ER: estrogen receptor

HER2: human epidermal growth factor receptor 2

HR: hazard ratio

IHC: immunohistochemistry

MRI: magnetic resonance imaging

NAC: neoadjuvant chemotherapy

OS: overall survival

pCR: pathological complete remission

PR: progesterone receptor

RFS: recurrence-free survival

9

CHAPTER 1

Introduction and thesis outline

11

Introduction

Breast cancer is the most common type of cancer in women in the Netherlands. The incidence of

breast cancer is still increasing. In 2014 more than 14,500 women were diagnosed with invasive

breast cancer, while in 2005 over 12,000 breast cancers were detected [1].

A hopeful trend is that the 5-year survival of breast cancer is increasing. For breast cancers

diagnosed during 2008-2012, the 5-year survival is 87% compared to 77% in the period 1989-1993.

The improvement in survival of breast cancer is likely due to effective adjuvant treatment such as

systemic therapy and the introduction of the national breast cancer screening program in 1989 [2-

5]. The survival depends on the stage at which the breast cancer is detected.

The TNM (tumor, node, and metastasis) staging system developed by the American Joint Committee

on Cancer (AJCC) is the most commonly used system to describe the stages of breast cancer [6]. The

stage is a measure of the extent of disease, which is used to guide treatment and determine

prognosis.

For example, stage-I breast cancer has a 3-year survival rate of nearly 100%, while more locally

advanced disease such as stage-IIB and stage-III have 3-year survival rates of ~94% and ~75%,

respectively (fig. 1) [1].

Figure 1. Survival by breast cancer stage in the Netherlands. www.cijfersoverkanker.nl

12

In addition, breast cancer is a heterogeneous disease with different subtypes. Analysis of gene

expression arrays has resulted in the identification of several fundamentally different subtypes of

breast cancer [7]. These subtypes have different biological behavior, response to therapy and

prognosis. A simplified clinicopathological model based on immunohistochemistry represents a

convenient approximation of subtypes [8]. Three major breast cancer subtypes are easily

distinguished by immunohistochemistry: triple-negative (estrogen receptor (ER), progesterone

receptor (PR) and human epidermal growth factor receptor 2 (HER2) -negative), HER2-positive

(HER2-positive, ER and PR may be positive or negative) and ER-positive/HER2negative (ER-positive,

HER2 negative, PR may be positive or negative) [9,10]. These immunohistochemical subtypes

roughly correspond to the molecular subtypes Basal-like, HER2-enriched and Luminal, respectively

[11]. For example, triple negative/basal-like tumors are often aggressive and have a poorer

prognosis (at least within the first five years after diagnosis) compared to the ER-positive subtypes

(luminal A and luminal B tumors) [12]. Subtyping of breast cancer in subgroups may improve

understanding of tumor response and outcome and may result in optimized strategies for

personalized treatment [8].

Personalized breast cancer treatment

In general, the treatment plan is tailored to the biology of the tumor, TNM stage, overall health, and

age of the patient. Breast cancer treatment is a multimodality treatment consisting of local therapy

(surgery and/or radiation therapy) and/or adjuvant systemic treatment (chemotherapy and/or

hormone therapy and/or targeted therapy). The adjuvant systemic therapy aims to eradicate distant

micrometastasic disease that may be present at the time of diagnosis. Neoadjuvant chemotherapy

refers to systemic treatment given prior to surgery. Randomized trials have shown neoadjuvant

chemotherapy to be equally effective in terms of disease-free and overall-survival compared to

postoperative chemotherapy [13-15]. It is increasingly used in patients with (larger) breast cancers in

order to facilitate breast-conserving surgery instead of mastectomy, and to avoid axillary node

dissection in case of N+ disease. On average, in 20% of the patients treated with neoadjuvant

chemotherapy, down staging occurs allowing breast-conserving surgery with better cosmetic

outcome [16]. Another major advantage of neoadjuvant chemotherapy is the opportunity to

evaluate response of the breast tumor to treatment with the tumor in situ. Patients with a

confirmed pathological complete remission after neoadjuvant chemotherapy have a disease-free

and overall-survival benefit [17,18]. Additionally, more effective systemic therapies have become

available. Therefore, the main aim of neoadjuvant chemotherapy has gone beyond down-staging

only, into a more comprehensive purpose of achieving a pathological complete response.

13

The CTMM (Center for Translational Molecular Medicine) Breast Care study

Since 2000, patients with primary invasive breast cancer >3cm and/or at least one proven axillary

lymph node metastasis are treated with neoadjuvant chemotherapy in our cancer institute. The

patients received neoadjuvant chemotherapy in a single-institution randomized phase-II trial [19].

Response of the primary tumor was monitored with breast MRI before, during (halfway), and after

neoadjuvant chemotherapy.

In September 2008, the CTMM (Center for Translational Molecular Medicine) Breast Care study was

started. The program serves to develop biomarkers for response prediction and to refine techniques

for response monitoring. In this study, breast cancer patients received neoadjuvant chemotherapy

according to one of several prospective trial protocols. In this single-institutional response

monitoring study, response was monitored by MRI (and PET/CT). Patients underwent MRI

examinations, before, during (after 3 courses/6 weeks or, in case of HER2-positivity, 8 weeks) and

after neoadjuvant chemotherapy. Over the years, the number of breast cancer patients treated with

neoadjuvant chemotherapy has increased (figure 2).

Figure 2. MRI response evaluation in breast cancer patients treated with neo-adjuvant

chemotherapy at the Netherlands Cancer Institute. Period 2000 – 2014.

0

100

200

300

400

500

600

700

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Nu

mb

er

Year

MRI response evaluation in breast cancer patients treated with neoadjuvant

chemotherapy

Patients

MRI

14

Response Evaluation

Neoadjuvant chemotherapy provides an attractive setting for translational research. Assessment of

response has traditionally been based on physical examination, mammography and ultrasound of

the breast. However, these techniques were found to be less effective [20-22]. Dynamic contrast-

enhanced magnetic resonance imaging (MRI) has superior accuracy over conventional techniques

because, in addition to morphologic properties it provides visualization of functional properties of

the tumor such as those associated with angiogenesis [23,24]. Dynamic contrast-enhanced MRI is

the current standard practice for response evaluation of breast cancer treatment. Response can be

assessed by MRI at baseline, during and after neoadjuvant chemotherapy. Early response evaluation

during chemotherapy may allow adaption of the therapy according to the response of the primary

tumor. In patients with non-responding tumors, the chemotherapy regimen may be switched to a

(presumably) non-cross resistant regimen.

After completing neoadjuvant chemotherapy, MRI can be used to assess the final response. An

accurate assessment of residual disease after completion of neoadjuvant chemotherapy could be

relevant in the decision whether or not to undertake breast-conserving surgery. Many studies have

investigated the diagnostic role of MRI in evaluating residual disease after neoadjuvant

chemotherapy [25-27]. Compared to other conventional modalities, MRI has superior accuracy.

However, MRI can both overestimate and underestimate residual tumor [28,29]. The aim is to select

those patients who can be safely treated with breast-conserving surgery after neoadjuvant

chemotherapy. A second potential role of MRI after neoadjuvant chemotherapy is predicting long-

term outcome., In this respect, MRI could be of additional value in subgroups of breast cancer

patients, in whom pathological response after neoadjuvant chemotherapy is less predictive of

outcome [30].

The clinical value of MRI for monitoring the efficacy of neoadjuvant chemotherapy in breast cancer

has not been fully assessed, and is addressed in this thesis.

15

Outline of this thesis

The general aim of this thesis is to investigate the role of dynamic contrast-enhanced MRI in

monitoring response of breast cancer during neoadjuvant chemotherapy. The role of MRI with

respect to achieving personalized breast cancer treatment by improving response monitoring is

examined.

The predictive role of MRI during (halfway) neoadjuvant chemotherapy for early breast cancer

response is explored in part 1.

The initial MRI results with regard to predicting pathology outcome are described in chapter 2. A

practical MRI test, also known as MRI-criteria, is developed to identify which tumors will not achieve

a complete response.

The relevance of breast cancer subtype on MRI markers of therapy response is evaluated in chapter

3. For this purpose, breast cancer is divided into three subtypes: triple negative, HER2-positive and

ER-positive (HER2-negative).

ER-positive breast cancer patients in whom neoadjuvant chemotherapy was adapted according to

the achieved response at MRI halfway neoadjuvant chemotherapy are analysed in chapter 4.

The role of MRI after neoadjuvant chemotherapy to assess final breast cancer response and

outcome is explored in part 2.

Chapter 5 describes the potential of MRI to guide selection of surgery after neoadjuvant

chemotherapy. MRI features that improve the patient selection for breast conserving surgery were

explored.

In chapter 6, it is investigated whether MRI is able to identify ER-positive breast cancer patients who

have excellent or poor prognosis.

The thesis ends with a summary and general discussion in English (chapter 7) and summary in Dutch

(chapter 8).

16

References

1. http://www.cijfersoverkanker.nl (November 11, 2015). 2. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials (2005). Lancet 365 (9472):1687-1717. doi:10.1016/s0140-6736(05)66544-0 3. Bonadonna G, Moliterni A, Zambetti M et al. (2005) 30 years' follow up of randomised studies of adjuvant CMF in operable breast cancer: cohort study. BMJ (Clinical research ed) 330 (7485):217. doi:10.1136/bmj.38314.622095.8F 4. Berry DA, Cronin KA, Plevritis SK et al. (2005) Effect of screening and adjuvant therapy on mortality from breast cancer. The New England journal of medicine 353 (17):1784-1792. doi:10.1056/NEJMoa050518 5. Jones AL (2005) Reduction in mortality from breast cancer. BMJ (Clinical research ed) 330 (7485):205-206. doi:10.1136/bmj.330.7485.205 6. Edge SB BD, Compton CC (2010) AJCC (American Joint Committee on Cancer). Cancer staging manual. 7th edn. Springer-Verlag, New York 7. Perou CM, Sorlie T, Eisen MB et al. (2000) Molecular portraits of human breast tumours. Nature 406 (6797):747-752 8. Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ (2011) Strategies for subtypes--dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol 22 (8):1736-1747. doi:10.1093/annonc/mdr304 9. Desmedt C, Haibe-Kains B, Wirapati P et al. (2008) Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 14 (16):5158-5165 10. Sanchez-Munoz A, Garcia-Tapiador AM, Martinez-Ortega E et al. (2008) Tumour molecular subtyping according to hormone receptors and HER2 status defines different pathological complete response to neoadjuvant chemotherapy in patients with locally advanced breast cancer. Clin Transl Oncol 10 (10):646-653 11. de Ronde JJ, Hannemann J, Halfwerk H et al. (2010) Concordance of clinical and molecular breast cancer subtyping in the context of preoperative chemotherapy response. Breast Cancer Res Treat 119 (1):119-126 12. Voduc KD, Cheang MC, Tyldesley S, Gelmon K, Nielsen TO, Kennecke H (2010) Breast cancer subtypes and the risk of local and regional relapse. J Clin Oncol 28 (10):1684-1691. doi:10.1200/jco.2009.24.9284 13. Rastogi P, Anderson SJ, Bear HD et al. (2008) Preoperative chemotherapy: updates of National Surgical Adjuvant Breast and Bowel Project Protocols B-18 and B-27. J Clin Oncol 26 (5):778-785 14. Wolmark N, Wang J, Mamounas E, Bryant J, Fisher B (2001) Preoperative chemotherapy in patients with operable breast cancer: nine-year results from National Surgical Adjuvant Breast and Bowel Project B-18. J Natl Cancer Inst Monogr (30):96-102 15. Fisher ER, Wang J, Bryant J, Fisher B, Mamounas E, Wolmark N (2002) Pathobiology of preoperative chemotherapy: findings from the National Surgical Adjuvant Breast and Bowel (NSABP) protocol B-18. Cancer 95 (4):681-695 16. Mieog JS, van der Hage JA, van de Velde CJ (2007) Neoadjuvant chemotherapy for operable breast cancer. The British journal of surgery 94 (10):1189-1200. doi:10.1002/bjs.5894 17. Chollet P, Amat S, Cure H et al. (2002) Prognostic significance of a complete pathological response after induction chemotherapy in operable breast cancer. Br J Cancer 86 (7):1041-1046 18. Sataloff DM, Mason BA, Prestipino AJ, Seinige UL, Lieber CP, Baloch Z (1995) Pathologic response to induction chemotherapy in locally advanced carcinoma of the breast: a determinant of outcome. Journal of the American College of Surgeons 180 (3):297-306 19. Hannemann J, Oosterkamp HM, Bosch CA et al. (2005) Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 23 (15):3331-3342

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20. Vinnicombe SJ, MacVicar AD, Guy RL et al. (1996) Primary breast cancer: mammographic changes after neoadjuvant chemotherapy, with pathologic correlation. Radiology 198 (2):333-340 21. Fiorentino C, Berruti A, Bottini A et al. (2001) Accuracy of mammography and echography versus clinical palpation in the assessment of response to primary chemotherapy in breast cancer patients with operable disease. Breast Cancer Res Treat 69 (2):143-151 22. Marinovich ML, Macaskill P, Irwig L et al. (2015) Agreement between MRI and pathologic breast tumor size after neoadjuvant chemotherapy, and comparison with alternative tests: individual patient data meta-analysis. BMC cancer 15:662. doi:10.1186/s12885-015-1664-4 23. Esserman L, Kaplan E, Partridge S et al. (2001) MRI phenotype is associated with response to doxorubicin and cyclophosphamide neoadjuvant chemotherapy in stage III breast cancer. Ann Surg Oncol 8 (6):549-559 24. Balu-Maestro C, Chapellier C, Bleuse A, Chanalet I, Chauvel C, Largillier R (2002) Imaging in evaluation of response to neoadjuvant breast cancer treatment benefits of MRI. Breast Cancer Res Treat 72 (2):145-152 25. Marinovich ML, Macaskill P, Irwig L et al. (2013) Meta-analysis of agreement between MRI and pathologic breast tumour size after neoadjuvant chemotherapy. Br J Cancer 109 (6):1528-1536. doi:10.1038/bjc.2013.473 26. Hayashi Y, Takei H, Nozu S et al. (2013) Analysis of complete response by MRI following neoadjuvant chemotherapy predicts pathological tumor responses differently for molecular subtypes of breast cancer. Oncology letters 5 (1):83-89. doi:10.3892/ol.2012.1004 27. De Los Santos JF, Cantor A, Amos KD et al. (2013) Magnetic resonance imaging as a predictor of pathologic response in patients treated with neoadjuvant systemic treatment for operable breast cancer. Translational Breast Cancer Research Consortium trial 017. Cancer 119 (10):1776-1783. doi:10.1002/cncr.27995 28. Partridge SC, Gibbs JE, Lu Y, Esserman LJ, Sudilovsky D, Hylton NM (2002) Accuracy of MR imaging for revealing residual breast cancer in patients who have undergone neoadjuvant chemotherapy. AJR Am J Roentgenol 179 (5):1193-1199 29. Rieber A, Brambs HJ, Gabelmann A, Heilmann V, Kreienberg R, Kuhn T (2002) Breast MRI for monitoring response of primary breast cancer to neo-adjuvant chemotherapy. Eur Radiol 12 (7):1711-1719 30. von Minckwitz G, Untch M, Blohmer JU et al. (2012) Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol 30 (15):1796-1804. doi:10.1200/jco.2011.38.8595

19

PART 1

During Neoadjuvant

Chemotherapy

21

CHAPTER 2

Dynamic contrast-enhanced MRI for prediction of breast

cancer response to neoadjuvant chemotherapy: Initial

Results

Claudette E. Loo1, H. Jelle Teertstra1, Sjoerd Rodenhuis2, Marc J. van de Vijver3,

Juliane Hannemann3, Sarah H. Muller1, Marie-Jeanne Vrancken Peeters4,

Kenneth G. A. Gilhuijs1

Netherlands Cancer Institute, Amsterdam, The Netherlands:

1Department of Radiology

2Department of Medical Oncology

3Department of Pathology

4Department of Surgery

AJR Am J Roentgenol. 2008;191:1331-1338.

23

Abstract

Aim:

The aim of this study was to establish changes in contrast-enhanced MRI of breast cancer during

neoadjuvant chemotherapy that are indicative of pathology outcome.

Methods:

In 54 patients with breast cancer, dynamic contrast- enhanced MRI was performed before

chemotherapy and after two chemotherapy cycles. Imaging was correlated with final

histopathology. Multivariate analysis with cross-validation was performed on MRI features

describing kinetics and morphology of contrast uptake in the early and late phases of

enhancement. Receiver operating characteristic (ROC) analysis was used to develop a guideline

that switches patients at high risk for incomplete remission to a different chemotherapy regimen

while maintaining first-line therapy in 95% of patients who are not at risk (i.e., high specificity).

Results:

Change in largest diameter of late enhancement during chemotherapy was the single most

predictive MRI characteristic for tumor response in multivariate analysis (Az [area under the ROC

curve] = 0.73, p < 0.00001). Insufficient (< 25%) decrease in largest diameter of late enhancement

during chemotherapy was most indicative of residual tumor at final pathology. Using this criterion,

the fraction of unfavorable responders indicated by MRI was 41% (22/54). Approximately half (44%,

14/32) of the patients who showed favorable response at MRI achieved complete remission at

pathology. Conversely, 95% (21/22) of patients who showed unfavorable response at MRI had

residual tumor at pathology.

Conclusion:

Reduction of less than 25% in largest diameter of late enhancement during neoadjuvant

chemotherapy shows the potential to predict residual tumor after therapy with high specificity.

Keywords:

Breast carcinoma, chemotherapy response, MRI

24

Introduction

Primary systemic treatment, also called neoadjuvant chemotherapy, is increasingly gaining

acceptance as an alternative for postoperative adjuvant chemotherapy in breast cancer.

Neoadjuvant chemotherapy has been shown to be equally effective as postoperative chemotherapy

in terms of disease-free and overall survival [1-3].

A potential advantage of neoadjuvant chemotherapy is reduction of the size of the primary tumor,

increasing the probability that breast-conserving surgery can be performed [4]. Achieving a

pathologically confirmed complete remission or minimal disease at pathology [5] is consistently

associated with a favorable disease-free and overall survival [1,3,6]. It is reasonable to view complete

or near-complete remission at pathology as a surrogate marker of extreme chemotherapy

responsiveness and as an appropriate short- term goal of treatment. Unfortunately, complete

remission is achieved in only a minority of patients. Attempts to increase the rate of complete

remission include the administration of multiple drugs or higher doses of drugs, but also tailoring of

chemotherapy to the specific sensitivity of the individual tumor. This strategy allows an individual

patient to cross over to a different chemotherapy regimen if there is insufficient response and

complete remission is unlikely to occur. On the other hand, if major responsiveness is observed,

complete remission may ensue from continuation of the started chemotherapy regimen.

In vitro techniques continue to be unreliable in predicting response to chemotherapy [7].

Preoperative chemotherapy provides a unique opportunity to monitor response of the tumor and to

tailor the treatment to each individual patient. Monitoring of response has traditionally been based

on physical examination, mammography, and sonography of the breast. However, these techniques

were found to result in unsatisfactory accuracy [8,9].

Dynamic contrast-enhanced MRI allows visualization of functional properties of the tumor such as

those associated with angiogenesis [10] in addition to morphologic properties such as tumor size.

Several studies have found that MRI is the most accurate technique for evaluating the extent of

residual disease after systemic treatment [11-15]. MRI may even allow assessment of the

pathophysiologic response to chemotherapy, which occurs before volume changes [16,17].

Moreover, it has been suggested that application of MRI may improve the complete remission rate

[17-19]. However, the clinical value of dynamic MRI for predicting the efficacy of neoadjuvant

chemotherapy during treatment has not been fully assessed. Quantitative guidelines to assess

response to therapy based on MRI are currently lacking.

The purpose of our study was twofold. The first aim was to identify MRI features during neoadjuvant

chemotherapy that predict which tumors will achieve a complete or near-complete remission at

pathology and which will not. The second aim was to establish a practical MRI test to identify which

25

tumors will not achieve complete or near-complete remission with the given chemotherapy regimen

and may therefore benefit from a switch to an alternative regimen.

Materials and Methods

Selection of Patients

Patients with pathologically proven invasive breast cancer > 3 cm or at least one tumor-positive

axillary lymph node who were scheduled to receive neoadjuvant chemotherapy were eligible for this

retrospective study.

Between September 2000 and September 2004, 54 patients were included to identify MRI features

predictive of incomplete remission at final pathology in response to neoadjuvant chemotherapy. On

the basis of these features, we formulated an MRI response prediction test. The patients received

neoadjuvant chemotherapy in a single-institution randomized phase II trial at The Netherlands

Cancer Institute [7]. The institutional review board approved the study protocol, and written

informed consent was obtained from all patients.

In this trial, patients were randomized to receive doxorubicin 60 mg/m2 and cyclophosphamide 600

mg/m2 or doxorubicin 50 mg/ m2 and docetaxel 75 mg/m2. Chemotherapy was administered every

3 weeks in a total of six cycles.

Patients who declined randomization for the chemotherapy regimen received the standard

doxorubicin–cyclophosphamide chemotherapy and were also included in the MRI study. MRI was

performed before the first course of chemotherapy and before the third course (in the fifth or sixth

week of treatment).

Surgery

After the last course of chemotherapy, all selected patients underwent mastectomy or breast-

conserving therapy according to the standard protocols at our institute.

MRI Technique

MRI was performed on a 1.5-T Magnetom Vision scanner (Siemens Medical Solutions) with a

dedicated bilateral phased-array breast coil. Images were acquired with the patient in the prone

position and with both breasts imaged simultaneously. A comprehensive dynamic protocol consisted

of fast dynamic imaging in the first 45 seconds followed by slow dynamic imaging in five consecutive

series at 90-second intervals.

The protocol started with an unenhanced coronal 3D T1-weighted low-angle shot sequence.

Subsequently, 30 fast dynamic series were initiated; after the third series, a bolus of gadoteridol (Pro-

26

hance, Bracco-Byk Gulden; 14 mL, 0.1 mmol/kg) was administered IV at 2–4 mL/s by a power injector

(Spectris, Medrad).

The fast dynamic series (low resolution) were transverse 2D gradient-echo series (low-angle shot)

with seven slices of 8 mm (distance factor, 0.5) and a pixel size of 6.67 × 5.0 mm (acquisition time,

1,160 milliseconds; TR/TE, 29.19/1.4; flip angle, 30°; 1 acquisition; field of view, 320 mm). The slow

dynamic series (high resolution) consisted of a coronal low-angle shot 3D acquisition equivalent to

the unenhanced coronal 3D series, with a voxel size of 1.21 × 1.21 × 1.69mm and the following

parameters: acquisition; 8.1/4.0; flip angle 20°; and field of view, 310 mm. Acquisition time was 7.5

minutes for the entire dynamic series.

Radiologic assessment and clinical reading

Interpretation of breast MR images was done using a viewing station that permitted simultaneous

viewing of two series reformatted and linked in three orthogonal directions[20] [20]. Dynamic curves

of contrast enhancement in the first 45 seconds were also available. The viewing station displays all

image series (unenhanced and contrast-enhanced), subtraction images at 90-second intervals and

maximum intensity projections (MIPs) of both breasts (Fig. 1).

Using these tools, two dedicated radiologists experienced in evaluating MRI of the breast, and

working in consensus, interpreted the cases. The assessment of all features took approximately 15

minutes per scan. The radiologists were unaware of pathology outcome. Temporal and morphologic

characteristics of contrast uptake were scored in four groups (Table 1): bolus enhancement, initial

enhancement, late enhancement, and overall judgment.

The characteristics in the first group (Table 1, Bolus enhancement) all involve temporal features of

contrast uptake in the first 45 seconds after injection of the contrast agent (fast dynamic, low-

resolution series). The time between contrast enhancement in the aorta and in the tumor was

determined in regions of interest (ROIs) manually selected in the tumor and in the aorta. Relative

increase in enhancement of the tumor 3 seconds after the start of enhancement was calculated by

[(SI3 – SIstart) / SIstart] × 100%, where SIstart denotes the signal intensity at the first sign of enhancement

(abrupt increase of signal intensity of the tumor on the curve), and SI3, the intensity after 3 seconds.

Comparable equations were used for the time points at 12 and 17 seconds. The characteristics in the

second group (Table 1, Initial enhancement) were assessed in the series 90 seconds after contrast

injection (slow dynamic, high resolution) minus the unenhanced series. Change in extent of the

enhancing tumor was evaluated in both quantitative and qualitative terms. In quantitative terms, the

largest diameter of the tumor was assessed and measured in three reformatted planes (sagittal,

axial, and coronal), and the percentage of difference in the largest diameters between scans 1 and 2

27

was denoted (Table 1, Initial enhancement, footnote c). In cases of rim enhancement, the necrotic

core was included in measurement of the largest diameter (Figs. 1A–1C).

Fig. 1—Assessment of initial and late enhancement before initiating chemotherapy in 49-year-old

woman. A–F, Simultaneous viewing of subtracted images for initial enhancement (A–C) and late

enhancement (D–F) in sagittal (A, D), axial (B, E), and coronal (C, F) planes. Shown are measurements

of largest tumor diameter of late enhancement in three planes containing tumor with necrotic core.

A B C

D E F

28

In cases of multinodular or diffuse tumor growth, measurement of the complete enhancing area,

including intermediate (non- enhancing) tissue occupied by tumor, was assessed. In qualitative

terms, the differences in extent of the enhancing tumor between scan 2 and scan 1 were assessed in

four categories: progression, no change, decrease < 50%, or decrease ≥ 50%. Morphology of

enhancement was scored in three categories: mass, multinodular, and diffuse. In addition to the

patterns at scan 1 and scan 2, the change in pattern between scans 1 and 2 was denoted in three

categories: shrinking mass, diffuse reduction, and reduction to small residual foci in the original

tumor. Relative enhancement was given by [(SI90 – SI0) / SI0] × 100%, where SI0 denotes the signal

intensity at time point 0 (before contrast administration) and SI90, the time point after 90 seconds.

Each signal intensity was measured in an ROI that covered the most enhancing part of the tumor.

The characteristics in the third group (Table 1, Late enhancement) were assessed in the series 450

seconds after contrast injection minus the 90-second series. Washout was defined as an area of

decreased signal intensity at 450 seconds relative to 90 seconds, represented as an area of dark—i.e.,

black—signal intensity at subtracted images. Plateau was defined as an area of unchanged signal

intensity at 450 seconds relative to 90 seconds, represented as an area of dark—i.e., gray—signal

intensity on subtracted images. The largest diameter of the total area occupied by washout or

plateau kinetics in the tumor, including intermediate non-enhancing tissue (e.g., necrotic core), was

measured and defined as LDlate (Figs. 1D–1F), where LD is largest diameter. Differences in the extent

of late enhancement in the tumor between scan 1 and scan 2 were described in quantitative (Table

1, Late enhancement, footnote g) and in qualitative terms comparable to those described in the

preceding text for initial enhancement. Relative late enhancement was given by [(SI450 – SI90) / SI90] ×

100%, where SI450 denotes the signal intensity at 450 seconds. Measurement of signal intensity was

done in the part of the tumor that showed the strongest washout. These parts were examined by

interactively moving the cursor in the three formatted planes, producing underlying relative late

enhancement values (in percentages).

Overall assessment in the fourth group (Table 1, Overall judgment) was provided by the radiologists

who considered all of the aforementioned characteristics to produce a qualitative assessment of

response in four categories: complete remission (no enhancement), partial remission, no response,

and progression.

29

Table 1. Features of Contrast Uptake on Contrast-Enhanced MRI

Feature MRI Scan

1 MRI Scan

2 Change

Bolus enhancement (0–45 s)

Time between enhancement of aorta and enhancement of tumor (s)

Yes Yes Yes

Relative enhancement in tumor after 3, 12, and 17 s A (%) Yes Yes Yes

Initial enhancement (90 s)

Extent of enhancing tumor

Quantitative assessment of largest diameter (mm) Yes Yes YesC

Qualitative assessment of change B (categoric) No No Yes

Morphology D (categoric) Yes Yes YesE

Relative enhancement in tumor F(%) Yes Yes Yes

Late enhancement (450 s)

Extent of washout or plateau in tumor

Quantitative assessment of largest diameter (mm) Yes Yes YesG

Qualitative assessment of change B (categoric) No No Yes

Relative enhancement in tumor H (%) Yes Yes Yes

Overall judgment

Radiologic assessment of response I (categoric) No No Yes

Note- Yes or no indicates whether the feature was investigated. MRI scan 1 indicates MRI before chemotherapy. MRI scan 2 indicates MRI scan after two courses of chemotherapy. Change indicates whether or not there was a change in the feature between MRI scan 1 and MRI scan 2. A [(SI3, 12, 17 – SIstart)/ SIstart] x 100%, where SI is signal intensity. B Progression, no change, decrease <50%, decrease ≥50%. c [(LDinitialscan2 – LDinitialscan1)/ LDinitialscan1] x 100%, where LD is largest diameter; D Mass, multinodular, and diffuse. E Shrinking mass, diffuse reduction, reduction to small residual foci in the original tumor. F [(SI90-SI0)/SI0] x 100%. G [(LDlatescan2-LDlatescan1)/LDlatescan1] x 100% where late indicates late enhancement. H [(SI450-SI90)/SI90] x 100%. I Complete remission (no enhancement), partial response, no response, progression.

30

Evaluation of Response

Response of the primary tumor was determined by evaluating the surgical specimen at pathology.

Complete remission was defined as the complete absence of residual tumor cells at microscopy.

When a small number of scattered tumor cells were seen, the samples were classified as near-

complete pathologic remission. Because the aim of this study was to identify MRI features associated

with a high specificity of the primary tumor to chemotherapy, tumors with near- complete pathologic

remission were included in the group of complete remission for analytic purposes [7,21].

All other responses involving residual vital tumor in the surgical specimen were defined as

incomplete remission at final pathology. The presence or absence of tumor-positive axillary lymph

nodes was not taken into account for this analysis.

Statistical Analysis

The software programs SPSS 10 (SPSS) and Matlab R12 (TheMathWorks) were used for all analyses. A

p value of 0.002 was defined as a significant test result (p = 0.05 adjusted for the number of tested

characteristics using the Bonferroni correction). Univariate analyses were performed using Student’s

t tests for continuous normally distributed characteristics, Mann- Whitney U exact tests for

abnormally distributed continuous characteristics, and Fisher’s exact tests for binomial categorical

characteristics.

The features that yielded significant separation after Bonferroni correction were included in the

multivariate analysis. For multivariate analysis, logistic regression with feature selection by double

cross-validation was used [22,23]. The aim of this approach is to obtain a combination of

characteristics that is unlikely to be predictive by chance. The analysis consists of validation in an

inner loop and in an outer loop. In the outer loop, each case was left out consecutively. In the inner

loop, 100 10-fold cross-validations were performed for each feature combination. In each cross-

validation, a logistic model was built from the training set, and the area (Az) under the receiver

operating characteristic (ROC) curve was used to quantify the performance of the cross-validated

model [24]. Feature selection was restricted to three simultaneous covariates at most. The feature

combination that yielded the best performance was retrained on all cases in the inner loop and

subsequently applied to the omitted case in the outer loop to produce a posterior probability of

unfavorable response. This procedure was repeated until all cases were tested in the outer loop. The

feature combination that was selected most frequently was chosen to be the predictive model, and

the performance of this model was quantified by the area under the ROC curve obtained from the

posterior probabilities assigned to each case.

31

MRI Response Prediction Test

After identifying multivariate MRI features predictive for residual tumor, we chose a point on the

ROC curve corresponding to a maximum of 5% false-positive interpretations of complete remission

(which would lead to switch of therapy in excellent responders). This operating point was translated

into an MRI response prediction test to guide treatment decisions during chemotherapy.

32

Results

Patient characteristics are shown in Table 2.

Table 2. Patient and Tumor Characteristics of 54 Patients

Characteristic Value %

Patient age Mean 46 y

Range 24 -66 y

Tumor histology A

Ductal carcinoma 45 83 Lobular carcinoma 9 17

Tumor grade A

Unknown 18 33 I 1 3 II 23 64 III 12 33

Immunostaining A

HER2/neu

Unknown 7 13 Positive 13 24 Negative 34 63

Estrogen receptor A

Unknown 8 15 Positive 32 59 Negative 14 26

Progesterone receptor A

Unknown 8 15 Positive 25 46 Negative 21 39 Tumor diameter, clinical

Median 45 mm

Range 15–100 mm

Surgery

Mastectomy 28 52 Breast-conserving therapy 26 48 Pathology response

Complete 15 28 Incomplete 39 72

Note—Data are numbers of patients unless otherwise specified. A Assessed by sonography-guided biopsy before chemotherapy. Tumors were classified as progesterone receptor–positive or estrogen receptor–positive if > 1% of the cells were stained positive. Tumors were classified as HER2-positive when they were scored 3+ at immunohistochemistry or when gene amplification was shown at in situ hybridization.

33

Table 3. Univariate Assessment of MRI Characteristics Associated with Differences Between Complete and Incomplete Responses at Pathology

Az MRI Characteristic p

0.85 Change of largest late enhancement diameter, scan 2 relative to scan 1 0.00002

0.84 Radiologic assessment of residual tumor, scan 2 (four categories) 0.0003

0.82 Fast enhancement 10 s after injection, scan 2 0.0004

0.81 Evaluation of late enhancement area, scan 2 relative to scan 1 (four categories) 0.001

0.81 Change of fast enhancement 15 s after injection, scan 2 relative to scan 1 0.002

0.8 Change of fast enhancement 10 s after injection, scan 2 relative to scan 1 0.001

0.78 Late enhancement, scan 2 0.001

0.78 Initial enhancement, scan 2 0.003

0.78 Evaluation of enhancement area, scan 2 relative to scan 1 (four categories) 0.005

0.76 Change of largest initial enhancement diameter, scan 2 relative to scan 1 0.007


0.74 Change of fast enhancement 3s after injection, scan 2 relative to scan 1 0.077

0.69 Initial enhancement, scan 1 0.028

0.66 Change of late enhancement, scan 2 relative to scan 1 0.617

0.64 Time between enhancement of aorta and enhancement of tumor (onset), scan 2 0.106

0.63 Late enhancement, scan 1 0.215

0.62 Change of initial enhancement, scan 2 relative to scan 1 0.398

0.61 Change of fast enhancement onset, scan 2 relative to scan 1 0.214

0.6 Time between enhancement of aorta and enhancement of tumor (onset), scan 1 0.705

0.55 Pattern of enhancement, scan 1 (three categories) 0.114



Note - Az indicates area under the receiver operating characteristic curve. Boldface indicates statistical significance (p<0.002 after Bonferroni correction)

Pathology Results

Thirty-nine of 54 (72%) patients had residual tumor, and 15 (28%) had complete remission at final

pathology.

34

MRI Characteristics

In univariate analysis, six MRI characteristics were found to be significantly associated with residual

tumor at pathology (Table 3). In multivariate analysis, only a single MRI characteristic remained:

change in largest diameter of late enhancement in the tumor on scan 2 relative to scan 1: LDlate2–1

= [(LDlatescan2 – LDlatescan1) / LDlatescan1] × 100%. The area under the ROC curve is 0.73 after double

validation. Because of the prior condition that therapy of the excellent responders (complete

remission at pathology) be switched to alternative therapy in fewer than 5% cases, the operating

point on the ROC curve is at 25% reduction in the largest diameter of late enhancement in the tumor

on scan 2 relative to scan 1 (LDlate2–1).

Application of this operating point (consistency analysis) confirmed that 21 of 22 patients (95.5%)

were correctly associated with residual tumor (Fig. 2, lower arm of diagram). The additional effect of

the choice of a low false-positive test was that only 21 (54%) of the 39 patients with residual tumor

at pathology were correctly identified.

When LDlate2–1 was at least 25%, 14 of the 15 patients with complete remission at pathology were

correctly identified. The true-positive fraction was 93.3% (14/15) (Fig. 2, upper arm). Thirteen

patients showed complete disappearance of washout or plateau in the tumor during treatment

(LDlate2–1 = 100%). Nine (9/15, 60%) had complete remission at final pathology.

Fig. 2—Flow diagram shows change of

largest diameter of late enhancement

in tumor on MRI scan 2 relative to MRI

scan 1 (LDlate2–1) of 54 tumors

divided into two groups. Upper arm

shows group with at least 25%

LDlate2–1; lower arm shows group

< 25% LDlate2–1. Complete remission

at pathology occurred in 15 patients,

incomplete remission (residual tumor

at pathology) in 39.

35

The MRI response prediction test was formulated as follows: Less than 25% reduction of the largest

diameter of late enhancement on MRI (scan 2 relative to scan 1) during chemotherapy is indicative of

residual tumor (Figs. 3 and 4). In the remainder of this article, we define this outcome as an

unfavorable response predicted with MRI.

Fig. 3—Example of favorable response predicted by MRI in 48-year-old woman.

Fig.3 A–F, Shown are largest diameter of late enhancement (LDlate) in tumor (dark area) in sagittal

(A, D), axial (B, E), and coronal (C, F) planes before chemotherapy (MRI scan1, A–C) and after two

courses of chemotherapy (MRI scan 2, D–F). LDlate at MRI scan 1 is 28 mm and at MRI scan 2 is 11

mm. Percentage of difference, LDlate2–1, = [(28 –11) / 28] × 100% = 61% reduction. Favorable

response is to be anticipated according to MRI response prediction test. After chemotherapy was

completed, final pathology showed complete remission.

36

Fig. 4—Example of unfavorable response predicted by MRI in 48-year-old woman.

Fig4. A–F, Shown are largest diameter of late enhancement (LDlate) in tumor (dark area) in sagittal

(A, D), axial (B, E), and coronal (C, F) planes before chemotherapy (MRI scan 1, A–C) and after two

courses of chemotherapy (MRI scan 2, D–F). LDlate at MRI scan 1 is 37 mm and at MRI scan 2 is 32

mm. Percentage of difference, LDlate2–1, = [(37 – 32) / 37] × 100% = 14% reduction. Unfavorable

response is to be anticipated according to MRI response prediction test. After chemotherapy was

completed, final pathology showed residual tumor.

Discussion

Identifying effective tools is essential to monitor treatment response, to tailor treatments, and to

optimize patient benefit from neoadjuvant chemotherapy.

37

We found that the change of largest diameter of the late enhancement region (LD- late2–1) is the best

predictor of final pathologic response on MRI during neoadjuvant chemotherapy among a large set of

MRI features. This characteristic is a combination of morphology (extent) and kinetics (late

enhancement) associated with tumor vascularity. Reduction less than 25% during therapy was

associated with residual disease at pathology after therapy.

Others also studied the relation between morphologic features of a tumor and treatment outcome.

Initial tumor size has long been known to predict patient survival and is the basis of most disease-

staging systems (TNM classification). In a study by Cheung et al. [25], who evaluated 33 patients with

serial MRI, it was found that all complete responders had a marked early size reduction of more than

45%.

A study performed by Partridge et al. [26] showed that initial tumor volume measured on MRI is the

most significant predictive variable of recurrence-free survival, which is entirely in accordance with

the rationale of the TNM classification. Their multivariate analysis showed that the initial MRI tumor

volume and the change in MRI volume after completion of chemotherapy were significant

independent predictors for recurrence-free survival. Early change in tumor volume at MRI after one

chemotherapy cycle showed a trend of association with recurrence-free survival.

Almost all studies focused on tumor enhancement in the very early (0–60 seconds) phase or initial

enhancement (60–120 seconds) rather than delayed enhancement. One of the first published studies

by Gilles et al. [15] showed correlation between intensity of enhancement and the presence of

residual tumor after treatment. Our current study evaluated the potential value of a combined MRI

protocol involving very early, initial, and late enhancement. Although we found the change of largest

diameter of initial enhancement on MRI scan 2 relative to that in MRI scan 1 important to predict

pathology outcome (Table 2), the change in largest diameter of late enhancement after multivariate

analysis was found to be the strongest predictive characteristic. Although more limited than

assessment of volume, the largest diameter measurements (in three planes) are easily applicable to

sites that have no access to dedicated volumetric analysis tools. We were not able to compare our

results with recurrence-free survival or survival because of short follow-up time.

To our knowledge, the only other study that reported measurements of late enhancement in the

tumor was performed by El Khoury et al. [27]. Those authors examined the MRI quantification of the

washout changes in breast tumors. They reported that quantification of washout variation in breast

tumors is feasible and reproducible, and a significant reduction of washout volume was noted during

chemotherapy (after two courses). Limitations of that study were the small number of patients (n =

19) and that only one patient achieved a complete response at pathology. Nonetheless, the results of

our study using largest-diameter measurements are in agreement with these findings.

38

In our study, complete disappearance of washout or plateau in the tumor was observed in 13 of 54

tumors. In nine (69%) patients, this was associated with complete remission at pathology. In only

four (10%) patients with residual tumor at final pathology, complete disappearance of washout or

plateau in the tumor was noted. Balu-Maestro et al. [28] reported the disappearance of early

abnormal enhancement in five cases in which complete histologic response occurred. Rieber et al.

[29]found that flattening of the time–intensity curve (i.e., disappearance of washout) of breast

cancer after one course of chemotherapy and the absence of contrast uptake after four courses

indicate responders.

The combination of morphologic and kinetic characteristics to have predictive value during

neoadjuvant chemotherapy has also been reported by others. In the 30 patients studied by

Martincich et al. [30], a reduction in the early enhancement ratio and > 65% reduction in tumor

volume after two cycles of chemotherapy were associated with a major histologic response

(univariate analysis); these parameters did not retain statistical significance in multivariate analysis.

Rather than focusing on initial and late enhancement, others applied pharmacokinetic models of

contrast uptake using the entire time–signal intensity curve to study the response to neoadjuvant

chemotherapy [16][17][30]. Padhani et al. [17] studied the changes in contrast agent kinetics during

chemotherapy to determine whether kinetic measures can be used to predict final pathologic

response. Their initial clinical results in 25 patients showed that size (morphology) and transfer

constant range (kinetics) were equally accurate in predicting the absence of pathologic response

after two cycles of treatment.

Although pharmacokinetic models have the potential advantage of giving insight into the underlying

physiologic processes of contrast uptake, it is generally difficult to compare results among different

studies because of the current lack of standardization in these models. As in any diagnostic test, we

had to choose a cutoff value that balances the true-positive fraction of the MRI test against the false-

positive fraction. Switching therapy away from an already effective regimen (false- positive test

result) may harm the outcome of patients with excellent response. A multidisciplinary team of

radiologists, surgeons, and medical oncologists decided that the MRI test—a diagnostic tool under

investigation— should not cause potential harm to more than 5% of the patients in the current

clinical setting. Consequently, only 54% of patients with residual tumor at pathology could be

correctly identified. Another way of considering this, however, is that almost half the number of

patients may benefit from switching therapy with negligible risk, compared with the current clinical

practice of not switching. Another advantage of this conservative threshold is that it allows fine-

tuning of the trade-off in subsequent studies.

39

Our study also has some limitations. The study results were assessed in a single-institution study in a

relatively small set of patients. The suggested MRI response prediction test needs to be evaluated in

prospectively included patients from multiple institutions in whom chemotherapy will be switched as

a result of the MRI test. Another aspect of validation concerns assessment of the impact of different

chemotherapeutic agents on the performance of the MRI test. The ultimate outcome of any

successful regimen is destruction of the tumor, including its neovascular system, which is evaluated

by the MRI response prediction test. However, the timing of the second MRI or the 25% operating

point may be fine-tuned to various chemotherapy regimens. Another limitation is that experienced

radiologists evaluated the MRI in consensus, so we were not able to assess intra- and interobserver

variability.

In summary, our study shows that change of largest late enhancement diameter in the tumor on

serial MRI has the potential to assess early breast cancer response to neoadjuvant chemotherapy. In

clinical practice, the MRI response prediction test may offer the oncologist an objective tool of high

specificity to tailor the chemotherapy for each individual patient. However, additional assessment of

the proposed MRI test in larger numbers of patients will be required to validate these findings.

Acknowledgments

We thank Angelique Schlief of data management and Eline Deurloo of the radiology department for

their dedication and contributions.

40

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17. Padhani AR, Hayes C, Assersohn L et al. (2006) Prediction of clinicopathologic response of breast cancer to primary chemotherapy at contrast-enhanced MR imaging: initial clinical results. Radiology 239 (2):361-374 18. Manton DJ, Chaturvedi A, Hubbard A et al. (2006) Neoadjuvant chemotherapy in breast cancer: early response prediction with quantitative MR imaging and spectroscopy. Br J Cancer 94 (3):427-435 19. Pickles MD, Lowry M, Manton DJ, Gibbs P, Turnbull LW (2005) Role of dynamic contrast enhanced MRI in monitoring early response of locally advanced breast cancer to neoadjuvant chemotherapy. Breast Cancer Res Treat 91 (1):1-10 20. Gilhuijs KG, Deurloo EE, Muller SH, Peterse JL, Schultze Kool LJ (2002) Breast MR imaging in women at increased lifetime risk of breast cancer: clinical system for computerized assessment of breast lesions initial results. Radiology 225 (3):907-916 21. Honkoop AH, van Diest PJ, de Jong JS et al. (1998) Prognostic role of clinical, pathological and biological characteristics in patients with locally advanced breast cancer. Br J Cancer 77 (4):621-626 22. Deurloo EE, Klein Zeggelink WF, Teertstra HJ et al. (2006) Contrast-enhanced MRI in breast cancer patients eligible for breast-conserving therapy: complementary value for subgroups of patients. Eur Radiol 16 (3):692-701 23. Ntzani EE, Ioannidis JP (2003) Predictive ability of DNA microarrays for cancer outcomes and correlates: an empirical assessment. Lancet 362 (9394):1439-1444 24. Metz CE (1986) ROC methodology in radiologic imaging. Invest Radiol 21 (9):720-733 25. Cheung YC, Chen SC, Su MY et al. (2003) Monitoring the size and response of locally advanced breast cancers to neoadjuvant chemotherapy (weekly paclitaxel and epirubicin) with serial enhanced MRI. Breast Cancer Res Treat 78 (1):51-58 26. Partridge SC, Gibbs JE, Lu Y et al. (2005) MRI measurements of breast tumor volume predict response to neoadjuvant chemotherapy and recurrence-free survival. AJR Am J Roentgenol 184 (6):1774-1781 27. El Khoury C, Servois V, Thibault F et al. (2005) MR quantification of the washout changes in breast tumors under preoperative chemotherapy: feasibility and preliminary results. AJR Am J Roentgenol 184 (5):1499-1504 28. Balu-Maestro C, Chapellier C, Bleuse A, Chanalet I, Chauvel C, Largillier R (2002) Imaging in evaluation of response to neoadjuvant breast cancer treatment benefits of MRI. Breast Cancer Res Treat 72 (2):145-152 29. Rieber A, Zeitler H, Rosenthal H et al. (1997) MRI of breast cancer: influence of chemotherapy on sensitivity. Br J Radiol 70 (833):452-458 30. Martincich L, Montemurro F, De Rosa G et al. (2004) Monitoring response to primary chemotherapy in breast cancer using dynamic contrast-enhanced magnetic resonance imaging. Breast Cancer Res Treat 83 (1):67-76

43

CHAPTER 3

Magnetic resonance imaging response monitoring of breast

cancer during neoadjuvant chemotherapy: Relevance of

breast cancer subtype

Claudette E. Loo1, Marieke E. Straver2, Sjoerd Rodenhuis3, Sara H. Muller1, Jelle

Wesseling4, Marie-Jeanne T.F.D. Vrancken Peeters2, Kenneth G.A. Gilhuijs1,5

The Netherlands Cancer Institute Amsterdam, The Netherlands:


2Department of Surgery



University Medical Center Utrecht, The Netherlands:


J Clin Oncol. 2011 29:660-666.

https://cc2umpdq5cjidifkh79y8atc.sec.amc.nl/science/article/pii/S0167814012002174#aff2




45

Abstract

Purpose

To evaluate the relevance of breast cancer subtypes for magnetic resonance imaging (MRI) markers

for monitoring of therapy response during neoadjuvant chemotherapy (NAC).

Patients and methods

MRI examinations were performed in 188 women before and during NAC. MRI interpretation

included lesion morphology at baseline, changes in morphology, size, and contrast uptake kinetics

(initial and late enhancement). By using immunohistochemistry, tumors were divided into three

subtypes: triple negative, human epidermal growth factor receptor 2 (HER2) positive, and estrogen

receptor (ER) positive/HER2 negative. Tumor response was assessed dichotomously (i.e., presence or

absence of residual tumor in the surgical specimen). Complementary, a continuous scale assessment

was used (the breast response index [BRI], representing the relative change in tumor stage).

Multivariate regression analysis and receiver operating characteristic analysis were employed to

establish significant associations.

Results

Residual tumor at pathology was present in 31 (66%) of 47 triple-negative tumors, 23 (61%) of 38

HER2-positive tumors, and 96 (93%) of 103 ER-positive/HER2-negative tumors. Multivariate analysis

of residual disease showed significant associations between breast cancer subtype and MRI (area

under the curve [AUC], 0.84; P < .001). BRI also showed significant correlation among breast cancer

subtype, MRI, and age (Pearson’s r = 0.465; P < .001). In subset analysis, this was only significant for

triple-negative tumors (P < .001) and HER2-positive tumors (P < .05). Residual tumor after NAC in the

triple-negative and HER2-positive group is significantly associated with the change in largest

diameter of late enhancement during NAC (AUC, 0.76; P < .001). No associations were found for ER-

positive/ HER2-negative tumors.

Conclusions

MRI during NAC to monitor response is effective in triple-negative or HER2-positive disease but is

inaccurate in ER-positive/HER2-negative breast cancer.

46

Introduction

Neoadjuvant chemotherapy (NAC) for breast cancer was equally effective as postoperative

chemotherapy in terms of disease-free and overall survival [1-4]. A pathologically confirmed

complete remission (pCR) or minimal disease [5] after chemotherapy is consistently associated with

disease-free and overall survival benefit [1,2,4,6]. Unfortunately, breast cancer is a highly

heterogeneous disease, and only a minority of patients achieves a pCR.

Several markers are routinely employed to predict treatment outcome and to select therapy [7-9].

The most frequently used markers include the estrogen receptor (ER), the progesterone receptor

(PR), and the human epidermal growth factor receptor2 (HER2). Three major breast cancer subtypes

are easily distinguished by immunohistochemistry: triple-negative (i.e., ER, PR and HER2 negative),

HER2-positive (i.e., HER2 positive; ER and PR may be positive or negative), and ER-positive (i.e., ER

positive, HER2 negative, PR may be positive or negative) types [10,11]. These immunohistochemical

subtypes correspond roughly to the molecular subtypes of basal-like, HER2 enriched, and luminal,

respectively [12]. Subtyping of typically heterogeneous breast cancer in these three groups may

improve understanding of tumor response and may result in optimized strategies for patient-

tailored treatment [13,14].

Even within these subgroups, the response to chemotherapy varies widely. Early monitoring of the

efficacy of systemic therapy may therefore recognize tumors that fail to respond and may offer the

possibility to adapt the therapy.

In contrast to conventional breast imaging, dynamic contrast-enhanced magnetic resonance imaging

(MRI) has the ability to differentiate between nonvascularized therapy-induced fibrosis and residual

vital tumor [15-18]. It may thus allow early identification of nonresponders and may be predictive of

the presence of residual tumor after completion of neoadjuvant chemotherapy [17]. As a result, it

could spare the patient additional exposure to ineffective and toxic treatment, and it may

conceivably even guide the adaptation of drug regimens.

In contrast to the impact of subtyping by immunohistochemistry on response and prognosis,

[13,14,19] little is known about the ability of MRI to monitor response in the different subtypes. The

kinetics of contrast uptake and other MRI features associated with response could differ between

these subtypes. If so, this could have major consequences for the design of future neoadjuvant

studies and also for the interpretation of previous studies that have employed MRI for response

monitoring. The purpose of our study was to evaluate the relevance of breast cancer subtype on MRI

markers of therapy response during neoadjuvant chemotherapy.

47

Patients and Methods

Selection of Patients

Patients with pathologically proven invasive breast cancer greater than 3 cm and/or with at least

one tumor-positive lymph node were offered NAC. All patients received NAC between 2000 and

2008, either in one of two studies or according to the standard arm of those studies [20,21]. The

institutional review board approved the study protocols, and informed consent was obtained from

all patients. Patients with HER2-positive tumors treated without trastuzumab in the regimen were

excluded from this analysis. Patients who had received two MRI examinations, one before and a

second during NAC (after 6 weeks or, in case of trastuzumab, 8 weeks) and who underwent surgery

after NAC were included.

Treatment

For neoadjuvant chemotherapy, four different regimens were employed as described previously

[20,21]. Briefly, most HER2-negative tumors, either ER- positive or negative, received six courses of

cyclophosphamide and doxorubicin, administered in a dose-dense schedule (every 2 weeks). A

minority received six courses of capecitabine and docetaxel or of doxorubicin and docetaxel. When

no or little response was noted after three courses, chemotherapy was switched to a

(hypothetically) non– cross-resistant regimen [15]. This would result in three courses of

cyclophosphamide and doxorubicin followed by three courses of capecitabine and docetaxel (or vice

versa).

All HER2-positive tumors were treated with a trastuzumab-based regimen. The trastuzumab-based

regimen started with an 8-week course of paclitaxel, trastuzumab, and carboplatin and was followed

by either two additional 8-week courses of paclitaxel, trastuzumab, and carboplatin or four courses

of trastuzumab with fluorouracil, epirubicin, and cyclophosphamide.

After the last course of chemotherapy, all selected patients underwent breast-conserving therapy or

mastectomy according to the standard protocols at our institute.

MRI Technique

Initially, MRI was performed on a 1.5 T Magnetom Vision scanner with dedicated bilateral phased

array breast coil (Siemens, Erlangen, Germany). From April 2007, MRI was performed on a 3.0 T

Achieva scanner with a 7-elements sense breast coil (Philips Medical Systems, Best, the

Netherlands). Images were acquired with the patient in prone position and with both breasts

imaged. The standard dynamic protocol started with an unenhanced coronal three-dimensional fast

48

field echo (thrive) sense T1-weighted sequence. A bolus (14 mL) of gadolinium containing contrast

(0.1 mmol/kg) was administered intravenously at 3 mL/sec by using a power injector followed by a

bolus of 30 mL of saline solution. Subsequently, dynamic imaging was performed in five consecutive

series at 90-second intervals. The voxel size was 1.21 X 1.21 X 1.69 11L (1.5 T) or 1.1 X 1.1 X 1.2 11L

(3.0 T). The following scanning parameters were used: acquisition time of 90 seconds (1.5 T and 3.0

T); ratio of repetition time to echo time, 8.1:4.0 (1.5 T) or 4.4:2.3 (3.0 T); flip angle, 20 degrees (1.5 T)

or 10 degrees (3.0 T); field of view, 310 (1.5 T) or 360 (3.0T).

Radiologic Assessment and Clinical Reading

Interpretation of the breast MRI results was done by using a viewing station that permitted

simultaneous viewing of two series reformatted and linked in three orthogonal directions [22]. The

subtraction images were also color coded, representing different levels and curve types of

enhancement.

All MRI interpretations were revised by an experienced breast radiologist (C.E.L.; > 7 years, > 700

MRI breast reviews per year), who was unaware of breast cancer subtype and final pathology

outcome. The MRI examinations before chemotherapy (baseline) and during chemotherapy were

analyzed in one session to ensure interpretative consistency.

Temporal and morphologic characteristics of contrast uptake were scored as previously described

[15]. Briefly; tumor extent, morphology and relative enhancement were assessed during initial

enhancement (90 seconds) and late enhancement (450 seconds) at baseline MRI and MRI during

NAC.

The extent of the tumor was assessed by its largest diameter in three reformatted planes (i.e.,

sagittal, axial, and coronal) at initial and late enhancements. The percentage difference in largest

tumor diameter between baseline MRI and MRI during NAC was assessed at initial and late

enhancements. Supported by color coding, the area within the tumor with strongest contrast uptake

was determined. These parts were examined by interactively moving the cursor, producing

underlying relative enhancement values (in percent ages). Morphology was scored in three groups:

unifocal mass, multifocal mass, and nonmass (diffuse)[23]. At MRI during NAC, the pattern of tumor

reduction was denoted in five categories: shrinking mass, diffuse decrease, reduction to small foci,

no enhancement, and no change.

49

Histopathologic Analysis

Tumors were classified according to the standard criteria of the World Health Organization. From

pretreatment core biopsies, tumors were classified in three subgroups according to their receptor

status: triple-negative, HER2-positive, and ER-positive/HER2-negative tumors.

Immunohistochemistry for ER, PR, and HER2 was interpreted according to the Dutch guidelines

(http://www.oncoline.nl).

ER and PR were considered positive if > 10% of nuclei stained positive. Tumors with HER2 scores of

3+ (i.e., strong homogeneous staining) were considered positive. In case of 2+ scores (i.e., moderate

complete membranous staining in > 10% of tumor cells), chromogenic in situ hybridization was used

to determine HER2 amplification (gene copy number > 6 per tumor cell).

Response of the Primary Breast Tumor

Tumor response was assessed dichotomously (i.e., presence or absence of residual tumor in the

surgical specimen). In addition, a continuous scale assessment was used for complementary tests (by

using the breast response index [BRI][24]). All surgical specimens were reviewed by one of two

experienced breast cancer pathologists (J.W. or M.vdV.). For the dichotomous assessment, complete

remission was defined as complete absence of residual tumor cells at microscopy. A small number of

scattered cells were classified as near-complete remission. Because we aimed to identify MRI

features associated with a high sensitivity of the primary tumor to chemotherapy, tumors with near-

complete remission were included in the group of pCR for analytic purposes [21,25]. All specimens

involving residual vital tumor were defined as pathologic incomplete remission.

For the continuous-scale assessment, BRI was derived from the change in T stage before treatment

and the T stage of residual tumor at pathology after treatment [24]. In short, for each decrease in T

stage, one point was awarded, except for the transition from T1 to T0. One additional point was

awarded for achieving a near-pCR, and two points were awarded for a pCR of the breast. The

accumulated points were divided by the maximum number of achievable T stage points (i.e., T stage

+ 1), resulting in a number between zero (nonresponse) and one (complete response). Axillary lymph

node status was not taken into account for this analysis.

50


SPSS version 15.1 (SPSS Inc, Chicago, IL) was used to analyze changes in MRI during NAC associated

with presence of residual disease after NAC. The positive predictive value (PPV) was calculated by

dividing the number of patients with a positive test and residual disease by the total number of

patients with a positive test. Univariate analyses were performed using t tests, Mann- Whitney U

exact tests and x2 tests. A P value < .05 was considered a significant test result. For multivariate

analysis, logistic and linear regression with stepwise feature selection was used (P to entry, .05; P to

removal, .10). The following MRI (baseline and during NAC) and clinical features were included in the

multivariate analysis: lesion morphology, largest tumor diameter, and relative enhancement (%) at

initial and late enhancements; pattern of reduction; change in largest tumor diameter and change in

relative enhancement at initial and at late enhancement; breast cancer subtype; chemotherapy

regimen; and age. Receiver operating characteristic curve analysis was used to compute the area

under the curve.

51

Results

Patients and Pathology

A total of 188 patients were included. The tumor subtype in most patients was ER positive/HER2

negative (55%) followed by triple negative (25%) and HER2 positive (20%) (Table 1).

Table 1. Patient Demographic and Clinical Tumor Characteristics

Total (N = 188)

Characteristic No. %

Age, years

Mean 46 year

Range 23-76 year

T stage prior to NAC

T1 6 3

T2 97 52

T3 62 33

T4 23 12

pN stage prior to NAC

pN0 (SNB negative) 28 15

pN1 (SNB positive/FNAC positive) 125 66

pN3 (infra/supraclavicular) 11 6

pNx (cN0) 24 13

Histology

Ductal carcinoma 139 74

Lobular carcinoma 21 11

Adenocarcinoma NOS 28 15

Subtype by receptor status

ER positive* 103 55

Triple negative** 47 25

HER2 positive 38 20

Abbreviations: NAC, neoadjuvant chemotherapy; SNB, sentinel node biopsy; FNAC, fine-needle aspiration cytology; NOS, not otherwise specified; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2. * HER2 negative. ** ER, progesterone receptor, and HER2 negative.

52

Significant differences in presence of residual tumor at pathology were found in the three

subgroups. Residual tumor occurred most often in ER- positive/HER2-negative tumors and least

often in HER2-positive tumors (P < .001; Table 2).

Table 2. Tumors stratified by Subtype, Pathologic Response, Chemotherapy Regimen, Histology and ER

Triple Negative HER2 Positive ER Positive/HER2

Negative

Tumor Variable

(n = 47) (n = 38) (n = 103)

No. % No. % No. %

Pathologic response

Residual disease 31 66 23 60 96 93

Complete remission 16 34 15 40 7 7

Chemotherapy regimen

AC 31 59

AC + CD 12 33

CD or AD 4 11

Trastuzumab-based 38

Histology

Ductal carcinoma 40 29 70

Lobular carcinoma 0 3 18

Adenocarcinoma NOS 7 6 15

ER

Negative 47 13 0

Positive 0 25 103

Abbreviations: ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; AC, cyclophosphamide and doxorubicin; CD, capecitabine and docetaxel; AD, doxorubicin and docetaxel; NOS, not otherwise specified.

None of the 21 lobular carcinomas achieved complete remission at pathology after NAC. The type of

lesion at baseline MRI of the lobular carcinomas was predominantly diffuse/nonmass (n = 9) and

multifocal mass (n = 8). In the HER2-positive group, 16 of the ER-positive tumors (64%) and seven of

the ER-negative tumors (54%) showed residual disease at final pathology.

53

MRI

At baseline MRI, the triple-negative tumors presented significantly more often as a unifocal mass

(57%) than the HER2-positive tumors (18%) and the ER-positive/HER2-negative tumors (33%; P =

.001; Table 3). Conversely, HER2-positive tumors presented more often as multifocal masses (53%)

than the triple-negative tumors (32%) and ER-positive tumors (30%; P = .02; Table 3). Triple-

negative tumors regressed significantly more often as a shrinking mass at MRI during NAC than the

other two subtypes (P < .001; Table 3). The enhancement kinetics and largest tumor diameter at MRI

are given in Table 4. Multivariate logistic regression analysis of residual disease (presence or

absence) showed significant associations with breast cancer subtype, late enhancement during NAC

and pattern of reduction between baseline MRI and MRI during NAC. The area under the receiver

operating characteristic curve was 0.84 (P < .001). In subset analyses, the association was significant

for the triple-negatives (P <.001) and HER2-positives (P = .05), but absent for the ER-positives/ HER2-

negatives (P = .07). Without the lobular carcinomas, the significance of the association improves in

the Her2-positive (P = .016) and in the ER-positive/HER2-negative group (P = .05).

Multivariate linear regression analysis of the BRI values showed significant associations with breast

cancer subtype, age and change in largest tumor diameter at initial enhancement between baseline

MRI and MRI during NAC (Fig 1). The overall Pearson’s correlation coefficient was 0.465 (P < .001). In

subset analyses, the correlation was significant for the triple-negative tumors (Pearson’s r = 0.605; P

< .001) and HER2-positive tumors (Pearson’s r = 0.426; P < .01) but absent for the ER-positive/HER2-

negative tumors (Pearson’s r = 0.074; P = .458).

In multivariate analysis, there were no markers significantly associated with either residual disease

(Fig 2C) or BRI (Fig 1C) in the ER-positive/HER2-negative group. Multivariate analysis of residual

disease in the remaining group (triple-negative and HER2-positive tumors; n = 85) showed that only

the change in largest tumor diameter at late enhancement between baseline MRI and MRI during

NAC retained significance (area under the receiver operating characteristic curve, 0.76; P < .001; Fig

2).

55

Table 4. MRI measurements of Tumor Size and Kinetics Stratified by Subtype

Variable

Triple Negative

HER2 Positive

ER Positive/HER2

Negative

n = 47 n = 38 n = 103

Largest diameter baseline MRI

Initial enhancement, mm

Mean 50 54 48

Range 24-111 16-99 14-112

Late enhancement, mm

Mean 45 46 36

Range 21-106 dec-97 0-98

Change in largest diameter, %*

Mean initial enhancement −44 −50 −29

Mean late enhancement −60 −72 −48

Relative enhancement baseline MRI, %

Initial enhancement 189 202 184

Late enhancement −17 −16 −15

Change relative enhancement, %**

Initial enhancement −5 −36 −7

Late enhancement −48 −124 −82

Dynamic curve type baseline MRI

Type 1 continuous 0 0 2

Type 2 plateau 0 0 5

Type 3 washout 47 38 96

Dynamic curve type MRI during NAC

Type 1 continuous 8 8 20

Type 2 plateau 4 1 9

Type 3 washout 30 17 69

No enhancement 5 12 5

Abbreviations: MRI, magnetic resonance imaging; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; NAC, neoadjuvant chemotherapy. * Change in largest diameter is the difference in diameter (%) between baseline MRI and MRI during NAC ** Change in relative enhancement is the difference in relative enhancement (%) between baseline MRI and MRI during NAC.

56

Fig 1.

Fig 1. —Breast response index (BRI) in relation to age and change in tumor diameter at initial

enhancement on magnetic resonance imaging (MRI) during neoadjuvant chemotherapy relative to

the baseline MRI. A BRI of 1.0 denotes a pathologic complete response, and a BRI of 0 indicates no

response at all. (A) Triple-negative tumors (n = 47); (B) human epidermal growth factor receptor 2 –

positive tumors (n = 38); and (C) estrogen receptor–positive tumors (n = 103). Only in A (P < .001) and

B (P < .01) was correlation found (yielding separation of colors).

Fig. 2

Fig 2. —Pathology (residual tumor or complete remission) in relation to largest tumor diameter (in

millimeters) at baseline magnetic resonance imaging (MRI) and change in tumor diameter at late

enhancement on MRI during neoadjuvant chemotherapy. (A) Triple-negative tumors (n = 47); (B)

human epidermal growth factor receptor 2–positive tumors (n = 38); and (C) estrogen receptor–

positive tumors (n = 103). Only in A (P < .001) and B (P = .05) was correlation found.

57

Discussion

In 188 patients with breast cancer, MRI was found to visualize response during NAC differently

depending on breast cancer subtype. Changes at MRI during NAC correlated well with pathology

outcome for triple-negative and HER2-positive tumors, but not for ER-positive/HER2- negative

tumors.

It is now widely accepted that breast cancer is not a single disease but rather comes in several

subtypes with different pathology, prognosis, and treatment. Our findings show that the imaging

characteristics of these subtypes differ as well and that response to chemotherapy can be measured

accurately by MRI in some, but not in the largest subgroup (ER positive/HER2 negative).

MRI of triple-negative tumors more often showed a unifocal mass at baseline. MRI of HER2-positive

tumors showed multifocal masses before chemotherapy in 53% of the cases. These findings concur

with observations in small tumors reported outside the setting of response monitoring [24,26-28].

MRI of ER-positive/HER2-negative tumors showed neither a dominant morphology at baseline nor a

consistent pattern of reduction at MRI during NAC.

Our study shows that the earlier reported correlation between subtype and morphology of the

tumor at MRI is also valid for relatively large tumors selected for NAC. Moreover, only triple-negative

tumors have a typical shrinking mass reduction pattern at MRI during NAC.

In our study, the correlations between changes in MRI during NAC and tumor regression after

therapy were only observed for the triple-negative and HER2-positive tumors. This striking

observation might be explained by the heterogeneous appearance, the low rate of pCR in the ER-

positive/HER2-negative group, and the high rate of lobular carcinomas. Although we added near-pCR

to the group of complete remissions to increase our sensitivity of detecting residual disease, the

contribution of near-pCR was relatively small (2%). If a strict definition of complete remission (i.e.,

pCR) is used, the rate of absence of residual disease decreases to 5%, but breast cancer subtype

remains of significant importance in multivariate analysis. The low rate of pCR in the ER-

positive/HER2-negative group may explain the absence of significant associations with MRI (using

binary regression analysis). To explore this hypothesis, we additionally used the BRI, which was

previously developed in an attempt to quantify the response to chemotherapy on a continuous scale.

The BRI only takes relatively large decreases in tumor size into account. It is a relatively crude

measure in which the change in T stage before and after chemotherapy is expressed in a value

between 0 (no response) and 1 (pCR). As a result, BRI may reflect

58

tumor shrinkage better than the binary pCR/no-pCR variable (particular when pCR in a subgroup is

infrequent). However, significant correlations could not be established between MRI and BRI, either.

Although tumor diameter at baseline MRI was not correlated with BRI itself (Pearson’s correlation, -

0.01; P = .89), potential errors in the assessment of tumor diameter at baseline MRI may also be

reflected in the BRI, causing an undesirable association. Without the lobular carcinomas, which never

achieved a pCR, the significance of correlations improved in the ER-positive/ HER2-negative group.

Because ER-positive/HER2-negative tumors more often manifest as nonmass lesions at MRI,

assessment of size is more challenging and could also account for the observed lack of correlation.

On the basis of these findings, we recommend caution when interpreting the response of ER-

positive/HER2-negative breast tumors during NAC using MRI.

In the remaining group (triple-negative and HER2-positive tumors), we showed that the change in

largest tumor diameter at late enhancement at MRI during NAC is most predictive of outcome. This

finding is in agreement with a previous study [15].

To our knowledge, this is the first study that addresses the dependency between breast cancer

subtype and changes in MRI during NAC predictive of residual tumor after chemotherapy. Earlier

studies have reported on MRI evaluation after completion of NAC to assess residual tumor in breast

cancer subgroups [29,30].

Our study has some limitations. We have chosen to divide the total study group in three commonly

used subgroups by using immunohistochemistry rather than potentially more precise techniques,

such as subtyping that is based on mRNA expression [31,32]. Microarray analysis was only available

from a limited number of patients in our study group. Moreover, in a previous study by de Ronde et

al, [12] mRNA expression was found to have a high concordance with standard

immunohistochemistry, between triple-negative tumors and basal-like tumors and between ER-

positive/HER2-negative and luminal tumors. [12] The differentiation between luminal A and luminal

B could, however, not be made on the basis of the PR expression, as suggested in another study [33].

During the study period, different chemotherapy regimens were used. Because a trastuzumab-based

regimen is now the standard of care for HER2-positive tumors, we excluded HER2-positive tumors

treated with older regimens. Our HER2-positive subgroup was not sufficiently large to allow

additional stratification into ER-positive and ER-negative tumors. Patients with ER-positive and

triple-negative tumors that showed only a minor response after three courses often changed their

chemotherapy regimens. Selecting poor performers could lead to selection bias, but the different

chemotherapy regimens were taken into account in multivariate analysis. The chemotherapy

regimen did not turn out to be significantly associated with final pathology. An increase in the pCR

59

rate as a result of switching chemotherapy in non-responders was not observed in our study or in

other trials [34]. Possibly, tumor biology may be more important to establish response than the

actual chemotherapy regimen used. Nonetheless, the potential existence of non– cross-resistant

regimens and their use in treatment adaptation is still under investigation. By optimizing the

interpretation of MRI to underlying tumor biology, we hope to increase the chance of success of

these studies. Another limitation is that all results were assessed by one radiologist in a single

institution study. As a result, we were not able to evaluate inter- or intra observer variability.

In conclusion, if response during chemotherapy is monitored by MRI, the radiologist must be aware

of the breast cancer subtype to interpret assessment of the response. Changes in MRI during

neoadjuvant chemotherapy are predictive of pathology outcome only in triple-negative and HER2-

positive tumors, but changes are less predictive in ER-positive/HER2-negative breast cancer.

60

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19. Buzdar AU, Ibrahim NK, Francis D et al. (2005) Significantly higher pathologic complete remission rate after neoadjuvant therapy with trastuzumab, paclitaxel, and epirubicin chemotherapy: results of a randomized trial in human epidermal growth factor receptor 2-positive operable breast cancer. J Clin Oncol 23 (16):3676-3685 20. Straver ME, Rutgers EJ, Rodenhuis S et al. (2010) The Relevance of Breast Cancer Subtypes in the Outcome of Neoadjuvant Chemotherapy. Ann Surg Oncol:Apr 6. [Epub ahead of print] 21. Hannemann J, Oosterkamp HM, Bosch CA et al. (2005) Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 23 (15):3331-3342 22. Gilhuijs KG, Deurloo EE, Muller SH, Peterse JL, Schultze Kool LJ (2002) Breast MR imaging in women at increased lifetime risk of breast cancer: clinical system for computerized assessment of breast lesions initial results. Radiology 225 (3):907-916 23. American College of Radiology (2003) Breast Imaging and Reporting Data System (BI-RADS). American College of Radiology, Reston, Va 24. Rodenhuis S, Mandjes IA, Wesseling J et al. (2010) A simple system for grading the response of breast cancer to neoadjuvant chemotherapy. Ann Oncol 21 (3):481-487 25. Honkoop AH, van Diest PJ, de Jong JS et al. (1998) Prognostic role of clinical, pathological and biological characteristics in patients with locally advanced breast cancer. Br J Cancer 77 (4):621-626 26. Uematsu T, Kasami M, Yuen S (2009) Triple-negative breast cancer: correlation between MR imaging and pathologic findings. Radiology 250 (3):638-647 27. Chen JH, Agrawal G, Feig B et al. (2007) Triple-negative breast cancer: MRI features in 29 patients. Ann Oncol 18 (12):2042-2043 28. Wang Y, Ikeda DM, Narasimhan B et al. (2008) Estrogen receptor-negative invasive breast cancer: imaging features of tumors with and without human epidermal growth factor receptor type 2 overexpression. Radiology 246 (2):367-375 29. Chen JH, Feig B, Agrawal G et al. (2008) MRI evaluation of pathologically complete response and residual tumors in breast cancer after neoadjuvant chemotherapy. Cancer 112 (1):17-26 30. Moon HG, Han W, Lee JW et al. (2009) Age and HER2 expression status affect MRI accuracy in predicting residual tumor extent after neo-adjuvant systemic treatment. Ann Oncol 20 (4):636-641 31. Perou CM, Sorlie T, Eisen MB et al. (2000) Molecular portraits of human breast tumours. Nature 406 (6797):747-752 32. Hu Z, Fan C, Oh DS et al. (2006) The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 7:96 33. Carey LA, Dees EC, Sawyer L et al. (2007) The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res 13 (8):2329-2334 34. von Minckwitz G, Kummel S, Vogel P et al. (2008) Neoadjuvant vinorelbine-capecitabine versus docetaxel-doxorubicin-cyclophosphamide in early nonresponsive breast cancer: phase III randomized GeparTrio trial. J Natl Cancer Inst 100 (8):542-551

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CHAPTER 4

Neoadjuvant chemotherapy adaption and serial MRI

response monitoring in ER-positive HER2-negative breast

cancer

Lisanne S. Rigter1, Claudette E. Loo2, Sabine C. Linn1, Gabe S. Sonke1, Eric van

Werkhoven3, Esther H. Lips4,5, Hillegonda A Warnars2, Petra K. Doll2, Annemarie

Bruining2, Ingrid A. Mandjes6, Marie-Jeanne Vrancken Peeters, Jelle Wesseling5,

Kenneth G.A. Gilhuijs2,8, and Sjoerd Rodenhuis1

The Netherlands Cancer Institute, Amsterdam, The Netherlands:



3Department of Statistics

4Department of Molecular Pathology


6Department of Data Center

7 Department of Surgical Oncology

University Medical Center Utrecht, Utrecht, The Netherlands:

8Department of Radiology / Image Sciences Institute

Br J Cancer. 2013 109:273-8.

https://cc2umpdq5cjidifkh79y8atc.sec.amc.nl/science/article/pii/S0720048X13005494





https://cc2umpdq5cjidifkh79y8atc.sec.amc.nl/science/article/pii/S0720048X13005494#aff0010








65

Abstract

Background

Changing the neoadjuvant chemotherapy regimen in insufficiently responding breast cancer is not a

standard policy. We analyzed a series of patients with ‘luminal’-type breast cancer in whom the

second half of neoadjuvant chemotherapy was selected based on the response to the first half.

Methods

Patients with estrogen receptor-positive (ER +) human epidermal growth factor receptor 2-negative

(HER2 -) breast cancer received three courses of neoadjuvant dose-dense doxorubicin and

cyclophosphamide (ddAC). Three further courses of ddAC were administered in case of a ‘favorable

response’ on the interim magnetic resonance imaging (MRI) and a switch to docetaxel and

capecitabine (DC) was made in case of an ‘unfavorable response’, using previously published

response criteria. The efficacy of this approach was evaluated by tumor size reductions on serial

contrast-enhanced MRI, pathologic response and relapse-free survival.

Results

Two hundred and forty-six patients received three courses of ddAC. One hundred and sixty-four

patients (67%) had a favorable response at the interim MRI, with a mean tumor size reduction of 31%

after the first three courses and 34% after the second three courses. Patients with unfavorable

responsive tumors had a mean tumor size reduction of 12% after three courses and received three

courses of DC rather than ddAC. This led to a mean shrinkage of 27%.

Conclusions

The tumor size reduction of initially less responsive tumors after treatment adaptation adds further

evidence that a response-adapted strategy may enhance the efficacy of neoadjuvant chemotherapy.

66

Introduction

Neoadjuvant chemotherapy has been shown to be equally effective as adjuvant chemotherapy in

terms of breast cancer survival [1], when the preoperative regimen is the same as the postoperative

adjuvant regimen. It is tempting to assume that neoadjuvant chemotherapy could be superior to

adjuvant chemotherapy if the regimen were adapted to the response of the primary tumor.

If the tumor fails to decrease in size, a switch could be made to a (presumably) non-cross-resistant

regimen that could be more effective than the first one. This simple concept has not been adopted in

practice, perhaps because early experience suggested that a change of chemotherapy should be

made anyway [2] and perhaps because response monitoring is difficult and suitable criteria for a

satisfactory response after the first course(s) are not available. More recently, however, a report

from the German Breast Group suggested that response-adapted chemotherapy could be effective:

breast cancer patients who received vinorelbine and capecitabine after failure of a combination of

docetaxel, doxorubicin and cyclophosphamide (TAC) had a better survival than those who continued

on TAC [3].

Response monitoring can be performed by means of physical Response monitoring can be performed

by means of physical examination, by sonographic measurement or by mammographic measurement

[4,5]. Contrast-enhanced magnetic resonance imaging (MRI) is generally regarded as the most

accurate imaging method for invasive breast cancer [6,7] and is increasingly used for the evaluation

of neoadjuvant chemotherapy response. Our group has previously published criteria for a

satisfactory MRI response during chemotherapy [8]. We have recently shown that these criteria are

strongly predictive for a pathologic complete remission (pCR) in triple-negative disease, but are less

accurate in tumors that are estrogen receptor-positive (ER+) and human epidermal growth factor

receptor 2-negative (HER2 -) [9]. The latter group of patients frequently receives preoperative

chemotherapy with the objective to decrease tumor size to facilitate breast-conserving therapy. A

pCR, however, is only rarely achieved. Consequently, the pCR is not an ideal measure of tumor

response and it has recently been shown that it is of no prognostic value in lower-grade ER+ HER2 -

(‘luminal A’) disease [10]. We have proposed a simple measure of down staging, the ‘Neoadjuvant

Response Index’, to better quantify the responsiveness of this subgroup to neoadjuvant

chemotherapy [11]. Whether this index is predictive of recurrence-free survival is still under

investigation and awaits longer follow-up and/or independent confirmation.

Here, we review the data of a series of consecutive patients with ER+ HER2 - breast cancer in our

single-institution neoadjuvant chemotherapy program, who were started on neoadjuvant

chemotherapy with dose-dense doxorubicin and cyclophosphamide (ddAC). The program serves to

67

develop biomarkers for response prediction and to refine techniques for response monitoring. The

objective of this analysis was to evaluate a consecutive series of participating patients with high-risk

ER+ HER2 - breast cancer who received response-adapted neoadjuvant chemotherapy and to help

prepare future controlled studies to further develop such a strategy.

Specifically, we wished to investigate the degree of tumor shrinkage after a change of chemotherapy

regimen because of an unsatisfactory response to ddAC.

Patients and Methods

Patients

Patients between 18 and 70 years of age were included when invasive ER+ HER2 - breast cancer was

present, that was either 43 cm in size or was associated with at least one tumor positive axillary

lymph node. Both tumors of the surrogate intrinsic subtypes luminal A and luminal B were offered

neoadjuvant chemotherapy; we have shown previously that major response can be observed in

luminal A tumors as well [12]. When bilateral cancer was found, the larger tumor was used for this

analysis.

A previous diagnosis of invasive breast cancer was a reason for exclusion. Only patients who received

initial chemotherapy consisting of ddAC were included. All patients either took part in a single-

institution clinical trial, which was approved by the ethical committee, or were treated off study

according to the standard arm of the trial. All patients included in the clinical trial gave written

informed consent, all other patients consented orally.

Treatment

All patients began neoadjuvant chemotherapy with three courses of ddAC (doxorubicin 60 mg m — 2

and cyclophosphamide 600 mg m —2 on day 1, every 14 days, with PEG-filgrastim on day 2) between

2004 and 2012. Three courses of docetaxel and capecitabine (DC, docetaxel 75 mg m —2 on day 1,

every 21 days and capecitabine 2 x 1000 mg m —2 on days 1–14) were administered when an

‘unfavorable response’ was detected by MRI evaluation after the three initial courses. When a

‘favorable response’ was achieved, three further courses of ddAC were administered.

Following chemotherapy, all patients underwent surgery (either mastectomy or breast-conserving

therapy), radiation therapy when indicated and at least 5 years of endocrine treatment according to

national guidelines.

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MRI technique and assessment

Contrast-enhanced MRI monitoring was performed as described previously [8,9]. Briefly, images

were acquired with the patient in prone orientation using a dedicated breast coil and with both

breasts imaged. The standard dynamic protocol started with an unenhanced coronal three-

dimensional fast-field echo (thrive) T1-weighted sequence. A bolus (14 ml) of gadolinium-containing

contrast (0.1 mmol kg —1) was administered intravenously at 3ml s —1 using a power injector followed

by a bolus of 30 ml of saline solution. Subsequently, dynamic imaging was performed in five

consecutive series at 90-s intervals. Temporal and morphologic characteristics of contrast uptake

were assessed as described previously.

Response criteria: MRI

Contrast-enhanced MRI was performed before chemotherapy (baseline), after three courses of

chemotherapy (interim) and after six courses of chemotherapy (post chemotherapy). The criteria for

either a ‘favorable’ or an ‘unfavorable’ response were applied as published [8]. Reduction of more

than 25% in the largest diameter of the tumor at late enhancement on the interim MRI relative to

the baseline MRI was regarded as a ‘favorable’ response. All other responses were classified as

‘unfavorable’. The largest tumor diameter was assessed in three reformatted planes by one of four

experienced breast MR radiologists (CL, HW, PD, AB). The initial enhancement and late enhancement

were individually measured. The total area of breast tissue including non-enhancing tissue was used

in case of multifocal disease or a diffuse (non-mass) tumor. The reduction in largest tumor diameter

at initial enhancement was calculated by dividing the difference in tumor diameter between interim

and baseline MRI by the tumor diameter at baseline MRI.

Response criteria: microscopy

Three common definitions of pCR were used: no residual invasive tumor in the breast (ypT0/is

ypN0/þ); no residual invasive tumor in both the breast and the lymph nodes (ypT0/is ypN0); and the

absence of any tumor (invasive or non-invasive) in breast and lymph nodes (ypT0 ypN0).

Survival analysis

Relapse-free survival (RFS) was also used as an end point and was defined as the length of time from

the first treatment to local or distant relapse or death by any cause. Ipsilateral ductal carcinoma in

situ, contralateral breast cancer and second primary invasive cancer were not regarded as ‘events’

for this analysis.

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Staging

As substantially more clinical lymph node staging information was available than is used for the

clinical N-staging according to the UICC, we adapted the N-stage to match a more detailed method. A

negative sentinel node was assigned stage cNa; positive sentinel node stage cNb; non-palpable and

fine-needle aspiration (FNA)-positive node stage cNc; axillary palpable and FNA-positive stage cNd;

and periclavicular and FNA-positive stage cNe.

Immunohistochemistry

On average, three ultrasound-guided pre-treatment core biopsies of the primary tumor were taken

using a 14G core needle, after which two biopsies were snap-frozen in liquid nitrogen and stored at

—80◦C for molecular analysis and one biopsy was formalin-fixed and embedded in paraffin for

classification and immunohistochemistry (IHC). Estrogen receptor and progesterone receptor (PR)

were evaluated as positive when at least 10% of tumor cells showed nuclear staining. Human

epidermal growth factor receptor 2 status was scored negative when IHC showed no or only weak or

incomplete membranous staining (score 0 or 1+) or chromogenic in situ hybridization revealed no

amplification after moderate membrane staining (score 2+). Ki-67 was used for assessment of

proliferation status and to assess surrogate intrinsic subtypes [13]. The Mib-1 antibody was used for

determination of Ki-67 status, using the cutoff point of 14% of positive staining. This cutoff point was

determined as it yielded the best separation of luminal A and luminal B tumors, as defined by the

PAM50 algorithm in the subgroup of tumors of which mRNA expression arrays were available. Ki-67

cutoff point was determined by preparing ROC curves comparing results with PAM50 intrinsic

subtypes [14]. As Ki-67 status was not determined for all tumors, histological grade (when available)

was also used for a second definition of ‘surrogate intrinsic subtypes’ [13]. Histological grade was

determined using the Elston and Ellis method [15]. High endocrine responsiveness was defined as at

least 50% of the tumor cell nuclei stained positive, for both ER and PR, in the absence of HER2

amplification [16]. Surrogate definitions of intrinsic subtypes were used, based on IHC. ‘Luminal A’

tumors are ER+ and/or PR+, HER2 - and have <14% of the nuclei staining positive for Ki-67 (or, when

based on histological grade, grade 1 or 2). ‘Luminal B (HER2 -)’ tumors are ER+ and/or PR+, HER2 -

and Ki-67 ≥14% (or histological grade 3) [13].

Statistics

The software program SPSS version 20 (SPSS Inc., Chicago, IL, USA) was used for all analyses. For the

assessment of associations between characteristics and MRI response or pCR, the Fisher’s exact test

was used. Mann–Whitney U-tests were used for the comparison of MRI measured tumor size

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reduction percentage and potential predictive markers. Relapse-free interval analysis was performed

using Kaplan–Meier curves and Cox regression analysis

Results

Patients

A total of 309 patients with ER+ HER2 - breast cancer began neoadjuvant chemotherapy with three

courses of ddAC between October 2004 and March 2012 (Table 1). Of these, 292 patients had an MRI

after the first three courses and were evaluable for response. The second chemotherapy regimen

was selected according to protocol in 275 patients. For 246 patients, all three serial MRI

measurements of the initial enhancement diameter were reviewed (Table 1 and Figure 1). A total of

7 (2.8%) of all 246 patients achieved a pCR (ypT0 ypN0) after six courses. Additional (postoperative)

adjuvant chemotherapy was administered in 43 (17%) out of 246 patients (14 unfavorable

responders, 29 favorable responders) and consisted usually of taxane treatment (12 weekly

administrations of paclitaxel, 80 mg m —2 when the patient was taxane-naive). The median follow-up

was 35 months with a lead follow-up of 98 months. The 5-year relapse free survival for all 246

patients was 87%, with an overall 5-year survival of 96%.

Fig 1. — CONSORT diagram showing MRI evaluations

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Table 1. Patient and tumor characteristics

Number of patients 246 Median age, (range) in years 48 (18-68) Tumor stage cT1 21 cT2 91 cT3 43 cT4 9 N–stage cNa (negative) 49 cNb (FNA negative, sentinel node positive) 40 cNc (ultrasound-guided FNA positive) 50 cNd (palpable nodes, FNA positive) 98 cNe (FNA-positive periclavicular node(s)) 9 Histological grade 1 14

2 95 3 30 Ns a 107 Histology

Ductal 190

Lobular 33 Ductal/lobular 6 Other 17 ER (%)

10–49 8

50–100 177 positive b 5

PR (%)

0–49 108

50–100 132 ND (no PR (%) available) 6 Surrogate intrinsic subtype: based on Ki-67

Luminal A (ER/PR + ; HER2 - ; Ki-67 low) 128

Luminal B/HER2 - (ER/PR + ; HER2 - ; Ki-67 high) 60 ND (no Ki-67 available) 58 Surrogate intrinsic subtype: based on histological grade

Luminal A (ER/PR + ; HER2 - ; grade 1 or 2) 109

Luminal B/HER2 - (ER/PR + ; HER2 - ; grade 3) 30

ND (no reliable grade available a) 107

Abbreviations: ER = oestrogen receptor; FNA = fine-needle aspiration; HER2 = human epidermal receptor 2; ND = not done; PR = progesterone receptor. a Reliable estimation of histological grade is frequently not possible in small core biopsies. b The exact percentage was not available.

Patients and tumor characteristics and interim MRI response

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All three MRI evaluations were available for 246 patients. One hundred and sixty-four patients (67%)

achieved a favorable response as determined by the MRI criteria (over 25% decrease in the largest

tumor diameter of late enhancement) and 82 patients (33%) had an unfavorable response after three

courses of ddAC. A favorable response was more often seen in patients with positive N-stage

(P=0.011), but it was not more frequent in incompletely endocrine-responsive tumors or in tumors of

higher grade or with higher Ki-67 (Table 2).

Interim MRI response and outcome

In 246 patients, 18 pathologic complete remissions of the breast (7%) were observed, 7 complete

remissions of both breast and axilla (3%) and 4 complete remissions of breast and axilla in the

absence of residual carcinoma in situ (2%). A favorable MRI response was associated with a higher

pCR rate than an unfavorable response (P=0.04 for ypT0/is ypN0/þ), but the numbers were very

small. Eight relapse events (10%) occurred in the 82 unfavorably responding patients and 16 relapses

(10%) in the 164 favorably responding ones (NS, P=0.99) (Table 3).

Interim MRI response and serial MRI evaluation

The first three courses of ddAC resulted in a mean tumor size reduction of 31% in 164 favorable

response patients, which was followed by three more courses of ddAC. In 82 unfavorable response

patients who had achieved a mean tumor size reduction of only 12%, a switch to the DC regimen was

made.

The overall radiologic tumor size reduction percentage after six courses of chemotherapy was higher

in patients who had achieved a favorable response on the interim MRI (56%) than in patients who

had not achieved a favorable response (35%). The fractional reduction in tumor size as measured by

MRI over the second set of three courses, however, was similar for both the initially favorable (34%)

and the initially unfavorable (27%) responders (Table 4 and Figure 2). Seven favorably responding

tumors had a radiologic CR on their second MRI, which – by definition – resulted in a tumor size

reduction of 0% after the second course of ddAC.

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Table 2. Patient and Tumor Characteristics and Interim MRI Response (after three courses of neoadjuvant chemotherapy)

MRI favorable response (N=164)

MRI unfavorable

response (N=82)

Characteristic N (%) N (%) P-value

T-stage

0.885 cT1/cT2 112 (68) 57 (70)

cT3/cT4 52 (32) 25 (31)

N-stage

0.011

cN negative 25 (15) 24 (29)

cN positive 139 (85) 58 (71)

Histology

0.112 Lobular 26 (18) 7 (9)

Ductal 120 (82) 70 (91)

Other 18 5

Age (years)

0.412

<50 101 (62) 46 ((56)

≥50 63 (38) 36 (44)

Endocrine responsiveness

0.585 Incomplete (ER or PR < 50%) 74 (47) 35 (43)

High (ER and PR ≥ 50%) 83 (53) 46 (57)

ND 7 1

Surrogate intrinsic subtype (Ki-67)

0.510

Luminal A (< 14) 82 (66) 46 (72)

Luminal B ( ≥ 14) 42 (34) 18 (28)

ND 40 18

Surrogate intrinsic subtype (grade)

1.0 Luminal A (1/2) 73 (79) 36 (78)

Luminal B (3) 20 (22) 10 (22)

ND 71 36

Abbreviations: ER=oestrogen receptor; MRI=magnetic resonance imaging; ND=not done; PR=progesterone receptor. A reduction of over 25% of the late enhancement diameter on the second contrast-enhanced MRI was regarded as a favorable response (Loo et al, 2008).

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Table 3. Association of Interim MRI response after three courses of neoadjuvant chemotherapy with outcome measures

% pCR % pCR % pCR

MRI response

category N

ypT0/is ypN0/+

ypT0/is ypN0

ypT0 ypN0 RFS hazard ratio

(95% CI)

Favorable 164 10 4 2 Ref.

Unfavorable 82 2 1 1 0.995 (0.42–2.33)

P-value A 0.04 0.43 1.0 0.99

Abbreviations: CI=confidence interval; pCR=pathologic complete remission; RFS=relapse-free survival; ypT0/is ypN0/+=no residual invasive tumor in the breast; ypT0/is ypN0=no residual invasive tumor in breast and lymph nodes; ypT0 ypN0=the absence of any tumor (invasive or non-invasive) in breast and lymph nodes. A pCR, Fisher’s exact test; RFS and Cox regression analysis.

Table 4. Mean MRI Tumor Size Reductions by Chemotherapy regimen adaption

MRI response category N

Tumor size reduction (%)

Courses 1, 2 and 3

Courses 4, 5 and 6

Overall

MRI 1 vs 2 MRI 2 vs 3 MRI 1 vs 3

(mean %) (mean %) (mean %)

Favorable

(6 × ddAC) 164 31 34 A 56

Unfavorable

(3 × ddAC, 3 × DC) 82 12 27 35

Abbreviations: DC, docetaxel-capecitabine; ddAC=dose-dense doxorubicin and cyclophosphamide; MRI=magnetic resonance imaging. Patients were evaluated by three MRIs; MRI 1: baseline, before neoadjuvant chemotherapy, MRI 2: interim, after three courses of ddAC, MRI 3: post chemotherapy, after three courses of ddAC or after three courses of DC. A N=157 for the reduction percentage on MRI 2 vs 3 of favorable responders, because seven patients had achieved a complete remission on MRI 2 and were not used for the calculation of this percentage.

75

Fig 2. — Waterfall plots of the MRI tumor size reductions before and after MRI response evaluation.

Each bar represents one of the 246 patients who had three MRI measurements of the breast tumor

(initial enhancement diameters). (A and B) Tumor size reduction in 164 favorable responders to the

first three courses of ddAC (A), and to the second three courses of ddAC (B). (C and D) Tumor size

reduction of 82 unfavorable responders to the first three courses of ddAC (C), and to the three

courses of DC (D).The tumor size reductions after the first three courses are – by definition – smaller

for the ‘unfavorable responders’ than for the ‘favorable responders’. Over courses 4 through 6, after

regimen adaptation in case of unfavorable response, the tumor size reductions are similar for the

two response categories (P=0.157).

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Patient and tumor characteristics and outcome

The predictive and prognostic impact of tumor characteristics was analyzed with pCR and RFS as end

points (Table 5). Lower age was associated with a higher pCR rate (ypT0/is) (10.2% vs 3.0%, P=0.044).

The effect of age persisted when the end point was ypT0/is ypN0 but was no longer significant when

the strictest pCR definition was used (ypT0 ypN0). The relapse-free survival was only affected by age,

resulting in a worse prognosis when diagnosed over the age of 50 years (HR 3.5 (95% CI: 1.5–8.3),

P=0.004). The use of surrogate intrinsic subtypes gave inconclusive results. The luminal B subtype

based on grade was associated with a higher pCR rate (ypT0/is, 16.7% vs 4.6%, P=0.038). There was

no difference in relapse-free survival between surrogate intrinsic subtypes based on grade. Surrogate

intrinsic subtypes based on Ki-67 resulted in a higher pCR rate (ypT0/is) for luminal B tumors

(P=0.056) but in a worse relapse-free survival rate (HR 2.8 (95% CI: 1.0–8.1), P=0.049).

Surrogate intrinsic subtypes

Tumors were classified as either surrogate luminal A or surrogate luminal B; the distinguishing

feature between these was either the Ki-67 staining percentage or, alternatively, histological grade

(I/II vs III) [13]. The optimal Ki-67 cutoff point for differentiating the luminal A and luminal B

surrogate intrinsic subtypes was determined in 60 tumor samples, of which both the Ki-67

percentage and the PAM50 intrinsic subtype definition (determined by mRNA expression microarray

analysis) was available. Any cutoff point between 10 and 15% yielded essentially the same result and

the usual cutoff of 14% was therefore used. Cohen’s k was calculated to establish the degree of

concordance between the two definitions of surrogate luminal A and luminal B vs the PAM50

classifier. The k values were 0.48 and 0.31 for Ki-67% and histological grade, respectively.

Discussion

The use of adjuvant or neoadjuvant chemotherapy in ER+ HER2 - breast cancer (‘luminal tumors’) is

challenging. It is clear that this subgroup of breast cancers includes tumors that are not responsive to

chemotherapy [13] and even those that only infrequently achieve a pCR. As a group, however, the

luminal subtype does derive benefit from (neo) adjuvant chemotherapy, including an important

survival advantage [17]. One strategy to improve the efficacy of chemotherapy could be, at least in

theory, neoadjuvant chemotherapy with adaptation of the regimen to the response of the primary

tumor.

78

We have reviewed our single-institution experience of neoadjuvant chemotherapy in ER+ HER2 -

tumors, unselected for (other) biological features. The treatment strategy consisted of initial

chemotherapy with three courses of ddAC with a response adapted approach; if a satisfactory

response was achieved, as defined by at least a 25% decrease of the late enhancement diameter on

MRI, the ddAC was continued to a total of six courses. If not, the treatment plan was changed to

three courses of DC, a combination of a taxane and an antimetabolite (docetaxel and capecitabine).

A total of 309 patients was started on this approach and 246 patients were evaluated by three serial

MRIs. Here, we describe the efficacy of this strategy in relation to the characteristics of the primary

tumors.

Our neoadjuvant program has a non-randomized design, with the primary objectives to develop tests

that are predictive of response and to refine the techniques to monitor response during treatment.

Contrast-enhanced MRI, although the best imaging method currently available to evaluate primary

breast cancer [6,7] was shown not to be a very reliable predictor of pathologic response [9].

Nevertheless, an ‘unfavorable response’ on the interim MRI was associated with a lower rate of pCR

of the breast (ypT0/is) (Table 3). For other pCR definitions and for relapse-free survival, the results in

the initially favorable responder group were similar to those of the initially unfavorable responder

group, which switched to the presumably non-cross-resistant regimen.

The validity of this adaptive strategy cannot be established from our non-controlled study, but some

support for the concept has been presented in a recent analysis of the German Breast Group [3]. We

did, however, obtain serial MRI measurements before the initiation of chemotherapy, and also after

three and six courses. If the switch to a docetaxel-based regimen in unfavorably responding patients

would indeed be effective, one would expect more shrinkage of the tumor between the interim and

post chemotherapy MRI in this group than had been observed between the baseline and the interim

MRI. This is indeed what was found (Table 4 and Figure 2).

Unsurprisingly, the reduction in diameter of the breast tumor at initial enhancement after the first

three courses of ddAC was less (12%) in the unfavorably responding patients than in the responding

ones (31%), as the ‘unfavorable’ group was defined by a closely related MRI parameter, the

reduction in diameter of the tumor at late enhancement. The second set of three courses, however,

led to 27% shrinkage in the previously unfavorably responding patients, which is comparable to the

initial shrinkage in favorable responders (31%) and the second set of three courses in the initially

favorable responders (34%). Apparently, DC was able to induce a satisfactory response, when ddAC

was not (Figure 2). The average total percentage of tumor shrinkage remained lower in the initially

unfavorable responders (35%) than in the favorable responders (56%), despite the efficacy of the

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alternative chemotherapy regimen. This could very well be the result of having received only three

effective courses of chemotherapy, whereas the (initially) favorable responders had received six

effective courses, with a percentage of tumor shrinkage during the second set of three courses (34%)

that was similar to that of courses 1 through 3 (31%). If this explanation is correct, one might

consider extending the DC therapy in initially unfavorable responders to six rather than three

courses, to obtain a similar total reduction in tumor size. Evaluation of such a strategy will require

randomized studies.

Alternative explanations for the apparent efficacy of the adaptive strategy are, of course,

conceivable. For example, some tumors (perhaps slowly proliferating ones) could require more time

than others to shrink in size but could, given time, eventually achieve the same reduction in size as

more rapidly responding ones. This could be an alternative explanation for the data in Table 2. We

have, however, found very few differences between the tumors with favorable and unfavorable

responses after three courses of ddAC (Table 2). In contrast to what one might expect, unfavorable

response tumors did not contain more low-grade or ‘highly endocrine-responsive’ tumors. There was

no prognostic impact of the early responsiveness, although such an effect could possibly have been

obscured by the administration of additional, postsurgical adjuvant chemotherapy. However, the

percentage of patients receiving additional chemotherapy was equal in the two response categories:

14 (17%) of the 82 unfavorable responders and 29 (18%) of the 164 favorable responders.

For the whole group, the neoadjuvant chemotherapy regimen and strategy performed close to what

one would expect based on the results of others. For instance, the predicted pCR percentage was

consistent with the prediction by the nomogram published by Colleoni et al [18]. This model is based

on three characteristics of the tumor, the percentage of ER, PR and Ki-67, and the number of

chemotherapy courses administered.

An important question is how the adaptation strategy could be optimized. First of all, the methods to

monitor response need refining. Magnetic resonance imaging results are unreliable to predict pCR in

this subgroup [9]. Recently published data from our group [19] and from others suggest that the

addition of or combination with PET/CT could improve the accuracy of the response evaluation [20].

In addition, more appropriate outcome measures than pCR should be defined for ‘luminal’ tumors,

that can be assessed in a replicable manner after the completion of local treatment, and that

correlate robustly with relapse-free survival. Even if the pCR, regardless of its definition, would be

predictive of survival, the rate of occurrence is so low that it would be of little use in ER+ HER2 -

breast cancer.

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In conclusion, this analysis of a series of consecutive patients who underwent neoadjuvant

chemotherapy using a response adapted chemotherapy approach suggests that a change in

chemotherapy regimen may still be effective when the initial chemotherapy is not. It thereby

supports an analysis of the cumulative data from the German Breast Group that suggested a survival

advantage for a switch of chemotherapy regimen in nonresponding patients. If correct, a response

adaptive chemotherapy selection in the neoadjuvant setting might further improve the cure rate of

patients with larger breast cancers, underscoring the need for controlled trials of this approach.

Acknowledgements

We thank Anita Paape, Marjo Holtkamp and Margaret Schot for their contribution to this study. A

part of this study was performed within the framework of CTMM, the Center for Translational and

Molecular Medicine (http: //www.ctmm.nl), project Breast CARE (grant no. 03O-104).

References

1. Mauri D, Pavlidis N, Ioannidis JP (2005) Neoadjuvant versus adjuvant systemic treatment in breast cancer: a meta-analysis. J Natl Cancer Inst 97 (3):188-194. doi:10.1093/jnci/dji021 2. Smith IC, Heys SD, Hutcheon AW et al. (2002) Neoadjuvant chemotherapy in breast cancer: significantly enhanced response with docetaxel. J Clin Oncol 20 (6):1456-1466 3. von Minckwitz G, Untch M, Loibl S (2013) Update on neoadjuvant/preoperative therapy of breast cancer: experiences from the German Breast Group. Current opinion in obstetrics & gynecology 25 (1):66-73. doi:10.1097/GCO.0b013e32835c0889 4. Rosen EL, Blackwell KL, Baker JA et al. (2003) Accuracy of MRI in the detection of residual breast cancer after neoadjuvant chemotherapy. AJR Am J Roentgenol 181 (5):1275-1282

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5. Prati R, Minami CA, Gornbein JA, Debruhl N, Chung D, Chang HR (2009) Accuracy of clinical evaluation of locally advanced breast cancer in patients receiving neoadjuvant chemotherapy. Cancer 115 (6):1194-1202. doi:10.1002/cncr.24154 6. Yeh E, Slanetz P, Kopans DB et al. (2005) Prospective comparison of mammography, sonography, and MRI in patients undergoing neoadjuvant chemotherapy for palpable breast cancer. AJR Am J Roentgenol 184 (3):868-877 7. Shin HJ, Kim HH, Ahn JH et al. (2011) Comparison of mammography, sonography, MRI and clinical examination in patients with locally advanced or inflammatory breast cancer who underwent neoadjuvant chemotherapy. Br J Radiol 84 (1003):612-620. doi:10.1259/bjr/74430952 8. Loo CE, Teertstra HJ, Rodenhuis S et al. (2008) Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy: initial results. AJR Am J Roentgenol 191 (5):1331-1338 9. Loo CE, Straver ME, Rodenhuis S et al. (2011) Magnetic resonance imaging response monitoring of breast cancer during neoadjuvant chemotherapy: relevance of breast cancer subtype. J Clin Oncol 29 (6):660-666. doi:10.1200/jco.2010.31.1258 10. von Minckwitz G, Untch M, Blohmer JU et al. (2012) Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol 30 (15):1796-1804. doi:10.1200/jco.2011.38.8595 11. Rodenhuis S, Mandjes IA, Wesseling J et al. (2010) A simple system for grading the response of breast cancer to neoadjuvant chemotherapy. Ann Oncol 21 (3):481-487 12. Lips EH, Mulder L, de Ronde JJ et al. (2012) Neoadjuvant chemotherapy in ER+ HER2- breast cancer: response prediction based on immunohistochemical and molecular characteristics. Breast Cancer Res Treat 131 (3):827-836. doi:10.1007/s10549-011-1488-0 13. Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ (2011) Strategies for subtypes--dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol 22 (8):1736-1747. doi:10.1093/annonc/mdr304 14. Parker JS, Mullins M, Cheang MC et al. (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27 (8):1160-1167. doi:10.1200/jco.2008.18.1370 15. Ellis IO, Galea M, Broughton N, Locker A, Blamey RW, Elston CW (1992) Pathological prognostic factors in breast cancer. II. Histological type. Relationship with survival in a large study with long-term follow-up. Histopathology 20 (6):479-489 16. Colleoni M, Bagnardi V, Rotmensz N et al. (2009) Increasing steroid hormone receptors expression defines breast cancer subtypes non responsive to preoperative chemotherapy. Breast Cancer Res Treat 116 (2):359-369. doi:10.1007/s10549-008-0223-y 17. Peto R, Davies C, Godwin J et al. (2012) Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100,000 women in 123 randomised trials. Lancet 379 (9814):432-444. doi:10.1016/s0140-6736(11)61625-5 18. Colleoni M, Bagnardi V, Rotmensz N et al. (2010) A nomogram based on the expression of Ki-67, steroid hormone receptors status and number of chemotherapy courses to predict pathological complete remission after preoperative chemotherapy for breast cancer. Eur J Cancer 46 (12):2216-2224. doi:10.1016/j.ejca.2010.04.008 19. Koolen BB, Pengel KE, Wesseling J et al. (2013) FDG PET/CT during neoadjuvant chemotherapy may predict response in ER-positive/HER2-negative and triple negative, but not in HER2-positive breast cancer. Breast 22 (5):691-697. doi:10.1016/j.breast.2012.12.020 20. Tateishi U, Miyake M, Nagaoka T et al. (2012) Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic contrast-enhanced MR imaging--prospective assessment. Radiology 263 (1):53-63. doi:10.1148/radiol.12111177

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PART 2

After Neoadjuvant

Chemotherapy

85

CHAPTER 5

MRI-model to guide the surgical treatment in breast cancer

patients after neoadjuvant chemotherapy

Marieke E. Straver1, Claudette E. Loo2, Emiel J.T. Rutgers1, Hester S.A.

Oldenburg1, Jelle Wesseling3, Marie-Jeanne T.F.D. Vrancken Peeters1, and

Kenneth G.A. Gilhuijs2,5


1Department of Surgical Oncology






Ann Surg. 2010;251:701-707

https://cc2umpdq5cjidifkh79y8atc.sec.amc.nl/science/article/pii/S0960977613000027











87

Abstract

Objective

The aim of this study was to establish a magnetic resonance imaging (MRI)-based interpretation

model to facilitate the selection of breast-conserving surgery (BCS) after neoadjuvant

chemotherapy (NAC).

Summary of Background Data:

Although MRI is the most reliable method to assess tumor size after NAC, criteria for the correct

selection of surgery remain unclear.

Method

In 208 patients, dynamic contrast-enhanced MRI was performed before and after NAC. Imaging was

correlated with pathology. Differences <20 mm in tumor extent were considered to accurately

indicate disease extent. Multivariate analysis with cross-validation was performed to analyze

features affecting the potential of MRI to correctly indicate BCS (i.e., residual tumor size <30 mm on

pathology).

Results

The accuracy of MRI to detect residual disease was 76% (158/208). The positive and negative

predictive value of MRI were 90% (130/144) and 44% (28/64), respectively. In 35 patients (17%), MRI

underestimated the tumor size by >20 mm and in 27 patients (13%) this would have lead to

incorrect indication of BCS. The features most predictive of indicating feasibility of BCS in tumors

<30 mm on preoperative MRI were the largest diameter at the baseline MRI, the reduction in

diameter and the tumor subtype based on hormone-, and human epidermal growth factor

receptor 2-status (area under the curve: 0.78).

Conclusions

Optimal selection of patients for BCS after NAC based on MRI should take into account (1) the tumor

size at baseline (2) the reduction in tumor size, and (3) the subtype based on hormone-, and human

epidermal growth factor receptor 2-status.

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Introduction

Neoadjuvant chemotherapy (NAC) is increasingly being used in the management of breast cancer.

A major clinical benefit is down staging of the tumor. As a result, inoperable advanced tumors may

become operable and patients with large operable tumors may be offered breast-conserving

surgery (BCS)[1].

The decision to undertake BCS after NAC is complex and influenced by both the surgical

considerations and patient’s desires. Surgical considerations involve the breast-tumor index,

age, multifocality, localization, histology, and the presence of ductal carcinoma in situ (DCIS) [2].

Recently, Chen et al showed that the appropriate decision to select the surgical procedure

must be based on whether tumor-free margins can be achieved [3]. Therefore, precise

preoperative assessment of the residual tumor extent after NAC is crucial to plan the surgical

management of the patient. Proper therapy selection minimizes the rates of unnecessary

mastectomies, re-excisions, and associated distress to the patient.

The correlation between the extent of the tumor at pathology and preoperative assessments of

the size obtained by physical examination and conventional imaging is impaired by chemotherapy-

induced necrosis and fibrosis [4-6]. Several studies have shown that contrast-enhanced

magnetic resonance imaging (MRI) is superior to conventional methods to assess the extent of

residual disease [7-10].

The ability of MRI to distinguish fibrous from vascularized tissue after the administration of

contrast medium underlies this advantage.

Despite its complementary value over conventional techniques, the precision of MRI to visualize

the extent of residual disease in the breast after NAC still remains controversial [8,11]. The aim

of the present study was (1) to assess the accuracy of MRI in detecting residual disease, (2) to

assess the potential of MRI to guide selection of surgery after neoadjuvant chemotherapy, and

(3) to explore MRI features that improve the patient selection for BCS after NAC.

Methods

Patients

In our institute, patients with invasive breast cancer greater than 3 cm and/or involved lymph

nodes are typically eligible for NAC. Patients who had a MRI before and after NAC and who were

treated with surgery after NAC were eligible for this retrospective study (n = 208). All patients

received NAC between 2000 and 2008 in one of 2 ongoing clinical studies or received treatment

according to the standard arm of these trials. Monitoring of tumor response before, during and,

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after the administration of NAC with dynamic contrast enhanced MRI was part of the study

protocol [12]. The clinical studies were approved by the institutional ethical committee, and

informed consent was obtained from all patients.

Treatment

The treatment regimen depended on the presence or absence of human epidermal growth factor

receptor 2 (HER2) amplification. Preoperative chemotherapy for HER2-negative tumors employed

one of the following regimens: (dose dense) AC (6 cycles of doxorubicin and cyclophosphamide), 6

cycles of doxorubicin and docetaxel, or 6 cycles of capecitabine and docetaxel or the combination

of 3 cycles of dose dense AC and 3 cycles of capecitabine and docetaxel. For HER2-positive tumors, the

regimens included (dose dense) AC and after 2005, paclitaxel, trastuzumab, and carboplatin. After the

last course of chemotherapy patients underwent BCS or mastectomy. In all patients a marker was

placed in the tumor prior to NAC for surgical detection and to optimally examine the tumor- bearing

area in the surgical specimen after NAC. Recommendation for surgery was made by a

multidisciplinary team of breast cancer specialists including surgeons, radiologists, pathologists,

radiation, and medical oncologists. Typically, residual breast cancer >3 cm, multicentric breast cancer

(in more than one quadrant) and extensive microcalcifications were considered a contraindication for

BCS.

MRI Acquisition and Interpretation

Initially MRI was performed on a 1.5 T Magnetom Vision scanner with a dedicated bilateral phased-

array breast coil (Siemens, Erlangen, Germany). After March 2007, MRI was performed on a 3.0 T

Achieva scanner with a dedicated 7-channel sense breast coil (Philips Medical Systems, Best, The

Netherlands). Images were acquired with the patient in prone position. The dynamic protocol started

with an unenhanced coronal 3D T1-weighted low-angle shot sequence (Flash 3D). Contrast

(gadolinium chelate) was administered intravenously using a bolus injection (2 mL/s) at a dose of 0.1

mmol per kilogram of bodyweight followed by a 20 mL saline solution flush. Subsequently, 5

consecutive series at 90-second intervals were acquired. Interpretation of breast MR images was

done using a viewing station that permitted simultaneous viewing of 2 series reformatted and linked

in 3 orthogonal directions [12,13]. One radiologist (C.E.L.) with experience in reading breast MRI

assessed all cases. She was unaware of the pathology outcome. The largest diameter of the tumor

was assessed at the initial enhancement series (90 seconds after contrast injection) and in the late

enhancement series (450 seconds after contrast injection). Largest diameters were measured in 3

reformatted planes: sagittal, axial, and coronal. In cases of rim enhancement, the necrotic core was

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included in the measurement of the largest diameter. In cases of multinodular or diffuse tumor

growth, measurement of the complete enhancing area, including intermediate (non- enhancing)

tissue occupied by tumor, was assessed on maximum intensity projection images. Patients with no

enhancement in the original tumor area were radiologically considered as complete responders. In

addition, morphology of enhancement was scored in 3 categories: mass, multinodular, and diffuse.

The change in pattern between scans before and after chemotherapy was denoted in 5 categories:

stable disease, shrinking mass, diffuse reduction, reduction to small residual foci in the original tumor

area, and no enhancement (complete remission).

Mathematical Model to Assess the Potential of MRI to Select the Surgical Treatment

To assess the accuracy of MRI in visualizing the extent of residual tumor after NAC, the largest tumor

diameter at initial enhancement at preoperative MRI was compared with the measurements of

residual tumor in the resection specimen at pathology. Taking typically intended excision margins of

10 mm into account, MRI was considered to accurately indicate disease extent when the size

discrepancy between the MRI-visible lesion and the tumor extent at pathology was <20 mm (Fig.

1). In patients with the largest tumor diameter of <30 mm at MRI after NAC, BCS was considered

to be preoperatively feasible. In patients with a discrepancy >20 mm, we assessed whether MRI

correctly indicated BCS. A correct indication of BCS was defined as a preoperatively feasible BCS

combined with tumor size <30 mm at pathology (i.e., a true-positive selection of BCS).

Conversely, preoperatively feasible BCS and tumor size >30 mm at pathology was considered an

incorrect indication of BCS (i.e., a false-positive selection of BCS).

Fig 1. — A tumor excision with isotropic

margins may be incomplete when the

difference in largest diameter of the tumor

at preoperative magnetic resonance imaging

(MRI) and at pathology exceeds 20 mm.

Pathologic

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Examination

Prior to neoadjuvant treatment, core biopsies

of the breast tumor (14G) were taken under ultrasound guidance. Tumors were classified into 3

subgroups according to their receptor status using immunohistochemical staining: (1) estrogen

receptor (ER) positive and HER2-negative tumors, (2) triple-negative tumors (ER-negative,

progesterone receptor-negative and HER2-negative), and (3) HER2-positive tumors. The surgical

specimens were sectioned in 3 mm thick slices and processed using standard protocols. A pathologic

complete remission of the primary tumor was defined as the absence of invasive carcinoma at

microscopic examination, regardless of the presence of carcinoma in situ. In cases with evidence of

residual invasive cancer, the diameter of the tumor was determined within or across slices,

whichever was larger.


To assess the accuracy of MRI in detecting residual disease, we determined the sensitivity: TP/(TP +

FN), specificity: TN/(TN + FP), positive predictive value: TP/(TP + FP), negative predictive value:

TN/(TN+FN), and overall accuracy: (TP +TN)/total number of cases. SPSS version 15.1 (SPSS Inc,

Chicago, IL) and Matlab R12 (TheMathWorks) were used to analyze factors associated with true-

positive and false-positive selection of BCS according to the definitions stated above. Univariate

analyses were performed using Student’s t tests, Mann-Whitney U exact tests, and Fisher exact tests.

A P value of 0.002 was defined as a significant test result (P = 0.05 adjusted for the number of tested

characteristics using the Bonferroni correction). A larger subset of features with P value <0.3 were

included in the multivariate analysis: largest diameter at baseline (initial and late enhancement),

the intensity of the enhancement, type of lesion at baseline MRI, reduction in largest diameter

after NAC (initial and late enhancement), size at MRI after neoadjuvant chemotherapy, pattern of

tumor decline, and histologic and molecular subtype. For multivariate analysis, binary logistic

regression with feature selection by double cross-validation was used[12]. Receiver operating

characteristic (ROC) curve analysis of the logistic model was employed to establish its diagnostic

accuracy (area under the curve). We chose a point on the ROC curve corresponding to a maximum of

5% false-positive interpretations of the model (i.e., departure from BCS towards mastectomy while

the actual tumor size was smaller than 30 mm). This operating point was translated into a model

to guide surgical treatment planning after neoadjuvant chemotherapy.

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Results

Patient and tumor characteristics of the 208 patients are presented in Table 1.

Table 1. Patients and Tumor Characteristics

Total N = 208

No. (%)

Mean age 46 yr Range 23–76 yr T stage (prior to NAC)

T1 6 (3) T2 108 (52) T3 70 (34) T4 24 (11) pN stage (prior to NAC)

pN0 (SNB-) 31 (15) pN1 (SNB+/FNA+) 138 (66) pN3 (sub/supraclavicular) 12 (6) pNX (cN0) 27 (13) Histology

Ductal 168 (81) Lobular 25 (12) Others 15 (7) Subtype (based on receptor status)

ER+ (ER+, HER2-) 103 (49) TN (ER-, PR-, HER2-) 47 (23) HER2+ 58 (28) Primary systemic therapy

Anthracycline-like 102 (49) Anthracycline-taxane 52 (25) Capecitabine/docetaxel 16 (8) PTC 38 (18) Surgery breast

Mastectomy 112 (54) BCS 96 (46)

SNB indicates sentinel node biopsy; FNA, fine needle aspiration; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2; TN, triple negative; PTC, paclitaxel, trastuzumab, carboplatin; BCS, breast conserving surgery; NAC, neoadjuvant chemotherapy.

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Accuracy to Detect Residual Disease

After NAC, MR imaging showed a complete remission (no enhancement) in 64 of the 208

patients. Among these 64 patients, 36 (56%) had residual disease at pathologic examination

varying from microscopic residual disease to regions from 1 to 80 mm. Of the 144 patients who

had residual disease on MRI, 14 patients had no invasive tumor cells at pathologic examination.

In 5 of these 14 patients, only DCIS was found in the resection specimen, which is difficult to

distinguish from invasive tumor using MRI. Overall the sensitivity of MRI to detect invasive

residual disease was 78% (130/166, 95% confidence interval: 0.71– 0.83)). The specificity was

67% (28/42, 95% confidence interval: 0.51– 0.79) and the accuracy was76% (158/208). The

positive and negative predictive value were 90% (130/144) and 44% (28/64), respectively.

The Potential of MRI to Guide Selection of Surgery after Neoadjuvant Chemotherapy

In 46/208 patients (22%), the difference between tumor size on MRI and tumor size on

pathology was more than 20 mm. In 17% (36/208) of these patients, MRI incorrectly indicated

the type of surgical treatment when considering the pathology (Fig. 2). Solely based on the MRI,

27 patients would have incorrectly undergone BCS (disease extent at final MRI <30 mm and

residual disease extent at pathology >30 mm). In 9 patients, MRI alone would have led to

mastectomy (extent >30 mm) while the actual extent at pathology was <30 mm with clear

margins. Thus, MRI correctly indicated the surgical treatment in 172 patients (83%). Incorrect

indication of the surgical treatment was mainly caused by underestimation of disease extent

(27/208).

Fig 2. —The potential of MRI to guide selection of surgery after neoadjuvant

chemotherapy. Underestimation of the tumor size by MRI with >20 mm is observed

in17% of the patients.

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In 13% of the patients, underestimation lead to an unjustified selection of breast-

conserving surgery (BCS).Overestimation of the tumor size with >20 mm is observed

in 5% of the patients and in 4% overestimation lead to an unjustified mastectomy (MST).

Variables Affecting the Efficacy of MRI on Surgical Planning

Additionally, we analyzed variables that affected the efficacy of MRI to yield a correct indication

of surgical treatment. The largest diameter of the late enhancement at baseline was

significantly smaller in cases where the indicated type of surgery was justified. In the group with

correctly indicated surgery, the largest diameter was 38 mm (standard deviation: 19 mm), and

in the group with incorrectly indicated surgery it was 49 mm (standard deviation: 27 mm), P =

0.004. This is partly caused by a larger a priori chance of being eligible for BCS when the tumor is

smaller. Univariate analysis (Table 2) showed that the following variables also significantly

influenced the accuracy of MRI: (1) type of lesion on baseline MRI, (2) pattern of tumor decline,

and (3) histologic subtype.

Table 2. Univariate Analysis: Variables Influencing the Accuracy of MRI

MRI indicated

Incorrect BCS

Incorrect MST

Total Incorrect

treatment Indication Indication

N= 208 N=36 N=27 N=9 P- value

Type of lesion on baseline

0.001 Massa 79 6 (8%) 6 0

Diffuse 59 19 (32%) 15 4

Multifocal 70 11 (16%) 6 5

Pattern of decline

0.006

Stable disease 28 1 (4%) 0 1

Shrinking mass 40 4 (10%) 3 1

Diffuse decline 29 5 (17%) 4 1

Small foci 43 11 (27%) 5 6

Complete remission 64 15 (23%) 15 0

Other 4 0

Histology

<0.001 Ductal 168 21 (13%) 13 8

Lobular 25 12 (48%) 12 0

Other 15 3 (20%) 2 1

BCS indicates breast-conserving surgery; MST, mastectomy

MRI-Model for Surgical Planning After Neoadjuvant Chemotherapy

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Because underestimation of residual disease was a common pitfall in the assessment with MRI, we

explored the variables causing incorrect indication of BCS in a multivariate analysis. Focusing at

correct indication of BCS, 3 variables were significant at multivariate analysis: the largest diameter of

late enhancement at baseline, reduction in largest diameter of the initial enhancement, and the

subtype based on hormone receptor and HER2 status. The sensitivity of the corresponding logistic

model at the 5% threshold for false-positive departures from BCS was 44%. The operating point

on the ROC curve was chosen with a false positive fraction of 5%, because we aimed to minimize the

number of patients eligible for BCS to be unnecessary switched to a mastectomy. Hence, the model

suggests that incorrect indication of BCS at MRI may be reduced with 44%. The MRI model (Fig. 3)

shows that the accuracy of MRI is low in ER-positive tumors, increases in HER2-postive tumors, and is

high in triple negative tumors.

Fig 3. —Multivariate model to guide surgical decision making in tumors ≤ 30 mm at MRI after

neoadjuvant therapy. Given the current typical indication for BCS (largest tumor diameter on

final MRI ≤ 30 mm), the conditions are shown when to assume an incorrect decision based on

5% false-positive departures to MST. The left line indicates the cut-off value for estrogen

receptor (ER)-positive tumors. BCS is indicated under the line, MST is indicated above the line.

The line in the middle shows the cut off for human epidermal growth factor receptor 2-positive

tumors and the right line indicates the cut off for triple-negative tumors. The gray area

represents tumors > 30 mm on final MRI, which are typically indicated for MST.

Moreover, the model shows that the reduction in tumor size is inversely related to the accuracy of

MRI. MRI accurately indicates feasibility of BCS when a small reduction is observed, but is less

accurate when a complete remission (100% reduction) is observed. Finally, the tumor size at baseline

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is an important variable; small tumors have a higher probability to be correctly selected for BCS. For

example, the model shows that an ER-positive patient with a baseline tumor of 6 cm and complete

remission at MRI (100% reduction) is preferably treated with a mastectomy, whereas a patient with a

triple-negative tumor of 6 cm and a complete remission on MRI may be treated with BCS. Figure 4

shows the data stratified by subtype. The model cut-off lines produced enriched groups of correct

BSC selection (crosses above the line) at low false-positive rate (open dots above the line). Note that

the model has most effect on ER-positive tumors, but has less impact on triple negative tumors,

because MRI is already accurate for this subgroup.

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Fig 4. —The predictive value of the model stratified by subtypes. In patients with ER-positive tumors (A), MRI

incorrectly indicated BCS in 14 patients (crosses). In human epidermal growth factor receptor 2-positive

patients (B), and triple-negative patients (C), MRI incorrectly indicated BCS in 6 and 2 patients (crosses),

respectively. The model cut-off lines produced enriched groups of incorrect BCS indication (crosses above

line) at low false-positive rate (open dots above line), which has most effect on ER-positive tumors.

98

Discussion

In this report, the accuracy of MRI after NAC is described in a series of 208 patients treated with

NAC. The accuracy in detecting the presence of residual disease after NAC was 76% (158/208).

In 83% of the patients MRI indicated the correct surgical treatment. Most incorrect indications

were due to underestimation of the residual disease. Therefore, we assessed which tumor

characteristics are most likely to cause such underestimation, and established a model to

improve the selection of patients for BCS. This model includes (1) the tumor size at baseline, (2)

the reduction in tumor size, and (3) the subtype based on hormone receptor and HER2

amplification. Although prior studies showed superior ability of contrast- enhanced MRI to

visualize breast-cancer extent compared with conventional breast imaging (mammography and

ultrasonography) [7-10], recent studies performed primarily outside the neoadjuvant setting

have not yet demonstrated significant reduction in overall rates of incomplete tumor excision

after MRI [14,15]. It is yet to be determined whether this ambiguity is explained by residual

inaccuracy to depict disease extent, or inaccuracy to translate preoperative MRI findings to the

patient on the operating table.

In this study, we showed that the accuracy of MRI in depicting disease extent may be affected by the

disruptive down- stream effects of the chemotherapy agents on the neovascular tumor bed (which

MRI visualizes). As a result MRI was limited in the prediction of a complete remission; the negative

predictive value was 44% (28/64). The decision to omit surgical treatment can therefore not be based

on a complete response assessed at MRI. The underestimation may be caused by the relatively low

spatial resolution which limits the ability to detect microscopic disease, small scattered tumor cells,

and changes in MRI signal intensity affected by residual neovasculature. Despite this limitation, MRI

correctly indicated the surgical treatment, BCS versus mastectomy, in 83% of the patients. Hence, the

relatively low negative predictive value of the MRI will not necessarily result in incomplete breast

surgery if a representative amount of tumor is removed from the appropriate region during BCS.

Therefore, it is crucial to localize the tumor before the start of NAC with a marker.

In addition to its ability to detect residual disease, we analyzed the potential of MRI to indicate

breast-conserving therapy. In the setting of primary surgery, it is typically accepted that patients with

tumors <30 mm on MRI may be suitable for BCS [16]. After NAC we showed, however, that 15%

of these patients were not suitable for BCS due to larger than anticipated extent of disease at

pathology. Especially when a complete remission is observed on MRI after neoadjuvant

chemotherapy, it remains questionable which type of surgery must be performed–mastectomy or

BCS. To improve the selection of therapy, a multivariate model was explored taking factors into

consideration that affected the accuracy of MRI. It is critical to note that this model assumes the BCS

99

criterion that the tumor on the final MRI is smaller than 30 mm. The first variable that affected the

accuracy of MRI was the largest diameter of late enhancement on MRI before the start of

neoadjuvant chemotherapy. This characteristic is a combination of morphology and kinetics

associated with tumor vascularization. The second variable was the reduction in tumor size after

neoadjuvant chemotherapy. In agreement with this observation, Rieber et al showed that the

response of the tumor was inversely correlated with the accuracy to determine the size of residual

tumor at MRI, especially in the complete responders [11].

The third variable of our model was the type of tumor based on hormone and HER2 status. Comparable

results are obtained in a recent study by Chen et al. They showed that MRI could predict a pathologic

complete remission with higher accuracy in HER2-positive disease, but had a higher false-negative rate in

HER2-negative disease [17]. Addition- ally, we show that within the HER2-negative tumors, the accuracy

is much higher in triple-negative tumors compared with ER-positive tumors. This may be explained by

the differences in sensitivity to systemic therapy between HER2-positive and triple-negative tumors

compared with ER-positive patients [18,19]. It should be considered, however, that patients with

HER2-positive tumors included after 2005 received neoadjuvant trastuzumab in combination with

chemotherapy, whereas patients included prior to 2005 did not. Therefore, it may be argued that

the model should be validated in a large cohort of HER2-positive, trastuzumab-treated patients. It is

likely that the accuracy of MRI will further improve when all HER2-positive patients are treated with

trastuzumab. In contrast to the positive effect on the accuracy of MRI in tumors treated with

trastuzumab, recent studies suggests that antiangiogenic agents, like bevacizumab and taxane-

containing regimens may negatively influence the accuracy of MRI [17,20].

To create the model, a conservative cut-off value was chosen to balance the true-positive rate

against a low false-positive fraction, i.e., a low rate (5%) of unnecessary switches to mastectomy.

Consequently, only 44% of the patients in whom BCS was incorrectly indicated could be

identified. Another way of considering this is that almost half of the number of the patients may

be spared a re-excision or completion mastectomy, compared with the current clinical practice

where all patients with tumors smaller than 30 mm on final MRI would be treated with BCS. In

the current study we employed multivariate analysis rather than considering individual factors

separately. Hence, the model was aimed at extracting complementary information from clinical,

imaging, and core histology features, rather than focusing on a single most predictive feature which

is typically pursued in other studies [11,17,21,22].

100

Future validation is, however, needed before implementing the model in clinical practice. Other

variables, like lobular subtype, multifocality, and a diffuse growing pattern have also been shown

to influenced the accuracy of MRI and have been considered in surgical decision making

[8,17,20,23]. The presence of DCIS, patients wish and prognostic predictors of loco regional

recurrences should be taken into account [24,25].

In conclusion, we show that underestimation is the most common pitfall of MRI after

neoadjuvant chemotherapy, leading to an incorrect indication for BCS in 15% of the patients.

This may be improved by using criteria that include the tumor size at baseline MRI, the

reduction in tumor size and the tumor subtype based on hormone receptor and HER2-status.

Acknowledgments

The authors thank all surgeons, radiologists, and pathologists who participated in this study for

their input and support.

References

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7. Boetes C, Mus RD, Holland R et al. (1995) Breast tumors: comparative accuracy of MR imaging relative to mammography and US for demonstrating extent. Radiology 197 (3):743-747. doi:10.1148/radiology.197.3.7480749 8. Rosen EL, Blackwell KL, Baker JA et al. (2003) Accuracy of MRI in the detection of residual breast cancer after neoadjuvant chemotherapy. AJR Am J Roentgenol 181 (5):1275-1282 9. Bhattacharyya M, Ryan D, Carpenter R, Vinnicombe S, Gallagher CJ (2008) Using MRI to plan breast-conserving surgery following neoadjuvant chemotherapy for early breast cancer. Br J Cancer 98 (2):289-293. doi:10.1038/sj.bjc.6604171 10. Segara D, Krop IE, Garber JE et al. (2007) Does MRI predict pathologic tumor response in women with breast cancer undergoing preoperative chemotherapy? J Surg Oncol 96 (6):474-480 11. Rieber A, Brambs HJ, Gabelmann A, Heilmann V, Kreienberg R, Kuhn T (2002) Breast MRI for monitoring response of primary breast cancer to neo-adjuvant chemotherapy. Eur Radiol 12 (7):1711-1719 12. Loo CE, Teertstra HJ, Rodenhuis S et al. (2008) Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy: initial results. AJR Am J Roentgenol 191 (5):1331-1338 13. Gilhuijs KG, Deurloo EE, Muller SH, Peterse JL, Schultze Kool LJ (2002) Breast MR imaging in women at increased lifetime risk of breast cancer: clinical system for computerized assessment of breast lesions initial results. Radiology 225 (3):907-916 14. Turnbull L (2008) Magnetic resonance imaging in breast cancer: results of the COMICE trial. Breast Cancer Research 10 (3):1-2. doi:10.1186/bcr2008 15. Pengel KE, Loo CE, Teertstra HJ et al. (2009) The impact of preoperative MRI on breast-conserving surgery of invasive cancer: a comparative cohort study. Breast Cancer Res Treat 116 (1):161-169. doi:10.1007/s10549-008-0182-3 16. Mauriac L, Durand M, Avril A, Dilhuydy JM (1991) Effects of primary chemotherapy in conservative treatment of breast cancer patients with operable tumors larger than 3 cm. Results of a randomized trial in a single centre. Ann Oncol 2 (5):347-354 17. Chen JH, Feig B, Agrawal G et al. (2008) MRI evaluation of pathologically complete response and residual tumors in breast cancer after neoadjuvant chemotherapy. Cancer 112 (1):17-26 18. Straver ME, Glas AM, Hannemann J et al. (2010) The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res Treat 119 (3):551-558. doi:10.1007/s10549-009-0333-1 19. Carey LA, Dees EC, Sawyer L et al. (2007) The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res 13 (8):2329-2334 20. Denis F, Desbiez-Bourcier AV, Chapiron C, Arbion F, Body G, Brunereau L (2004) Contrast enhanced magnetic resonance imaging underestimates residual disease following neoadjuvant docetaxel based chemotherapy for breast cancer. Eur J Surg Oncol 30 (10):1069-1076. doi:10.1016/j.ejso.2004.07.024 21. Chen JH, Baek HM, Nalcioglu O, Su MY (2008) Estrogen receptor and breast MR imaging features: a correlation study. J Magn Reson Imaging 27 (4):825-833. doi:10.1002/jmri.21330 22. Warren RM, Bobrow LG, Earl HM et al. (2004) Can breast MRI help in the management of women with breast cancer treated by neoadjuvant chemotherapy? Br J Cancer 90 (7):1349-1360 23. Sadetzki S, Oberman B, Zipple D et al. (2005) Breast conservation after neoadjuvant chemotherapy. Ann Surg Oncol 12 (6):480-487. doi:10.1245/aso.2005.07.021 24. Garimella V, Qutob O, Fox JN et al. (2007) Recurrence rates after DCE-MRI image guided planning for breast-conserving surgery following neoadjuvant chemotherapy for locally advanced breast cancer patients. Eur J Surg Oncol 33 (2):157-161. doi:10.1016/j.ejso.2006.09.019 25. Chen AM, Meric-Bernstam F, Hunt KK et al. (2005) Breast conservation after neoadjuvant chemotherapy. Cancer 103 (4):689-695. doi:10.1002/cncr.20815

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CHAPTER 6

Survival is associated with complete response on MRI after

neoadjuvant chemotherapy in ER-positive HER2-negative

breast cancer

Claudette E. Loo1, Lisanne S. Rigter2, Kenneth E. Pengel1, Jelle Wesseling3,

Sjoerd Rodenhuis2, Marie-Jeanne T. F. D. Vrancken Peeters4, Karolina

Sikorska5, Kenneth G. A. Gilhuijs1,6


1 Department of Radiology

2 Department of Medical Oncology


4Department of Surgical Oncology

5 Department of Biostatistics


6Department of Radiology and the Image Sciences Institute

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Accepted for publication in Breast Cancer Research

105

Abstract

Purpose

A pathological complete remission (pCR) of estrogen receptor (ER)-positive/ HER2-negative breast

cancer is rarely achieved after neoadjuvant chemotherapy (NAC). In addition, the prognostic value of

pCR for this breast cancer subtype is limited. We explored whether response evaluation by MRI is

associated with recurrence-free survival after NAC in ER-positive/HER2-negative breast cancer.

Methods

MRI examinations were performed in 272 women with ER-positive/HER2-negative breast cancer

before, during and after NAC. MRI interpretation included lesion morphology at baseline, changes in

morphology, size, and contrast uptake kinetics. These MRI features, clinical characteristics and final

pathology were correlated with recurrence-free survival.

Results

The median follow up time was 41 months. There were 35 women with events, including 19 breast

cancer related deaths.

At multivariable analysis, age younger than 50 years (hazard ratio (HR) = 2.55; 95% confidence

interval (CI) (1.3, 5.02), p=0.007), a radiological complete response after NAC (HR= 14.11; CI (1.81,

1818); p=0.006) and smaller diameters of washout/plateau enhancement at MRI after NAC (HR=

1.02; CI (1.00, 1.04), p=0.036) were independently associated with best recurrence-free survival.

Pathological response was not significant; HR= 2.12(0.86-4.64, p=0.096).

Conclusions

MRI, after NAC in ER-positive/HER2-negative tumors may be predictive of recurrence-free survival. A

radiological complete response at MRI after NAC is associated with an excellent prognosis.

Key Words:

Breast cancer, neoadjuvant chemotherapy, Magnetic Resonance imaging, recurrence-free survival,

Estrogen receptor.

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Introduction

Neoadjuvant chemotherapy (NAC) for breast cancer has been shown to be equally effective

as postoperative chemotherapy in terms of disease-free and overall survival [1-4].

Several markers are routinely employed to predict treatment outcome and to select therapy [5-7].

The most frequently used include the estrogen receptor (ER), the progesterone receptor (PR) and the

human epidermal growth factor receptor 2 (HER2). Three major breast cancer subtypes are easily

distinguished by immunohistochemistry (IHC): triple-negative (ER, PR and HER2 -negative), HER2-

positive (HER2-positive, ER and PR may be positive or negative) and ER-positive/HER2negative (ER-

positive, HER2 negative, PR may be positive or negative) [8,9]. These immunohistochemical subtypes

correspond roughly to the molecular subtypes Basal-like, HER2-enriched and Luminal, respectively

[10]. Subtyping of typically heterogeneous breast cancer in these three groups may improve

understanding of tumor response and outcome and may result in optimized strategies for patient-

tailored treatment [11,12].

Even within these subgroups, the response to and outcome after chemotherapy vary widely.

A pathologically confirmed complete remission (pCR) or minimal disease [13,14] after

chemotherapy is associated with a disease-free and overall survival benefit.[1,15,2,16]. More

recently, however, it has been shown that this relation is absent for luminal A tumors [17],

which comprise approximately half of the tumors that express the estrogen receptor but

which do not contain a HER2 gene amplification. Nevertheless, a pCR is often used as a

surrogate marker to predict long-term outcome in this subgroup. Of the ER-

positive/HER2negative tumors only a small fraction will achieve a pCR, while the prognosis is

better than that of triple negative breast cancer [17]. Therefore a pathological complete

response after neoadjuvant chemotherapy in ER-positive/HER2negative tumors is certainly

not a practical prognostic indicator. It is possible that dynamic contrast-enhanced MRI, which

visualizes functional properties of the tumor such as those associated with angiogenesis, may

be used as a practical prognostic indicator.

The benefit of MRI over other imaging modalities for monitoring response during and after

neoadjuvant chemotherapy has been extensively reported [18-21]. Also prediction of

pathological response after neoadjuvant chemotherapy by MRI has been extensively studied

[22-24]. A recent published study evaluated volumetric MR imaging for predicting recurrence-

free survival after NAC in breast cancer patients [25].

However, the role of MRI after neoadjuvant chemotherapy in predicting survival for ER-

positive/HER2negative tumors in particular has not been completely assessed yet. The

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purpose of this study was to explore whether MRI is associated with recurrence-free survival

after neoadjuvant chemotherapy in ER-positive/HER2negative breast cancer.

Material and Methods

Selection of patients

Patients between 18 and 70 years of age with pathologically proven invasive ER-

positive/HER2-negative breast cancer of either > 3 cm in size and/or at least one tumor-

positive lymph node were offered neoadjuvant chemotherapy (NAC). All patients received

NAC between January 2000 and June 2012, and all either took part in a single-institution

clinical trial (approved by the ethical committee), or were treated off study according to the

standard arm of the trial [26,27]. The institutional review board had approved the study

protocols and informed consent was obtained from all patients. Only patients with ER-

positive/HER2-negative tumors based on immunohistochemistry without a prior history of

breast cancer were included in this analysis. Only patients who had undergone MRI

examinations, before (baseline), during (after three courses) and after NAC and who

underwent surgery after NAC were included.

Treatment

For neoadjuvant chemotherapy, four different regimens were employed [27,26]. Between

2000 and 2004 patients were randomized to receive, either six cycles of AC or six cycles of

AD, with AC being considered as standard treatment. AC consisted of doxorubicin 60 mg/m2

and cyclophosphamide 600 mg/m2 every three weeks, whereas patients in the AD arm were

treated with six cycles of doxorubicin 50 mg/m2 and docetaxel 75 mg/m2. After 2004, patients

started with three courses of ddAC (doxorubicin 60 mg/ m−2 and cyclophosphamide

600 mg/ m−2 on day 1, every 14 days, with PEG-filgrastim on day 2). When an ‘unfavorable’

response was noted at MRI after 3 courses (defined as a reduction of less than 25% in the

largest diameter of the tumor plateau/washout enhancement [28]), chemotherapy was

switched to a (theoretically) non-cross-resistant regimen. In such a case, three courses of

ddAC were followed by 3 courses of docetaxel and capecitabine (DC, docetaxel 75 mg/ m−2 on

day 1, every 21 days and capecitabine 2 × 1000 mg/ m−2 on days 1–14). In case of a ‘favorable

response’, chemotherapy was continued with 3 further courses of ddAC.

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After the last course of chemotherapy, all patients underwent surgery (breast conserving

surgery or mastectomy with or without axillary lymph node dissection), post-operative

external beam radiation therapy, and adjuvant endocrine therapy according standard

guidelines.

MRI Imaging and Evaluation

Initially, MRI was performed on a 1.5 T Magnetom Vision scanner with a dedicated bilateral phased

array breast coil (Siemens, Erlangen, Germany). From April 2007 MRI was performed on a 3.0 T

Achieva scanner with a dedicated 7-elements sense breast coil (Philips Medical Systems, Best, The

Netherlands). Images were acquired with the patient in prone position and with both breasts imaged

simultaneously. The standard dynamic protocol started with an unenhanced coronal 3D FFE (thrive)

sense T1-weighted sequence. A bolus (14mL) of gadolinium containing contrast (0.1 mmol/kg) was

administered intravenously at 3 mL/s using a power injector followed by a bolus of 30 ml of saline

solution. Subsequently, dynamic imaging was performed in five consecutive series at 90 s intervals.

The voxel size was 1.21 x 1.21 x 1.69 mm3 (1.5T) or 1.1 x 1.1 x 1.2 mm3 (3.0T). The following scanning

parameters were used: acquisition time 90 s (1.5T and 3.0T); TR/TE: 8.1/4.0 (1.5T) or 4.4/2.3 (3.0T);

flip angle 20° (1.5T) or 10° (3.0T); FOV 310 (1.5T) or 360 (3.0T).

Interpretation of the breast MR images was done using a viewing station that permitted

simultaneous viewing of two series reformatted and linked in three orthogonal directions [29]. The

viewing station displays all imaging series (unenhanced and contrast-enhanced), subtraction images

at 90s intervals and maximum intensity projection (MIP) of both breasts. The displayed images were

also color coded, representing different levels and curve types of enhancement. Specifically, the

color indicated the shape of the time-signal intensity (contrast enhancement) curve at each pixel

location [30]: Type-I (i.e., persistent enhancement >10% after the first post-contrast image), Type-II

(i.e., plateau enhancement between -10% and +10% during late enhancement), and Type-III (i.e.,

washout kinetics resulting in > 10% signal decrease during late enhancement) [30]. These colors were

coded yellow, light-red and dark-red, respectively, where initial enhancement (90s) equaled or

exceeded 100% and green, light-blue and dark-blue, respectively, where initial enhancement was

between 50% and 100%. The viewing station was developed in close collaboration with the breast

radiologists at the Netherlands Cancer Institute. The radiologists have been using the system since

2000. The MR images were assessed by four breast radiologists, who were unaware of outcome. The

patients were randomly distributed among the radiologists. The MRI examinations before (baseline),

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during and after chemotherapy were analyzed by the same radiologist in one session to ensure

interpretive consistency.

Temporal and morphologic characteristics of contrast uptake were scored as previously

described [28]. In short, tumor extent, morphology and relative enhancement were assessed

during initial enhancement (90s) and late enhancement (450s) at all subsequent MRI exams.

The extent of the tumor was assessed by its largest diameter in three reformatted planes

(sagittal, axial and coronal) at initial and at late (washout/plateau) enhancement separately.

If a non-mass (diffuse) enhancement or multifocal disease was visible, the total area including

non-enhancing breast tissue between lesions was measured on MIP images. The largest value

of the three diameters was recorded. The percentage difference in largest tumor diameter

between subsequent MRI exams was also assessed, both at initial and at late enhancement.

Supported by the color-coding the area within the tumor with strongest contrast uptake at

initial and at late enhancement was determined. Measurement of the signal intensity (initial

and late enhancement ) was performed manually by placing a region of interest in the most

malignant area (dark-red) and moving the cursor in this area to find most malignant values in

real-time (in percentages). Morphology of the enhancing tumor was scored in three groups:

unifocal mass, multifocal mass and non-mass (diffuse) enhancement [31]. At MRI during and

after NAC the pattern of tumor reduction was denoted in 5 categories: shrinking mass,

diffuse decrease, reduction to small foci, no enhancement, and no change.

A complete absence of contrast enhancement in the original tumor bed at MRI after NAC was

defined as a radiological complete response. Consequently, small enhancing foci in the

original tumor bed was considered as residual enhancing tumor.

Histopathologic Analysis

Prior to NAC at least three 14G ultrasound-guided core biopsies of the breast cancer were

taken. Subsequently, most tumors were marked with a radiopaque marker. ER and PR status

were determined by immunohistochemistry and considered positive if ≥10% of nuclei stained

positive. HER2 status was assessed by scoring the intensity of membrane staining using

immunohistochemistry. Tumors with a score of 3+ (strong homogeneous staining) were

considered positive. In case of 2+ scores (moderate homogeneous staining) chromogenic in

situ hybridization (CISH) was used to determine HER2 amplification (gene copy number of six

or more per tumor cell). For this study ER-positive/HER2-negative tumors were selected.

Pathology response

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Three common definitions of pCR were used: 1: no residual invasive tumor in the breast

(ypT0/is) [32,15]; 2: no residual invasive tumor in the breast or axilla (ypT0/isN0) [33]; and 3:

a near-complete response, indicating the presence of only a small number of scattered tumor

cells in the breast (ypT<mic) [14].


The primary endpoint was recurrence-free survival (RFS), defined according to the

standardization of events and endpoints (STEEP) criteria [34]. According to this definition an

event is either a local, regional or distant breast cancer recurrence or death due to any cause.

Second primaries (including contralateral breast cancer) were not considered an event.

The last data were collected in September 2014, and patients for whom no event had

occurred were censored at the last date of being seen alive. The median follow-up was

calculated using reverse Kaplan Meier approach. Patient characteristics are presented in

tables as medians (percentiles) for continuous variables and frequencies for categorical

variables. All clinical variables were analyzed as categorical predictors (table 1). The MRI

characteristics were analyzed as categorical variables (table 2) or continuous variables (table

3). For the categorical predictors, the first mentioned category was taken as a reference and

HR compares the subsequent categories to the reference. For the continuous predictors, the

HR represents a change in hazard for one unit change in the predictor. The clinical and MRI

characteristics were first associated with the outcome in univariable Cox models. Next, the

significant and clinically relevant parameters were analyzed jointly in a multivariable Cox

model. When at least one of the analyzed subgroups had no events, the Cox regression with

Firth’s penalized likelihood was used for the estimation of the hazard ratios. Confidence

intervals were then computed using profile likelihood. This technique has been implemented

in the R package coxphf.

The optimal cut points and their significance for the continuous variables were estimated

using maximally selected rank statistics as implemented in the R package maxstat. Variables

for which p<0.05 were considered significant. The final model was built by combining

statistical evidence (significant p-values) as well as clinical relevance (age, pathological

response). All statistical analyses were performed using R software (version 3.1.0) or SPSS

(version 20).

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Results

Between January 2000 and June 2012 428 ER-positive/HER2-negative breast cancers patients

were registered in the NAC breast database of our institute. Two-hundred and seventy-nine

patients had response evaluation with MRI (before, during and after), underwent surgery and

had no distant metastasis. Seven patients were excluded; 4 because of a history of breast

cancer, 2 because of technically insufficient MRI, and 1 patient turned out to have HER2-

positive breast cancer. The majority of the 272 women were pre-menopausal, had invasive

ductal carcinoma, positive nodal stage prior to NAC and T2 tumors (table 1.). The largest

diameter of the initial tumor at MRI was 4,3 cm median (range 1,0-11,5 cm). The median age

at diagnosis was 47 years (range 19-68). The median follow-up time was 41 months (3.4

years). There were 35 women with an event; 31 women had distant metastases, 2 had an

additional local/regional recurrence, one only a local/regional recurrence and one patient

died without any recurrence reported. There were 20 deaths: 19 breast cancer related deaths

and 1 death due to another malignancy. The RFS for

the study group is shown in figure 1.

Fig 1 Recurrence-free survival of 272 ER-

positive/HER2-negative breast cancer

patients after neoadjuvant chemotherapy

(solid curve); and the 95% confidence

interval. Above the x-axis the number of

patients at risk is shown.

272 146 104 44 30 10

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Table 1. Univariable Cox proportional hazard analysis of clinical variables with RFS

Recurrence Free Survival

Variable No. of

patients No. of events

P value

Hazard Ratio 95% CI

T stage prior to NAC

0.731

T1 28 1

T2 149 19

2.42 0.32, 18.16

T3 79 12

2.7 0.35, 20.99

T4 16 3

2.91 0.30, 28.09

N stage prior to NAC

0.558

negative 55 6

positive 217 29

1.29 0.54, 3.11

Clinical stage

0.847

II 185 24

III 86 11

0.93 0.46, 1.91

unknown 1

Age

0.008

≤ 50 years at diagnosis 177 17

> 50 years at diagnosis 95 18

2.49 1.28, 4.85

Menopausal Status

0.017

pre-menopausal 161 15

peri-menopausal 16 2

1.42 0.32, 6.24

post-menopausal 91 18

2.74 1.38, 5.46

unknown 4

Histology*

0.835

Adenocarcinoma nos 18 3

Ductal carcinoma 207 27

1.39 0.42, 4.62

Lobular carcinoma 39 4

0.93 0.21, 4.16

other 8 1

1.08 0.11, 10.42

Progesteron receptor*

0.199

negative 76 13

positive 192 21

0.63 0.31, 1.26

unknown 4

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Tumor grade*

0.14

good 28 2

moderate 117 16

3.57 0.8, 15.93

poor 32 5

3.52 0.66, 18.73

unknown 95

Chemotherapy regimen

0.89

ddAC 167 20

AC-CD 77 8

1.23 0.54, 2.83

AD 14 4

0.79 0.25, 2.55

CD 13 3

1.33 0.39, 4.51

unknown 1

Pathologic response

ypT0/isypN0: no 261 35 0.41

yes 11 0

0.37 0, -

ypT0/is: no 251 34 0.29

yes 21 1

0.39 0.05, 2.88

ypT<mic: no 221 28 0.91

yes 51 7 0.95 0.42, 0.91

Table1. Abbreviations; RFS= recurrence-free survival; CI= confidence interval; *=determined on pre-chemotherapy ultrasound-guided biopsy; (dd)AC= (dose-dense)cyclophosphamide and doxorubcin; CD= capecitabine and docetaxel;AD= doxorubcin and docetaxel; ypT0/isypN0= no residual invasive tumor in breast and axilla; ypT0/is =no residual invasive tumor in the breast; ypT<mic = few scattered tumor cells in the breast; - = CI bound could not be estimated; numbers in bold are significant values

Univariable Cox model for clinical and pathological parameters

Among the clinical and pathological parameters, a post-menopausal status (HR= 2.73, p=

0.04) and age over 50 years (HR= 2.49, p= 0.01) were associated with worse RFS (table 1).

pCR, according to any investigated definition, was not associated with improved RFS (table 1,

fig 2). Twenty-one (7,7%) patients achieved an ypT0/is of the primary tumor after NAC. Only

one recurrence was found in this group (p=0.29). Eleven (4%) patients achieved an

ypT0/isypN0 after NAC. In this group, no events occurred (p=0.41). Also, a near complete

pathological response (ypTmic) which was observed in 51 patients (7 events) was not

associated with RFS (p=0.91). Kaplan Meier curves of pathology response are shown in figure

2.

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Figure 2A, B, C Kaplan Meier curves of ER-positive tumors RFS of pathology response after NAC. The

solid line indicates patients with no response. Above the x-axis the number of patients at risk for

each group is shown. A blue line is ypT0N0 (no residual invasive tumor in the breast and axilla)

(p=0.41); B blue line is ypT0/is (no residual invasive tumor in the breast) (p=0.29); C blue line is

ypT<mic is a near-complete response (only a small number of scattered tumor cells in the breast)

(p=0.91).

215 135 97 41 27 9 no response

21 11 7 3 3 1 ypT0/is 261 141 100 42 28 9 no response

11 5 4 2 2 1 ypT0/ypN0

221 115 83 34 22 7 no response

51 31 21 10 8 3 ypT<mic

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Table 2. Univariable Cox proportional hazard analysis of MRI variables with RFS

No. of No. of Recurrence Free Survival

Variable patients events P value Hazard Ratio 95% CI

Lesion morphology baseline MRI 0.612

Mass unifocal 91 10

Mass multifocal 96 12

1.29 0.71, 3.70

Non mass (diffuse) 77 13

1.60 0.57, 3.01

Mass & non mass 8 0

4.38 0.03, 41.66

Pattern of reduction at MRI after NAC

0.029

No change 23 4

Shrinking mass 96 10

0.56 0.19, 1.89

Diffuse decrease 56 10

0.78 0.27, 2.64

Small foci 53 11

0.95 0.34, 3.19

No enhancement 44 0

0.06 0, 0.53

Dynamic curve type after NAC

0.008

No enhancement 44 0

continuous 89 16

13.54 1.83, 1728.03

plateau 82 5

7.46 0.84, 980.87

8washout 57 14

17.59 2.35, 2248.46

Radiological complete response

0.004

Yes 44 0

No 228 35

12.81 - , 1621.10

RECIST evaluation MRI initial after NAC - baseline

0.009

No enhancement after NAC 44 0

PR (LD initial↓≥ 30%) 154 23

11.63 - , 1477.68

NR (LD initial↓ < 30%) 74 12

16.53 2.17, 2119.55

RECIST evaluation MRI initial after NAC - during

0.037

No enhancement during & after NAC 10 0

No enhancement after NAC 36 0

0.44 0, 80.78

PR (LD initial↓≥ 30%) 82 11

3.99 0.52, 513.45

NR (LD initial ↓ < 30%) 144 24

4.95 0.68, 629.57

RECIST evaluation MRI late after NAC - baseline

0.05

No washout/plateau baseline & after NAC 8 0

No washout/plateau after NAC 136 17

3.08 0.41, 394.53

PR (LD late ↓≥ 30%) 93 12

3.54 0.46, 455.8

NR (LD late ↓<30%) 35 6

11.57 1.31, 1525.99

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Univariable Cox model for MRI parameters

No tumor enhancement (i.e., a radiological complete response) after NAC (HR= 12.81, p=

0.004) was significantly associated with superior RFS (table 2). Forty-four (16,2%) of the 272

patients achieved a radiological complete response at MRI after NAC. No events were found

in this group. Kaplan Meier curves for ER-positive/HER2-negative breast cancer patients show

significant difference in RFS between patients with a radiological complete response and

those with residual enhancement at MRI (log-rank p=0.012; figure 3).

RECIST evaluation MRI late after NAC - during

0.46

No plateau/washout during & after NAC 61 6

No plateau/washout after NAC 84 11

1.17 0.43, 3.17

PR (LD late ↓≥ 30%) 58 9

1.65 0.59, 4.64

NR (LD late ↓<30%) 69 9 2.08 0.74, 5.87

Table 2. Abbreviations; RFS=recurrence free survival; CI=confidence interval; NAC=neoadjuvant chemotherapy; LD=largest diameter; PR= partial remission; initial= enhancement 90s; late= washout/plateau enhancement 450s; NR= non responder; ↓= decrease; - = CI bound could not be estimated; numbers in bold are significant values.

117

Figure 3 Kaplan –Meier curves for RFS of ER-positive tumors based on radiological complete

response (no enhancement; black curve) and those with residual enhancement (blue curve)

at MRI after neoadjuvant chemotherapy. Log-rank test p=0.012. Above the x-axis the number

of patients at risk for each group is shown.

Also the largest diameter of the region with washout/plateau (late) enhancement was

associated with RFS at baseline MRI (HR= 1.017, p= 0.027), during NAC (HR= 1.024, p=0.006)

and after NAC (HR= 1.03, p=0.003) (table 3). The most significant cut-off point for the largest

diameter of washout/plateau enhancement after NAC was estimated for the value 22mm.

Log rank test p-value < 0.001 (figure 4). In addition, the percent change in largest diameter of

the region with washout/plateau enhancement between baseline and after NAC (HR= 1.013,

p= 0.021) was associated with RFS (table 3).

Log-rank p=0.012

44 21 16 9 7 2 enhancement

228 125 88 35 23 8 dual tumor enhancement

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Figure 4 Kaplan Meier curve for recurrence-free survival of ER-positive tumors with

washout/plateau enhancement smaller than 22mm (black curve) and those with a diameter

of washout/plateau larger than 22mm (blue curve) after neoadjuvant chemotherapy at MRI.

LD = largest diameter. Above the x-axis the number of patients at risk for each group is

shown.

Log-rank p < 0.001

229 130 95 41 28 9 LD washout/plateau< 22mm

43 16 9 3 2 1 LD washout/plateau> 22mm

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Multivariable analysis

In the multivariable analysis we fitted a Cox model including radiological complete response

after NAC, the largest diameter of washout/plateau at MRI after NAC, patient’s age and

pathological response (ypT<mic) . The first three predictors remained statistically significant

with HR=: 14.11 (1.8-1818, p=0.006), 1.02 (1.00-1.04, p=0.036) and 2.55 (1.3-5.02, p=0.007)

respectively. Pathological response did not retain significance; HR= 2.12(0.86-4.64, p=0.096).

Discussion

In a series of 272 consecutive patients with ‘luminal”, (ER-positive/HER2-negative) breast

cancer, a radiological complete remission assessed at MRI after NAC was associated with

significantly improved recurrence-free survival after NAC. All of the 44 (16%) patients with a

radiological complete response remained free of disease during follow up.

This finding may be of clinical importance. Luminal breast cancer is the most common breast

cancer and represents approximately 2/3rd of all cases. Luminal tumors only rarely achieve a

pathological complete remission (pCR). In this study, only 8% (21/272) achieved a pCR of the

breast and even less, 4% (11/272), a pCR of breast and axilla. In our study neither pCR (i.e.,

ypT0is or ypT0isN0) nor near-pCR was predictive of improved recurrence-free survival. These

findings are in accordance with previously published work [17]. Also other studies showed

that pCR is not a suitable surrogate end point for patients with ER-positive/HER2-negative

grade 1 or 2 (luminal A) breast cancer [35,36].

We investigated the potential of MRI to predict recurrence-free survival. MRI after

completion of chemotherapy was found to be of particular prognostic value in the current

study. Apparently, the lack of enhancement at MRI, which provides information about

functional properties of the tumor, is associated with prognosis in slowly proliferating

tumors, but pCR is not.

Many studies have evaluated the role of MRI after NAC as a diagnostic tool to serve as

surrogate for final pathology [37-39]. The majority of studies have focused on the correlation

of tumor size with that at pathology to validate MRI as a tool to detect residual disease and to

guide surgical planning. In terms of tumor size, MRI may underestimate or overestimate

compared to pathology, resulting in false-negative and false-positive results [40,41]. Other

studies have shown that a complete response after neoadjuvant chemotherapy at MRI is

associated with the presence of residual tumor at pathology in 26-56% of cases [26,42]. More

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recent studies have indicated that the accuracy of MRI in estimating tumor size after

neoadjuvant chemotherapy varies with breast cancer subtype and tumor morphology

[39,24,43,22]. The best accuracy is achieved in HER2-positive and triple-negative tumors

[39,24,22]. We found that a radiological complete response in ER-positive breast cancer is

associated with an excellent prognosis. However in 36% (16/44) of these cases, (microscopic)

residual tumor at final pathology was found. We used a very strict definition of a radiological

complete response in which even small enhancing foci in the original tumor bed are

considered as residual tumor. Especially in diffuse tumors (non-mass enhancement) that

disintegrate into (very) small foci the radiological assessment can be challenging and in

clinical practice small enhancing foci may occasionally be interpreted incorrectly as a

radiological complete response. We have observed such interpretation discrepancies

between the retrospective dedicated review of our study and the clinical routine MRI

assessment. For future validation studies it will be important to maintain the strict definition

of a radiological complete response.

The policy of changing the chemotherapy regimen in case of an unfavorable MRI response

during NAC could have led to an increase in the (radiological) complete remission rate in our

study. This was certainly the objective of the policy, but whether this really succeeded needs

to be further studied in controlled trials. We assumed that a larger reduction in tumor size on

MRI could correlate with a smaller volume of residual tumor but it could also serve as a

measure of chemotherapy sensitivity. The latter could be critically important for the

likelihood that micro-metastatic disease has eradicated or reduced, which is the primary

objective of NAC. The differences between a radiological CR and a pCR in this respect,

include the more frequent occurrence of a radiological CR in this type of tumors and perhaps

the higher likelihood of radiological CR in tumor subtypes that tend to recur less often or less

early than others. Although a detailed subgroup analysis could not be performed due to the

limited number of patients, there was no indication that the association between radiological

CR and RFS was different for different chemotherapy regimens or between patients who did

and those who did not cross-over to a different chemotherapy regimen (table 1).

The value of MRI with or without prognostic markers such as those derived from pathology, is

yet unclear when it comes to predicting disease-free survival of patients with ER-

positive/HER2-negative breast cancer. A few studies have investigated the predictive role of

MRI in breast cancer survival after NAC without using a distinction in subgroups [44-46]. In a

relative small study group of 58 patients with a short median follow up of 33 months,

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Partridge et al showed that initial MRI volume before NAC, and final change in MRI volume

were significant predictors of recurrence-free survival [44]. Yi et al. evaluated 158 breast

cancer patients with MRI before and after NAC. They concluded that a smaller reduction in

tumor volume and a smaller reduction in washout component, assessed with computer aided

evaluation, were associated with worse recurrence-free survival [45].

Jafri et al. evaluated the optimal threshold for measuring functional tumor volume in 64

patients. They concluded that functional tumor volume is able to predict RFS and could be

used as a biomarker [46].

These three studies did not report how many patients achieved a radiological or a clinical

complete response at MRI nor did they analyze breast cancer subgroups.

A more recent published study ( ACRIN 6657) noted that functional tumor volume (tumor

volume percent enhancement >70%) after NAC is a strong predictor for RFS in breast cancers

[25]. Their Kaplan-Meier analyses performed by subtype suggest that the ability of functional

tumor volume to discriminate differences differs per breast cancer subtype. After NAC, a

greater RFS separation was found in 78 ER-positive/HER2-negative and 41 HER2-positive

breast cancers than in the whole group. Instead of volumetric measurements, we assessed

the largest diameter at initial (MIP, 90 s) and late (washout/plateau) enhancement at MRI. In

accordance with Yi we found that the largest diameter of washout/plateau and the change of

this diameter are significantly associated with RFS in our subset of ER-positive breast cancer.

However, in daily clinical practice a radiological complete response is a more straightforward

and potentially a more reproducible measure to identify patients with ER-positive/HER2-

negative breast cancer who have a good prognosis. On the other hand, in patients with

residual enhancement at MRI, and who thus may have a less favorable prognosis, the largest

diameter of washout/plateau enhancement may be used to decide if additional

chemotherapy is required. For this study population the most significant cut-off point was

estimated for a largest diameter of 22mm. However, before we can actually use this value we

need to validate this in a larger study group, preferably with longer follow up.

Our study has some limitations. These involve potential suboptimal selection of groups and

differences in chemotherapy regimens. Although the total study group is relatively large,

only 35 recurrences occurred during a follow-up time that is relatively brief for ER-

positive/HER2-negative (luminal) tumors. This resulted in wide confidence intervals of the

hazard ratios. In this study the tumor grade determined on the biopsy was known in only 177

(65%) patients. As a result we were not able to allow additional stratification in luminal A and

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luminal B tumors. Ideally, subtyping would also have been done based on gene expression

rather than on immunohistochemistry, and the median follow-up would have been longer,

with more recurrences available for analysis. On the other hand, the predictive effect of a

radiologic complete response may be especially clear in the first 5 years after NAC. The

Oxford overview has shown that chemotherapy prevents recurrences within the first 5 years,

while the preventive effect of endocrine treatment, which is at least as important in luminal

tumors, extends beyond 10 years [47]. As a result, effective chemotherapy may prevent early

relapse, seen after limited follow-up, when the endocrine treatment effect is not yet

dominant.

Another limitation is that different dedicated breast radiologists in a single institution using

strict criteria assessed the results . As a result, we were not able to evaluate inter or intra-

observer variability. Further exploration with a longer follow-up and an external validation

cohort will be useful to validate our results.

In conclusion, a radiological complete response at MRI after NAC of an ER-

positive/HER2negative tumor is associated with excellent outcome. In case of residual

enhancement at MRI after NAC, the largest diameter of late enhancement may be helpful to

identify patients who may need additional treatment.

Acknowledgments:

We thank Anita Paape, Gonneke Winter, Petra de Koekkoek and Annemarie Fioole of the

radiology department and Nicola Russell of the radiotherapy department for their dedication

and contributions.

Funding:

This study was in part performed within the framework of CTMM, the center for Translational

Molecular Medicine (www.ctmm.nl); project Breast CARE (grant 03O-104).

Conflict of interest: None to declare.

http://www.ctmm.nl/

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CHAPTER 7

Summary, general discussion and conclusions

131

Chapter 1 Introduction and thesis outline

Breast cancer is the most common type of cancer in women in the Netherlands [1]. Despite improved

diagnostic tools, the introduction of the national breast cancer screening program and the availability

of targeted adjuvant systemic treatment, women are still dying from the consequences of breast

cancer. In particular young women with biologically aggressive and more extensive disease (TNM

stage≥ II) are at risk. In addition to local therapy, consisting of surgery and/or radiotherapy, these

women are treated with adjuvant systemic treatment [2]. Increasingly, the systemic chemotherapy is

given prior to surgery. This so called neoadjuvant chemotherapy strategy has the objective to

downstage breast cancers in order to facilitate breast-conserving surgery, in addition to its primary

role in eliminating micrometastatic disease. Furthermore, neoadjuvant chemotherapy offers the

ability to monitor response of the breast cancer to chemotherapy while the tumor is still in situ. After

the neoadjuvant chemotherapy, surgery can be converted from mastectomy to breast-conserving

surgery when a satisfactory response of the tumor is noticed. Because a pathological complete

response (pCR) after chemotherapy is associated with a better prognosis [3-6], the ultimate goal of

response monitoring is to identify non-responsive tumors that do not result in pCR. In these cases a

switch to a (presumably) non-cross-resistant chemotherapy could be made[7]. This policy may lead

to an improved tailor-made or more personalized breast cancer treatment. The critical point is the

accuracy of response monitoring.

MRI is increasingly used to evaluate response of breast cancer because conventional imaging

(mammography and ultrasound) is less reliable for this purpose [8,9]. Nevertheless, the precise role

of dynamic contrast-enhanced MRI in assessment of residual disease and predicting long-term

outcome during and after neoadjuvant chemotherapy, especially in breast-cancer subgroups, is

unknown. Therefore, the general aim of this thesis was to investigate the role of MRI in monitoring

response of breast cancer to neoadjuvant chemotherapy and as a result, to improve personalized

breast cancer treatment.

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Chapter 2

The first objective of this thesis was to explore the predictive role of MRI during neoadjuvant

chemotherapy to assess early breast cancer response. First, we identified MRI features predictive of

final pathology in 54 patients. Subsequently, we established a practical MRI prediction test (also MRI

criteria) to identify which tumors will not achieve a pathological complete remission. We found that

the change in largest diameter of the late enhancement region at MRI during neoadjuvant

chemotherapy is the best predictor of final pathology. We chose a point on the ROC curve that allows

only 5% false-positives, in order to prevent excellent responders from being switched to a different

therapy. A reduction less than 25% of the largest diameter of late enhancement on MRI during

neoadjuvant chemotherapy is indicative of residual tumor at pathology after chemotherapy. Using

these MRI criteria, the fraction of patients in whom chemotherapy will be switched was 41% (22/54).

Of the patients with a favorable response (reduction >25%) approximately half (44%, 14/32) achieved

a pathological complete remission. We suggested that the MRI criteria (reduction of less than 25%

largest diameter at MRI during neoadjuvant chemotherapy) may offer clinical oncologists an

objective tool of high specificity to personalize breast cancer treatment.

Chapter 3

Breast cancer is a heterogeneous disease consisting of different subtypes with different biological

behavior. Therefore, we evaluated the relevance of breast cancer subtype for MRI to predict tumor

response to neoadjuvant chemotherapy in 188 patients. Breast tumors were divided in three

subgroups using immunohistochemistry; 1) triple negative, 2) HER2-positive and 3) ER-Positive/HER2-

negative. We found that breast cancer subtype and MRI during neoadjuvant chemotherapy were

significantly associated with final pathology and the BRI (breast response index [10]). In subgroup

analyses we were able to assess that changes in MRI during neoadjuvant chemotherapy are

predictive of pCR in triple-negative and HER2-positive tumors, but not in the ER-positive/HER2-

negative subtype. This implicates that both the radiologist and the oncologist must be aware of the

breast cancer subtype when MRI before and during neoadjuvant chemotherapy is employed to

assess treatment efficacy.

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Chapter 4

In chapter 4 we evaluated the effect of response-adapted neoadjuvant chemotherapy in patients

with ER-positive/HER2-negative breast cancer. The chemotherapy (dose-dense doxorubicin and

cyclophosphamide (ddAC)) was adapted according to the previously defined MRI criteria in case of an

‘unfavorable’ response (i.e., less than 25% reduction in largest diameter of the late enhancement at

MRI during neoadjuvant chemotherapy) to docetaxel and capecitabine (DC). The degree of tumor

reduction at MRI after switching chemotherapy was compared with that of the non-switchers

(favorable response). Tumors with a favorable response showed a size reduction of 31% on MRI

halfway neoadjuvant chemotherapy, in contrast to a size reduction of 12% in the unfavorable

response group. After switching chemotherapy a size reduction of 27% was observed after

completing chemotherapy. This reduction is comparable to the 34% of the group that did not switch.

Use of this approach for response-adapted chemotherapy suggests that a change in chemotherapy

regimen may still be effective when the initial chemotherapy is not.

Chapter 5

In chapter 5, an MRI-based interpretation model is presented to improve patient selection for breast-

conserving surgery after neoadjuvant chemotherapy. The decision to undertake breast-conserving

surgery after neoadjuvant chemotherapy is complex and influenced by both surgical issues and

patients’ wishes. Precise pre-operative assessment of the residual disease extent after neoadjuvant

chemotherapy is crucial to plan the appropriate breast surgery. In 208 patients who were examined

with MRI after neoadjuvant chemotherapy residual disease was accurately detected in 76%

(158/208). The positive and negative predictive value of MRI was 90% (130/144) and 44% (28/64),

respectively. In 35 patients (17%) the tumor size was underestimated compared to final pathology

and in 27 (13%) this led to an unjustified selection of breast-conserving surgery. The MRI-model is

based on features most predictive of the feasibility of breast-conserving surgery; 1) largest diameter

at the baseline MRI, 2) the reduction in tumor size and 3) tumor subgroup (area under the curve:

0.78). This model may be used by clinicians as a tool to support decision making for breast-

conserving surgery or not.

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Chapter 6

A pathological complete response (used as a surrogate end point of survival) has been shown to be

of limited prognostic value in ER-positive/HER2-negative breast cancer. In chapter 6 we investigated

whether MRI is associated with recurrence-free survival after neoadjuvant chemotherapy in ER-

positive/HER2-negative breast cancer. The MRI examinations of 272 patients after neoadjuvant

chemotherapy were of prognostic value. At multivariable analysis, age younger than 50 years (HR=

2.37; 95%; CI (1.22, 4.63), p=0.01), a radiological complete response after neoadjuvant

chemotherapy (HR= 9.57; CI (1.32, 1217.22); p=0.02), and smaller diameters of washout/plateau

enhancement at MRI after neoadjuvant chemotherapy (HR1.02; CI (1.00, 1.04), p=0.049) were

independently associated with best recurrence-free survival. In particular a radiological complete

response on MRI after neoadjuvant chemotherapy is associated with excellent prognosis. These

results suggest that MRI after neoadjuvant chemotherapy could be used as a complementary

endpoint in the treatment of ER-positive/HER2-negative breast cancer.

135

General discussion

In this thesis we explored the role of dynamic contrast-enhanced MRI in monitoring response of

breast cancer during neoadjuvant chemotherapy. It forms part of more than 10 years research about

response monitoring and personalized breast cancer treatment in our cancer institute. The research

program serves to develop biomarkers for response prediction and to refine imaging techniques for

response monitoring.

The first part of the thesis covered the role of MRI during neoadjuvant chemotherapy.

The most important aim of (neoadjuvant) chemotherapy is to achieve a pCR which is considered a

surrogate end point for improved disease-free and overall survival. Early prediction of tumor

response only makes sense if the imaging method is accurate and an alternative treatment available.

We observed that it is important to take breast cancer subtype into account when assessing

response during (halfway) neoadjuvant chemotherapy. MRI can be accurately used in triple-negative

and HER2-positive breast cancer patients to predict pathology. Insufficient (unfavorable) response at

MRI halfway neoadjuvant chemotherapy will not lead to a pathologic complete response and offers

the possibility to adapt the (chemo) therapy regimen. We formulated general MRI-criteria (25%

decrease of largest diameter of late enhancement) which may be helpful to decide if neoadjuvant

chemotherapy has to be adapted halfway. In ER-positive patients in whom chemotherapy was

adapted due to an unfavorable MRI response during chemotherapy we noted a size reduction after

switching chemotherapy.

Other research groups like ACRIN 6667 (Imaging group of I-SPY) and TBCRC 017 also studied

performance of MRI in predicting pathological response [11-14]. In agreement with our results, the

multicenter trial of the I-SPY group has established that size could be an early predictor of pathology

[14]. This group also confirmed that outcome substantially varies among tumor subgroups [13]. More

recently, the imaging group of the I-SPY trial reported that MR imaging is helpful to demonstrate

alterations in treatment response among breast cancer subgroups that may lead to tailored imaging

approaches with improved predictive performance[15]. This study used 2 dimensional (largest

diameter) and 3 dimensional (volume) tumor size measurements in 216 women. Among size

measurements at MRI early during treatment (after 1 cycle), volume estimates are superior to largest

diameter for predicting pathology after neoadjuvant chemotherapy. Also after 4 cycles of

anthracycline-based chemotherapy, volume was more predictive of pathology outcome. However, a

volume cut-off point defined by MRI, helpful in adapting chemotherapy by subgroup is missing.

136

The second part of the thesis covered the role of MRI after neoadjuvant chemotherapy.

For the assessment of response after neoadjuvant chemotherapy we observed that it is important to

take breast cancer subtype into account. Breast cancer subtype, besides largest diameter at baseline

MRI and reduction in tumor size at MRI, is of great importance and influences the feasibility of

breast-conserving surgery. Accuracy of MRI was highest for triple-negative and HER2-positive

tumors.

Our finding that breast cancer subtype is important in planning surgery after neoadjuvant

chemotherapy was confirmed by the group of McGuire et al [16]. In agreement with our results this

study group noted that the highest accuracy was seen in HER2-positive and triple-negative breast

cancer and lowest in ‘luminal’ subtype breast cancer.

A multi-institutional study of the TBCRC 017 group concluded that MRI findings were not clearly

associated with the extent of breast surgery [12]. A wide variation of factors such as the treating

institution (surgeon choice), receptor status, T-stage at diagnosis and young age were more

significant than MRI response data in the choice of surgical treatment in their study. A decision

model, such as the proposed model in chapter 5, could be used as an objective tool to direct the

choice of surgery in order to prevent unnecessary mastectomies.

The MRI after completion of chemotherapy is typically used to guide surgery, but can also be used as

a prognostic tool to predict survival. In ‘luminal-type’ tumors, in which a complete response at

pathology is rarely achieved, it was noted that a complete response at MRI (no enhancement in the

original tumor bed) was associated with an excellent prognosis. In agreement with the findings of the

German study group we assessed that pathological complete response was not associated with

prognosis [17]. A recently published paper evaluated tumor volume changes on MRI for predicting

recurrence-free survival after neoadjuvant chemotherapy in 162 patients [15]. The absolute

functional tumor volume after chemotherapy showed the strongest association with recurrence-free

survival. A multivariable analysis revealed that the combination of MRI, histopathology and breast

cancer subtype was associated with the strongest predictive performance. These results are in

agreement with our results. A subgroup analysis of the ER-positive/HER2-negatives was not

performed in this study, possibly because of a lack of follow-up data.

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CTMM

In the context of the CTMM Breast Care study, other MR techniques like diffusion weighted imaging

(DWI) and other imaging techniques like PET/CT were explored. In 32 patients changes in diffusion,

expressed by the ADC-value, on MRI during neoadjuvant chemotherapy were studied (unpublished

work). In 9 patients we were not able to measure the ADC-value after chemotherapy because the

tumor had completely vanished and delineation was not possible. For the remaining patients we did

not observe an additional value of DWI because the changes in ADC-value were associated with the

findings from the contrast-enhancement. However from a meta-analysis performed by Wu et al. it

was reported that combined use of contrast-enhanced and DWI by MRI has the potential to improve

the diagnostic performance of response monitoring [18].

In an explorative analysis of 93 patients included in the CTMM Breast Care study, it was shown that

the combined use of contrast-enhanced breast MRI with PET/CT halfway the neoadjuvant

chemotherapy improves the prediction of the pathology outcome over that of each modality on its

own [19]. Of interest was that breast cancer subtype was an important factor to be taken into

account. The accuracy of combined imaging was influenced by breast cancer subtype. Subsequent

combined imaging (PET/CT and MRI) in 188 patients, subcategorized in different breast cancer

subtypes, showed that the scenario ‘contrast-enhanced MRI on its own’ was the most optimal

technique for response monitoring in HER2-positive and triple-negative tumors. In contrast, for ER-

positive tumors this study showed that a combination of contrast-enhanced MRI and PET/CT was the

best strategy for response evaluation [Schmitz et al., submitted].

The more recently introduced hybrid PET/MRI scanners may be more suitable for response

evaluation since tumor response can be monitored not only in the breast but also in the axillary

lymph nodes.

Future research

Future prospective research should validate our findings that the performance of MRI for response

monitoring is influenced by the subtype of breast cancer. It needs to focus on improving MRI

techniques, implementation of combined imaging techniques and validation of prior results for

different breast cancer subtypes in order to improve patient tailored treatment. Furthermore it

would be interesting to know how it would impact results if subtypes and its relation to MRI

performance would be taken into account in clinical diagnostic trials.

138

Future research will be needed to validate our finding that a complete response on MRI is predictive

of an excellent prognosis after neoadjuvant treatment. In the near future a study will start which will

be investigating whether in case of a radiological complete response at MRI marker-guided biopsies

after neoadjuvant chemotherapy can predict pathology. In addition research will be needed whether

surgery can be omitted in case of a radiological complete response, especially in luminal-type

tumors. Continuing trials, introducing new MRI techniques and sequences, will lead to

improvements in the quality and reliability of MRI.

Conclusions and Recommendations

Our findings demonstrate the potential clinical relevance of contrast-enhanced MRI for monitoring

response of breast cancer during and after neoadjuvant chemotherapy. We defined MRI criteria (i.e.,

chemotherapy regimen in case of an ‘unfavorable’ response during neoadjuvant chemotherapy. We

have demonstrated that during chemotherapy, MRI is effective in monitoring response in triple-

negative and HER2-positive disease, but it is inaccurate in ER-positive/HER2-negative breast cancer.

Switching chemotherapy based on the MRI criteria of unfavorable responders with ER-positive/HER2-

negative tumors causes tumor size reduction. A response-adapted strategy using MRI may enhance

the efficacy of neoadjuvant chemotherapy.

After neoadjuvant chemotherapy, the tumor size at baseline MRI, the reduction in tumor size on MRI

and breast cancer subtype should be taken into account to select patients for breast-conserving

surgery. A radiological complete response on MRI after chemotherapy is associated with an excellent

prognosis in ER-positive/HER2-negative breast cancer.

Based on the results of this thesis we recommend the use of MRI for the evaluation of response of

breast cancer to neoadjuvant chemotherapy. Our results suggest that the performance of MRI in the

assessment of response during and after neoadjuvant chemotherapy could be influenced by the

breast cancer subtype. Although prospective and large validation studies are needed to confirm this

finding, we believe that it is relevant to consider this finding if MRI is opted for evaluation of

treatment response.

139

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CHAPTER 8

Samenvatting

143

Hoofdstuk 1 Introductie en opbouw proefschrift

Borstkanker is de meest voorkomende vorm van kanker bij vrouwen in Nederland [1]. Ondanks

verbeterde diagnostiek, introductie van het nationale bevolkingsonderzoek borstkanker en de

beschikbaarheid van adjuvante (aanvullende) systemische behandeling, sterven er vrouwen aan de

gevolgen van borstkanker. Vooral jonge vrouwen met biologisch agressieve en uitgebreidere ziekte

(TNM stadium ≥II) hebben een verhoogd overlijdensrisico. Naast lokale therapie, bestaande uit

chirurgie en/of radiotherapie (bestraling), worden deze vrouwen aanvullend behandeld met een

systemische therapie, zoals chemo- en/of hormonale therapie [2]. In toenemende mate wordt deze

systemische behandeling voorafgaand aan de chirurgie gegeven. Deze zogenaamde neoadjuvante

chemotherapie-strategie heeft primair tot doel uitzaaiingen (micrometastasen) te elimineren en

daarnaast borsttumoren zo te verkleinen (downstagen), dat een borstsparende operatie mogelijk

wordt. Daarbij maakt neoadjuvante chemotherapie het mogelijk om de reactie (respons) van de

borstkanker op chemotherapie te evalueren (monitoren) met de primaire tumor nog in situ. Na de

neoadjuvante chemotherapie kan de chirurgie, bij voldoende tumorrespons, worden omgezet van

een mastectomie(borstamputatie) naar een borstsparende operatie. Aangezien een pathologisch

complete remissie (pCR = geen tumorcellen meer aanwezig) na neoadjuvante chemotherapie

geassocieerd is met een betere prognose, is het uiteindelijke doel van respons monitoren om non-

responsieve tumoren ( die dus geen pCR zullen bereiken) te kunnen onderscheiden. In deze gevallen

kan de chemotherapie omgezet (geswitcht) worden naar een (vermoedelijk) non-cross-resistente

chemotherapie. Dit beleid kan leiden tot een verbeterde op-maat-gemaakte of gepersonaliseerde

borstkankerbehandeling. Een betrouwbare respons-evaluatie is van wezenlijk belang. MRI wordt in

toenemende mate gebruikt om de respons van borstkanker op chemotherapie te evalueren

aangezien conventionele beeldvorming (mammografie en echo) minder betrouwbaar is [3,4]. Echter,

de exacte rol van dynamische contrast MRI in het bepalen van residuele ziekte en het voorspellen

van lange termijn uitkomsten tijdens en na neoadjuvante chemotherapie, vooral in borstkanker

subgroepen, is onbekend.

Het doel van dit proefschrift is om de rol van de MRI, in het bijzonder dynamische MRI voor en na

intraveneus contrast (dynamic contrast-enhanced MRI), te onderzoeken bij het evalueren van

borstkankerrespons op neoadjuvante chemotherapie teneinde de “borstkankerbehandeling op

maat" te verbeteren.

144

Hoofdstuk 2

Als eerste werd de voorspellende waarde van de MRI voor het vaststellen van een vroege

borstkankerrespons tijdens neoadjuvante chemotherapie onderzocht. Eerst hebben we MRI

karakteristieken geïdentificeerd, die in een groep van 54 patiënten voorspellend waren voor de

definitieve pathologie uitslag na chemotherapie (complete of niet-complete remissie). Daarna

hebben we een praktische voorspellende MRI test (ook wel MRI criteria genoemd) vastgesteld om

tumoren te identificeren die geen pathologisch complete remissie (pCR)zullen bereiken. We hebben

vastgesteld dat de verandering in langste diameter van de late aankleuring op MRI tijdens

neoadjuvante chemotherapie het best voorspellende MRI kenmerk is van de definitieve pathologie.

We hebben een punt op de ROC curve (langste diameter late aankleuring) gekozen dat slechts 5%

fout-positieven toestaat, teneinde te voorkomen dat excellente responders van chemotherapie

zouden moeten switchen naar een andere therapie. Een afname van minder dan 25% van de langste

diameter van late aankleuring op MRI tijdens neoadjuvante chemotherapie is indicatief voor

resttumor bij pathologisch onderzoek na chemotherapie. Door het toepassen van deze MRI criteria

zou 41% (22/54) van de patiënten van chemotherapie switchen. Patiënten met een gunstige respons

(afname ≥25%) behalen in bijna de helft van de gevallen (44%, 14/32) een pathologisch complete

respons. Klinische oncologen zouden de MRI criteria (afname van meer of minder dan 25% langste

diameter op MRI tijdens chemotherapie) kunnen gebruiken als een objectief middel met een hoge

specificiteit voor een borstkankerbehandeling op maat.

Hoofdstuk 3

Borstkanker is een ziekte bestaande uit een verzameling van verschillende tumor subtypen met

verschillend biologisch gedrag. Daarom hebben we bij 188 patiënten met MRI de relatie tussen

borstkankersubtype en de borstkanker respons op neoadjuvante chemotherapie onderzocht.

Borstkanker werd met gebruik van immuunhistochemie (naar hormoonreceptor status)

onderverdeeld in drie subgroepen; 1) triple-negatief, 2) HER2-positief en 3) ER-positief/HER2-

negatief. We vonden dat borstkankersubtype en MRI tijdens neoadjuvante chemotherapie significant

geassocieerd zijn met definitieve pathologie na chemotherapie (pCR of geen pCR) en de BRI (borst

response index[5]). Tijdens subgroep analyse hebben we vastgesteld dat veranderingen op MRI

tijdens neoadjuvante chemotherapie voorspellend zijn voor pCR in triple-negatieve en HER2-

positieve tumoren, maar niet bij ER-positieve/HER2-negatieve tumoren. Dit betekent dat zowel de

radioloog als de oncoloog zich bewust moet zijn van het subtype wanneer MRI voorafgaand en

145

tijdens neoadjuvante chemotherapie gebruikt wordt om het effect van de behandeling vast te

stellen.

Hoofdstuk 4

In hoofdstuk 4 evalueerden we het effect van een respons-aangepaste neoadjuvante chemotherapie

bij patiënten met ER-positieve/HER2-negatieve borstkanker. De chemotherapie (dose-dense

doxorubicine en cyclofosfamide (ddAC)) werd aangepast op geleide van de eerder gedefinieerde MRI

criteria (ongunstige respons <25% afname in langste diameter van de late aankleuring op MRI tijdens

neoadjuvante chemotherapie) naar docetaxel en capecitabine (DC). De mate van tumor afname op

MRI na switchen van chemotherapie werd vergeleken met die van de non-switchers (met gunstige

respons). Tumoren met een gunstige respons hadden een gemiddelde afname in omvang van 31% op

MRI halverwege neoadjuvante chemotherapie, tegenover een afname van 12% in de ongunstige

respons groep. Nadat de chemotherapie geswitcht was in de ongunstige respons groep trad er alsnog

een afname in omvang van 27% op na afronden van het tweede deel van de neoadjuvante

chemotherapie. Deze afname is vergelijkbaar met de 34% van de groep die niet is geswitcht. Het

gebruik van een respons-aangepaste chemotherapie suggereert dat een verandering in

chemotherapie regime effectief kan zijn wanneer de initiële chemotherapie dat niet is.

Hoofdstuk 5

In hoofdstuk 5 wordt een op MRI gebaseerd interpretatiemodel gepresenteerd dat de patiënten

selectie voor borstsparende chirurgie kan verbeteren. De beslissing om borstsparend te opereren na

neoadjuvante chemotherapie is complex en wordt beïnvloed door zowel chirurgische mogelijkheden

als de wens van de patiënt. Een nauwkeurige preoperatieve bepaling van resterende ziekte na

neoadjuvante chemotherapie is cruciaal bij het plannen van de optimale borstoperatie. Resterende

ziekte werd accuraat op MRI na neoadjuvante chemotherapie gedetecteerd in 76% (158/208) van de

patiënten. De positieve en negatieve voorspellende waarde van MRI was 90% (130/144) en 44%

(28/64), respectievelijk. Bij 35 patiënten (17%) werd de tumor omvang onderschat vergeleken met

definitieve pathologie na chemotherapie en in 27 (13%) leidde dit tot een ongerechtvaardigde keuze

voor een borstsparende operatie. Het MRI model is gebaseerd op karakteristieken die het meest

voorspellend zijn voor de haalbaarheid van borstsparende chirurgie: 1) langste diameter op de

baseline MRI, 2) de reductie in tumor omvang en 3) tumor subtype (oppervlakte onder de curve:

0.78). Dit model kan klinisch worden toegepast ter onderbouwing van de afweging wel of geen

borstsparende chirurgie.

146

Hoofdstuk 6

In hoofdstuk 6 hebben we onderzocht of er een verband bestaat tussen MRI na neoadjuvante

chemotherapie en ziektevrije overleving van patiënten met ER-positieve/HER2-negatieve

borstkanker. De MRI scans van 272 ER-pos/HER-2 negatieve patiënten bleken inderdaad variabelen

met een prognostische waarde te bevatten. Met behulp van multivariate analyse bleken de

variabelen: leeftijd jonger dan 50 jaar (HR= 2.37; 95%; CI (1.22, 4.63), p=0.01), een radiologische

complete remissie na neoadjuvante chemotherapie (HR= 9.57; CI (1.32, 1217.22); p=0.02), en

kleinere uitwas/plateau op MRI na neoadjuvante chemotherapie (HR1.02; CI (1.00, 1.04), p=0.049)

onafhankelijk geassocieerd te zijn met de langste ziektevrije overleving. Met name een radiologisch

complete remissie op MRI na neoadjuvante chemotherapie is geassocieerd met een excellente

prognose. Deze resultaten suggereren dat MRI na neoadjuvante chemotherapie gebruikt zou kunnen

worden als complementair eindpunt tijdens de behandeling van ER-positieve/HER2-negatieve

borstkanker.

147

Conclusies en Aanbevelingen

Onze bevindingen tonen de klinische toepasbaarheid van dynamische contrast MRI van de borst om

borstkanker respons te monitoren tijdens en na neoadjuvante chemotherapie. We hebben MRI

criteria (afname van minder dan 25% van de langste diameter van late aankleuring op MRI)

gedefinieerd als objectieve parameter om het chemotherapie regime te switchen halverwege

neoadjuvante chemotherapie. We hebben aangetoond dat tijdens neoadjuvante chemotherapie MRI

effectief is om respons te monitoren van triple-negatieve en HER2-positieve borstkanker, maar

ineffectief bij ER-positieve/HER2-negatieve borstkanker. Het switchen van chemotherapie gebaseerd

op de MRI criteria bij ER-positieve/HER2-negatieve tumoren met een ongunstige respons veroorzaakt

een toegevoegde afname van de omvang. Door de chemotherapie aan te passen aan de hand van de

respons op MRI zou de doelmatigheid van de neoadjuvante chemotherapie vergroot kunnen worden.

Na neoadjuvante chemotherapie zullen de tumoromvang op de baseline MRI, de afname in

tumoromvang en het borstkanker subtype meegenomen moeten worden bij de selectie van

geschikte patiënten voor borstsparende chirurgie. Een radiologisch complete remissie op MRI na

neoadjuvante chemotherapie is geassocieerd met een excellente prognose bij ER-positieve/HER2-

negatieve borstkanker.

Het is aan te bevelen om de respons van borstkanker op neoadjuvante chemotherapie te evalueren

met MRI. Bij het beoordelen van de respons tijdens en na neoadjuvante chemotherapie op de MRI is

het borstkanker subtype van groot belang. Met betrekking tot respons evaluatie beschouwen wij

onze bevindingen tot onderdeel van voortgaand onderzoek. In de toekomst zal het onderzoek zich

kunnen toeleggen op het verbeteren van MRI technieken, implementatie van gecombineerde

beeldvormende technieken en validatie van eerdere resultaten voor de verschillende borstkanker

subtypen ten einde de op maat gemaakte behandeling van borstkanker verder te verbeteren.

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Breast Cancer Res Treat. 2012 Jan;131(1):117-26. doi: 10.1007/s10549-011-1767-9. Epub 2011 Sep 21.

PubMed PMID: 21935602.

23: Alderliesten T, Loo CE, Pengel KE, Rutgers EJ, Gilhuijs KG, Vrancken Peeters MJ. Radioactive seed

localization of breast lesions: an adequate localization method without seed migration. Breast J. 2011

Nov-Dec;17(6):594-601. doi: 10.1111/j.1524-4741.2011.01155.x. Epub 2011 Sep 12. PubMed PMID:

21906208.

151

24: Loo CE, Straver ME, Rodenhuis S, Muller SH, Wesseling J, Vrancken Peeters MJ, Gilhuijs KG. Magnetic

resonance imaging response monitoring of breast cancer during neoadjuvant chemotherapy: relevance of

breast cancer subtype. J Clin Oncol. 2011 Feb 20;29(6):660-6. doi: 10.1200/JCO.2010.31.1258. Epub 2011

Jan 10. PubMed PMID: 21220595.

25: Rijnsburger AJ, Obdeijn IM, Kaas R, Tilanus-Linthorst MM, Boetes C, Loo CE, Wasser MN, Bergers E,

Kok T, Muller SH, Peterse H, Tollenaar RA, Hoogerbrugge N, Meijer S, Bartels CC, Seynaeve C, Hooning MJ,

Kriege M, Schmitz PI, Oosterwijk JC, de Koning HJ, Rutgers EJ, Klijn JG. BRCA1-associated breast cancers

present differently from BRCA2-associated and familial cases: long-term follow-up of the Dutch MRISC

Screening Study. J Clin Oncol. 2010 Dec 20;28(36):5265-73. doi: 10.1200/JCO.2009.27.2294. Epub 2010

Nov 15. PubMed PMID: 21079137.

26: Schmitz AC, van den Bosch MA, Loo CE, Mali WP, Bartelink H, Gertenbach M, Holland R, Peterse JL,

Rutgers EJ, Gilhuijs KG. Precise correlation between MRI and histopathology - exploring treatment

margins for MRI-guided localized breast cancer therapy. Radiother Oncol. 2010 Nov;97(2):225-32. doi:

10.1016/j.radonc.2010.07.025. Epub 2010 Sep 7. PubMed PMID: 20826026.

27: Elshof LE, Rutgers EJ, Deurloo EE, Loo CE, Wesseling J, Pengel KE, Gilhuijs KG. A practical approach to

manage additional lesions at preoperative breast MRI in patients eligible for breast conserving therapy:

results. Breast Cancer Res Treat. 2010 Dec;124(3):707-15. doi: 10.1007/s10549-010-1064-z. Epub 2010 Jul

22. PubMed PMID: 20652399.

28: Alderliesten T, Loo C, Paape A, Muller S, Rutgers E, Peeters MJ, Gilhuijs K. On the feasibility of MRI-

guided navigation to demarcate breast cancer for breast-conserving surgery. Med Phys. 2010

Jun;37(6):2617-26. PubMed PMID: 20632573.

29: Straver ME, Loo CE, Alderliesten T, Rutgers EJ, Vrancken Peeters MT. Marking the axilla with

radioactive iodine seeds (MARI procedure) may reduce the need for axillary dissection after neoadjuvant

chemotherapy for breast cancer. Br J Surg. 2010 Aug;97(8):1226-31. doi: 10.1002/bjs.7073. PubMed

PMID: 20602508.

30: Straver ME, Rutgers EJ, Rodenhuis S, Linn SC, Loo CE, Wesseling J, Russell NS, Oldenburg HS, Antonini

N, Vrancken Peeters MT. The relevance of breast cancer subtypes in the outcome of neoadjuvant

chemotherapy. Ann Surg Oncol. 2010 Sep;17(9):2411-8. doi: 10.1245/s10434-010-1008-1. Epub 2010 Apr

6. PubMed PMID: 20373039; PubMed Central PMCID: PMC2924493.

31: Straver ME, Loo CE, Rutgers EJ, Oldenburg HS, Wesseling J, Vrancken Peeters MJ, Gilhuijs KG. MRI-

model to guide the surgical treatment in breast cancer patients after neoadjuvant chemotherapy. Ann

Surg. 2010 Apr;251(4):701-7. doi: 10.1097/SLA.0b013e3181c5dda3. PubMed PMID: 20224378.

32: Mann RM, Loo CE, Wobbes T, Bult P, Barentsz JO, Gilhuijs KG, Boetes C. The impact of preoperative

breast MRI on the re-excision rate in invasive lobular carcinoma of the breast. Breast Cancer Res Treat.

2010 Jan;119(2):415-22. doi: 10.1007/s10549-009-0616-6. PubMed PMID: 19885731.

33: Obdeijn IM, Loo CE, Rijnsburger AJ, Wasser MN, Bergers E, Kok T, Klijn JG, Boetes C. Assessment of

152

false-negative cases of breast MR imaging in women with a familial or genetic predisposition. Breast

Cancer Res Treat. 2010 Jan;119(2):399-407. doi: 10.1007/s10549-009-0607-7. PubMed PMID: 19876732.

34: Loo CE, van Pel R. [Diagnostic image. A woman with an abnormal screening mammogram]. Ned

Tijdschr Geneeskd. 2009;153:B474. Dutch. PubMed PMID: 19857311.

35: Teertstra HJ, Loo CE, van den Bosch MA, van Tinteren H, Rutgers EJ, Muller SH, Gilhuijs KG. Breast

tomosynthesis in clinical practice: initial results. Eur Radiol. 2010 Jan;20(1):16-24. doi: 10.1007/s00330-

009-1523-2. Epub 2009 Aug 6. PubMed PMID: 19657655.

36: Straver ME, van Adrichem JC, Rutgers EJ, Rodenhuis S, Linn SC, Loo CE, Gilhuijs KG, Oldenburg HS,

Wesseling J, Russell NS, Antonini N, Vrancken Peeters MT. [Neoadjuvant systemic therapy in patients with

operable primary breast cancer: more benefits than breast-conserving therapy]. Ned Tijdschr Geneeskd.

2008 Nov 15;152(46):2519-25. Dutch. PubMed PMID: 19055260.

37: Loo CE, Teertstra HJ, Rodenhuis S, van de Vijver MJ, Hannemann J, Muller SH, Peeters MJ, Gilhuijs KG.

Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy:

initial results. AJR Am J Roentgenol. 2008 Nov;191(5):1331-8. doi: 10.2214/AJR.07.3567. PubMed PMID:

18941065.

38: Pengel KE, Loo CE, Teertstra HJ, Muller SH, Wesseling J, Peterse JL, Bartelink H, Rutgers EJ, Gilhuijs KG.

The impact of preoperative MRI on breast-conserving surgery of invasive cancer: a comparative cohort

study. Breast Cancer Res Treat. 2009 Jul;116(1):161-9. doi: 10.1007/s10549-008-0182-3. Epub 2008 Sep

21. PubMed PMID: 18807269.

39: Meijnen P, Oldenburg HS, Loo CE, Nieweg OE, Peterse JL, Rutgers EJ. Risk of invasion and axillary

lymph node metastasis in ductal carcinoma in situ diagnosed by core-needle biopsy. Br J Surg. 2007

Aug;94(8):952-6. PubMed PMID: 17440955.

40: Alderliesten T, Schlief A, Peterse J, Loo C, Teertstra H, Muller S, Gilhuijs K. Validation of semiautomatic

measurement of the extent of breast tumors using contrast-enhanced magnetic resonance imaging.

Invest Radiol. 2007 Jan;42(1):42-9.PubMed PMID: 17213748.

41: van Rijk MC, Tanis PJ, Nieweg OE, Loo CE, Olmos RA, Oldenburg HS, Rutgers EJ, Hoefnagel CA, Kroon

BB. Sentinel node biopsy and concomitant probe-guided tumor excision of nonpalpable breast cancer.

Ann Surg Oncol. 2007 Feb;14(2):627-32.Epub 2006 Dec 6. PubMed PMID: 17151797.

42: Hannemann J, Oosterkamp HM, Bosch CA, Velds A, Wessels LF, Loo C, Rutgers EJ, Rodenhuis S, van de

Vijver MJ. Changes in gene expression associated with response to neoadjuvant chemotherapy in breast

cancer. J Clin Oncol. 2005 May 20;23(15):3331-42. PubMed PMID: 15908647.

43: Kaas R, Kroger R, Hendriks JH, Besnard AP, Koops W, Pameijer FA, Prevoo W, Loo CE, Muller SH. The

significance of circumscribed malignant mammographic masses in the surveillance of BRCA 1/2 gene

mutation carriers. Eur Radiol. 2004 Sep;14(9):1647-53. Epub 2004 Apr 9. PubMed PMID: 15083333.

153

CONTRIBUTION AUTHORS

Claudette E. Loo, H. Jelle Teertstra, Sjoerd Rodenhuis, Marc J. van de Vijver, Juliane Hannemann, Sarah H. Muller, Marie-Jeanne Vrancken Peeters, Kenneth G. A. Gilhuijs. Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy: Initial Results. Study design and concept: CL, KG, SR, SM Data acquisition: JT, CL, KG Data analysis and interpretation: SR, SM, CL, KG Statistical analysis: CL, KG Manuscript writing: CL, KG Manuscript editing: All authors Manuscript review: All authors

Claudette E. Loo, Marieke E. Straver, Sjoerd Rodenhuis, Sara H. Muller, Jelle Wesseling, Marie-Jeanne T.F.D. Vrancken Peeters, Kenneth G.A. Gilhuijs. Magnetic resonance imaging response monitoring of breast cancer during neoadjuvant chemotherapy: Relevance of breast cancer subtype. Study design and concept: SR, KG, CL Data acquisition: CL, JW, MS, KG Data analysis and interpretation: CL, SR, KG Statistical analysis: CL, KG Manuscript writing: MS, CL, KG Manuscript editing: All authors Manuscript review: All authors

Lisanne S. Rigter, Claudette E. Loo, Sabine C. Linn, Gabe S. Sonke, Eric van Werkhoven, Esther H. Lips, Hildegonda H Warnars, Petra K. Doll, Annemarie Bruining, Ingrid A. Mandjes, Marie-Jeanne Vrancken Peeters, Jelle Wesseling, Kenneth G.A. Gilhuijs, and Sjoerd Rodenhuis. Neoadjuvant chemotherapy adaption and serial MRI response monitoring in ER-positive HER-negative breast cancer. Study design and concept: LR, SR, KG Data acquisition: CL, IM, LR, AB, HG, PD Data analysis and interpretation: CL, SR, LR Statistical analysis: EvW, SR, LR Manuscript writing: LR, SR, CL Manuscript editing: All authors Manuscript review: All authors

Marieke E. Straver, Claudette E. Loo, Emiel J.T. Rutgers, Hester S.A. Oldenburg, Jelle Wesseling, Marie-Jeanne T.F.D. Vrancken Peeters, and Kenneth G.A. Gilhuijs. MRI-model to guide the surgical treatment in breast cancer patients after neoadjuvant chemotherapy. Study design and concept: MS, MVP, CL, KG Data acquisition: MS, JW, CL, MVP Data analysis and interpretation: MVP, KG, CL, MS Statistical analysis: KG, MS Manuscript writing: MS, CL, MVP, KG Manuscript editing: All authors Manuscript review: All authors

Claudette E. Loo, Lisanne S. Rigter, Kenneth E. Pengel, Jelle Wesseling, Sjoerd Rodenhuis, Marie-Jeanne T. F. D. Vrancken Peeters, Karolina Sikorska, Kenneth G. A. Gilhuijs. Survival is associated with complete response on MRI after neoadjuvant chemotherapy in ER-positive HER2-negative breast cancer.

Study design and concept: KG, SR, CL, LR Data acquisition: CL, LR, KP, JW Data analysis and interpretation: CL, SR, KS, KG Statistical analysis: KS, CL, KG, SR Manuscript writing: CL, SR, KG Manuscript editing: All authors Manuscript review: All authors
















154

PHD PORTFOLIO

Name PhD student: Claudette Loo Period: 2007 - 2016 Name supervisors: Prof. dr. S. Rodenhuis, Prof. dr. R.G.H. Beets-Tan, Dr. K. G.A. Gilhuijs

General courses

Year Workload

Time ECTS

BROK (Basiscursus Regelgeving Klinisch Onderzoek) 2006 40 hrs 1.4

PubMed 2007 8 hrs 0.25

Basic Statistics course 2007 24 hrs 0.85

Reference manager / Endnote 2008 16 hrs 0.57

LRCB breast screening course 2011 32 hrs 1.1

Teach the teacher 2012, 2014 28 hrs 1

Spreken in het openbaar (AMC) 2015 8 hrs 0.25

National and international conferences

European Conference of Radiology (ECR) Vienna, Austria 2005, 2012 28 hrs 1

NKI- AVL Breast Cancer Symposium 2002 - 2015 42 hrs 1.5

EBCC3 2008, 2014, 28 hrs 1

Sandwichcourse (NVVR) breast 2007, 2015, 2016

14 hrs 0.5

The breast course 2009 16 hrs 0.57

Pearl breast course IDKD 2014 8 hrs 0.25

EUSOBI (European Society of Breast Imaging) annual scientific meeting 2012 - 2016 28 hrs 1

Meetings:

Regular attendance of Breast tumor workgroup AVL

Regular attendance of multidisciplinary breast cancer meeting AVL

Regular attendance of multidisciplinary breast tumor group IKNL

Regular attendance of Dutch College of Breast Imaging (DCBI) meeting

Presentations Organization Year

Oral:

Monitoring Response To Neoadjuvant Chemotherapy In Locally Advanced Breast Cancer: Efficacy Of Contrast-Enhanced MRI To Predict Presence Of Residual Disease.

ECR2 2005

Interpretation of DCE MRI for early prediction of breast cancer response to neoadjuvant chemotherapy: Initial results

EBCC3 2008

MRI monitoring of breast-cancer response during neoadjuvant chemotherapy: should molecular subtype be considered?

RSNA1 2009

Is MRI of the breast predictive for long term outcome after neoadjuvant chemotherapy?

RSNA1 2011

10 jaar respons monitoring met MRI in het NKI-AVL: Wat valt er te leren Mammacarcinoom symposium NKI-AVL

2011

MRI: wanneer niet? Mammacarcinoom symposium NKI-AVL

2012

MRI after neoadjuvant chemotherapie in ER-positive HER2-negative breast cancer predicts disease-free survival

Staff meeting Division of diagnostic oncology AVL

2013

Radiologische aspecten en respons monitoring tijdens neo-adjuvante chemotherapie

BOOG Neo-adjuvante studies

2013

Markering en respons evaluatie MRI BBB 2014

Response monitoring of neoadjuvant chemotherapy 3rd Breast 2015

155

Oncology & biopsy master class

To mark or not to mark? SWC mammaradiologie

2015

MRI as an imaging biomarker of response evaluation: Response-adapted strategies EUSOBI 2016

Posters:

Clinical guidelines for early detection of tumor response to neoadjuvant chemotherapy for breast cancer using contrast enhanced MRI.

SABCS3 2007

Interpretation of DCE MRI for early prediction of breast cancer response to neoadjuvant chemotherapy: Initial results

EBCC1 2008

Relevance of MRI to predict disease free survival after neoadjuvant chemotherapy of breast cancer.

SABCS3

2011

The value of a radiological complete response at MRI after neoadjuvant chemotherapy in breast cancer for disease-free survival.

ECR2 2012

Abstracts:

Co-author of more than 30 abstracts presented at several national and international congresses

2007-2015

Peer reviewed publications

In thesis: 5 Journal Year

Claudette E. Loo, H. Jelle Teertstra, Sjoerd Rodenhuis, Marc J. van de Vijver, Juliane Hannemann, Sarah H. Muller, Marie-Jeanne Vrancken Peeters, Kenneth G. A. Gilhuijs. Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy: Initial Results.

AJR Am J Roentgenol.

2008

Claudette E. Loo, Marieke E. Straver, Sjoerd Rodenhuis, Sara H. Muller, Jelle Wesseling, Marie-Jeanne T.F.D. Vrancken Peeters, Kenneth G.A. Gilhuijs. Magnetic resonance imaging response monitoring of breast cancer during neoadjuvant chemotherapy: Relevance of breast cancer subtype.

J Clin Oncol. 2011

Lisanne S. Rigter, Claudette E. Loo, Sabine C. Linn, Gabe S. Sonke, Eric van Werkhoven, Esther H. Lips, Hildegonda H Warnars, Petra K. Doll, Annemarie Bruining, Ingrid A. Mandjes, Marie-Jeanne Vrancken Peeters, Jelle Wesseling, Kenneth G.A. Gilhuijs, and Sjoerd Rodenhuis. Neoadjuvant chemotherapy adaption and serial MRI response monitoring in ER-positive HER-negative breast cancer.

Br J Cancer. 2013

Marieke E. Straver, Claudette E. Loo, Emiel J.T. Rutgers, Hester S.A. Oldenburg, Jelle Wesseling, Marie-Jeanne T.F.D. Vrancken Peeters, and Kenneth G.A. Gilhuijs. MRI-model to guide the surgical treatment in breast cancer patients after neoadjuvant chemotherapy.

Ann Surg. 2010

Claudette E. Loo, Lisanne S. Rigter, Kenneth E. Pengel, Jelle Wesseling, Sjoerd Rodenhuis, Marie-Jeanne T. F. D. Vrancken Peeters, Karolina Sikorska, Kenneth G. A. Gilhuijs. Survival is associated with complete response on MRI after neoadjuvant chemotherapy in ER-positive HER2-negative breast cancer.

Accepted for publication Breast Cancer Research

2015

Others: 39

See List of publications page 133 2005 - 2015

Teaching

Supervision medical students during their scientific internship NKI-AVL 2008-2015

Award

Jan Hendriksprijs (prijs vernoemd naar Jan Hendriks, voor jonge onderzoekers op het gebied van beeldvorming bij borstkanker)

2011

1: Radiological Society of North America 2: European Congress of Radiology 3: European breast cancer conference 4: San Antonio Breast Cancer Symposium

















156

DANKWOORD

Voor u ligt 10 jaar werk. Het is geen sinecure om te promoveren, klinisch te werken, te werken voor

de borstkankerscreening en een gezin te runnen. Tijdens dit hele traject hebben velen mij op de

meest uiteenlopende manieren geholpen. Aan iedereen ben ik dank verschuldigd. De volgende

mensen wil ik in het bijzonder noemen.

Jelle Teertstra, jij bracht het balletje aan het rollen en opperde het idee om mijn wetenschappelijke

activiteiten te bundelen en bracht me in contact met mijn promotor Prof. Sjoerd Rodenhuis. Sjoerd,

jouw snelle heldere directe reacties hebben mij geleid naar betere inzichten en publicaties met

klinische relevantie. Ik ben trots dat ik jouw allerlaatste promovendus mag zijn.

Mijn tweede promotor is Prof. Regina Beets-Tan. Beste Regina, wat geweldig dat je mij de kans hebt

gegeven om het daadwerkelijk af te ronden. Ik hoop in de toekomst samen meer van dit soort

resultaten te behalen.

Kenneth Gilhuijs, mijn copromotor, vanaf het begin geloofde jij er in en zag mogelijkheden. Jij had

altijd een luisterend oor en nam de tijd voor mij (ook als die er niet was en gemaakt moest worden).

Daarnaast heb ik je leren kennen als een gedreven wetenschapper die hecht aan het klinisch belang

van onderzoek. Door jou heb ik veel kunnen leren over de ins en outs in wetenschap. Ik hoop dat we

onze waardevolle samenwerking kunnen blijven voortzetten.

De leden van de promotiecommissie, wil ik allen hartelijk bedanken voor de tijd die jullie hebben

genomen voor de inhoudelijke beoordeling van dit proefschrift.

Promotiebegeleidingscommissie. Jelle Wesseling en Paula Elkhuizen dank voor de mooie

gesprekken, jullie steun in goede en minder goede tijden. Marie Jeanne Vrancken Peeters wat een

prachtig bevlogen mens ben je, een voorrecht om mee te mogen werken .

Ook mijn overige coauteurs wil ik bedanken voor het meedenken, de kritische kanttekeningen en

waardevolle suggesties.

Alle collega’s en medewerkers van de afdeling radiologie en mammateam AVL wil ik bedanken voor

hun steun, bevlogenheid in de dagelijkse klinische samenwerking en klinische implementatie. Ik kijk

er naar uit om het gezamenlijk onderzoek te continueren zodat de patiëntenzorg verder kan -

verbeteren.

157

Lieve pap en mam jullie onvoorwaardelijke liefde en steun voor mij is voor jullie zo vanzelfsprekend.

Jullie hebben mij gestimuleerd om het beste uit mezelf te halen. Ik heb me door jullie altijd geliefd en

gesteund gevoeld en dat maakt dat ik ben gekomen waar ik nu ben.

Lieve Liselot en Ties wat een geluk dat ik jullie moeder mag zijn. Jullie zijn mijn roze spiegel.

Dot, mijn lieve meisje, wat heb jij een doorzettingsvermogen en een positieve wil om er in elke

situatie iets van te maken. Jij maakt me bewust dat er altijd een zonnige kant is.

Ties, mijn mannetje, met jou kan ik afspraken maken en je organiseert en helpt graag. Voor mij

betekent het stick to the plan.

Allerliefste Roeland, liefde van mijn leven, de dag dat jij mijn leven binnenstapte voelde ik dit is het.

In de tien jaar samen hebben we onze dromen geleefd en veel bereikt. Ik vind je heerlijk, jouw

positieve denken, het vooruitkijken, onze inspirerende keukentafelgesprekken en je praktische steun

hebben mij enorm geholpen bij het klaren van de klus. Samen betekent voor mij met jou.

159

Curriculum Vitae

Claudette Elisabeth Loo was born on July 25, 1967 in Amsterdam the Netherlands. After graduating

from secondary school at the Willem de Zwijger College in Bussum, she studied Medicine at the VU

University in Amsterdam. After two years of working at the surgery department of the OLVG in

Amsterdam she performed her residency in Radiology in Leiden at the Leiden University Medical

Centre (then AZL). In 2002 she started a fellowship oncology at the radiology department at the

Netherlands Cancer Institute – Antoni van Leeuwenhoek (AVL) in Amsterdam. During the fellowship

she focused on the diagnostic imaging of breast cancer, with a special interest in breast MRI. She

became a dedicated breast radiologist and settled in the radiology staff and diagnostic research

group. She is a deputy trainer of the oncology internship AVL for residents of the AMC and

responsible of the breast radiology fellowship at the AVL. Since 2011 she is working for the Dutch

national breast cancer screening program as a screening radiologist and coordinating the radiology

group ‘Noord-Holland Noord’. Her primary research topic is on breast MRI, which has resulted in this

PhD thesis.

uva-dare (digital academic repository) dynamic contrast ...for monitoring response to neoadjuvant...

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