esmo e-learning: imaging biomarkers in breast oncology ... · imaging biomarkers in breast oncology...

Imaging biomarkers in breast

oncology practice

Elizabeth O’FlynnClinical Lecturer and Consultant Radiologist

Institute of Cancer Research and Royal Marsden Hospital,

London, United Kingdom

Background

Neoadjuvant chemotherapy (NAC):

Clinical response rates 70–98%1,2

Pathological complete response (pCR) 3–16%3

1. Powles TJ, et al. J Clin Oncol 1995;13:547–552; 2. Fisher B, et al. J Clin Oncol 1998;16:2672–2685;

3. Swain SM, et al. Cancer Res 1987;47:3889–94.

Images courtesy of Dr Elizabeth O’Flynn.

Pre-treatment End of treatmentPre-treatment Post-treatment (pCR)

Signal void from markerTumour

Predicting response

1. After completion of NAC to guide surgery

2. At baseline (prior to commencing NAC)

3. At an early time point (1 or 2 cycles after commencing NAC)

Predicting response after completion

of NAC

MRI gives more accurate staging compared to clinical examination

mammography and US1–4

1. Chagpar AB, et al. Ann Surg 2006;243:257–264; 2. Akawawa K, et al. Breast J 2006;12:130–137; 3. Montemurro F, et al.

Eur Radiol 2005,15:1224–1233; 4. Marinovich ML, et al. Br J Cancer 2013;109:1528–1536.

Author n

Pooled mean difference

(95% confidence intervals) (cm)

MRI

Clinical

exam Mammo US

Marinovich et al.

201319

0.1

(-0.2, 0.3)

-0.3

(-0.7, 0.0)

0.4

(-0.5, 1.3)

0.1

(-0.1, 0.4)

Underestimation of residual disease

Post-treatment

Tumour reduced

enhancement

Tumour

Pre-treatment


Overestimation of residual disease

Pre-treatment Post-treatment

Tumour Residual enhancement



of NAC

Author nSensitivity

(%)

Specificity

(%)PPV NPV AUC

De Los Santos et al.

20131 746 83 47 47 83 74

Hayashi et al.

20132 260 44 90 73 73 78

Ko et al.

20133 166 96 65 - - 89

Chen et al.

20124 64 39 92 - - -

Hylton et al.

20125 216 - - - - 84

1. De Los Santos JF, et al. Cancer 2013;1777–1783; 2. Hayashi Y, et al. Oncol Lett 2013;5:83–89; 3. Ko ES, et al. Ann Surg

Oncol 2013;20:2562–2568; 4. Chen et al. Chin Med J 2012;125:1862–1866; Hylton NM. et al. Radiology 2012;263:663–672.


of NAC

Author nSensitivity

(%)

Specificity

(%)PPV NPV AUC


20131 746 83 47 47 83 74

Hayashi et al.

20132 260 44 90 73 73 78

Ko et al.

20133 166 96 65 - - 89

Chen et al.

20124 64 39 92 - - -

Hylton et al.

20125 216 - - - - 84

1. De Los Santos JF, et al. Cancer 2013;1777–1783; 2. Hayashi Y, et al. Oncol Lett 2013;5:83–89; 3. Ko ES, et al. Ann Surg

Oncol 2013;20:2562–2568; 4. Chen et al. Chin Med J 2012;125:1862–1866; Hylton NM; et al. Radiology 2012;263:663–672.

Molecular subtypes of breast cancer

Molecular subtype Biomarker profile Prevalence

Luminal AER+ and/or PR+,

HER2-, low Ki67<14%42-59%

Luminal B

ER+ and/or PR+ and HER2+

ER+ and/or PR+, HER2-,

high Ki67>14%

6-19%

Basal-like/ triple negativeER-, PR- , HER2-,

cytokeratin 5/6+ and/or EGFR+14-20%

HER2 ER-, PR-, HER2+ 7-12%

ER = oestrogen receptor

PR = progesterone receptor

HER2 = human epidermal growth factor receptor 2

EGFR = epidermal growth factor receptor

Carey LA, et al. JAMA 2006;295:2492–2502; Nielsen TO, et al. Clin Cancer Res 2004;10:5367–5374; Perou CM, et al. Nature

2000;406:747–752; Rakha EA, et al. Eur J Cancer 2006;42:3149–3156; Sorlie T, et al. Proc Natl Acad Sci USA 2001;

98:10869–10874

MRI predicting response through subtype

Author n Findings

Hayashi et al.

20131 264 Better accuracy in triple negative cancers

Ko et al.

20132 166Worse accuracy in ER positive cancers and low

grade tumours

Chen et al.

20123 50Better accuracy in triple negative cancers and

high grade tumours

McGuire et al.

20114 203

Better accuracy in ER negative/ HER2 positive

cancers

Worse accuracy in luminal cancers

Kuzucan et al.

20125 54Worse accuracy in hormone positive cancers and

low grade tumours


20136 746Better accuracy in triple negative / HER2 positive

cancers

1. Hayashi Y, et al. Oncol Lett 2013;5:83–89; De Los Santos JF, et al. Cancer 2013;1777–1783; 2. Ko ES, et al. Ann Surg

Oncol 2013;20:2562–2568; 3. Chen et al. Chin Med J 2012;125:1862–1866; 4. McGuire KP et al. Ann Surg Oncol Ann Surg

Oncol 2011;18:3149–3154; 5. Kuzucan A, et al. Clin Breast Cancer 2012;12:110–118; 6. De Los Santos JF, et al. Cancer

2013;1777–1783.


Author n Findings

Hayashi et al.


Ko et al.

20132 166Worse accuracy in ER positive cancers and low

grade tumours

Chen et al.


high grade tumours

McGuire et al.

20114 203


cancers


Kuzucan et al.

20125 54Worse accuracy in hormone positive cancers and

low grade tumours


20136 746Better accuracy in triple negative / HER2

positive cancers

1. Hayashi Y, et al. Oncol Lett 2013;5:83–89; De Los Santos JF, et al. Cancer 2013;1777–1783; 2. Ko ES, et al. Ann Surg Oncol

2013;20:2562–2568; 3. Chen et al. Chin Med J 2012;125:1862–1866; 4. McGuire KP et al. Ann Surg Oncol 2011;18:3149–

3154; 5. Kuzucan A, et al. Clin Breast Cancer 2012;12:110–118; 6. De Los Santos JF, et al. Cancer 2013;1777–1783.


Author n Findings

Hayashi et al.


Ko et al.

20132 166Worse accuracy in ER positive cancers and

low grade tumours

Chen et al.


high grade tumours

McGuire et al.

20114 203


cancers


Kuzucan et al.

20125 54Worse accuracy in hormone positive cancers

and low grade tumours


20136 746Better accuracy in triple negative / HER2 positive

cancers

1. Hayashi Y, et al. Oncol Lett 2013;5:83–89; De Los Santos JF, et al. Cancer 2013;1777–1783; 2. Ko ES, et al. Ann Surg Oncol

2013;20:2562–2568; 3. Chen et al. Chin Med J 2012;125:1862–1866; 4. McGuire KP et al. Ann Surg Oncol 2011;18:3149–

3154; 5. Kuzucan A, et al. Clin Breast Cancer 2012;12:110–118; 6. De Los Santos JF, et al. Cancer 2013;1777–1783.

T2W MRI T1W DCE-MRI DWI b=1150 ADC map

Triple negative breast cancer

Dogan BE et al. Am J Roentgenol 2010;194:1160–1166; Chen JH, et al. Ann Oncol 2007:18:2042–2043; Wang Y, et al.

Radiology 2008;246:367–375; Noh JM, et al. J Breast Cancer 2013;16:308–314.

Enhancing rimHigh T2 centrally Restricted diffusion rim


Author n Study Sensitivity Specificity

Lobbes et al.

20131 35Systematic

review

Range

25 - 100%

Range

50 - 97%

Marinovich et al.

20132 44 Meta-analysis

Pooled

estimate

83 - 87%

Pooled

estimate

54 - 83%

MRI accuracy for residual disease

1. Lobbes MB, et al. Insights Imaging 2013;4:163–175; 2. Marinovich L, et al. J Natl Cancer Inst 2013;105:321–333.

Technique n Author Sensitivity Specificity PPV NPV

Clinical

exam

32 Arimappamagan

et al. 200486 64 40 94

US 32 Arimappamagan

et al. 2004

Heiken et al.

2013

86

58

100

70

100

57

96

71

MRI 88 Heiken et al.

201359 61 43 75

Nomogram 291 Schipper et al.

201443 88 65 75

Imaging techniques for predicting pCR in restaging the axilla post NAC

Schipper et al. Eur J Radiol 2015;84:41–47

Predicting response at baseline

Author n Factors predictive of response

Li et al.

20101 264 Traditional prognostic factors

Uematsu et al.

20102 166 Mass effect and wash-out pattern

Park et al.

20103 50 Lower pre-treatment ADC

Fangberget et al.

20114 264 HER2 overexpression

1. Li SP, et al. Radiology 2010;257:643–652; 2. Uematsu T, et al. Eur Rad 2010;20:2315-–2322; 3. Park SH, et al. Radiology

2010; 257:56–63; 4. Fangberget A, et al. Eur Radiol 2011;21:1188–1199.

MRI

Standard

Measurements

(RECIST)

MR Spectroscopy

Intrinsic

Susceptibility

Weighted

MRI (R2*)

Diffusion-

Weighted

Imaging (DWI)

Dynamic

Contrast

Enhanced MRI

(DCE-MRI)

Predicting response at an early time point

MRI

Standard

Measurements

(RECIST)

MR Spectroscopy

Intrinsic

Susceptibility

Weighted

MRI (R2*)

Diffusion-

Weighted

Imaging (DWI)

Dynamic

Contrast

Enhanced MRI

(DCE-MRI)

b=1150

Time-signal

Intensity

curves

Ktrans, kep, ve

Apparent Diffusion

Coefficient (ADC)

Choline

peak at

3.2ppm

R2*=1/T2*

Tumour diameter

Tumour volume


MRI

Standard

Measurements

(RECIST)

MRI parameters

Tumour Diameter

Tumour Volume

Image courtesy of Dr Elizabeth O’Flynn.

Dynamic

Contrast

Enhanced MRI

(DCE-MRI)

MRI parameters

VASCULARITY

Semi-quantitative parameters:

Time-signal intensity curves

Maximum signal intensity

Absolute MRI signal intensity

Relative MRI signal intensity

Normalised MRI signal intensity

Initial Area Under the Gadolinium Curve (IAUGC)

Enhancement Fraction

Pharmacokinetically modelled parameters:

Ktrans

kep

Ve

Textural analysis


Dynamic contrast enhanced (DCE)-MRI

Ktrans

Transfer constantkep

rate constant

renal excretion

Gd-DTPA

iv injection

Blood plasma

Ve

extravascular extracellular

space

Normal Tumour

Endothelial cells3

Pericyte – red3

Pharmacokinetic modelling1,2

1. Courtesy of O’Flynn EAM, et al. Breast Cancer Research 2011;13:204; 2. Tofts PS, et al. J Magn Reson Imaging

1999;10:223–232; 3. McDonald DM, et al. Nat Med 2003;9:713–725. Reprinted by permission from Macmillan Publishers Ltd:

Nature Medicine, © 2003

DCE-MRI Assessing treatment response

Author n RespondersNon-

responders

Time point

imaged after

NAC

Ah-See et al.

20081 19Ktrans ↓ 40%

kep ↓ 33%

Ktrans ↑ 18%

kep ↑ 7%2 cycles

Pickles et al.

20052 68

Ktrans ↓ 20%

kep ↓ 20%

ve ↑ 4%

Ktrans ↓ 20%

kep ↓ 36%

ve ↑ 28%

“early time

point”

Padhani et al.

20063 15Ktrans ↓ 22%

kep ↓ 62%

Ktrans ↓ 7%

kep ↓ 25%

1 cycle

2 cycles

Yu et al.

20074 29Ktrans ↓ 5%

kep ↓ 14%

Ktrans ↑ 8%

kep ↑ 7%1 cycle

Yu et al.

20105 32Ktrans ↓ 49%

ve ↓ 27%

Ktrans ↓ 18%

ve ↓ 13%2 cycles

1. Ah-See ML, et al. Clin Can Res 2008;14:6580–6589; 2. Pickles MD, et al. Breast Cancer Res Treat 2005;91:1–10; 3.Padhani

et al. Radiology 2006;239:361–374; 4. Yu JH, et al. J Magn Reson Imaging 2007;26:615–623; 5.Yu Y, et al. Radiology

2010;257:47–55.

Diffusion-

Weighted

Imaging (DWI)

MRI parameters

DWI b=1150 ADC map

CELLULARITY

ADC = Apparent Diffusion Coefficient



● ● ●

●

Random Brownian

MotionFree diffusion

Low signal intensity DWI

High signal ADC

Restricted diffusion

High signal intensity

DWI

Low signal ADC

cell water molecule

Normal tissue Tumour

Diffusion-Weighted Imaging (DWI)

Sensitive to factors affecting microscopic motion of water

b (s/mm2)

In (

S/S

0


b = 0

b = 350

b = 700

b = 1150

ADC map

S = S0e-b.ADC

DWI


Rise in ADC

Tumour size static

1. O’Flynn EA, et al. Eur Radiol 2012;22:1512–1518; 2. Pickles MD, et al. Magn Reson Imaging 2006;24:843–847

DWI

ADC values reproducible1

DWI has shown an increase in ADC prior to any change in breast

tumour size2

0 1 2

Treatment cycles

0.60.5

0.70.80.91.01.11.21.31.41.5

No

rmalised

ADC (normalised) Diameter (normalised)

DWI – Assessing treatment response

Author n RespondersTime point imaged after

NAC

Pickles et al.

20061 10ADC ↑ 16%

ADC↑ 27%

1 cycle

2 cycles

Sharma et al.

20092

14

24

29

ADC ↑ 15%

ADC ↑ 27%

ADC ↑35%

1 cycle

2 cycles

3 cycles

Nilsen et al.

20103 25 ADC ↑ 25% 4 cycles

Fangberget et al.

20114 29 ADC ↑ 40% 4 cycles

1. Pickles MD, et al. Magn Reson Imaging 2006;24:843–847; 2. Sharma U, et al. NMR Biomed 2009;22:104–113;

3. Nilsen l, et al. Acta Oncol 2010;49:354–360; 4. Fangberget A, et al. Eur Radiol 2011;21:1188–1199.

MR

Spectroscopy

MRI parameters

Voxel over

enhancing tumour

METABOLISM

Magnified spectrum illustrates

a positive Choline peak at a

frequency of 3.2 ppm

Graph courtesy of Dr Geoffrey Payne

Image courtesy of Dr Elizabeth O’Flynn

Spectroscopy –

Assessing treatment response

Author n Responders Non-responders

Time point

imaged after

NAC

Jacobs et al.

20111 18 [Cho] ↓ 35% [Cho] ↓ 11% 1 cycle

Tozaki et al.

20102 16 [Cho] ↓ 56% [Cho] ↓ 24% 2 cycles

Baek et al.

20093 35[Cho] ↓ 68% [Cho] ↓ 37%

2 cycles

Danishad et al.

20104 25

[Cho] ↓ 28%

[Cho] ↓ 49%

[Cho] ↓ 94%

[Cho] ↓ 8%

[Cho] ↓ 16%

[Cho] ↓ 39%

1 cycle

2 cycles

3 cycles

1. Jacobs MA, et al. Breast Cancer Res Treat 2011;128:119–126; 2. Tozaki M, et al. J Magn Reson Imaging 2010 ;31:895–902;

3. Baek HM, et al. Radiology 2009;251:653–662; 4. Danishad, et al. NMR Biomed 2010;23:233–241.

Intrinsic

Susceptibility

Weighted

MRI (R2*)

MRI parameters

T2* sequence

multiple echo

times

R2* map

OXYGENATION

R2*=1/T2*


Author n Responders Time point imaged after NAC

Li et al.

2010 27 ↑ 10% 2 cycles

Li SP, et al. Radiology 2010;257:643–652.

Intrinsic susceptibility weighted

imaging / R2*

Breast cancer patients R2* lower in tumour than normal parenchyma

prior to chemo

Early prediction of response

Authors Study n Findings

Prevos et al.

20121

Systematic

review15

Most frequently studies parameters:

Tumour diameter or volume

Ktrans, kep, ve, ADC

1. Prevos R, et al. Eur Rad 2012;22:2607–2616; Hylton NM, et al. Radiology 2012;263:663–672.

I-SPY TRIAL: Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis

Authors Study n Findings

Hylton et al.

20122 I-SPY 216

MR Imaging findings stronger

predictor of pCR than clinical exam

Greatest advantage observed using

volumetric measurement of tumour

response early in treatment

Multiparametric MRI

Improved diagnostic

accuracy combining

DCE-MRI, DWI

and MR Spectroscopy

Change in enhancement

fraction after 2 cycles

was the best

discriminator of response

1. Pinker K, et al. Invest Radiol 2014;49:421–430;

2. O’Flynn EA, et al. ISMRM Proceedings. 2014.

Images courtesy of Dr Elizabeth O’Flynn

Summary

Many MRI parameters and time points at which to predict response

No definite advantage of MRI assessment over US but more larger

scale studies needed

Tumour subtype plays a crucial role accuracy of MRI

Assessment of tumour volume and the ADC hold most potential for

incorporation into routine clinical practice

Standardisation required

Acknowledgments

ICR The Institute of Cancer research

Cancer Research UK

The Royal Marsden – NHS Foundation Trust

THANK YOU!

esmo e-learning: imaging biomarkers in breast oncology ... · imaging biomarkers in breast oncology...

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