prostate cancer - center for biomedical imaging · 2013-03-31 · 5.1 imaging modalities (cont.)...

Prostate Cancer – Facts, Diagnosis, Use of Medical Images in

Guiding Biopsy and Improving Cancer Detection

Yangming OuSBIA @ UPENNApril, 10, 2007

Literature Review

Outline

• Prostate• Prostate Cancer• Diagnosis of Prostate Cancer• Biopsy Strategies• Imaging/Image Analysis to aid diagnosis

1. Prostate

Fig 1. Sagittal view of prostate and peripheral organs[1].

Fig 2. Prostate zonal anatomy[2].

2. Prostate Cancer (1)

• Definition: adenocarcinoma (glandular cancer)• Symptoms: urination & ejaculation problems

Normal[3]

Infection[3] Enlargement[3]

(Benign Prostate Hyperlasia)Cancer[4]

mild severe

2. Prostate Cancer (2)

• Causes: unknown• Epidemiology

age[5], genetics (race[5], family history) diet, lifestyle, medication, etc.

• Riskmetastasis [8]

2. Prostate Cancer (3)Incidence Rate [5] Fatality Rate [5]

Cancer Statistics[5]. 2007

3. Diagnosis of Prostate Cancer[6]

• No symptom at early stage• Prostate-specific antigen (PSA) test• Digital rectal exam (DRE)• Biopsy• Staging• Imaging for diagnosis and staging

3.1 Prostate-Specific Antigen (PSA) test

• Antigen• PSA• PSA test [1] (unit: ng/ml)

< 4 (or, <6.5 for 65 or older): normal4-10: 25% chances>10: 50 chances

• Problem

3. Diagnosis of Prostate Cancer

3.2 Digital Rectal Exam (DRE)[6]

• Check the size, shape and texture of the prostate

• Able to find cancers in men with normal PSA

• However, DRE only find advanced cancer – no effect in early diagnosis


3.3 Biopsy• The only test to confirm diagnosis

cut-out

inner stylet

outer core


Trans-Rectal UltraSound (TRUS) guided biopsy[7]

3.4 Prostate Cancer Grading/Staging

• Conducted if prostate cancer confirmed in biopsy• Tumor/Nodes/Metastases (TNM) system, T1-T4• Gleason System, score 2-10

Staging by TNM system. [7]


3.5 Imaging

TRUS, sagittal

CT

MRI, T2-weighted, fast spin-echo. 1.5T. Left to right: Axia/Coronal/Sagittal

Hricak et al, Med. Physics, 2007 [8]


4. Biopsy Strategies

• Motivation

To optimize the needle biopsy placement with 1) maximum prostate cancer detection rate2) minimum number of biopsy cores

4.1 Random Systematic Method4. Biopsy Strategies

Biopsy Plane [9] The most increasing point is 10-core biopsy. [9]

Noguchi et al, 2006

4.2 Computerized Biopsy Strategies• Zeng et al, 2000. & Mazal et al, 2001.

- divide the prostate into 48 (or 64 in Mazal’s work) boxes

- analyze statistical cancer occurrence in those boxes- place needles in a subset of those boxes

• Shen et al, 2004.- voxel-wise registration by AFDM- search k independent locations with

maximum statistical cancer occurrence


They are all based on statistical cancer distribution of a large number of prostate specimens, or, population-based cancer information.

4.3 Possible improvement • Patient-specific biopsy protocols• How?

a) suspicious cancer tissues in a patient’s own image-- patient-specific cancer information

b) statistical cancer distribution in a large number of prostate specimens-- population-based cancer information

• So, patient-specific + population-based information • Challenge:

Can we detect prostate cancer in images and achieve desirable accuracy?


5. Imaging/Image Analysis to aid diagnosis

• Imaging Modalities- T2-Weighted (T2W)- Diffusion Weighted Imaging (DWI)- Dynamic Contrast Enhanced Imaging (DCE)- MR Spectroscopy (MRS)

• Image Analysis literature

5.1.1 T2-weighted image

5.1. Imaging Modalities

Hricak et al, Radiology. 2007

5.1.1 T2-weighted image (cont.)5.1. Imaging Modalities

Kirkham et al, European Urology. 2006

5.1.2 Diffusion Weighted Image (DWI)

Conclusion: T2W+DWI > T2W

Shimofusa et al, J. Comput. Assist. Tomogr., 2005

T2W DWI


5.1.3 Apparent Diffusion Coefficient (ADC)

Desouza et al, The British Journal of Radiology, 2007


Conclusion from 33 patients:ADC values are significantly lower in malignant area than normal area.

5.1.4 Dynamic Contrast Enhanced MR

• Four parameters on time-concentration curve:- start of enhancement (onset)- time to peak enhancement- peak enhancement- washout time

• Challenge: Spatial-temporal tradeoff


Futterer et al, Radiology, 2005

5.1.4 DCE-MR (cont.)

T2W DEC-1

DEC-2 Histological

Conclusion: T2W+DCE > DCE > T2W

Futterer et al, Radiology, 2005


5.1.3 DCE-MR (cont.)5.1. Imaging Modalities

Kirkham et al, European Urology. 2006

5.1.5 MR Spectroscopy (MRS)• MRS provides metabolic

information of tissues• It displays relative

concentration of citrate, creatine, choline and polyamines for each voxel.

• (Cho+Cr)/Cit


5.1.6 Multi-modality Analysis

Futterer et al, Radiology. 2006

Conclusion: T2W+DEC+spectroscopy

T2W DCE-1

DCE-2 DCE-3

Spectroscopy


5.1.6 Multi-modality Analysis (cont.)

Tanimoto et al, J. MRI. 2007

Conclusion: T2W+DWI+ADC+DEC > each separately

DWI ADCT2W

DCE-1 DCE-2


5.1 Imaging Modalities (cont.)• Choi, JY, et al. Functional MR imaging of prostate cancer. Radiographics. 2007 Jan-

Feb;27(1):63-75 • Prando, A. Dynamic contrast enhanced, pelvic phased array magnetic resonance imaging of

localized prostate cancer for predicting tumor volume: correlation with radical prostatectomy findings. Int Braz J Urol. 2006 Nov-Dec;32(6):727-8.

• Girouin, N, et al. Prostate dynamic contrast-enhanced MRI with simple visual diagnostic criteria: is it reasonable? Eur Radiol. 2006 Nov 28

• Villers, A, et al. Dynamic contrast enhanced, pelvic phased array magnetic resonance imaging of localized prostate cancer for predicting tumor volume: correlation with radical prostatectomy findings. J Urol. 2006 Dec;176(6 Pt 1):2432-7.

• Futterer, JJ, et al. Prostate cancer localization with dynamic contrast-enhanced MR imaging and proton MR spectroscopic imaging. Radiology. 2006 Nov;241(2):449-58.

• Kozlowksi, P, et al. Combined diffusion-weighted and dynamic contrast-enhanced MRI for prostate cancer diagnosis--correlation with biopsy and histopathology. J Magn Reson Imaging. 2006 Jul;24(1):108-13.

• Kim, CK, et al. Localization of prostate cancer using 3T MRI: comparison of T2-weighted and dynamic contrast-enhanced imaging. J Comput Assist Tomogr. 2006 Jan-Feb;30(1):7-11


5.1 Imaging Modalities - Summary• Available modalities

- functional MR: DCE + DWI/ADC + Spectroscopy- structural MR: T2W- functional + structural MR

• Research Trends- Information fusion + automated cancer detection- which modality is more important- Multi-modality used in cancer staging- 1.5T or 3T?


5.2 Image Analysis in Prostate Cancer Diagnosis


Prostate Cancer Detection in ex vivo T2 MR images- Texture feature: GLCM + Gabor- Tissue Classification - Average 42.35% detection accuracy

Madabhushi et al, TMI. 2005

5.2 Image Analysis in Prostate Cancer Diagnosis (cont.)


Chan et al. Med. Physics. 2003

T2W ADC

T2W

Training schemeProbability Map

Feature: GLCM + DCTClassifier: FLD or SVMGround Truth: manual + biopsy validation

PD

6. Summary

• Prostate cancer is a big issue• Early diagnosis is very important• Biopsy is the gold-standard to confirm diagnosis• To optimize biopsy, patient-specific and

population-based cancer info. can be utilized• Multi-channel MR (T2W+DWI+ADC+DCE+MRS)

has stronger differentiation ability than single MR modality

Reference• [1] Wiki. http://en.wikipedia.org/wiki/Prostate_cancer• [2] http://www.prostate-cancer.org.uk/images/info/prostateZones.gif• [3] U.S. Food & Drug Administration (FDA)

http://www.fda.gov/fdac/features/2006/306_prostate.html• [4] http://www.malecare.org/prostate-cancer_42.htm• [5] A. Jemel, et al. Cancer Statistics. CA Cancer J Clin. 2007; 57:43-66 • [6] American Cancer Society: How is prostate cancer found?• [7] Prostate Cancer Grading. http://edoc.hu-berlin.de/dissertationen/kaiser-simone-2004-06-

10/HTML/chapter1.html• [8] hricak et al, Imaging Prostate Cancer: A Multidisciplinary Perspective. Radiology. 243(1): 28-

52.• [9] Noguchi et al. International Journal of Urology. 2006 (13):1296-1303.• [10] Shimofusa et al, J. Comput. Assist. Tomogr., 2005• [11] Futterer et al, Radiology, 2005• [12] Futterer et al, Radiology. 2006• [13] Tanimoto et al, J. MRI. 2007• [14] Choi et al, RadioGraphics. 2007• [15] Madabhushi et al, TMI. 2005• [16] Chan et al. Med. Physics. 2003• [17] Zeng et al. Comput. Graph. 2000• [18] Shen et al. Medical Image Analysis. 2004.• [19] Mazal et al. European Urology. 2001.

prostate cancer - center for biomedical imaging · 2013-03-31 · 5.1 imaging modalities (cont.)...

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