Prostate cancer detection from model-free T1-weighted time series and diffusion imaging

20 March 2015 Prostate cancer detection from model-free T1-weighted time series and diffusion imaging

Nandinee Fariah Haq, Piotr Kozlowski, Edward C. Jones, Silvia D. Chang, S. Larry Goldenberg, Mehdi Moradi

Proceedings Volume 9414, Medical Imaging 2015: Computer-Aided Diagnosis; 94142X (2015) https://doi.org/10.1117/12.2082337
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

The combination of Dynamic Contrast Enhanced (DCE) images with diffusion MRI has shown great potential in prostate cancer detection. The parameterization of DCE images to generate cancer markers is traditionally performed based on pharmacokinetic modeling. However, pharmacokinetic models make simplistic assumptions about the tissue perfusion process, require the knowledge of contrast agent concentration in a major artery, and the modeling process is sensitive to noise and fitting instabilities. We address this issue by extracting features directly from the DCE T1-weighted time course without modeling. In this work, we employed a set of data-driven features generated by mapping the DCE T1 time course to its principal component space, along with diffusion MRI features to detect prostate cancer. The optimal set of DCE features is extracted with sparse regularized regression through a Least Absolute Shrinkage and Selection Operator (LASSO) model. We show that when our proposed features are used within the multiparametric MRI protocol to replace the pharmacokinetic parameters, the area under ROC curve is 0.91 for peripheral zone classification and 0.87 for whole gland classification. We were able to correctly classify 32 out of 35 peripheral tumor areas identified in the data when the proposed features were used with support vector machine classification. The proposed feature set was used to generate cancer likelihood maps for the prostate gland.

Citation Download Citation

Nandinee Fariah Haq, Piotr Kozlowski, Edward C. Jones, Silvia D. Chang, S. Larry Goldenberg, and Mehdi Moradi "Prostate cancer detection from model-free T1-weighted time series and diffusion imaging", Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94142X (20 March 2015); https://doi.org/10.1117/12.2082337

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available