Multiparametric MR imaging of prostate cancer foci: assessing the detectability and localizability of Gleason 7 peripheral zone cancers based on image contrasts

Eli Gibson; Mena Gaed; Thomas Hrinivich; José A. Gómez; Madeleine Moussa; Cesare Romagnoli; Jonathan Mandel; Matthew Bastian-Jordan; Derek W. Cool; Suha Ghoul; Stephen E. Pautler; Joseph L. Chin; Cathie Crukley; Glenn S. Bauman; Aaron Fenster; Aaron D. Ward

doi:10.1117/12.2043324

21 March 2014 Multiparametric MR imaging of prostate cancer foci: assessing the detectability and localizability of Gleason 7 peripheral zone cancers based on image contrasts

Eli Gibson, Mena Gaed, Thomas Hrinivich, José A. Gómez, Madeleine Moussa, Cesare Romagnoli, Jonathan Mandel, Matthew Bastian-Jordan, Derek W. Cool, Suha Ghoul, Stephen E. Pautler, Joseph L. Chin, Cathie Crukley, Glenn S. Bauman, Aaron Fenster, Aaron D. Ward

Author Affiliations +

Proceedings Volume 9041, Medical Imaging 2014: Digital Pathology; 90410N (2014) https://doi.org/10.1117/12.2043324
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Purpose: Multiparametric magnetic resonance imaging (MPMRI) supports detection and staging of prostate cancer, but the image characteristics needed for tumor boundary delineation to support focal therapy have not been widely investigated. We quantified the detectability (image contrast between tumor and non-cancerous contralateral tissue) and the localizability (image contrast between tumor and non-cancerous neighboring tissue) of Gleason score 7 (GS7) peripheral zone (PZ) tumors on MPMRI using tumor contours mapped from histology using accurate 2D–3D registration. Methods: MPMRI [comprising T2-weighted (T2W), dynamic-contrast-enhanced (DCE), apparent diffusion coefficient (ADC) and contrast transfer coefficient images] and post-prostatectomy digitized histology images were acquired for 6 subjects. Histology contouring and grading (approved by a genitourinary pathologist) identified 7 GS7 PZ tumors. Contours were mapped to MPMRI images using semi-automated registration algorithms (combined target registration error: 2 mm). For each focus, three measurements of mean ± standard deviation of image intensity were taken on each image: tumor tissue (m_T±s_T), non-cancerous PZ tissue < 5 mm from the tumor (m_N±s_N), and non-cancerous contralateral PZ tissue (m_C±s_C). Detectability [D, defined as m_T-m_C normalized by s_T and s_C added in quadrature] and localizability [L, defined as m_T-m_N normalized by s_T and s_N added in quadrature] were quantified for each focus on each image. Results: T2W images showed the strongest detectability, although detectability |D|≥1 was observed on either ADC or DCE images, or both, for all foci. Localizability on all modalities was variable; however, ADC images showed localizability |L|≥1 for 3 foci. Conclusions: Delineation of GS7 PZ tumors on individual MPMRI images faces challenges; however, images may contain complementary information, suggesting a role for fusion of information across MPMRI images for delineation.

Citation Download Citation

Eli Gibson, Mena Gaed, Thomas Hrinivich, José A. Gómez, Madeleine Moussa, Cesare Romagnoli, Jonathan Mandel, Matthew Bastian-Jordan, Derek W. Cool, Suha Ghoul, Stephen E. Pautler, Joseph L. Chin, Cathie Crukley, Glenn S. Bauman, Aaron Fenster, and Aaron D. Ward "Multiparametric MR imaging of prostate cancer foci: assessing the detectability and localizability of Gleason 7 peripheral zone cancers based on image contrasts", Proc. SPIE 9041, Medical Imaging 2014: Digital Pathology, 90410N (21 March 2014); https://doi.org/10.1117/12.2043324

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