Voxel Level Radiologic-Pathologic Validation of Restriction Spectrum Imaging Cellularity Index with Gleason Grade in Prostate Cancer

Restriction spectrum imaging (RSI-MRI), an advanced diffusion imaging technique, can potentially circumvent current limitations in tumor conspicuity, in vivo characterization, and location demonstrated by multiparametric magnetic resonance imaging (MP-MRI) techniques in prostate cancer detection. Prior reports show that the quantitative signal derived from RSI-MRI, the cellularity index, is associated with aggressive prostate cancer as measured by Gleason grade (GG). We evaluated the reliability of RSI-MRI to predict variance with GG at the voxel-level within clinically demarcated prostate cancer regions.

Ten cases were processed using whole mount sectioning after radical prostatectomy. Regions of tumor were identified by an uropathologist. Stained prostate sections were scanned at high resolution (75 μm/pixel). A grid of tiles corresponding to voxel dimensions was graded using the GG system. RSI-MRI cellularity index was calculated from presurgical prostate MR scans and presented as normalized z-score maps. In total, 2,795 tiles were analyzed and compared with RSI-MRI cellularity.

RSI-MRI cellularity index was found to distinguish between prostate cancer and benign tumor (t = 25.48, P < 0.00001). Significant differences were also found between benign tissue and prostate cancer classified as low-grade (GG = 3; t = 11.56, P < 0.001) or high-grade (GG ≥ 4; t = 24.03, P < 0.001). Furthermore, RSI-MRI differentiated between low and high-grade prostate cancer (t = 3.23; P = 0.003).

Building on our previous findings of correlation between GG and the RSI-MRI among whole tumors, our current study reveals a similar correlation at voxel resolution within tumors. Because it can detect variations in tumor grade with voxel-level precision, RSI-MRI may become an option for planning targeted procedures where identifying the area with the most aggressive disease is important. Clin Cancer Res; 22(11); 2668-74. ©2016 AACR.

Clinical cancer research : an official journal of the American Association for Cancer Research. 2016 Jun 01 [Epub]

Ghiam Yamin, Natalie M Schenker-Ahmed, Ahmed Shabaik, Dennis Adams, Hauke Bartsch, Joshua Kuperman, Nathan S White, Rebecca A Rakow-Penner, Kevin McCammack, J Kellogg Parsons, Christopher J Kane, Anders M Dale, David S Karow

Department of Radiology, University of California San Diego School of Medicine, San Diego, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California., Department of Pathology, University of California San Diego School of Medicine, San Diego, California., Department of Pathology, University of California San Diego School of Medicine, San Diego, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California., Department of Surgery, University of California San Diego School of Medicine, San Diego, California., Department of Surgery, University of California San Diego School of Medicine, San Diego, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California. Department of Neurosciences, University of California, San Diego, La Jolla, California., Department of Radiology, University of California San Diego School of Medicine, San Diego, California. .