A model describing diffusion in prostate cancer. Issue 1 (21st July 2016)

• Record Type: Journal Article
• Authors: Gilani, Nima; Malcolm, Paul; Johnson, Glyn
• Is Part Of: Magnetic resonance in medicine. Volume 78:Issue 1(2017)
• Page Start: 316
• Page End: 326
• Publication Date: 2016-07-21
• Subjects: prostate MRI -- diffusion -- kurtosis -- Gleason score -- biexponential diffusion; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.26340
• Languages: English
• ISSNs: 0740-3194

Abstract

Abstract : Purpose: Quantitative diffusion MRI has frequently been studied as a means of grading prostate cancer. Interpretation of results is complicated by the nature of prostate tissue, which consists of four distinct compartments: vascular, ductal lumen, epithelium, and stroma. Current diffusion measurements are an ill‐defined weighted average of these compartments. In this study, prostate diffusion is analyzed in terms of a model that takes explicit account of tissue compartmentalization, exchange effects, and the non‐Gaussian behavior of tissue diffusion. Method: The model assumes that exchange between the cellular (ie, stromal plus epithelial) and the vascular and ductal compartments is slow. Ductal and cellular diffusion characteristics are estimated by Monte Carlo simulation and a two‐compartment exchange model, respectively. Vascular pseudodiffusion is represented by an additional signal at b = 0. Most model parameters are obtained either from published data or by comparing model predictions with the published results from 41 studies. Model prediction error is estimated using 10‐fold cross‐validation. Results: Agreement between model predictions and published results is good. The model satisfactorily explains the variability of ADC estimates found in the literature. Conclusion: A reliable model that predicts the diffusion behavior of benign and cancerous prostate tissue of different Gleason scores has been developed. Magn Reson Med 78:316–326, 2017. © 2016 International Society for Magnetic Resonance in Medicine