Multi‐Site Concordance of Diffusion‐Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness

Background Diffusion‐weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. Purpose To compare 14 site‐specific parametric fitting implementations applied to the same dataset of whole‐mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. Study Type Prospective. Population Thirty‐three patients prospectively imaged prior to prostatectomy. Field Strength/Sequence 3 T, field‐of‐view optimized and constrained undistorted single‐shot DWI sequence. Assessment Datasets, including a noise‐free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono‐exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi‐exponential diffusion (BID), pseudo‐diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). Statistical Test Levene's test, P