Restriction Spectrum Imaging as a Quantitative Biomarker for Prostate Cancer With Reliable Positive Predictive Value.

Overview

abstract

PURPOSE: The positive predictive value of the Prostate Imaging Reporting and Data System (PI-RADS) for clinically significant prostate cancer (csPCa, grade group [GG] ≥2) varies widely between radiologists. The restriction spectrum imaging restriction score (RSIrs) is a biophysics-based metric derived from diffusion MRI that could be an objectively interpretable biomarker for csPCa. We aimed to evaluate performance of RSIrs for patient-level detection of csPCa in a large and heterogenous dataset, and to combine RSIrs with clinical and imaging parameters for csPCa detection. MATERIALS AND METHODS: At 7 centers, participants underwent prostate MRI between January 2016 and March 2024. We calculated patient-level csPCa probability based on maximum RSIrs in the prostate and compared patient-level csPCa detection to apparent diffusion coefficient (ADC) and PI-RADS using AUC. We also evaluated csPCa discrimination by GG and combining RSIrs with clinical risk factors through multivariable regression. RESULTS: Among patients who met the inclusion criteria (n = 1892), probability of csPCa increased with higher RSIrs. Among biopsy-naïve patients (n = 877), AUCs for GG ≥ 2 vs non-csPCa were RSIrs = 0.73 (0.69-0.76), ADC = 0.54 (0.50-0.57), and PI-RADS = 0.75 (0.71-0.78). RSIrs significantly outperformed ADC (P < .01) and was comparable with PI-RADS (P = .31). RSIrs and PI-RADS combined outperformed either alone. The model with RSIrs, PI-RADS, age, and PSA density achieved the best discrimination of csPCa. CONCLUSIONS: RSIrs is an accurate and reliable quantitative biomarker that performs better than conventional ADC and comparably with expert-defined PI-RADS for patient-level detection of csPCa. RSIrs provides objective estimates of probability of csPCa that do not require radiology expertise.