Quantitative Histogram Analysis of 5.0T Multiparametric MRI for Discrimination Between Prostate Cancer and Benign Hyperplasia.

IntroductionAccurate differentiation between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) remains a critical diagnostic challenge with direct implications for clinical management, in part due to the inherent subjectivity of the clinical reference standard Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). This study aimed to validate the diagnostic efficacy of ultra-high-field 5.0T multiparametric magnetic resonance imaging (mpMRI) histogram analysis for PCa and BPH differentiation.MethodsThis retrospective consecutive cohort study enrolled 85 patients (41 with pathologically confirmed PCa and 44 with BPH). Fourteen standardized histogram features were extracted from apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) parameters (D, D*, and f), and T2 mapping sequences. A multiparametric diagnostic model was constructed and validated via 5-fold stratified cross-validation.ResultsMultiple histogram parameters showed statistically significant between-group differences after Holm-Bonferroni correction for multiple comparisons (all P < 0.001), with the minimum ADC value demonstrating strong negative correlations with serum prostate-specific antigen (PSA) level (r = -0.578, P < 0.001) and Gleason score (r = -0.767, P < 0.001); the cross-validated multiparametric model yielded a mean area under the curve (AUC) of 0.9667 (95% CI: 0.924-1.000), which achieved superior diagnostic accuracy compared with the single-parameter ADC model (P < 0.05 via DeLong test).ConclusionThese findings suggest that 5.0T MRI-based quantitative histogram analysis is a promising noninvasive tool for differentiating PCa from BPH with high accuracy. It offers particular value for reducing diagnostic uncertainty in indeterminate PI-RADS 3 lesions and supporting personalized clinical decision-making.