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

Area of Science:

• Radiology and Imaging
• Oncology
• Medical Diagnostics

Background:

• Differentiating prostate cancer (PCa) from benign prostatic hyperplasia (BPH) is challenging due to the subjectivity of PI-RADS v2.1.
• Accurate differentiation is crucial for appropriate clinical management and treatment decisions.

Purpose of the Study:

• To validate the diagnostic efficacy of 5.0T multiparametric MRI (mpMRI) histogram analysis for differentiating PCa from BPH.
• To assess the performance of quantitative histogram features in distinguishing between these two conditions.

Main Methods:

• Retrospective analysis of 85 patients (41 PCa, 44 BPH) using 5.0T mpMRI.
• Extraction of 14 histogram features from ADC, IVIM (D, D*, f), and T2 mapping sequences.
• Development and validation of a multiparametric diagnostic model using 5-fold cross-validation.

Main Results:

• Significant differences in histogram parameters between PCa and BPH groups (P < 0.001).
• Minimum ADC value negatively correlated with PSA and Gleason score (r = -0.578, P < 0.001 and r = -0.767, P < 0.001, respectively).
• Multiparametric model achieved a mean AUC of 0.9667, outperforming the single-parameter ADC model.

Conclusions:

• 5.0T MRI-based quantitative histogram analysis is a highly accurate noninvasive tool for PCa vs. BPH differentiation.
• This method reduces diagnostic uncertainty, particularly for PI-RADS 3 lesions.
• Findings support personalized clinical decision-making in prostate diagnostics.