Diagnostic Value Analysis of PI-RADS v2.1 Combined with ADC Values in the Risk Stratification of Prostate Cancer Gleason Scores: A Retrospective Study

Background: Prostate cancer is a remarkable global health concern, necessitating accurate risk stratification for optimal treatment and outcome prediction. By highlighting the potential of imaging-based approaches to improve risk assessment in prostate cancer, this research aims to evaluate the diagnostic efficacy of the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 combined with apparent diffusion coefficient (ADC) values to gain increased context within the broad landscape of clinical needs and advancements in prostate cancer management. Methods: The clinical data of 145 patients diagnosed with prostate cancer were retrospectively analysed. The patients were divided into low-moderate- and high-risk groups on the basis of Gleason scores. PI-RADS v2.1 scores were assessed by senior radiologists and ADC values were calculated by using diffusion-weighted imaging. Statistical, univariate logistic regression, and receiver operating characteristic curve analyses were employed to evaluate the diagnostic efficacy of each index and combined PI-RADS v2.1 scores and ADC values. Results: This study found significant differences in PI-RADS v2.1 scores and ADC values between the low-moderate- and high-risk groups (p < 0.001). Logistic regression analysis revealed associations of various clinical indicators, PI-RADS score and ADC values with Gleason risk classification. Amongst indices, mean ADC demonstrated the highest sensitivity (0.912) and area under curve (AUC) value (0.962) and the combination of PI-RADS v2.1 with mean ADC showed high predictive value for the Gleason risk grading of prostate cancer with a high AUC value (0.966). Conclusions: This study provides valuable evidence for the potential utility of imaging-based approaches, specifically PI-RADS v2.1 combined with ADC values, in enhancing the accuracy of risk stratification in prostate cancer.