Related Experiment Video
Updated: Apr 5, 2026
A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Integrating Prostate-Specific Antigen Density and Prostate Imaging Reporting and Data System Scores to Optimize
1Department of Urology, University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital, Istanbul, Turkey.
Background:
Prebiopsy multiparametric MRI (mpMRI) reported using the Prostate Imaging Reporting and Data System (PI-RADS) improves prostate cancer triage, yet false-positive findings remain common and may drive unnecessary biopsy. Prostate-specific antigen density (PSAD) is an inexpensive laboratory-derived adjunct that may refine MRI-based risk stratification.
Methods:
We retrospectively screened 713 transrectal ultrasound (TRUS)-guided biopsy episodes from a single experienced urologist's practice at a tertiary referral hospital between October 2022 and August 2025 and included 375 men with prebiopsy mpMRI reported using PI-RADS version 2.1 and complete data for prespecified predictors. All patients underwent systematic 12-core TRUS-guided biopsy. Clinically significant prostate cancer (csPCa) was defined as International Society of Urological Pathology (ISUP) grade group ≥ 2. We developed logistic regression models combining PSAD and PI-RADS (parsimonious model) and adding age and digital rectal examination (DRE) (full model). Discrimination (AUC), calibration, and clinical utility (decision curve analysis) were assessed, and the incremental value of PSAD beyond PI-RADS for csPCa was quantified using IDI and continuous NRI.
Results:
csPCa was present in 93/375 (24.8%) and any prostate cancer in 144/375 (38.4%). For csPCa prediction, AUC was 0.746 for PI-RADS and 0.760 for PSAD; the combined PSAD+PI-RADS model achieved AUC 0.798 and the full model AUC 0.794. Adding PSAD to PI-RADS improved IDI (0.0528; p < 0.001) and total continuous NRI (0.3926; p < 0.001), driven mainly by improved down-classification of non-csPCa cases.
Conclusions:
Integrating PSAD with PI-RADS improved csPCa risk stratification compared with PI-RADS alone, with predominant benefit as a biopsy-sparing, rule-out adjunct. External validation is required for clinical implementation.
Insights
Prostate-specific antigen density (PSAD) combined with multiparametric MRI (mpMRI) PI-RADS scoring improves prostate cancer risk stratification. This integration helps spare patients unnecessary biopsies by better identifying clinically significant prostate cancer (csPCa).
Area of Science:
- Urology
- Radiology
- Oncology
Background:
- Multiparametric MRI (mpMRI) using PI-RADS improves prostate cancer triage but has common false positives leading to unnecessary biopsies.
- Prostate-specific antigen density (PSAD) is a cost-effective biomarker that may enhance MRI-based risk stratification.
Purpose of the Study:
- To evaluate the added value of PSAD in combination with PI-RADS for predicting clinically significant prostate cancer (csPCa).
- To assess if combining PSAD and PI-RADS improves risk stratification compared to PI-RADS alone.
Main Methods:
- Retrospective analysis of 375 men undergoing transrectal ultrasound (TRUS)-guided biopsy with prebiopsy mpMRI (PI-RADS v2.1).
- Logistic regression models were developed combining PI-RADS with PSAD, age, and digital rectal examination (DRE).
- Discrimination (AUC), calibration, and clinical utility were assessed, quantifying PSAD's incremental value using IDI and NRI.
Main Results:
- The combined PSAD+PI-RADS model achieved an AUC of 0.798 for csPCa prediction, outperforming PI-RADS alone (AUC 0.746).
- Adding PSAD to PI-RADS significantly improved discrimination (IDI: 0.0528, p<0.001; NRI: 0.3926, p<0.001).
- The primary benefit was improved down-classification of non-csPCa cases, aiding in biopsy decisions.
Conclusions:
- Integrating PSAD with PI-RADS enhances csPCa risk stratification beyond PI-RADS alone.
- The combination serves as a valuable biopsy-sparing tool, primarily for ruling out csPCa.
- External validation is recommended before widespread clinical implementation.
