Related Experiment Video
Updated: May 28, 2025
A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
MRI-based risk stratification for clinically significant prostate cancer detection at biopsy: The value of
Antonia M Pausch1, Soleen Ghafoor1, Rebecca Notter1
1Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland.
Purpose:
To explore the use of different, zonal-specific PSA density (PSAD) variants in combination with the Prostate Signal Intensity Homogeneity Score (PSHS) to improve the detection of clinically significant prostate cancer (csPCa) and thus potentially help in risk stratification and adequate patient selection for prostate biopsy.
Methods:
This retrospective, single-center study included patients with available PSA values who were suspected of having prostate cancer and underwent multiparametric MRI (mpMRI) in combination with a subsequent prostate biopsy. Histopathologic biopsy results served as reference standard. Whole-gland (PSAD-T), peripheral zone (PSAD-PZ), and transition zone (PSAD-TZ) PSA densities were computed based on MRI-derived volume assessment. The diagnostic performance of these PSAD variants in predicting csPCa was assessed using ROC analysis. Conditional inference trees were used to examine the value of combining PI-RADS, PSAD-TZ and PSHS.
Results:
Among the 297 patients included, 126 (42.4 %) were diagnosed with csPCa based on histopathologic biopsy results. PSAD-TZ demonstrated superior diagnostic performance (AUC 0.78) for csPCa prediction compared to PSAD-T (AUC 0.75) and PSAD-PZ (AUC 0.63). Conditional inference tree analysis revealed that patients with negative or indeterminate mpMRI (PI-RADS ≤ 3) and an elevated PSAD-TZ in combination with low PSHS scores (≤3), which indicate increased background signal intensity changes of the peripheral zone, were at an elevated risk for a missed csPCa.
Conclusions:
Integrating PI-RADS, PSAD-TZ, and PSHS may enhance risk stratification for csPCa at biopsy, enabling more precise identification of patients at an elevated risk who may require further evaluation. This approach may consequently reduce false-negative MRI results and facilitate more precise decision-making regarding biopsy indications.
