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.
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.
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.
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.
European journal of radiology. 2025 Feb 04 [Epub ahead of print]
Antonia M Pausch, Soleen Ghafoor, Rebecca Notter, Stephan Benke-Bruderer, Stefanie von Felten, Niels J Rupp, Daniel Eberli, Andreas M Hötker
Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland., Clinical Trials Center, University Hospital Zurich, Switzerland., Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Switzerland., Department of Pathology and Molecular Pathology, University Hospital Zurich, Switzerland; Faculty of Medicine, University of Zurich, Switzerland., Department of Urology, University Hospital Zurich, Switzerland., Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland. Electronic address: .