318 Background: Prostate cancer is highly prevalent, and diagnostic pathways must maximize detection of clinically significant disease (csPCa) while minimizing overdiagnosis and resource burden. Micro-ultrasound (microUS) offers real-time, high-resolution lesion targeting and could reduce reliance on pre-biopsy MRI. We compared csPCa detection and diagnostic accuracy between microUS-targeted biopsy (microUS-TBx) and MRI-targeted biopsy (MRI-TBx). Methods: Systematic searches of MEDLINE (PubMed), Embase, and ClinicalTrials.gov were completed on July 4, 2025 and updated Aug 5, 2025. Eligible studies directly compared microUS-TBx with MRI-TBx in adults undergoing prostate biopsy and reported csPCa (typically ISUP ≥2). Primary endpoint: per-patient csPCa detection. Secondary endpoints: sensitivity and specificity for csPCa. Random-effects meta-analysis (Hartung-Knapp) estimated detection ratios (microUS/MRI); heterogeneity was summarized with I². Diagnostic accuracy was synthesized using a bivariate random-effects model. Prespecified analyses included biopsy-naïve status, use of concomitant systematic cores, and risk of bias (QUADAS-2). PROSPERO registration pending at submission. Results: Twenty-two studies (including one randomized trial) were included. Micro-US-TBx detected 2,194 csPCa cases; MRI-TBx detected 2,237. The pooled detection ratio (Micro-US vs MRI) was 0.99 (95% CI, 0.88–1.11; I² = 78.5%), indicating comparable yield. Pooled sensitivity/specificity were 0.86/0.38 for Micro-US-TBx and 0.84/0.40 for MRI-TBx. Heterogeneous biopsy triggers (e.g., PI-RADS ≥3 only vs biopsy-all) and frequent use of concomitant systematic biopsy introduced spectrum and partial verification/incorporation biases, which may shift detection rates, limit generalizability to routine care, and obscure standalone modality accuracy. Conclusions: Micro-US-TBx demonstrated csPCa detection and diagnostic accuracy comparable to MRI-TBx. Given potential advantages in access and cost, MicroUS is a viable alternative for integration into prostate cancer diagnostic pathways, particularly in resource-limited settings.
Suartz et al. (2026) studied this question.