Background: Prostate cancer (PCa) screening has relied on prostate-specific antigen (PSA) levels to screen patients for biopsy. However, the limited specificity of serum PSA leads to high rates of negative biopsies and detection of clinically insignificant cancers. Tumor-derived extracellular vesicles, microscopic particles released by tumor cells and ubiquitously found in all bodily fluids, have emerged as novel biomarkers for a diverse set of malignancies. This study explored the utility of urine prostate-specific extracellular vesicles (ProsEVs) identified by unique surface protein markers with novel flow cytometry-based techniques as biomarkers for PCa screening. Methods: This prospective study recruited at a tertiary care center between Oct 2019 and Mar 2022. Patients with PSA≥2 ng/ml underwent prebiopsy mpMRI followed by transperineal prostate biopsy (PI-RADS 1-2) or combined MRI-guided biopsy (PI-RADS ≥ 3). Patients with metastatic PCa or prior systemic therapy were excluded. Urine samples were collected at MRI using Colli-Pee. ProsEVs were labeled using monoclonal antibodies for PSMA and STEAP1 and ProsEV concentrations were determined using nanoscale flow cytometry. EV densities were calculated by normalizing EV counts to prostate volume. Multivariable logistic regression models were constructed and model performance was compared used ROC curve analysis. Results: This study had a total of 179 patients prospectively recruited, 95 were diagnosed with Gleason score (GS) ≥ 7 prostate cancer (csPCa), while the remaining had GS <7 or benign disease. Analysis of urinary ProsEV densities revealed a significant dose-response relationship between benign, GS <7 PCa and GS ≥ 7 PCa groups and ProsEV densities (p=0.01 for PSMA, and <0.001 for STEAP1). The log sum of the PSMA and STEAP1 EV densities exhibited the strongest correlation with other ProsEV variables and was selected for model development. ROC curve analysis showed that the final model including Log Sum ProsEVs, PSA, and PI-RADS outperformed one including PSA and PI-RADS (0.733 vs 0.651, p=0.02). Specificity for detecting csPCa at a sensitivity of 90% was 39.5% in the final model compared to 37% for PSA and PI-RADS (Table). Conclusions: This study highlights the potential of urine ProsEVs as novel biomarkers for improving screening specificity for csPCa detection. Future works should explore analysis of intra-ProsEV content to further improve specificity and advance liquid biopsy techniques.