Background: The growing role of multiparametric MRI (mpMRI) and MRI-targeted biopsy (MRI-TBx) suggests they may replace random systematic biopsy (SBx), specifically detection and subsequent treatment of clinically significant prostate cancer (csPCa). Objectives: To perform a systematic review and meta-analysis of randomised controlled trials (RCTs) comparing the detection rates (DR) of csPCa using MRI-TBx alone, SBx alone, or their combination in biopsy naïve patients suspected of having prostate cancer (PCa). Methods: PubMed, MEDLINE, Embase, and the Cochrane Library were searched up to 23 March 2023, for RCTs comparing PCa DR between biopsy strategies in patients with suspected prostate cancer. Detection rates were pooled using random/fixed effect models, and the study quality was assessed using the Cochrane risk of bias revised tool. Results: Ten RCTs (involving 3646 patients) were analysed, revealing that the combined biopsy method achieved higher overall csPCa DR compared to the SBx method alone (RR = 1.40 [95% CI = 1.15–1.71] and 1.47 [95% CI = 1.13–1.92], respectively). However, there was no significant difference in DR for clinically insignificant prostate cancer (ciPCa) between the two methods. Conclusions: This review concludes that MRI-TBx and SBx detect overall and clinically significant prostate cancer (csPCa) better than SBx alone. The variety of factors requires cautious interpretation, yet these findings are the strongest evidence. The combination technique is recommended for biopsy-naïve groups, but more study is needed to optimise execution and overcome uncertainties.

Background/Objectives: Patients with suspicious prostate mpMRI but negative baseline biopsy remain challenging to manage, as some are later diagnosed with clinically significant prostate cancer (csPCa). This study evaluated whether baseline whole-gland radiomic features from T2-weighted imaging and apparent diffusion coefficient (ADC) maps could predict subsequent csPCa detection. Methods: This retrospective radiomics sub-analysis of the MULTIPROS trial included men with suspicious baseline mpMRI findings (PI-RADS v2.0 categories 3–5) and no csPCa detected at baseline biopsy. The primary outcome was subsequent csPCa detection during follow-up, defined as ISUP Grade Group ≥2. Whole-gland prostate segmentation was performed on baseline T2-weighted images using a semi-automated approach with manual refinement, and the resulting T2-derived masks were applied to the spatially corresponding ADC maps. Radiomic features were extracted using PyRadiomics version 3.1.0a2 after standardised preprocessing. Feature robustness was assessed in a 20-patient reproducibility subset using intra- and inter-reader intraclass correlation coefficients, followed by correlation filtering and LASSO-based feature prioritisation. Radiomics-only, clinicoradiological-only, and clinicoradiological–radiomic logistic regression models were evaluated using stratified five-fold cross-validation. Results: T2-based modelling included 151 patients, of whom 36/151 (23.8%) had subsequent csPCa detected; the median time to csPCa detection or last follow-up was 64 months. ADC analyses included 144 patients, of whom 34/144 (23.6%) had subsequent csPCa detected. The T2 clinicoradiological–radiomic model achieved a mean AUC of 0.696 ± 0.060, compared with 0.713 ± 0.072 for the T2 clinicoradiological-only model and 0.456 ± 0.091 for the T2 radiomics-only model. In the ADC-available cohort, ADC radiomics-only, ADC clinicoradiological–radiomic, and combined T2 + ADC clinicoradiological–radiomic models achieved mean AUCs of 0.684 ± 0.052, 0.635 ± 0.157, and 0.663 ± 0.106, respectively. Calibration was imperfect, with deviations at higher predicted probabilities and overprediction in the highest predicted-risk bin. Conclusions: Baseline whole-gland MRI radiomics showed limited and inconsistent predictive value for subsequent csPCa detection after negative biopsy and did not demonstrate consistent incremental improvement over clinicoradiological predictors. These findings are exploratory and hypothesis-generating, and external validation is required before clinical use.