The Pelvic Cancer MRI Toolbox: Integrating PI-RADS and VI-RADS in Clinical Pathways

Abstract Purpose of Review This narrative review aims to compare the conceptual frameworks of two standardized MRI scoring systems—PI-RADS (Prostate Imaging Reporting and Data System) and VI-RADS (Vesical Imaging Reporting and Data System). Both systems translate multiparametric MRI findings into a shared, clinically actionable language by employing dominant-sequence logic (DWI for peripheral-zone prostate lesions, T2-weighted imaging for transition-zone prostate lesions, and bladder-wall layer assessment anchored to the detrusor line) with DCE serving as a problem-solving sequence. Additionally, this narrative review highlights the quality prerequisites for each system and explores how structured reporting can reduce inter-reader variability. A literature search was conducted using the electronic databases PubMed, Scopus, and Web of Science. The search strategy employed combinations of the following keywords: “PI-RADS,” “VI-RADS,” “multiparametric MRI,” “prostate cancer,” “bladder cancer,” “structured reporting,” and “imaging reporting and data system.” Recent Findings Adherence to PI-RADS and VI-RADS algorithms improves diagnostic accuracy and reproducibility across readers with varying experience levels. Key advances include refinement of dominant-sequence criteria, validation of DCE’s role as a tie-breaker rather than a primary sequence, and development of minimum technical standards for image acquisition. Both systems have shown high negative predictive values for ruling out clinically significant disease, though challenges remain in inter-reader agreement for equivocal (category 3) lesions and in transitioning from expert centers to community practice. Summary Structured reporting using PI-RADS and VI-RADS provides a standardized lexicon that facilitates consistent lesion characterization, reduces unnecessary biopsies, and streamlines multidisciplinary care pathways. Despite differences in target organ anatomy and sequence weighting, both systems share core design principles—dominant-sequence anchoring, binary descriptor checklists, and progressive score escalation with increasing suspicion. Ongoing efforts should focus on validating these systems in prospective cohorts and integrating artificial intelligence tools to further harmonize interpretation.