{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T06:37:06Z","timestamp":1784097426884,"version":"3.55.0"},"reference-count":100,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:00:00Z","timestamp":1742947200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>The Prostate Imaging\u2013Reporting and Data System (PI\u2010RADS) is a widely\u2010adopted framework for assessing prostate cancer risk using multiparametric MRI. However, as advancements in imaging and data analytics emerge, PI\u2010RADS faces pressure to integrate novel quantitative techniques, enhanced imaging protocols, and artificial intelligence (AI) solutions to improve diagnostic accuracy. This review examines the recent innovations in advanced imaging, clinical, and AI methods that can provide more informative MRI scans and discuss their potential incorporation into PI\u2010RADS. Techniques like multi\u2010shot echo\u2010planar imaging and reduced field\u2010of\u2010view DWI show promise in improving scan quality, but may present challenges with respect to technical complexity, cost, and standardization. Others, like restriction spectrum imaging and luminal water imaging, offer new possibilities for lesion characterization, yet remain difficult to implement consistently across clinical settings. In addition, integrating clinical parameters and AI\u2010driven tools within PI\u2010RADS could enhance risk stratification, but may introduce greater complexity, potentially impacting ease\u2010of\u2010use. We discuss the implications of these advancements for PI\u2010RADS, balancing the potential diagnostic benefits with the challenges of maintaining accessibility and reproducibility in clinical practice. This review provides a comprehensive overview of how emerging MRI techniques and AI may redefine prostate cancer imaging standards.<\/jats:p><jats:p>\n<jats:bold>Evidence Level:<\/jats:bold> 5.<\/jats:p><jats:p>\n<jats:bold>Technical Efficacy:<\/jats:bold> Stage 5.<\/jats:p>","DOI":"10.1002\/jmri.29754","type":"journal-article","created":{"date-parts":[[2025,3,29]],"date-time":"2025-03-29T15:55:33Z","timestamp":1743263733000},"page":"673-690","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Toward a Refined <scp>PI<\/scp>\u2010<scp>RADS<\/scp>: The Feasibility and Limitations of More Informative Metrics in Reviewing <scp>MRI<\/scp> Scans"],"prefix":"10.1002","volume":"62","author":[{"given":"Omer Tarik","family":"Esengur","sequence":"first","affiliation":[{"name":"Molecular Imaging Branch National Cancer Institute, National Institutes of Health  Bethesda Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hunter","family":"Stecko","sequence":"additional","affiliation":[{"name":"Molecular Imaging Branch National Cancer Institute, National Institutes of Health  Bethesda Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emma","family":"Stevenson","sequence":"additional","affiliation":[{"name":"Molecular Imaging Branch National Cancer Institute, National Institutes of Health  Bethesda Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0853-6494","authenticated-orcid":false,"given":"Baris","family":"Turkbey","sequence":"additional","affiliation":[{"name":"Molecular Imaging Branch National Cancer Institute, National Institutes of Health  Bethesda Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,3,26]]},"reference":[{"key":"e_1_2_10_2_1","volume-title":"StatPearls","author":"Jain M. 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