{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T20:42:44Z","timestamp":1790887364068,"version":"4.1.0"},"reference-count":70,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Prostate cancer is a common malignancy in men. With the advent of multiparametric MRI and the Prostate Imaging-Reporting and Data System (PI-RADS) framework for grading lesions, there have been multiple advancements in the management and treatment of the disease. There are several new advancements in prostate MRI technology that suggest further exciting developments in the field, ranging from novel imaging sequences to the application of machine learning methods and artificial intelligence (AI) across the imaging pipeline. In this review, we aim to provide context on the current advancements in prostate MRI and will discuss the benefits and drawbacks of several new imaging techniques including hybrid multidimensional MRI, low field strength MRI, restriction spectrum imaging, Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumour (VERDICT) MRI, luminal water imaging, and hyperpolarized C-13 MRI. Additionally, we will introduce several novel AI methods that have been proposed to improve MRI image quality, prostate lesion detection and characterization, as well as touch on the ethical implications of AI in medical imaging of the prostate.<\/jats:p>","DOI":"10.1093\/bjro\/tzag011","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T20:33:21Z","timestamp":1779482001000},"source":"Crossref","is-referenced-by-count":1,"title":["Current state of the art of new prostate MRI technologies and potential future developments"],"prefix":"10.1093","volume":"8","author":[{"given":"Rikhil D","family":"Makwana","sequence":"first","affiliation":[{"name":"Molecular Imaging Branch, NCI, NIH , Bethesda, MD 20892,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"3rd","given":"Donald C","family":"Wunsch","sequence":"additional","affiliation":[{"name":"Molecular Imaging Branch, NCI, NIH , Bethesda, MD 20892,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shonit","family":"Punwani","sequence":"additional","affiliation":[{"name":"Department of Imaging, University College London , London, WC1E 6BT,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fiona","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Imaging, University College London , London, WC1E 6BT,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tyler M","family":"Seibert","sequence":"additional","affiliation":[{"name":"Departments of Radiology, Radiation Medicine & Applied Sciences, Urology, and Bioengineering, University of California San Diego , La Jolla, CA 92093,","place":["United States"]}],"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, NCI, NIH , Bethesda, MD 20892,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,5,22]]},"reference":[{"key":"2026070804570597200_tzag011-B1","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.eururo.2020.09.042","article-title":"EAU-EANM-ESTRO-ESUR-SIOG Guidelines on Prostate Cancer\u20142020 Update. 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