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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">APM</journal-id><journal-title-group><journal-title>Advances in Precision Medicine</journal-title></journal-title-group><issn>2424-8592</issn><eissn>2424-9106</eissn><publisher><publisher-name>WHIOCE PUBLISHING PTE. LTD.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18063/APM.v11i4.1869</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research Progress of Multiparametric Magnetic Resonance Imaging in Predicting Extraprostatic Extension of Prostate Cancer</title><url>https://artdesignp.com/journal/APM/11/4/10.18063/APM.v11i4.1869</url><author>DengAiqing</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>11</volume><issue>4</issue><history><date date-type="pub"><published-time>2026-04-26</published-time></date></history><abstract>Extraprostatic extension (EPE) of prostate cancer is a key pathological feature that affects patient prognosis and the choice of treatment strategy. Accurate prediction of EPE is of significant clinical value in developing individualized treatment plans. Multiparametric magnetic resonance imaging (mpMRI), with its non-invasiveness, high spatial resolution, and multi-sequence imaging capabilities, has become a core imaging method for preoperative assessment of EPE. However, current imaging diagnosis of EPE still faces challenges such as high subjectivity, lack of standardized diagnostic criteria, and relatively low sensitivity in detecting minor extensions. In recent years, continuous breakthroughs in radiomics and artificial intelligence technologies are expected to significantly enhance the diagnostic performance of mpMRI. This article systematically reviews the optimization strategies of mpMRI imaging technology in the assessment of EPE in prostate cancer, explores the development from empirical interpretation to precise quantitative analysis of mpMRI features, focuses on the current application of radiomics in mpMRI-based prediction of EPE, and deeply analyzes the limitations of mpMRI in evaluating minor EPE. By integrating existing research evidence, it aims to provide clinicians with precise diagnostic strategies for EPE based on mpMRI, thereby contributing to the advancement of individualized diagnosis and treatment of prostate cancer.</abstract><keywords>Multiparametric magnetic resonance imaging,Prostate cancer,Extraprostatic extension</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] Bray F, Laversanne M, Sung H, et al., 2024, Global Cancer Statistics 2022: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin, 74(3): 229&amp;ndash;263.
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