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Dynamic contrast\u2010enhanced MRI (DCE\u2010MRI) may potentially contribute to the preoperative assessment of Ki\u201067 LI.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To investigate the feasibility of assessing Ki\u201067 LI of PAs preoperatively using delta\u2010radiomics based on DCE\u2010MRI.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Retrospective.<\/jats:p><\/jats:sec><jats:sec><jats:title>Population<\/jats:title><jats:p>605 PA patients (female\u2009=\u200947.1%, average age\u2009=\u200952.2) from two centers (high Ki\u201067 LI (\u2265\u20093%)\u2009=\u2009229; low Ki\u201067 LI (&lt;\u20093%)\u2009=\u2009376), divided into a training set (<jats:italic>n<\/jats:italic>\u2009=\u2009313), an internal validation set (<jats:italic>n<\/jats:italic>\u2009=\u2009196), and an external validation set (<jats:italic>n<\/jats:italic>\u2009=\u200996).<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>1.5\u2010T and 3\u2010T, DCE\u2010MRI.<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>This study developed a non\u2010delta\u2010radiomics model based on the non\u2010delta\u2010radiomic features directly extracted from four phases, a delta\u2010radiomics model based on the delta\u2010radiomic features, and a combined model integrating clinical parameters (Knosp grade and tumor diameter) with delta\u2010radiomic features. <jats:italic>U<\/jats:italic> test, recursive feature elimination (RFE), and least absolute shrinkage and selection operator (LASSO) regression were utilized to select important radiomic features. Support vector machine (SVM), XGBoost (XGB), logistic regression (LR), and Gaussian naive Bayes (GNB) were utilized to develop the models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Receiver operating characteristic (ROC) curve. Calibration curve. Decision curve analysis (DCA). Intraclass correlation coefficients (ICC). DeLong test for ROC curves. <jats:italic>U<\/jats:italic> test or <jats:italic>t<\/jats:italic> test for numerical variables. Fisher's test or Chi\u2010squared test for categorical variables. A <jats:italic>p<\/jats:italic>\u2010value &lt;\u20090.05 was considered statistically significant.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The combined model demonstrated the best performance in preoperatively assessing the Ki\u201067 LI of PAs, achieving AUCs of 0.937 and 0.897 in the internal and external validation sets, respectively. The models based on delta\u2010radiomic features outperformed the non\u2010delta\u2010radiomic model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>A delta\u2010radiomics\u2010based model using DCE\u2010MRI may show high diagnostic performance for preoperatively assessing the Ki\u201067 LI status of PAs.<\/jats:p><jats:p>\n<jats:bold>Evidence Level:<\/jats:bold> 3<\/jats:p><jats:p>\n<jats:bold>Technical Efficacy:<\/jats:bold> Stage 2<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.29764","type":"journal-article","created":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T03:35:01Z","timestamp":1742182501000},"page":"508-518","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Preoperative Assessment of Ki\u201067 Labeling Index in Pituitary Adenomas Using Delta\u2010Radiomics Based on Dynamic Contrast\u2010Enhanced 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