{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T17:35:20Z","timestamp":1790271320530,"version":"4.1.0"},"reference-count":40,"publisher":"Wiley","license":[{"start":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T00:00:00Z","timestamp":1707696000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer. Accurate preoperative prediction of histological grade holds potential for improving clinical management and disease prognostication.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To evaluate the performance of a radiomics signature based on multiphase MRI in assessing histological grade in solitary HCC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Retrospective.<\/jats:p><\/jats:sec><jats:sec><jats:title>Subjects<\/jats:title><jats:p>A total of 405 patients with histopathologically confirmed solitary HCC and with liver gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd\u2010EOB\u2010DTPA)\u2010enhanced MRI within 1\u2009month of surgery.<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>Contrast\u2010enhanced T1\u2010weighted spoiled gradient echo sequence (LAVA) at 1.5 or 3.0\u2009T.<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>Tumors were graded (low\/high) according to results of histopathology. Basic clinical characteristics (including age, gender, serum alpha\u2010fetoprotein (AFP) level, history of hepatitis B, and cirrhosis) were collected and tumor size measured. Radiomics features were extracted from Gd\u2010EOB\u2010DTPA\u2010enhanced MRI data. Three feature selection strategies were employed sequentially to identify the optimal features: SelectFromModel (SFM), SelectPercentile (SP), and recursive feature elimination with cross\u2010validation (RFECV). Probabilities of five single\u2010phase radiomics\u2010based models were averaged to generate a radiomics signature. A combined model was built by combining the radiomics signature and clinical predictors.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Pearson <jats:italic>\u03c7<\/jats:italic><jats:sup>2<\/jats:sup> test\/Fisher exact test, Wilcoxon rank sum test, interclass correlation coefficient (ICC), univariable\/multivariable logistic regression analysis, area under the receiver operating characteristic (ROC) curve (AUC), DeLong test, calibration curve, Brier score, decision curve, Kaplan\u2013Meier curve, and log\u2010rank test. A <jats:italic>P<\/jats:italic>\u2010value &lt;0.05 was considered statistically significant.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>High\u2010grade HCCs were present in 33.8% of cases. AFP levels (odds ratio [OR] 1.89) and tumor size (&gt;5\u2009cm; OR 2.33) were significantly associated with HCC grade. The combined model had excellent performance in assessing HCC grade in the test dataset (AUC: 0.801), and demonstrated satisfactory calibration and clinical utility.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>A model that combined a radiomics signature derived from preoperative multiphase Gd\u2010EOB\u2010DTPA\u2010enhanced MRI and clinical predictors showed good performance in assessing HCC grade.<\/jats:p><\/jats:sec><jats:sec><jats:title>Level of Evidence<\/jats:title><jats:p>3<\/jats:p><\/jats:sec><jats:sec><jats:title>Technical Efficacy<\/jats:title><jats:p>Stage 5<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.29289","type":"journal-article","created":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T09:55:07Z","timestamp":1707731707000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Multiphase <scp>MRI<\/scp>\u2010Based Radiomics for Predicting Histological Grade of 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