• Jinjing Zheng, Haibo Dong, Ming Li, Xueyao Lin, and Chaochao Wang.
• Department of Radiology, Ningbo Medical Center Lihuili Hospital, Ningbo University, China.
• Clinics (Sao Paulo). 2023 Jan 1; 78: 100238100238.

ObjectiveTo investigate the value of a nomogram based on multiparametric and multiregional MR images to predict Isocitrate Dehydrogenase-1 (IDH1) gene mutations in glioma.Data And MethodsThe authors performed a retrospective analysis of 110 MR images of surgically confirmed pathological gliomas; 33 patients with IDH1 gene Mutation (IDH1-M) and 77 patients with Wild-type IDH1 (IDH1-W) were divided into training and validation sets in a 7:3 ratio. The clinical features were statistically analyzed using SPSS and R software. Three glioma regions (rCET, rE, rNEC) were outlined using ITK-SNAP software and projected to four conventional sequences (T1, T2, Flair, T1C) for feature extraction using AI-Kit software. The extracted features were screened using R software. A logistic regression model was established, and a nomogram was generated using the selected clinical features. Eight models were developed based on different sequences and ROIs, and Receiver Operating Characteristic (ROC) curves were used to evaluate the predictive efficacy. Decision curve analysis was performed to assess the clinical usefulness.ResultsAge was selected with Radscore to construct the nomogram. The Model 1 AUC values based on four sequences and three ROIs were the highest in these models, at 0.93 and 0.89, respectively. Decision curve analysis indicated that the net benefit of model 1 was higher than that of the other models for most Pt-values.ConclusionA nomogram based on multiparametric and multiregional MR images can predict the mutation status of the IDH1 gene accurately.Copyright © 2023 HCFMUSP. Published by Elsevier España, S.L.U. All rights reserved.

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