Objective To explore the value of radiomics models based on conventional multi-sequence MRI in distin-guishing fibrous and non-fibrous meningiomas to aid in clinical preoperative preparation and prognostic assessment.Methods Clinical and multi-sequence MRI(including T1WI,T2WI,T2WIFLAIR,T1WI enhancement)data of a total of 317 patients with postoperative pathologically confirmed meningiomas from March 2013 to December 2022 were ret-rospectively analyzed.The enhanced area of meningioma was manually outlined as the region of interest(EnHROI),and the outlined area was expanded to the periphery by 3 mm and 5 mm to obtain EnH3mmROI and EnH5mmROI,respec-tively,and the radiomics features were extracted from the three kinds of ROIs of each MRI sequence,and the 5-fold cross-validation and LOOCV method was used for feature screening and model validation.Feature selection was per-formed using the correlation coefficient method and the least absolute shrinkage and selection operator(LASSO)algo-rithm,followed by model construction using the support vector machine algorithm(AVM),and finally the efficacy of the different prediction models was evaluated.Results The EnH3mmROI-based prediction model outperformed both the EnHROI-based model and the EnH5mmROI-based model in the assessment of radiomics models for predicting meningi-oma typing using the receiver-operating characteristic curve(ROC).The AUC value of the EnHROI-based model was 0.801,with an accuracy of 0.842;the AUC value of the EnH3mmROI-based model was 0.858,with an accuracy of 0.842;and the AUC value of the EnH5mmROI-based model was 0.841,with an accuracy of 0.868.Conclusion ①The effectiveness of the radiomics model based on EnH3mmROI was significantly better than that based on EnHROI and EnH5mmROI.②The radiomics model in predicting preoperative histologic typing of meningiomas based on convention-al multi-sequence MRI has clinical value,which can help to determine the prognosis and provide a basis for the clinical treatment plan.
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