Preoperative Prediction of Brain Invasion in Meningiomas: A Radiomics Model based on Multimodal MRI and Quantitative Clinical Factors

This study aimed to construct a radiomic model based on a large patient cohort to predict brain invasion (BI) in meningioma. By analyzing 97 patients with BI and 935 patients without BI, we found that the clinical risk factors for BI were male sex, tumor located at the skull base, and peritumoral edema volume. A binary logistic regression model combining these risk factors and multimodal MRI radiological characteristics was established. The constructed model achieved an excellent performance (AUC: 0.928) in terms of BI classification with an accuracy of 91.77%, which may be helpful for personalized treatment plan in meningioma.