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Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a
Jinna Yu1, Xin Kong2, Dong Xie1
1Department of Radiology, Shaoxing Second Hospital, Shaoxing, P.R. China.
Objective:
To develop a nomogram based on tumor and peritumoral edema (PE) radiomics features extracted from preoperative multiparameter MRI for predicting brain invasion (BI) in atypical meningioma (AM).
Methods:
In this retrospective study, according to the 2021 WHO classification criteria, a total of 469 patients with pathologically confirmed AM from three medical centres were enrolled and divided into training (n = 273), internal validation (n = 117) and external validation (n = 79) cohorts. BI was diagnosed based on the histopathological examination. Preoperative contrast-enhanced T1-weighted MR images (T1C) and T2-weighted MR images (T2) for extracting meningioma features and T2-fluid attenuated inversion recovery (FLAIR) sequences for extracting meningioma and PE features were obtained. The multiple logistic regression was applied to develop separate multiparameter radiomics models for comparison. A nomogram was developed by combining radiomics features and clinical risk factors, and the clinical usefulness of the nomogram was verified using decision curve analysis.
Results:
Among the clinical factors, PE volume and PE/tumor volume ratio are the risk of BI in AM. The combined nomogram based on multiparameter MRI radiomics features of meningioma and PE and clinical indicators achieved the best performance in predicting BI in AM, with area under the curve values of 0.862 (95% CI, 0.819-0.905) in the training cohort, 0.834 (95% CI, 0.780-0.908) in the internal validation cohort and 0.867 (95% CI, 0.785-0.950) in the external validation cohort, respectively.
Conclusions:
The nomogram based on tumor and PE radiomics features extracted from preoperative multiparameter MRI and clinical factors can predict the risk of BI in patients with AM.
Insights
This study developed a novel nomogram using multiparameter MRI radiomics and clinical factors to accurately predict brain invasion (BI) in atypical meningioma (AM), aiding in surgical planning.
Area of Science:
- Neurosurgery
- Radiology
- Oncology
Background:
- Atypical meningioma (AM) poses diagnostic challenges, particularly regarding brain invasion (BI).
- Accurate preoperative prediction of BI is crucial for effective surgical management and patient outcomes.
Purpose of the Study:
- To develop and validate a predictive nomogram for brain invasion (BI) in atypical meningioma (AM).
- The nomogram integrates radiomics features from multiparameter MRI and clinical factors.
Main Methods:
- Retrospective analysis of 469 atypical meningioma (AM) patients across three centers.
- Extraction of radiomics features from preoperative multiparameter MRI (T1C, T2, FLAIR) including tumor and peritumoral edema (PE).
- Development of a nomogram combining radiomics and clinical risk factors, validated internally and externally.
Main Results:
- Peritumoral edema (PE) volume and PE/tumor volume ratio were identified as risk factors for BI.
- The combined nomogram demonstrated high predictive performance: AUC 0.862 (training), 0.834 (internal validation), and 0.867 (external validation).
Conclusions:
- A nomogram integrating multiparameter MRI radiomics and clinical factors effectively predicts brain invasion (BI) in atypical meningioma (AM).
- This tool can aid clinicians in assessing BI risk preoperatively.
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