AUTHOR=Zhao Shaozhi , Zhao Qi , Jiao Yuming , Li Hao , Weng Jiancong , Huo Ran , Wang Jie , Xu Hongyuan , Zhang Junze , Li Yan , Wu Zhenzhou , Wang Shuo , Cao Yong , Zhao Jizong
TITLE=Radiomics Analysis for Predicting Epilepsy in Patients With Unruptured Brain Arteriovenous Malformations
JOURNAL=Frontiers in Neurology
VOLUME=12
YEAR=2021
URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2021.767165
DOI=10.3389/fneur.2021.767165
ISSN=1664-2295
ABSTRACT=Objectives: To investigate the association between radiomics features and epilepsy in patients with unruptured brain arteriovenous malformations (bAVMs) and to develop a prediction model based on radiomics features and clinical characteristics for bAVM-related epilepsy.
Methods: This retrospective study enrolled 176 patients with unruptured bAVMs. After manual lesion segmentation, a total of 858 radiomics features were extracted from time-of-flight magnetic resonance angiography (TOF-MRA). A radiomics model was constructed, and a radiomics score was calculated. Meanwhile, the demographic and angioarchitectural characteristics of patients were assessed to build a clinical model. Incorporating the radiomics score and independent clinical risk factors, a combined model was constructed. The performance of the models was assessed with respect to discrimination, calibration, and clinical usefulness.
Results: The clinical model incorporating 3 clinical features had an area under the curve (AUC) of 0.71. Fifteen radiomics features were used to build the radiomics model, which had a higher AUC of 0.78. Incorporating the radiomics score and clinical risk factors, the combined model showed a favorable discrimination ability and calibration, with an AUC of 0.82. Decision curve analysis (DCA) demonstrated that the combined model outperformed the clinical model and radiomics model in terms of clinical usefulness.
Conclusions: The radiomics features extracted from TOF-MRA were associated with epilepsy in patients with unruptured bAVMs. The radiomics-clinical nomogram, which was constructed based on the model incorporating the radiomics score and clinical features, showed favorable predictive efficacy for bAVM-related epilepsy.