癫痫
接收机工作特性
逻辑回归
颞叶
无线电技术
特征选择
医学
神经组阅片室
癫痫外科
磁共振成像
神经影像学
放射科
核医学
计算机科学
人工智能
神经学
心理学
神经科学
内科学
作者
Fangzhao Yin,Xiaoming Yan,Runshi Gao,Zhiwei Ren,Tao Yu,Zhuoling Zhao,Guojun Zhang
摘要
This study aimed to differentiate temporal-plus epilepsy (TPE) from temporal lobe epilepsy (TLE) using extraction of radiomics features from three-dimensional magnetization-prepared rapid acquisition gradient echo (3D-MPRAGE) imaging data.Data from patients with TLE or TPE who underwent epilepsy surgery between January 2019 and January 2021 were retrospectively analyzed. Thirty-three regions of interest in the affected hemisphere of each patient were defined on 3D-MPRAGE images. A total of 3531 image features were extracted from each patient. Four feature selection methods and 10 machine learning algorithms were used to build 40 differentiation models. Model performance was evaluated using receiver operating characteristic analysis.Eighty-two patients were included for analysis, 47 with TLE and 35 with TPE. The model combining logistic regression and the relief selection method had the best performance (area under the receiver operating characteristic curve, .779; accuracy, .875; sensitivity, .800; specificity, .929; positive predictive value, .889; negative predictive value, .867).Radiomics analysis can differentiate TPE from TLE. The logistic regression classifier trained with radiomics features extracted from 3D-MPRAGE images had the highest accuracy and best performance.
科研通智能强力驱动
Strongly Powered by AbleSci AI