论文标题
通过扩散加权MRI预测脑损伤患者癫痫发育的预测
Prediction of Epilepsy Development in Traumatic Brain Injury Patients from Diffusion Weighted MRI
论文作者
论文摘要
创伤后癫痫（PTE）是创伤性脑损伤（TBI）的终生并发症，是一个主要的公共卫生问题，其估计发病率在2％-50％之间，具体取决于TBI的严重性。目前，尚不清楚诱导TBI患者诱导癫痫发生的病理机制，癫痫界最具挑战性的目标之一是预测哪些TBI患者将患上癫痫病。在这项工作中，我们使用了14名在癫痫生物信息学研究中募集的TBI患者的扩散加权成像（DWI）进行抗癫痫疗法（EPIBIOS4RX）来测量和分析基于TRACT的空间统计（TBSS）分析，从而测量和分析分数各向异性（FA）。然后，我们使用这些测量值来训练两个支持向量机（SVM）模型，以预测哪些TBI患者患有癫痫病。我们对这14名具有休假两次交叉验证的患者进行了测试的方法使我们获得了0.857 $ \ pm $ 0.18的准确性（95％的信心水平），这证明了这是PTE早期表征的潜在有望。
Post-traumatic epilepsy (PTE) is a life-long complication of traumatic brain injury (TBI) and is a major public health problem that has an estimated incidence that ranges from 2%-50%, depending on the severity of the TBI. Currently, the pathomechanism that in-duces epileptogenesis in TBI patients is unclear, and one of the most challenging goals in the epilepsy community is to predict which TBI patients will develop epilepsy. In this work, we used diffusion-weighted imaging (DWI) of 14 TBI patients recruited in the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx)to measure and analyze fractional anisotropy (FA), obtained from tract-based spatial statistic (TBSS) analysis. Then we used these measurements to train two support vector machine (SVM) models to predict which TBI patients have developed epilepsy. Our approach, tested on these 14 patients with a leave-two-out cross-validation, allowed us to obtain an accuracy of 0.857 $\pm$ 0.18 (with a 95% level of confidence), demonstrating it to be potentially promising for the early characterization of PTE.
