首页> 外文期刊>Human brain mapping >Quantification of primary motor pathways using diffusion MRI tractography and its application to predict postoperative motor deficits in children with focal epilepsy
【24h】

Quantification of primary motor pathways using diffusion MRI tractography and its application to predict postoperative motor deficits in children with focal epilepsy

机译:使用扩散MRI牵引术的初级电机途径的定量及其应用,以预测局灶性癫痫患儿术后电机缺陷

获取原文
获取原文并翻译 | 示例
           

摘要

As a new tool to quantify primary motor pathways and predict postoperative motor deficits in children with focal epilepsy, the present study utilized a maximum a posteriori probability (MAP) classification of diffusion weighted imaging (DWI) tractography combined with Kalman filter. DWI was performed in 31 children with intractable focal epilepsy who underwent epilepsy surgery. Three primary motor pathways associated with "finger," "leg," and "face" were classified using DWI-MAP classifier and compared with the results of invasive electrical stimulation mapping (ESM) via receiver operating characteristic (ROC) curve analysis. The Kalman filter analysis was performed to generate a model to determine the probability of postoperative motor deficits as a function of the proximity between the resection margin and the finger motor pathway. The ROC curve analysis showed that the DWI-MAP achieves high accuracy up to 89% (finger), 88% (leg), 89% (face), in detecting the three motor areas within 20 mm, compared with ESM. Moreover, postoperative reduction of the fiber count of finger pathway was associated with postoperative motor deficits involving the hand. The prediction model revealed an accuracy of 92% in avoiding postoperative deficits if the distance between the resection margin and the finger motor pathway seen on preoperative DWI tractography was 19.5 mm. This study provides evidence that the DWI-MAP combined with Kalman filter can effectively identify the locations of cortical motor areas even in patients whose motor areas are difficult to identify using ESM, and also can serve as a reliable predictor for motor deficits following epilepsy surgery.
机译:作为一种用于量化初级电机途径的新工具,并预测局灶性癫痫患儿的术后电机缺陷,本研究利用了扩散加权成像(DWI)牵引与卡尔曼滤波器的最大后验概率(MAP)分类。 DWI在31名儿童中进行,患有顽固的局灶性癫痫患者接受了癫痫手术。使用DWI-MAP分类器对与“手指”,“腿”和“面部”进行分类的三个主电动机途径,并与通过接收器操作特性(ROC)曲线分析的侵入性电刺激映射(ESM)的结果进行比较。执行卡尔曼滤波器分析以产生模型,以确定术后电机缺陷的概率作为切除裕度与手指电机路径之间的邻近的函数。 ROC曲线分析表明,与ESM相比,DWI-MAP达到高达89%(手指),88%(手指),88%(腿),89%(面部)的高精度。此外,手指途径的术后减少与涉及手的术后电动机缺陷有关。如果在术前DWI牵引术中看到的切除率和手指电机通路的距离为19.5毫米,则预测模型揭示了避免术后缺陷的精度为92%。本研究提供了证据表明,DWI地图与卡尔曼滤波器相结合,即使在使用ESM难以识别的患者中,也可以有效地识别皮质电机区域的位置,并且还可以作为癫痫手术后电机缺陷的可靠预测器。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号