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

机译:使用弥散MRI术式定量量化主要运动路径及其在预测局灶性癫痫患儿术后运动功能障碍中的应用

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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:作为量化局灶性癫痫患儿主要运动路径和预测术后运动功能障碍的一种新工具,本研究利用弥散加权成像(DWI)超声成像与卡尔曼滤镜相结合的最大后验概率(MAP)分类。 DWI是在31例顽固性局灶性癫痫患儿中进行的。使用DWI-MAP分类器对与“手指”,“腿”和“脸部”相关的三个主要运动路径进行分类,并通过接收器工作特征(ROC)曲线分析与侵入性电刺激测绘(ESM)的结果进行比较。进行卡尔曼滤波分析以生成模型,以根据切除切缘和手指运动路径之间的接近程度确定术后运动功能障碍的可能性。 ROC曲线分析表明,与ESM相比,DWI-MAP在检测20毫米以内的三个运动区域时可实现高达89%(手指),88%(腿),89%(脸)的高精度。此外,术后手指通道纤维数量减少与手部术后运动功能障碍有关。该预测模型显示,如果术前DWI术中所见的切除切缘与手指运动路径之间的距离为19.5 mm,则避免术后缺陷的准确性为92%。这项研究提供了证据,即DWI-MAP结合卡尔曼滤波器可以有效地识别皮质运动区域的位置,即使在使用ESM难以识别运动区域的患者中,也可以作为癫痫手术后运动功能障碍的可靠预测指标。

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