Morgan Victoria L, Englot Dario J, Rogers Baxter P, Landman Bennett A, Cakir Ahmet, Abou-Khalil Bassel W, Anderson Adam W
Department of Radiology and Radiological Sciences, Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A.
Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, U.S.A.
Epilepsia. 2017 Jul;58(7):1251-1260. doi: 10.1111/epi.13762. Epub 2017 Apr 27.
Currently, approximately 60-70% of patients with unilateral temporal lobe epilepsy (TLE) remain seizure-free 3 years after surgery. The goal of this work was to develop a presurgical connectivity-based biomarker to identify those patients who will have an unfavorable seizure outcome 1-year postsurgery.
Resting-state functional and diffusion-weighted 3T magnetic resonance imaging (MRI) was acquired from 22 unilateral (15 right, 7 left) patients with TLE and 35 healthy controls. A seizure propagation network was identified including ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula, with bilateral midcingulate and precuneus. Between each pair of regions, functional connectivity based on correlations of low frequency functional MRI signals, and structural connectivity based on streamline density of diffusion MRI data were computed and transformed to metrics related to healthy controls of the same age.
A consistent connectivity pattern representing the network expected in patients with seizure-free outcome was identified using eight patients who were seizure-free at 1-year postsurgery. The hypothesis that increased similarity to the model would be associated with better seizure outcome was tested in 14 other patients (Engel class IA, seizure-free: n = 5; Engel class IB-II, favorable: n = 4; Engel class III-IV, unfavorable: n = 5) using two similarity metrics: Pearson correlation and Euclidean distance. The seizure-free connectivity model successfully separated all the patients with unfavorable outcome from the seizure-free and favorable outcome patients (p = 0.0005, two-tailed Fisher's exact test) through the combination of the two similarity metrics with 100% accuracy. No other clinical and demographic predictors were successful in this regard.
This work introduces a methodologic framework to assess individual patients, and demonstrates the ability to use network connectivity as a potential clinical tool for epilepsy surgery outcome prediction after more comprehensive validation.
目前，约60 - 70%的单侧颞叶癫痫（TLE）患者术后3年无癫痫发作。本研究的目的是开发一种基于术前连接性的生物标志物，以识别那些术后1年癫痫发作结果不佳的患者。
对22例单侧（15例右侧，7例左侧）TLE患者和35名健康对照者进行静息态功能和扩散加权3T磁共振成像（MRI）检查。确定了一个癫痫传播网络，包括同侧（癫痫灶同侧）和对侧海马、丘脑和岛叶，以及双侧中央扣带回和楔前叶。计算每对区域之间基于低频功能MRI信号相关性的功能连接性，以及基于扩散MRI数据流线密度的结构连接性，并将其转换为与同年龄健康对照相关的指标。
利用8例术后1年无癫痫发作的患者，确定了一种代表无癫痫发作结果患者预期网络的一致连接模式。使用Pearson相关性和欧几里得距离这两种相似性度量方法，在另外14例患者（Engel分级IA，无癫痫发作：n = 5；Engel分级IB - II，良好：n = 4；Engel分级III - IV，不佳：n = 5）中检验了与模型相似度增加与更好癫痫发作结果相关的假设。通过将两种相似性度量方法相结合，无癫痫发作连接模型成功地将所有结果不佳的患者与无癫痫发作和结果良好的患者区分开来（p = 0.0005，双侧Fisher精确检验），准确率达100%。在这方面，没有其他临床和人口统计学预测指标成功。
本研究介绍了一种评估个体患者的方法框架，并证明了在经过更全面验证后，将网络连接性用作癫痫手术结果预测潜在临床工具的能力。
