作者
Karim Mithani, Mirriam Mikhail, Benjamin R Morgan, Simeon Wong, Alexander G Weil, Sylvain Deschenes, Shelly Wang, Byron Bernal, Magno R Guillen, Ayako Ochi, Hiroshi Otsubo, Ivanna Yau, William Lo, Elizabeth Pang, Stephanie Holowka, O Carter Snead, Elizabeth Donner, James T Rutka, Cristina Go, Elysa Widjaja, George M Ibrahim
发表日期
2019/11
期刊
Annals of neurology
卷号
86
期号
5
页码范围
743-753
出版商
John Wiley & Sons, Inc.
简介
Objective
Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS response using structural and functional connectomic profiling.
Methods
Fifty‐six children, comprising discovery (n = 38) and validation (n = 18) cohorts, were recruited from 3 separate institutions. Diffusion tensor imaging was used to identify group differences in white matter microstructure, which in turn informed beamforming of resting‐state magnetoencephalography recordings. The results were used to generate a support vector machine learning classifier, which was independently validated. This algorithm was compared to a second classifier generated using 31 clinical covariates.
Results
Treatment responders demonstrated greater fractional anisotropy in left thalamocortical …
学术搜索中的文章
K Mithani, M Mikhail, BR Morgan, S Wong, AG Weil… - Annals of neurology, 2019