Chen Yingchuan, Zhu Guanyu, Liu Defeng, Liu Yuye, Zhang Xin, Du Tingting, Zhang Jianguo
Department of Neurosurgery, Fengtai Dist, Beijing Tiantan Hospital, Capital Medical University, South Four Ring West Road No. 119, B district, Beijing, 100070, China.
Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Neurotherapeutics. 2022 Mar;19(2):608-615. doi: 10.1007/s13311-022-01208-9. Epub 2022 Mar 23.
Subthalamic nuclei deep brain stimulation (STN-DBS) is a well-established treatment for Parkinson's disease (PD). Some studies have confirmed the long-term efficacy is associated with brain connectivity; however, whether the initial outcome is associated with brain connectivity and efficacy of prediction based on these factors has not been well investigated. In the present study, a total of 98 patients were divided into a training set (n = 78) and a test set (n = 20). The stimulation and medication responses were calculated based on the motor performance. The functional and structural connectomes were established based on a public database and used to measure the association between stimulation response and brain connectivity. The prediction of initial outcome was achieved via a machine learning algorithm-support vector machine based on the model established with the training set. It was found that the initial outcome of STN-DBS was associated with functional/structural connectivities between the volume of tissue activated and multiple brain regions, including the supplementary motor area, precentral and frontal areas, cingulum, temporal cortex, and striatum. These factors could be used to predict the initial outcome, with an r value of 0.4978 (P = 0.0255). Our study demonstrates a correlation between a specific connectivity pattern and initial outcome of STN-DBS, which could be used to predict the initial outcome of DBS.
丘脑底核深部脑刺激（STN-DBS）是一种成熟的帕金森病（PD）治疗方法。一些研究已证实其长期疗效与脑连接性相关；然而，初始疗效是否与脑连接性相关以及基于这些因素的疗效预测尚未得到充分研究。在本研究中，共98例患者被分为训练集（n = 78）和测试集（n = 20）。根据运动表现计算刺激和药物反应。基于一个公共数据库建立功能和结构连接组，并用于测量刺激反应与脑连接性之间的关联。基于用训练集建立的模型，通过机器学习算法——支持向量机实现对初始疗效的预测。研究发现，STN-DBS的初始疗效与被激活组织体积和多个脑区之间的功能/结构连接性相关，这些脑区包括辅助运动区、中央前回和额叶区、扣带、颞叶皮质和纹状体。这些因素可用于预测初始疗效，r值为0.4978（P = 0.0255）。我们的研究证明了特定连接模式与STN-DBS初始疗效之间的相关性，这可用于预测DBS的初始疗效。
