Abstract
Functional connectivity shows the ability to predict the outcome of subthalamic nucleus deep brain stimulation (DBS) in Parkinson disease (PD). However, evidence supporting its value in predicting the outcome of globus pallidus internus (GPi) DBS remains scarce. In this study the authors investigated patient-specific functional connectivity related to GPi DBS outcome in PD and established connectivity models for outcome prediction. The authors reviewed the outcomes of 21 patients with PD who received bilateral GPi DBS and presurgical functional MRI at the Ruijin Hospital. The connectivity profiles within cortical areas identified as relevant to DBS outcome in the literature were calculated using the intersection of the volume of tissue activated (VTA) and the local structures as the seeds. Combined with the leave-one-out cross-validation strategy, models of the optimal connectivity profile were constructed to predict outcome. Connectivity between the pallidal areas and primary motor area, supplementary motor area (SMA), and premotor cortex was identified through the literature as related to GPi DBS outcome. The similarity between the connectivity profile within the primary motor area, SMA, pre-SMA, and premotor cortex seeding from the VTA-GPi intersection from an out-of-sample patient and the constructed in-sample optimal connectivity profile predicts GPi DBS outcome (R = 0.58, p = 0.006). The predictions on average deviated by 13.1% ± 11.3% from actual improvements. On the contrary, connectivity profiles seeding from the GPi (R = -0.12, p = 0.603), the VTA (R = 0.23, p = 0.308), the VTA outside the GPi (R = 0.12, p = 0.617), or other local structures were found not to be predictive. The results showed that patient-specific functional connectivity seeding from the VTA-GPi intersection could help in GPi DBS outcome prediction. Reproducibility remains to be determined across centers in larger cohorts stratified by PD motor subtype.
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