Structural connectivity-based segmentation of the thalamus and prediction of tremor improvement following thalamic deep brain stimulation of the ventral intermediate nucleus.

OBJECTIVES: Traditional targeting methods for thalamic deep brain stimulation (DBS) performed to address tremor have predominantly relied on indirect atlas-based methods that focus on the ventral intermediate nucleus despite known variability in thalamic functional anatomy. Improvements in preoperative targeting may help maximize outcomes and reduce thalamic DBS-related complications. In this study, we evaluated the ability of thalamic parcellation with structural connectivity-based segmentation (SCBS) to predict tremor improvement following thalamic DBS. METHODS: In this retrospective analysis of 40 patients with essential tremor, hard segmentation of the thalamus was performed by using probabilistic tractography to assess structural connectivity to 7 cortical targets. The volume of tissue activated (VTA) was modeled in each patient on the basis of the DBS settings. The volume of overlap between the VTA and the 7 thalamic segments was determined and correlated with changes in preoperative and postoperative Fahn-Tolosa-Marin Tremor Rating Scale (TRS) scores by using multivariable linear regression models. RESULTS: A significant association was observed between greater VTA in the supplementary motor area (SMA) and premotor cortex (PMC) thalamic segment and greater improvement in TRS score when considering both the raw change (P = .001) and percentage change (P = .011). In contrast, no association was observed between change in TRS score and VTA in the primary motor cortex thalamic segment (P ≥ .19). CONCLUSIONS: Our data suggest that greater VTA in the thalamic SMA/PMC segment during thalamic DBS was associated with significant improvement in TRS score in patients with tremor. These findings support the potential role of thalamic SCBS as an independent predictor of tremor improvement in patients who receive thalamic DBS.