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Wiley, Annals of Neurology, 2022

DOI: 10.1002/ana.26324



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Probabilistic mapping reveals optimal stimulation site in essential tremor

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This paper is available in a repository.

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Data provided by SHERPA/RoMEO


Objective To obtain individual clinical and neuroimaging data of patients undergoing Deep Brain Stimulation for essential tremor from five different European centers to identify predictors of outcome and to identify an optimal stimulation site. Methods We analysed retrospectively baseline covariates, pre- and postoperative clinical tremor scores (12-month) as well as individual imaging data from 119 patients to obtain individual electrode positions and stimulation volumes. Individual imaging and clinical data was used to calculate a probabilistic stimulation map in normalized space using voxel-wise statistical analysis. Finally, we used this map to train a classifier to predict tremor improvement. Results Probabilistic mapping of stimulation effects yielded a statistically significant cluster that was associated with a tremor improvement greater than 50%. This cluster of optimal stimulation extended from the posterior subthalamic area to the ventralis intermedius nucleus and coincided with a normative structural-connectivity-based cerebello-thalamic tract (CTT). The combined features ?distance between the stimulation volume and the significant cluster? and ?CTT activation? were used as a predictor of tremor improvement. This correctly classified a greater than 50% tremor improvement with a sensitivity of 89% and a specificity of 57%. Interpretation Our multicentre ET probabilistic stimulation map identified an area of optimal stimulation along the course of the CTT. The results of this study are mainly descriptive until confirmed in independent datasets, ideally through prospective testing. This target will be made openly available and may be used to guide surgical planning and for computer-assisted programming of deep brain stimulation in the future. This article is protected by copyright. All rights reserved.