NeuroImage: Clinical (Jan 2025)

Strong connectivity to the sensorimotor cortex predicts clinical effectiveness of thalamic deep brain stimulation in essential tremor

  • F. Grimm,
  • M. Walcker,
  • L. Milosevic,
  • G. Naros,
  • B. Bender,
  • D. Weiss,
  • A. Gharabaghi

Journal volume & issue
Vol. 45
p. 103709

Abstract

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Introduction: The outcome of thalamic deep brain stimulation (DBS) for essential tremor (ET) varies, probably due to the difficulty in identifying the optimal target for DBS placement. Recent approaches compared the clinical response with a connectivity-based segmentation of the target area. However, studies are contradictory by indicating the connectivity to the primary motor cortex (M1) or to the premotor/supplementary motor cortex (SMA) to be therapeutically relevant. Objective: To identify the connectivity profile that corresponds to clinical effective targeting of DBS for ET. Methods: Patient-specific probabilistic diffusion tensor imaging was performed in 20 ET patients with bilateral thalamic DBS. Following monopolar review, the stimulation response was classified for the most effective contact in each hemisphere as complete vs. incomplete upper limb tremor suppression (40 assessments). Finally, the connectivity profiles of these contacts within the cortical and cerebellar tremor network were estimated and compared between groups. Results: The active contacts that led to complete (n = 25) vs. incomplete (n = 15) tremor suppression showed significantly higher connectivity to M1 (p < 0.001), somatosensory cortex (p = 0.008), anterior lobe of the cerebellum (p = 0.026) and SMA (p = 0.05); with Cohen’s (d) effect sizes of 0.53, 0.42, 0.25 and 0.10, respectively. The clinical benefits were achieved without requiring higher stimulation intensities or causing additional side effects. Conclusion: Clinical effectiveness of DBS for ET corresponded to a distributed connectivity profile, with the connection to the sensorimotor cortex being most relevant. Long-term follow-up in larger cohorts and replication in out-of-sample data are necessary to confirm the robustness of these findings.

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