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Using Saccadometry with Deep Brain Stimulation to Study Normal and Pathological Brain Function
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Enhancing Asleep Deep Brain Stimulation Targeting for Essential Tremor Using Machine Learning: The OPTIVIM Phase 2

Julien Engelhardt1,2, Emile Simon3, Nejib Zemzemi2,4

  • 1Neurochirurgie B, CHU de Bordeaux, Bordeaux, France.

Neurosurgery
|February 2, 2026
PubMed
Summary
This summary is machine-generated.

Optimized Deep Brain Stimulation (DBS) targeting using the OptimDBS algorithm showed significant tremor reduction in essential tremor patients. This asleep DBS approach, guided by MRI, offers comparable efficacy to awake methods without intraoperative monitoring.

Keywords:
Asleep surgeryClinical trialDeep brain stimulationEssential tremorMachine-learning

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Area of Science:

  • Neurosurgery
  • Neurology
  • Medical Imaging

Background:

  • Deep brain stimulation (DBS) is a key treatment for essential tremor.
  • Optimal targeting and accurate electrode placement for DBS remain challenging.
  • The OptimDBS algorithm uses MRI data to predict effective DBS targets.

Purpose of the Study:

  • To evaluate the efficacy and safety of asleep DBS guided by the OptimDBS algorithm.
  • To assess OptimDBS performance in an independent patient cohort without intraoperative controls.

Main Methods:

  • Prospective, single-arm, multicenter Phase 2 trial (OPTIVIM study).
  • 22 patients underwent asleep DBS guided by OptimDBS.
  • Primary outcome: Fahn-Tolosa-Marin scale at 3 months post-surgery.

Main Results:

  • Significant improvement in Fahn-Tolosa-Marin scores (61.3%).
  • Substantial reduction in tremor amplitude (81% right, 84% left) via accelerometry.
  • No serious adverse events reported; active contacts localized to effective target areas.

Conclusions:

  • OptimDBS-guided asleep DBS demonstrates comparable efficacy to existing DBS and ablative techniques.
  • Further long-term studies with larger cohorts are recommended for confirmation.