Radiofrequency Lesioning for Hemidystonia: A Systematic Review and Meta-Analysis with Individual Patient Data.

Abstract

Introduction: Radiofrequency lesioning (RL) had been a mainstay in functional neurosurgery for dystonic movement disorders before the widespread adoption of deep brain stimulation. Outcomes of RL in hemidystonia have varied. This review provides a systematic analysis of RL for hemidystonia and evaluates the spectrum of clinical outcome.

Methods: A systematic literature review was performed according to PRISMA guidelines in PubMed, Embase, and Web of Science using customized software (UiPath, NY) to identify all cohort studies, case series, and case reports on patients with hemidystonia treated with RF. Manuscripts were automatically searched for the term "hemidystonia." The selected manuscripts were then manually screened. Detailed information from two recent multi-patient studies was added. Outcome was assessed according to changes in rating scales or by the reported clinical descriptions. Clinical improvement then was classified as follows: (0) no improvement, (I) mild, (II) moderate, (III) marked improvement.

Results: Twenty-eight studies with individual patient data were included, totaling 101 cases published between 1962 and 2024. Thalamotomy/subthalamic region lesioning was performed in 80 cases, pallidotomy in 16, and both in 5. At the last follow-up, the overall distribution of clinical improvement was statistically significant (p = 0.0004) where the majority of patients (44.09%) showed moderate improvement. No significant differences were found between targets or etiologies, though patients with traumatic brain injury tended to fare worse. A significant negative linear correlation was found between the degree of improvement and age at surgery.

Conclusion: With advancements in targeting and technology, RL may represent a viable treatment option for selected patients with hemidystonia. However, given the current evidence limitations, prospective studies with standardized outcome assessments are needed to better characterize response variability and identify prognostic factors.