MRI-Guided Focused Ultrasound for the Treatment of Dystonia: A Narrative Review
Bibliographic record
Abstract
Contemporary surgical management of dystonia includes neuromodulation via deep brain stimulation (DBS) or ablative techniques such as radiofrequency (RF) ablation. MRI-guided focused ultrasound (MRgFUS) is an emerging modality that uses high-intensity ultrasound to precisely ablate targets in the brain; this is incisionless, potentially avoiding the surgical risks of a burr hole and transcortical tract to reach the anatomical target. There is some evidence of efficacy in essential tremor and Parkinson's disease (PD), but, to date, there is no study aggregating the evidence of MRgFUS in dystonia. In this narrative review, we searched Medline, Embase, CINAHL, EBSCO, and ClinicalTrials.gov for primary studies and clinical trials on MRgFUS in the treatment of dystonia. Data were analyzed concerning dystonia phenotype, reported outcomes, and complications. PD-related dystonia was also included within the scope of the review. Using our search criteria, six articles on the use of MRgFUS in adult dystonia and three articles on the use of FUS in dystonia in PD were included. Four trials on the use of FUS in dystonia were also found on ClinicalTrials.gov, one of which was completed in December 2013. All included studies showed evidence of symptomatic improvement, mostly in focal hand dystonia; improvements were also found in dystonia-associated tremor, cervicobrachial dystonia, and dystonia-associated chronic neuropathic pain as well as PD-related dystonia. Reported complications included transient neurological deficits and persistent arm pain in one study. However, the evidence is limited to level-4 case series at present. MRgFUS is an emerging modality that appears to be safe and effective, particularly in focal hand dystonia, without major adverse effects. However, the quality of evidence is low at present, and long-term outcomes are unknown. High-quality prospective studies comparing MRgFUS to other surgical techniques will be useful in determining its role in the management of dystonia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".