Magnetic resonance-guided ultrasound thalamotomy for essential tremor: a review
Bibliographic record
Abstract
INTRODUCTION: Essential tremor (ET) is a common neurological disorder characterized by involuntary, rhythmic shaking, primarily of the hands. While not life-threatening, ET significantly impairs quality of life. Pharmacological treatments, like beta-blockers or anticonvulsants, often have limited efficacy, leading patients to more aggressive alternatives such as surgical intervention. Recently, magnetic resonance-guided focused ultrasound has emerged as an alternative to surgical procedures, offering incisionless lesioning of the thalamus, resulting in immediate and sustained tremor reduction. AREAS COVERED: This review explores the MRgFUS technique in the treatment of ET, reviewing clinical efficacy, safety, and procedural advances. A literature search was conducted using PubMed for articles published between January 2015 and March 2024, with the terms: 'MRgFUS,' 'essential tremor,' 'focused ultrasound thalamotomy,' and 'bilateral thalamotomy.' Key points such as patient selection, skull density ratio, monitoring, thermal effects and tractography are discussed. EXPERT OPINION: MRgFUS has transformed the treatment of ET by providing a precise, incisionless alternative now included in clinical guidelines. Challenges such as SDR limitations or restricted approved-indications limit its extended use. Advances in targeting, thermometry and other biological effects such as histotripsy could expand accessibility and indications. By 2035, MRgFUS could become a standard outpatient procedure for ET and other brain disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".