Position Statement of the American Society for Stereotactic and Functional Neurosurgery on Focused Ultrasound Lesioning of the Brain by Non-neurosurgeons
Bibliographic record
Abstract
Since its US Food and Drug Administration approval in 2016, magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy has grown into one of the procedures of choice among patients with essential tremor (ET). Approved applications for the procedure have expanded over time from unilateral thalamotomy to treat ET and Parkinson disease tremor to bilateral staged thalamotomy for ET. As the procedure expands to healthcare environments beyond large academic centers, guidance is required to ensure that the responsible clinicians are appropriately trained to undertake this operative procedure. Although multidisciplinary movement disorder teams are important for the optimal management of patients, MRgFUS lesions are inherently surgical interventions. Neurosurgeons are trained to evaluate these patients, consider surgical alternatives and conduct these operations, particularly after completing a fellowship in the subspecialty of stereotactic and functional neurosurgery. At present, all high-level evidence regarding the safety and efficacy of MRgFUS lesions to treat movement disorders derives from procedures performed by neurosurgeons, so those results may not be generalizable to other physicians. Based on these considerations and potential liability issues, the American Society for Stereotactic and Functional Neurosurgery, which acts as the joint section representing the field of stereotactic and functional neurosurgery on behalf of the Congress of Neurological Surgeons and the American Association of Neurological Surgeons, puts forth this position statement that only neurosurgeons appropriately trained to conduct functional neurosurgery procedures should conduct MRgFUS surgical lesions.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.035 | 0.032 |
| Insufficient payload (model declined to judge) | 0.008 | 0.011 |
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".