Examining cognitive change in magnetic resonance-guided focused ultrasound capsulotomy for psychiatric illness
Bibliographic record
Abstract
Magnetic resonance-guided focused ultrasound (MRgFUS) anterior capsulotomy is a novel treatment option for patients with refractory obsessive compulsive disorder (OCD) or major depressive disorder (MDD). However, there is concern that lesional psychiatric surgery procedures may have adverse effects on cognition. In this study, we examined whether MRgFUS capsulotomy causes cognitive decline in patients with psychiatric illness. Ten patients with refractory OCD (n = 5) or MDD (n = 5) underwent MRgFUS capsulotomy. Cognitive functioning was measured at baseline as well as 6 months and 12 months postoperatively, with a battery of neuropsychological tests assessing domains of executive function, memory, and processing speed. Scores were analyzed at the individual-level, and changes ≥2 standard deviations were considered clinically significant. We also examined whether changes in clinical symptoms were associated with changes in cognitive performance. At baseline intellectual functioning was in the average to high-average range for the group. Following MRgFUS capsulotomy, there were no deteriorations in cognition that reached ≥2 standard deviations at 6 or 12 months. Eight out of ten patients demonstrated a ≥2 standard deviation improvement in at least one cognitive score at 6 or 12 months postoperatively. Improvements in clinical symptoms correlated significantly with self-reported improvements in frontal lobe function (p < 0.05), but not with objective measures of cognitive functioning. To summarize, MRgFUS capsulotomy did not result in cognitive decline in this cohort of patients with refractory OCD or MDD, suggesting that this procedure can be offered to patients with a very low risk of cognitive side effects.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 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".