Ventral targeted anterior capsulotomy for treatment-resistant depression and obsessive-compulsive disorder: A treatment method with cases
Bibliographic record
Abstract
Ablative surgery using bilateral anterior capsulotomy (BAC) is an option for treatment resistant depression (TRD) and obsessive-compulsive disorder (TROCD). The location extent of the lesion within anterior limb of the internal capsule (ALIC) remains uncertain. Accumulating evidence has suggested that the lesion should be located ventrally while limiting the dorsal extent. Our center is now targeting specific fiber tracts within the lower half of the ALIC. Presurgical diffusion tensor Magnetic Resonance Imaging (MRI) was used to identify individual fibre tracts within the ventral aspect of the ALIC in the last two patients who underwent BAC at our center. One patient had TRD and the other had both TROCD and TRD. Radiofrequency-induced thermal lesions were created in the identified targets with lesion volumes between 20 and 229 mm3 (average 95 mm3). Both patients were responders with neither experiencing significant side effects including compromised executive functions. The generalizability of our findings is limited because the outcome is based on two subjects. This work suggests that BAC can be individually tailored and more limited to the ventral aspect of the ALIC and is effective and safe for TRD and TROCD. Accumulating data also suggests that to be clinically effective the length of the capsulotomy should be about 10mm. BAC’s use may increase with the growing utilization and mastery of magnetic resonance guided focused ultrasound.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".