Tract Identification by Novel MRI Signal Changes following Stereotactic Anterior Capsulotomy
Bibliographic record
Abstract
BACKGROUND: Five patients underwent magnetic resonance imaging (MRI) following MRI-guided stereotactic bilateral anterior capsulotomy to detect lesion-related anatomic changes. METHODS: Five disabled and treatment-resistant patients with major depression (n = 4) and obsessive-compulsive disorder (n = 1) underwent stereotactic bilateral anterior capsulotomy. All patients had postoperative MRI at 2 months and at 1-4 years after surgery. An additional patient who had a pure motor deficit following a spontaneous basal ganglia hemorrhagic stroke was imaged as a comparator. RESULTS: The 2-month postcapsulotomy MRI showed a previously undescribed increase in T1-weighted signal within similar neural pathways for each patient. These pathways showed no changes in T2-weighted or fluid-attenuated inversion recovery sequences. The signal changes are different from the expected changes associated with anterograde Wallerian degeneration and identify retrograde changes in the proximal segment of the interrupted axon. CONCLUSION: Previously undescribed T1-weighted signal alterations following stereotactic surgery identify retrograde non-Wallerian changes in interrupted axons and provide a new method in identifying and tracing lesioned pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".