P.135 Impact of brainstem lesion location on symptoms and treatment response in Multiple Sclerosis-Associated Trigeminal Neuralgia
Bibliographic record
Abstract
Background: Trigeminal neuralgia (TN) is more common in multiple sclerosis (MS) patients than in the general population, likely due to demyelination impacting the trigeminal pathways. While brainstem lesions are associated with MS-TN, their precise role remains unclear. Methods: This study investigates the relationship between brainstem MS plaque location, TN symptoms, and treatment response. We retrospectively analyzed brain MRIs of MS-TN patients, segmenting and coregistering brainstem plaques in MNI space. A tractographic atlas of the trigeminal system was generated using high-resolution diffusion imaging from 30 patients. Lesion involvement was determined by intersection with the trigeminal tract, and its association with pain intensity and treatment outcomes was analyzed using linear regression. Results: Our research revealed 83% of MS-TN patients had brainstem lesions near the fourth ventricle. No single lesion hot spot was identified. Lesion volume did not predict symptom recurrence or treatment response. However, 97% of lesions intersected the trigeminal tract, supporting its association with TN symptoms. Conclusions: The strong overlap between lesions and the trigeminal tract suggests a potential pain generator in MS-TN. Further research is needed to determine whether similar lesions exist in asymptomatic MS patients and to confirm this hypothesis. Future studies will explore whether tract involvement better predicts clinical response to treatment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".