Hippocampal and trigeminal nerve volume predict outcome of surgical treatment for trigeminal neuralgia
Bibliographic record
Abstract
Background Many medically-refractory trigeminal neuralgia patients are non-responders to surgical treatment. Few studies have explored how trigeminal nerve characteristics relate to surgical outcome, and none have investigated the relationship between subcortical brain structure and treatment outcomes. Methods We retrospectively studied trigeminal neuralgia patients undergoing surgical treatment with microvascular decompression. Preoperative magnetic resonance imaging was used for manual tracing of trigeminal nerves and automated segmentation of hippocampus, amygdala, and thalamus. Nerve and subcortical structure volumes were compared between responders and non-responders and assessed for ability to predict postoperative pain outcome. Results In all, 359 trigeminal neuralgia patients treated surgically from 2005–2018 were identified. A total of 34 patients met the inclusion criteria (32 with classic and two with idiopathic trigeminal neuralgia). Across all patients, thalamus volume was reduced ipsilateral compared to contralateral to the side of pain. Between responders and non-responders, non-responders exhibited larger contralateral trigeminal nerve volume, and larger ipsilateral and contralateral hippocampus volume. Through receiver-operator characteristic curve analyses, contralateral hippocampus volume correctly classified treatment outcome in 82% of cases (91% sensitive, 78% specific, p = 0.008), and contralateral nerve volume correctly classified 81% of cases (91% sensitive, 75% specific, p < 0.001). Binomial logistic regression analysis showed that contralateral hippocampus and contralateral nerve volumes together classified outcome with 84% accuracy (Nagelkerke R 2 = 65.1). Conclusion Preoperative hippocampal and trigeminal nerve volume, measured on standard clinical magnetic resonance images, may predict early non-response to surgical treatment for trigeminal neuralgia. Treatment resistance in medically refractory trigeminal neuralgia may depend on the structural features of both the trigeminal nerve and structures involved in limbic components of chronic pain.
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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 | 0.002 |
| 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) | 0.002 | 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".