Temporal disconnection between pain relief and trigeminal nerve microstructural changes after Gamma Knife radiosurgery for trigeminal neuralgia
Bibliographic record
Abstract
OBJECTIVE: Gamma Knife radiosurgery (GKRS) is a noninvasive surgical treatment option for patients with medically refractive classic trigeminal neuralgia (TN). The long-term microstructural consequences of radiosurgery and their association with pain relief remain unclear. To better understand this topic, the authors used diffusion tensor imaging (DTI) to characterize the effects of GKRS on trigeminal nerve microstructure over multiple posttreatment time points. METHODS: Ninety-two sets of 3-T anatomical and diffusion-weighted MR images from 55 patients with TN treated by GKRS were divided within 6-, 12-, and 24-month posttreatment time points into responder and nonresponder subgroups (≥ 75% and < 75% reduction in posttreatment pain intensity, respectively). Within each subgroup, posttreatment pain intensity was then assessed against pretreatment levels and followed by DTI metric analyses, contrasting treated and contralateral control nerves to identify specific biomarkers of successful pain relief. RESULTS: GKRS resulted in successful pain relief that was accompanied by asynchronous reductions in fractional anisotropy (FA), which maximized 24 months after treatment. While GKRS responders demonstrated significantly reduced FA within the radiosurgery target 12 and 24 months posttreatment (p < 0.05 and p < 0.01, respectively), nonresponders had statistically indistinguishable DTI metrics between nerve types at each time point. CONCLUSIONS: Ultimately, this study serves as the first step toward an improved understanding of the long-term microstructural effect of radiosurgery on TN. Given that FA reductions remained specific to responders and were absent in nonresponders up to 24 months posttreatment, FA changes have the potential of serving as temporally consistent biomarkers of optimal pain relief following radiosurgical treatment for classic TN.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 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".