Extratemporal White Matter Abnormalities in Mesial Temporal Lobe Epilepsy Demonstrated with Diffusion Tensor Imaging
Bibliographic record
Abstract
PURPOSE: Recent studies have demonstrated bilateral white matter abnormalities in temporal lobe epilepsy (TLE) patients with unilateral mesial temporal sclerosis (MTS). The purpose of this project was to determine whether abnormalities of water diffusion are seen in extratemporal white matter of patients with TLE and pathologically confirmed MTS and to determine whether these findings are associated with worse surgical outcome. METHODS: Eleven patients with TLE and unilateral MTS confirmed in surgical specimens and 14 controls were studied by using cerebrospinal fluid-suppressed diffusion tensor imaging (DTI) and T2 relaxometry. RESULTS: Hippocampal T2 signal for patients was significantly elevated both ipsilateral (p<0.001) and contralateral (p=0.006) to MTS. DTI demonstrated reduced fractional anisotropy of the genu of the corpus callosum (p=0.003) and external capsule (p=0.02) and elevated mean diffusivity of the genu (p=0.005), splenium (p=0.03), and external capsule (p<0.001). For both the genu and external capsule, parallel diffusion of patients was not different from that of controls (genu, p=0.81; external capsule, p=0.45), whereas perpendicular diffusion was elevated (genu, p=0.001; external capsule, p<0.001). With mean postsurgical follow-up of 18.5 months, eight of 11 patients were entirely seizure free and the remaining three had all experienced a worthwhile reduction in seizure frequency. CONCLUSIONS: Our findings suggest that although patients with TLE and MTS have extensive bilateral and extratemporal pathology, these findings may not be associated with a worse postsurgical outcome.
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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) | 0.000 | 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) | 0.001 | 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".