Hippocampal microscopic fractional anisotropy is reduced in temporal lobe epilepsy
Bibliographic record
Abstract
Surgical resection is the method of choice for treating drug-resistant focal temporal lobe epilepsy (TLE). Postsurgical outcomes are better when magnetic resonance imaging (MRI) findings can localize the seizure focus for resection. However, many patients are MR-negative, meaning the focus cannot be differentiated from normal tissue in relaxation-weighted MRI. Diffusion MRI shows promise as a preoperative marker of neuronal abnormalities due to its sensitivity to cellular changes such as axon damage, indexed by fractional anisotropy. Microscopic fractional anisotropy is a recently introduced diffusion MRI metric that is sensitive to axon integrity regardless of axon orientation in both gray and white matter. In contrast, regular fractional anisotropy is only sensitive to axon integrity in coherently oriented bundles of fibers. This work investigated whether microscopic fractional anisotropy is sensitive to hippocampal abnormalities in drug-resistant TLE. Diffusion MRI was performed on a 3T scanner in 19 patients (age = 31 ± 10 years) with drug-resistant TLE (of which 10 were MR-negative) and 18 healthy volunteers (age = 38 ± 15). A deep-learning method was employed to segment the hippocampus into smaller subregions corresponding to the subiculum, cornu ammonis (CA) 1, CA2/3, and CA4 plus dentate gyrus (DG). Mean measurements of subregion volume, diffusivity, fractional anisotropy, and microscopic fractional anisotropy were compared between cohorts. In a subset of the TLE cohort suspected to have unilateral pathology (n = 15, age = 32 ± 10 years), the percentage differences between measurements ipsilateral and contralateral to the epileptogenic zone were evaluated to assess asymmetry. Microscopic fractional anisotropy was reduced in the hippocampus of drug-resistant TLE patients relative to healthy volunteers. In subregion-specific analysis, microscopic fractional anisotropy was significantly reduced in only the CA4/DG region in patients compared with healthy volunteers, after corrections for multiple comparisons. In the 15 patients with suspected unilateral pathology, microscopic fractional anisotropy was reliably and statistically lower in the ipsilateral CA4/DG region than in the contralateral side. Significant differences were not observed between TLE patients and healthy volunteers, or between hemispheres for patients with suspected unilateral pathology, for the fractional anisotropy or volume metrics. Diffusion MRI may complement standard imaging procedures by detecting abnormalities in MRI-negative patients. Due to its ability to detect abnormality regardless of axon orientation, microscopic fractional anisotropy may improve seizure focus localization in surgical candidates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".