A.3 Use of diffusion-weighted imaging to distinguish seizure-related change from limbic encephalitis
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Bibliographic record
Abstract
Background: Limbic encephalitis (LE) classically causes medial temporal lobe T2-hyperintensity on magnetic resonance imaging (MRI), but this can also occur with seizure activity. Identifying neuroimaging patterns that can distinguish between LE and seizure activity may help avoid diagnostic confusion in such challenging cases. Methods: Through retrospective review of Mayo Clinic patients who had medial temporal lobe T2-hyperintensity on MRI, we identified non-LE patients with seizure-related medial temporal lobe T2-hyperintensity. Their diffusion-weighted imaging (DWI) was reviewed to look for diffusion restriction patterns potentially unique to seizure activity. Next, a control cohort of LE patients with medial temporal lobe T2-hyperintensity was identified, and their DWI was reviewed to see if these diffusion restriction patterns could help distinguish seizure activity from LE. Results: We identified 10 non-LE patients who had medial temporal lobe T2-hyperintensity due to seizure activity; 9/10 had one of two medial temporal lobe diffusion restriction patterns we uncovered as being potentially unique to seizure activity. In contrast, only 5/57 LE patients had one of these diffusion restriction patterns identified, all of whom had seizures reported. Conclusions: We report two diffusion restriction patterns that may help distinguish seizure activity from LE. Recognition of these diffusion restriction patterns should prompt evaluation for possible seizure activity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it