Progressive contralateral hippocampal atrophy following Temporal Lobe Epilepsy Surgery (TLS)
Bibliographic record
Abstract
Background: Temporal Lobe Epilepsy is associated with bilateral gray (GM) and white matter (WM) loss. After surgical treatment progressive bilateral temporal and extra-temporal WM change occur, however, less is known regarding post-operative GM change. We set out to measure contralateral hippocampal volume (CHV) following TLS. Methods: 1.5T-3D-1mm-isotropic-MPRAGE scans in 26 TLE patients and 3 controls in two groups: longitudinal (n=10)(imaged POD1,2,3,6,60,120 and >360d) and single post-operative scan (n=16). Manual volumetry protocols. Results: We find significant CHV atrophy at delayed scan relative to baseline (mean atrophy 26.8%). In the longitudinal group there is significant and progressive atrophy from baseline to POD4-8 (72.6+/-6.5%), POD60-360 (69.7+/-12.3%) and >360 (58.5+/-10.6%). No significant atrophy in either the control group HV or contralateral CV over time. No significant difference in mean HV at the most delayed exam for surgery type (p=0.13) or side (p=0.24). Conclusions: We find a statistically significant CHV atrophy following surgery which is progressive over time. Our longitudinal within-subject design describes the time course and extent more fully than previous work. Caudate analysis indicates that early CHV atrophy is not due to global atrophy following brain surgery but rather may be due to deafferentation and deefferentation. Finally, we find no significant difference in atrophy when analyzed by surgical approach or surgical side.
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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".