Hippocampal subfield measurement and ILAE hippocampal sclerosis subtype classification with in vivo 4.7 tesla MRI
Bibliographic record
Abstract
OBJECTIVE: Neuropathological studies indicate that hippocampal sclerosis (HS) consists of three subtypes (ILAE types 1-3 HS). However, HS subtypes currently can only be diagnosed by pathological analysis of hippocampal tissue resected during epilepsy surgery or at autopsy. In vivo diagnosis of HS subtypes holds potential to improve our understanding of these variants in the ipsilateral as well as contralateral hippocampus. In this study, we aimed to: i) evaluate the reliability of our histology-derived segmentation protocol when applied to in vivo MRI; and ii) characterize variability of HS subtypes along the hippocampal long axis in patients with epilepsy. METHODS: Eleven subjects with unilateral HS were compared with ten healthy controls. We used 4.7 T MRI to acquire high resolution MR Images of the hippocampus in each subject. In vivo MRI-based diagnoses of HS subtypes were then determined in each patient by two methods: i) hippocampal subfield volumetry of the entire hippocampal body; and ii) subfield area analysis at multiple thin slices throughout the hippocampal body. RESULTS: Hippocampal body subfield segmentation demonstrated excellent reliability and volumetry of the symptomatic hippocampus revealed abnormalities in all eleven patients. Six subjects demonstrated findings consistent with type 1 HS while five subjects had volumetry-defined atypical HS (two with type 2 HS & three with type 3 HS) in the symptomatic hippocampus, while five subjects were found to have type 3 HS in the contralateral hippocampus. Subfield area analyses demonstrated remarkable variability of HS subtypes along the hippocampal long axis, both ipsilateral and contralateral to the seizure focus. SIGNIFICANCE: Our results provide preliminary evidence that determining HS Subtype using in vivo MRI may allow preoperative diagnosis of ILAE HS subtypes. Further studies are essential to determine the pathological correlates of these neuroimaging findings. The heterogeneity of abnormalities observed along the long axis of the hippocampus is consistent with previous autopsy studies and highlights the necessity of studying the entire hippocampus both ipsilateral and contralateral to the seizure focus in these future studies.
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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 | 0.001 | 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) | 0.001 | 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".