Imaging characteristics of temporopolar blurring in the context of hippocampal sclerosis
Bibliographic record
Abstract
We present an illustrative case to address anterior temporal lobe atrophy with poor delineation of the temporopolar gray-white matter interface based on T2-weighted and fluid-attenuated inversion recovery (FLAIR) images in patients with temporal lobe epilepsy associated with hippocampal sclerosis (TLE-HS). A 52-year-old woman with pharmacoresistant seizures since the age of six months underwent a previous MRI scan using a suboptimal protocol which was reported as unremarkable. MRI performed according to an epilepsy protocol showed classic signs of left HS and ipsilateral temporal polar atrophy with blurring of the gray-white matter boundary on FLAIR images. She underwent a left amygdalohippocampectomy and anterior temporal resection and remains seizure-free after 24 months. Histopathological analyses showed HS and no signs of focal cortical dysplasia (FCD). Blurring and atrophy of the ipsilateral temporal pole are common in TLE-HS and often misinterpreted as FCD. This relates to delayed myelination in patients with seizures before the age of two, is more pronounced on FLAIR sequences, and gives a false impression of cortical thickening. However, the T1-weighted images show a relatively well-demarcated cortical-subcortical transition and normal cortical thickness. By contrast, the cortical thickening in FCD is observed on both T1-weighted and FLAIR images. Since FCD also occurs in temporal lobe regions, it is important to differentiate the extra-hippocampal MRI abnormalities in TLE-HS from those likely to be FCD. This case highlights the importance of evaluation based on detailed imaging, which should always be conducted considering the EEG, seizure semiology, and other clinical information.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".