<i>In Vivo</i>Diffusion Tensor Imaging and Histopathology of the Fimbria-Fornix in Temporal Lobe Epilepsy
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Bibliographic record
Abstract
While diffusion tensor imaging (DTI) has been extensively used to infer micro-structural characteristics of cerebral white matter in human conditions, correlations between human in vivo DTI and histology have not been performed. Temporal lobe epilepsy (TLE) patients with mesial temporal sclerosis (MTS) have abnormal DTI parameters of the fimbria-fornix (relative to TLE patients without MTS) which are presumed to represent differences in axonal/myelin integrity. Medically intractable TLE patients who undergo temporal lobe resection including the fimbria-fornix provide a unique opportunity to study the anatomical correlates of water diffusion abnormalities in freshly excised tissue. Eleven patients with medically intractable TLE were recruited (six with and five without MTS) for presurgical DTI followed by surgical excision of a small specimen of the fimbria-fornix which was processed for electron microscopy. Blinded quantitative analysis of the microphotographs included axonal diameter, density and area, cumulative axon membrane circumference, and myelin thickness and area. As predicted by DTI the fimbria-fornix of TLE patients with MTS had increased extra-axonal fraction, and reduced cumulative axonal membrane circumference and myelin area. Consistent with the animal literature, water diffusion anisotropy over the crus of the fimbria-fornix was strongly correlated with axonal membranes (cumulative membrane circumference) within the surgical specimen (approximately 15% of what was analyzed with DTI). The demonstration of a correlation between histology and human in vivo DTI, in combination with the observation that in vivo DTI accurately predicted white matter abnormalities in a human disease condition, provides strong validation of the application of DTI as a noninvasive marker of white matter pathology.
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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 | 0.000 |
| 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) | 0.000 | 0.000 |
Machine scores (provisional)
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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