Evaluation of Subcortical White Matter and Deep White Matter Tracts in Malformations of Cortical Development
Bibliographic record
Abstract
AIMS: Abnormal cortical development will lead to abnormal axons in white matter. The purpose was to investigate (1) the microstructural changes in subcortical white matter adjacent to malformations of cortical development (MCD) and (2) the deep white matter tracts using diffusion tensor imaging (DTI). METHODS: Thirteen children with a variety of MCD were recruited. The fractional anisotropy (FA), trace, and eigenvalues (lambdamajor, lambdamedium, lambdaminor) of subcortical white matter of MCD were compared with contralateral normal side. The deep white matter tracts were graded based on the size, color hues and displacement of the tracts as visualized on color vector maps and tractography; grade 1 was normal tract size and color hue, grade 2 was reduced tract size but preserved color hue and grade 3 was loss of color hue or failure of tracking on tractography. RESULTS: The subcortical white matter adjacent to abnormal cortex demonstrated reduced FA (p < 0.05) and tendency to increase trace (p = 0.06). There was a significant elevation in lambdamedium and lambdaminor (p < 0.05), but no significant change in lambdamajor (p > 0.05). Twelve cases demonstrated alteration in white matter tracts. Seven cases of focal cortical dysplasia and two cases of transmantle MCD demonstrated grade 3 pattern of white matter tract. CONCLUSION: Reduced FA is a sensitive but nonspecific marker of alteration in microstructure of white matter. The elevated lambdamedium and lambdaminor may reflect a dominant effect of abnormal myelin. Alteration in white matter tracts was observed in most cases of MCD.
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How this classification was reachedexpand
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 | 0.001 | 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)
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 teacher head, 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".