Diffusion Tensor Imaging of Commissural and Projection White Matter in Tuberous Sclerosis Complex and Correlation with Tuber Load
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cortical and white matter changes have been identified outside the MR imaging-visible cortical/subcortical tubers in the tuberous sclerosis complex. The aim of this study was to evaluate DTI changes in the corpus callosum and internal capsules and to correlate the DTI changes with cortical/subcortical tuber load. MATERIALS AND METHODS: Twelve TSC patients and 23 controls underwent MR imaging including DTI. FA, trace, D( ||), and D() of genu and splenium of corpus callosum and right and left internal capsules were assessed. The number and volume of cortical/subcortical tubers were correlated with DTI indices of corpus callosum and internal capsules. RESULTS: In the genu and splenium, FA was lower and trace (P < .01) and D() were higher (P < .01), and in the internal capsules, trace was higher (P = .04) in TSC patients compared with controls. The total tuber volume correlated positively with trace of genu (r = 0.77, P < .01) and splenium (r = 0.69, P = .01) and with D() of splenium (r = 0.68, P = .01), and negatively with FA of splenium (r = -0.60, P = .04) of corpus callosum. The left and right hemispheric tuber volume correlated positively with trace of left (r = 0.56, P = .05) and right (r = 0.67, P = .02) internal capsules. CONCLUSIONS: Our findings of reduced FA, elevated trace, and elevated D() in the corpus callosum and internal capsules may be related to abnormalities in myelin. The correlations between tuber volume and DTI indices in corpus callosum and internal capsules suggested that more extensive malformation as demonstrated by larger tuber load was more likely to be associated with more severe DTI changes in the commissural and projection white matter.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".