Diffusion Tensor Imaging of White Matter in Children Born from Preeclamptic Gestations
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Individuals born from pregnancies complicated by preeclampsia have an elevated risk for cognitive impairment. Deviations in maternal plasma angiokines occur for prolonged intervals before clinical signs of preeclampsia. We hypothesized that fetal brain vascular and nervous tissue development become deviated during maternal progression toward preeclampsia and that such deviations would be detectable by MR imaging. MATERIALS AND METHODS: In this pilot study, 10 matched (gestational and current ages) pairs (5 boys/5 girls, 7-10 years of age) from preeclampsia or control pregnancies were examined by using diffusion tensor MR imaging. An unbiased voxel-based analysis was conducted on fractional anisotropy and mean diffusivity parametric maps. Six brain ROIs were identified for subsequent analysis by tractography (middle occipital gyrus, caudate nucleus and precuneus, cerebellum, superior longitudinal fasciculus, and cingulate gyrus). RESULTS: Statistical differences were present between groups for fractional anisotropy in the caudate nucleus (offspring from preeclamptic gestation > controls), volume of the tract for the superior longitudinal fasciculus (offspring from preeclamptic gestation > controls) and the caudate nucleus (offspring from preeclamptic gestation > controls), and for parallel diffusivity of the cingulate gyrus (offspring from preeclamptic gestation > controls). CONCLUSIONS: These novel preliminary results along with previous results from the same children that identified altered cerebral vessel calibers and increased regional brain volumes justify fully powered MR imaging studies to address the impact of preeclampsia on human fetal brain development.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".