A comparison of altered white matter microstructure in youth born with congenital heart disease or born preterm
Bibliographic record
Abstract
Introduction Alterations to white matter microstructure as detected by diffusion tensor imaging have been documented in both individuals born with congenital heart disease (CHD) and individuals born preterm. However, it remains unclear if these disturbances are the consequence of similar underlying microstructural disruptions. This study used multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) and neurite orientation dispersion and density imaging (NODDI) to characterize and compare alterations to three specific microstructural elements of white matter – myelination, axon density, and axon orientation – in youth born with CHD or born preterm. Methods Participants aged 16 to 26 years with operated CHD or born ≤33 weeks gestational age and a group of healthy peers of the same age underwent a brain MRI including mcDESPOT and high angular resolution diffusion imaging acquisitions. Using tractometry, average values of myelin water fraction (MWF), neurite density index (NDI), and orientation dispersion index (ODI) were first calculated and compared between groups for 30 white matter bundles. Afterwards, bundle profiling was performed to further characterize the topology of the detected microstructural alterations. Results The CHD and preterm groups both presented with widespread bundles and bundle segments with lower MWF, accompanied by some occurrences of lower NDI, relative to controls. While there were no differences in ODI between the CHD and control groups, the preterm group presented with both higher and lower ODI compared to the control group and lower ODI compared to the CHD group. Discussion While youth born with CHD or born preterm both presented with apparent deficits in white matter myelination and axon density, youth born preterm presented with a unique profile of altered axonal organization. Future longitudinal studies should aim to better understand the emergence of these common and distinct microstructural alterations, which could orient the development of novel therapeutic approaches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".