Trends in Term-Equivalent Age Brain Volumes in Infants Born Across the Gestational Age Spectrum
Bibliographic record
Abstract
Purpose: Our understanding of the influence of preterm birth and related perinatal exposures on early brain development is limited, hampering personalized optimization of neuroprotective strategies. This study assesses the effect of gestational age (GA) at birth on brain volumes at term-equivalent age (TEA) in infants without overt brain injury born across the GA spectrum. Methods: A cohort of infants born across the GA spectrum (25–40 weeks’ gestation) underwent 3T brain MRI around TEA (40–46 weeks postmenstrual age). Eight brain regions, intracranial and total tissue volumes were segmented using MANTiS (morphologically adaptive neonatal tissue segmentation toolbox). Segmentations were visually quality-checked and excluded if segmentation failed. Absolute TEA volume in relation to GA was assessed using univariate and multivariate (correction for postmenstrual age) linear regression analysis. Statistical significance was set at p < 0.05. Post hoc scatter plots of brain volumes relative to intracranial volumes were created. Results: Fifty infants were included (mean GA = 35.0 [SD = 3.3, range = 25.7–40.1] weeks). A higher GA at birth was significantly related to lower cerebrospinal fluid (p = 0.004) and amygdala (p = 0.02) volumes; no significant relation was found between GA and other volumes. Post hoc analyses showed positive trends between GA and several brain structures, including total brain tissue, cortical gray matter, deep gray matter, hippocampus, cerebellum and brainstem volumes. Conclusions: Our results suggest that GA has an effect on TEA brain volumes that is independent of brain lesions, with lower GA being associated with smaller brain tissue volumes and significantly larger cerebrospinal fluid volume. Preterm birth and related exposures may thus affect early brain growth and contribute to neurodevelopmental challenges encountered by preterm-born children.
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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) | 0.000 | 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".