Reduced gyrification in fetal growth restriction with prenatal magnetic resonance images
Bibliographic record
Abstract
Placental-related fetal growth restriction, resulting from placental dysfunction, impacts 3-5% of pregnancies and is linked to elevated risk of adverse neurodevelopmental outcomes. In response, the fetus employs a mechanism known as brain-sparing, redirecting blood flow to the cerebral circuit, for adequate supply to the brain. In this study we aimed to quantitatively evaluate disparities in gyrification and brain volumes among fetal growth restriction, small for gestational age and appropriate-for gestational-age fetuses. Additionally, we compared fetal growth restriction fetuses with and without brain-sparing. The study encompassed 106 fetuses: 35 fetal growth restriction (14 with and 21 without brain-sparing), 8 small for gestational age, and 63 appropriate for gestational age. Gyrification, supratentorial, and infratentorial brain volumes were automatically computed from T2-weighted magnetic resonance images, following semi-automatic brain segmentation. Fetal growth restriction fetuses exhibited significantly reduced gyrification and brain volumes compared to appropriate for gestational age (P < 0.001). Small for gestational age fetuses displayed significantly reduced gyrification (P = 0.038) and smaller supratentorial volume (P < 0.001) compared to appropriate for gestational age. Moreover, fetal growth restriction fetuses with BS demonstrated reduced gyrification compared to those without BS (P = 0.04), with no significant differences observed in brain volumes. These findings demonstrate that brain development is affected in fetuses with fetal growth restriction, more severely than in small for gestational age, and support the concept that vasodilatation of the fetal middle cerebral artery reflects more severe hypoxemia, affecting brain development.
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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 | 0.002 | 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".