Volumetric Brain MRI Study in Fetuses with Intrauterine Growth Restriction Using a Semiautomated Method
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: According to the medical literature, it is known that intrauterine growth restriction is associated with abnormal fetal brain findings. The aim of this study was to assess the volume of fetal brain structures in fetuses with intrauterine growth restriction compared with the control group and to examine the effect of intrauterine growth restriction on birth weight in relation to the effect on the volumes of these structures. MATERIALS AND METHODS: This historical cohort study included 26 fetuses diagnosed with intrauterine growth restriction due to placental insufficiency. The control group included 66 fetuses with MR imaging scans demonstrating normal brain structures. The volumes of the supratentorial brain, left and right hemispheres, and the cerebellum were measured using a semiautomatic method. In addition, the cerebellum and supratentorial brain ratio was calculated. The measurements of each brain structure were then converted to percentiles according to growth curves. RESULTS: > .39). The difference in brain volume percentiles was statistically smaller than the difference in birth weight and birth weight percentiles (Dolberg growth curves) between the groups. CONCLUSIONS: Intrauterine growth restriction affects the volume of brain structures, as measured by quantitative MR imaging. Compared with healthy controls, the effect on birth weight was more prominent than the effect on brain structures, possibly due to the "brain-preserving" capability.
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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 | 0.001 | 0.002 |
| 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) | 0.000 | 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 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".