EP15.17: Fetal brain to liver volume ratio measured by <scp>MRI</scp> is a useful indicator of <scp>IUGR</scp><i>in vivo</i> in late gestation
Bibliographic record
Abstract
Fetal brain to liver weight ratio has been identified as a useful diagnostic tool of intrauterine growth restrictions (IUGR) in a study of stillborn babies and neonatal deaths [1]. We sought to investigate whether fetal brain to liver volume ratio (BLVR), measured by MRI, could be used as a potential indicator of IUGR in vivo in live fetuses. This study included 16 fetuses in the normal group and 15 fetuses in the IUGR group between 32 and 39 weeks gestation. Meeting ≥ 2 of the 4 criteria proposed by Zhu et al. were used to define IUGR [2]. MRI measurements of the fetal liver and body volumes were performed using high-resolution 3D SSFP breath-hold acquisitions and post-processed using Mimics. The mean whole body, liver and brain volumes, and mean BLVR of the two groups were compared using Student's t test. T2 relaxation times of the umbilical vein (UV) and descending aorta (DAo) were also obtained according to our previously published techniques [2]. The mean gestational ages were not significantly different in the two groups (35.9 weeks for normal and 35.3 weeks for IUGR) and were thereby controlled for. The IUGR group had a significantly lower mean liver volume (79mL vs 137mL, P < 0.001), and a lower mean brain volume (242mL vs 289mL, P < 0.01) compared to the normal group. There was a positive correlation between liver to body volume ratio, and UV and DAo T2 (Pearson, P < 0.05 for both UV T2 and DAo T2), indicating the effect of blood oxygen saturation on liver development. BLVR was significantly higher in the IUGR group than the normal group (3.43 vs 2.15, P < 0.001) and could therefore serve as a potential tool for diagnosing the condition in utero. BLVR is a useful indicator of IUGR in late gestation. Further investigation into its sensitivity and specificity for diagnosing IUGR, either alone or together with other predictors, is warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".