Quantifying Myelin Water Fraction in a Guinea Pig Model of Spontaneous Intrauterine Growth Restriction
Bibliographic record
Abstract
ABSTRACT Intrauterine growth restriction (IUGR) is an obstetrical outcome where a fetus has not achieved its genetic potential. A consequence of IUGR is a decrease in brain myelin content. Myelin water imaging (MWI) has previously assessed fetal myelin water fraction (MWF) and can potentially assess myelination changes associated with IUGR. Thus, this study aims to quantify and compare the MWF of non-IUGR and IUGR fetal guinea pigs (GPs) in late gestation. Our sample consisted of 22 pregnant Dunkin-Hartley GPs with 71 fetuses (34 male) [mean ± standard deviation: 60 ± 1.2 days gestation]. Eight SPGR volumes [flip angles (α): 2° – 16°], and two sets of 8 bSSFP volumes (α: 8° – 64°), at 0° and 180° phase increments were acquired at 3.0 T. MWF maps were generated for each fetal GP brain using multicomponent driven equilibrium single pulse observation of T 1 /T 2 (mcDESPOT). Regions of interest (ROIs) were placed in the fetal corpus callosum (CC), fornix (FOR), and parasagittal white matter (PSW). Linear regression was performed between five fetal IUGR markers [body volume (BV), body-to-pregnancy volume ratio (BPrVR), brain-to-liver VR (BLVR), brain-to-placenta VR (BPlVR), and brain-to-BVR (BBVR)] and MWF for all regions (coefficient of determination, R 2 ). A t-test with a linear mixed model compared the MWF of non-IUGR and IUGR fetal GPs for all three regions (α = 0.05). The MWF values are as follows: (mean ± standard deviation): 0.23 ± 0.02 (fetal CC), 0.19 ± 0.02 (fetal CC – IUGR), 0.31 ± 0.02 (fetal FOR), 0.27 ± 0.01 (fetal FOR – IUGR), 0.28 ± 0.02 (fetal PSW), and 0.24 ± 0.03 (fetal PSW – IUGR). Significant differences in MWF were found between the non-IUGR and IUGR fetuses in every region. In conclusion, the mean MWF of IUGR fetal GPs is significantly lower than non-IUGR fetal GPs.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".