Technique for comprehensive fetal hepatic blood flow assessment in sheep using 4D flow MRI
Bibliographic record
Abstract
Key points The comprehensive visualization and quantification of in vivo fetal hepatic haemodynamics, particularly the shunting of ductus venosus blood, has been elusive and is not yet fully understood. We introduce the combination of chronically instrumented fetal sheep and 4D flow MRI of the whole fetal liver, which allows retrospective blood flow measurement in all visible vessels as well as qualitative assessment. The applicability and usefulness of this technique is exhibited in normally grown fetal Merino sheep in mid‐ and late‐gestation with detailed dynamic distribution of hepatic blood flow presented. The feasibility of this approach in clinical pathology is demonstrated in two growth‐restricted fetuses at mid‐gestation. Further exemplification of blood flow quantification is performed over major hepatic vessels. Abstract Although the fetal vasculature has been demarcated and well understood for several decades, the corresponding haemodynamics permitting oxygen‐ and nutrient‐rich blood delivery to the fetal organs has been comparatively difficult to study. We married two well‐established methods: 4D flow MRI, a volumetric and dynamic blood‐flow measurement technique, and chronically instrumented sheep to broadly assess fetal hepatic circulation. We performed this technique in mid‐ and late‐gestation fetal Merino sheep under normoxemic conditions and major hepatic vasculature was segmented to quantify blood flow and related parameters. Dynamic blood flow was visualized, exhibiting an acceleration of umbilical vein blood through the ductus venosus as well as spiralling into the inferior vena cava where its stream remained separate from that of the hepatic veins and lower body. Ductus venosus changes from mid‐ to late‐gestation included larger diameter (mid: 5.8 ± 0.9 vs. late: 7.1 ± 1.1 mm; P = 0.003) and cross‐sectional area (mid: 27.1 ± 8.6 vs. late: 40.4 ± 11.8 mm2; P = 0.003), and lower velocity averaged over the cardiac cycle (mid: 15.7 ± 5.4 vs. late: 9.8 ± 7.0 cm s‐1; P = 0.020). This resulted in higher magnitude blood flow (indexed to umbilical vein input) at mid‐gestation in the ductus venosus (mid: 0.73 ± 0.21; late: 0.46 ± 0.21; P = 0.008). The visualization and quantification results support the further use of this technique to better understand regional blood flow changes during normal or abnormal fetal growth, as well as to observe acute haemodynamic responses to physiological challenges or drug interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".