OC21.08: Pilot study: utilising MRI to measure cardiac function in the sheep fetus
Bibliographic record
Abstract
We assessed the feasibility of fetal sheep cardiac magnetic resonance (CMR) measurements of ventricular volume for chamber sizes and cardiac output against gold standard cine phase-contrast (PC) measurements made in the ascending aorta (AAo) and main pulmonary artery (MPA). 5 ewes with singleton pregnancies underwent surgery at 112-120d (term = 150d) to catheterise the fetal femoral artery. At 139-140d, ewes were anesthetised to undergo fetal CMR using the femoral arterial pressure waveform for cardiac gating. Short-axis cine imaging of the fetal hearts was acquired and the right (RV) and left (LV) ventricles were segmented to measure ejection fraction (EF), stroke volume (SV), right and left ventricular output (CO) and combined ventricular output (CVO). LV-CO and RV-CO were also measured by cine PC acquisitions of AAo and MPA flow respectively. All cardiac measurements were indexed to fetal weight. The ventricular output by ventricular volumetry and PC were compared by linear regression and Bland-Altman analysis. Our results are in keeping with previously reported microsphere measurements and we found good agreement between LV-CO and RV-CO by ventricular volumetry versus PC but with underestimation of output of approximately 10% by ventricular volumetry, which we attributed to incomplete coverage of the entire ventricular volume (figure 1). This data suggests that following appropriate modification of the field of view, this technique represents a valid approach to assessing cardiac function, chamber sizes, and cardiac output in the fetal sheep. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".