VP15.16: Fetal cardiac function evaluation with fetal a CMQ‐strain: feasibility and reproducibility
Bibliographic record
Abstract
Methods:The feasibility to acquire a 4D dataset of the aortic arch and to visualise fetal cardiac hemodynamics was evaluated in six fetuses (Gestation week 30 -35) and compared to a gated 2D cine phase contrast angiography sequence.Cardiac gating was performed using aMRI compatible Doppler ultrasound (DUS) device.The sequences were limited to 10 heart phases to minimise imaging time, resulting in a temporal resolution of 40ms and scan time of 2.30min.Morphologic images of the aorta and fetal heart were acquired using a retrospectively gated cine balanced steady-state free precession sequences.Visualisations and analysis were performed using Gyro Tools.Results: The aortic flow as well as flow in supra-aortic vessels could be clearly observed and their velocity could be measured applying the 4D flow measurement (figure 1).There was a partial blood turbulence in the atrium.This must be caused by the foramen ovale, which is the natural right-to-left atrial shunt.Quantitative measurements were well comparable between 4D and 2D phase contrast acquisitions for both the fetal phantom and for the human subjects.Fetal movement is a challenge due to long acquisition times and needs to be addressed in future studies.Conclusions: This preliminary study showed the possibility of visualisation and quantitative measurements of blood flow in-utero within the great fetal vessels with 4D phase contrast imaging utilizing the Doppler ultrasound gating method.The technique may be beneficial for visualisation and quantification of complex congenital cardiovascular malformations.
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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 | 0.006 | 0.006 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".