Structured analysis of the impact of fetal motion on phase-contrast MRI flow measurements with metric optimized gating
Bibliographic record
Abstract
The impact of fetal motion on phase contrast magnetic resonance imaging (PC-MRI) with metric optimized gating (MOG) remains unknown, despite being a known limitation to prenatal MRI. This study aims to describe the effect of motion on fetal flow-measurements using PC-MRI with MOG and to generate a scoring-system that could be used to predict motion-corrupted datasets at the time of acquisition. Ten adult volunteers underwent PC-MRI with MOG using a motion-device to simulate reproducible in-plane motion encountered in fetuses. PC-MRI data were acquired on ten fetuses. All ungated images were rated on their quality from 0 (no motion) to 2 (severe motion). There was no significant difference in measured flows with in-plane motion during the first and last third of sequence acquisition. Movement in the middle section of acquisition produced a significant difference while all referring ungated images were rated with a score of 2. Intra-Class-Correlation (ICC) for flow-measurements in adult and fetal datasets was lower for datasets with scores of 2. For fetal applications, the use of a simple three-point scoring system reliably identifies motion-corrupted sequences from unprocessed data at the time of acquisition, with a high score corresponding to significant underestimation of flow values and increased interobserver variability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".