Improving coronary ultrafast Doppler angiography using fractional moving blood volume and motion-adaptive ensemble length
Bibliographic record
Abstract
Abstract Coronary microperfusion assessment is a key parameter for understanding cardiac function. Currently, coronary ultrafast Doppler angiography is the only non-invasive clinical imaging technique able to assess coronary microcirculation quantitatively in humans. In this study, we propose to use fractional moving blood volume (FMBV), proportional to the red blood cell concentration, as a metric for perfusion. FMBV compares the power Doppler in a region of interest (ROI) inside the myocardium to the power Doppler of a reference area in the heart chamber, fully filled with blood. This normalization gives then relative values of the ROI blood filling. However, due to the impact of ultrasound attenuation and elevation focus on power Doppler values, the reference area and the ROI need to be at the same depth to allow this normalization. This condition is rarely satisfied in vivo due to the cardiac anatomy. Hereby, we propose to locally compensate the attenuation between the ROI and the reference, by measuring the attenuation law on a phantom. We quantified the efficiency of this approach by comparing FMBV with and without compensation on a flow phantom. Compensated FMBV was able to estimate the ground-truth FMBV with less than 5% variation. This method was then adapted to the in vivo case of myocardial perfusion imaging during heart surgery on human neonates. The translation from in vitro to in vivo required an additional clutter filtering step to ensure that blood signals could be correctly identified in the fast-moving myocardium. We applied the singular value decomposition filter on temporal sliding windows whose lengths were a function of myocardium motion. This motion-adaptive temporal sliding window approach was able to improve blood and tissue separation in terms of contrast-to-noise ratio, as compared to well-established constant-length sliding window approaches. Therefore, compensated FMBV and singular value decomposition assisted with motion-adaptive temporal sliding windows improves the quantification of blood volume in coronary ultrafast Doppler angiography.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".