Ultrasound‐guided identification of cardiac imaging windows
Bibliographic record
Abstract
PURPOSE: Currently, the use of cine magnetic resonance imaging (MRI) to identify cardiac quiescent periods relative to the electrocardiogram (ECG) signal is insufficient for producing submillimeter-resolution coronary MR angiography (MRA) images. In this work, the authors perform a time series comparison between tissue Doppler echocardiograms of the interventricular septum (IVS) and concurrent biplane x-ray angiograms. Our results indicate very close agreement between the diastasis gating windows identified by both the IVS and x-ray techniques. METHODS: Seven cath lab patients undergoing diagnostic angiograms were simultaneously scanned during a breath hold by ultrasound and biplane x-ray for six to eight heartbeats. The heart rate of each patient was stable. Dye was injected into either the left or right-coronary vasculature. The IVS was imaged using color tissue Doppler in an apical four-chamber view. Diastasis was estimated on the IVS velocity curve. On the biplane angiograms, proximal, mid, and distal regions were identified on the coronary artery (CA). Frame by frame correlation was used to derive displacement, and then velocity, for each region. The quiescent periods for a CA and its subsegments were estimated based on velocity. Using Pearson's correlation coefficient and Bland-Altman analysis, the authors compared the start and end times of the diastasis windows as estimated from the IVS and CA velocities. The authors also estimated the vessel blur across the diastasis windows of multiple sequential heartbeats of each patient. RESULTS: In total, 17 heartbeats were analyzed. The range of heart rate observed across patients was 47-79 beats per minute (bpm) with a mean of 57 bpm. Significant correlations (R > 0.99; p < 0.01) were observed between the IVS and x-ray techniques for the identification of the start and end times of diastasis windows. The mean difference in the starting times between IVS and CA quiescent windows was -12.0 ms. The mean difference in end times between IVS and CA quiescent windows was -3.5 ms. In contrast, the correlation between RR interval and both the start and duration of the x-ray gating windows were relatively weaker: R = 0.63 (p = 0.13) and R = 0.86 (p = 0.01). For IVS gating windows, the average estimated vessel blurs during single and multiple heartbeats were 0.5 and 0.66 mm, respectively. For x-ray gating windows, the corresponding values were 0.26 and 0.44 mm, respectively. CONCLUSIONS: In this study, the authors showed that IVS velocity can be used to identify periods of diastasis for coronary arteries. Despite variability in mid-diastolic rest positions over multiple steady rate heartbeats, vessel blurring of 0.5-1 mm was found to be achievable using the IVS gating technique. The authors envision this leading to a new cardiac gating system that, compared with conventional ECG gating, provides better resolution and shorter scan times for coronary MRA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 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".