The reproducibility of breathing maneuvers as a vasoactive stimulus in the heart: an oxygenation-sensitive resonance imaging study
Bibliographic record
Abstract
BACKGROUND: Endothelial dysfunction and impaired oxygenation of the heart is a hallmark of several diseases, including coronary artery disease, hypertension, diabetes, and sleep apnea. Recent studies indicate that oxygenation-sensitive cardiovascular magnetic resonance (OS-CMR) imaging combined with breathing maneuvers may allow for assessing coronary vascular responsiveness as a marker for coronary vascular function in various clinical settings. However, despite the use of OS-CMR in evaluating tissue oxygenation, the reproducibility of these standardized, combined breathing maneuvers as a vasoactive stimulus has yet to be systematically assessed or validated. In this study, we aimed to assess the reproducibility of vasoactive breathing maneuvers to assess vascular function in a population of healthy volunteers. METHODS: Eighteen healthy volunteers were recruited for the study. Inclusion criteria were an age over 18 years and absence of any evidence or knowledge of cardiovascular, neurological, or pulmonary disease. MRI was performed on a clinical 3 T MRI system (MAGNETOM Skyra, Siemens Healthineers, Erlangen, Germany). The OS-CMR acquisition was performed as previously described (1 min hyperventilation followed by a maximal, voluntary breath-hold). Standard statistical tests were performed as appropriate. RESULTS: , with an average heart rate of 72 ± 11 beats per minute, and ten of whom (56%) were female. There were no significant differences between global myocardial oxygenation (%[Formula: see text] SI) after hyperventilation (HV1: - 7.82 [Formula: see text] 5.2; HV2: - 7.89 [Formula: see text] 6.4, p = 0.9) or breath-hold (BH1: 5.34 [Formula: see text] 3.1; BH2: 6.0 [Formula: see text] 3.3, p = 0.5) between the repeated breathing maneuvers. The Bland-Altman analysis showed good agreement (bias: 0.074, SD of bias: 2.93). CONCLUSION: We conclude that in healthy individuals, the myocardial oxygenation response to a standardized breathing maneuver with hyperventilation and a voluntary breath-hold is consistent and highly reproducible. These results corroborate previous evidence for breathing-enhanced OS-CMR as a robust test for coronary vascular function.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".