Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction
Bibliographic record
Abstract
Oxygenation-sensitive cardiac magnetic resonance imaging (OS-CMR) is a diagnostic technique that uses the inherent paramagnetic properties of deoxyhemoglobin as an endogenous source of tissue contrast. Used in combination with standardized vasoactive breathing maneuvers (hyperventilation and apnea) as a potent non-pharmacologic vasomotor stimulus, OS-CMR can monitor changes in myocardial oxygenation. Quantifying such changes during the cardiac cycle and throughout vasoactive maneuvers can provide markers for coronary macro- and microvascular function and thereby circumvent the need for any extrinsic, intravenous contrast or pharmacologic stress agents. OS-CMR uses the well-known sensitivity of T2*-weighted images to blood oxygenation. Oxygenation-sensitive images can be acquired on any cardiac MRI scanner using a modified standard clinical steady-state free precession (SSFP) cine sequence, making this technique vendor-agnostic and easily implemented. As a vasoactive breathing maneuver, we apply a 4 min breathing protocol of 120 s of free breathing, 60 s of paced hyperventilation, followed by an expiratory breath-hold of at least 30 s. The regional and global response of myocardial tissue oxygenation to this maneuver can be assessed by tracking the signal intensity change. The change over the initial 30 s of the post-hyperventilation breath-hold, referred to as the breathing-induced myocardial oxygenation reserve (B-MORE) has been studied in healthy people and various pathologies. A detailed protocol for performing oxygen-sensitive CMR scans with vasoactive maneuvers is provided. As demonstrated in patients with microvascular dysfunction in yet incompletely understood conditions, such as inducible ischemia with no obstructive coronary artery stenosis (INOCA), heart failure with preserved ejection fraction (HFpEF), or microvascular dysfunction after heart transplantation, this approach provides unique, clinically important, and complementary information on coronary vascular function.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".