Abstract 16882: Comparison of Regadenoson and Adenosine in First Pass Quantitative Perfusion Cardiovascular Magnetic Resonance in Subjects With Suspected Coronary Microvascular Disease
Bibliographic record
Abstract
Introduction: Regadenoson and adenosine are commonly used vasodilators in myocardial perfusion imaging for detection of coronary artery disease. There are no comparative studies of the vasodilator properties of two agents in subjects with suspected coronary microvascular disease (CMD). We aimed to compare the potency of two vasodilators by quantifying myocardial perfusion in subjects with suspected CMD. Methods: Subjects with angina and more than two risk factors for CMD (females, or males with diabetes, metabolic syndrome, HTN, hyperlipidemia, and smoking) who had no obstructive coronary disease by invasive coronary angiography or CT angiography were enrolled for first-pass perfusion images using dual sequence. Stress perfusion images were acquired on 1.5T or 3.0T GE Healthcare during adenosine infusion or regadenoson. Rest perfusion images were acquired either 10 minutes following the cessation of adenosine or reversal with aminophylline. Myocardial blood flow (MBF) in ml/min/g and myocardial perfusion reserve (MPR) were quantified using Fermi deconvolution. Results: A total of thirty-two subjects were recruited with a mean age of 62±11 years, 53% men, history of hypertension in 91%, diabetes in 72%, hyperlipidemia in 75%, and tobacco use in 16%. Twenty (63%) of subjects underwent adenosine, while twelve (38%) of subjects underwent regadenoson. Regadenoson produced similar stress MBF compared to adenosine (2.30 ± 0.54 vs. 2.35 ± 0.61 ml/min/g, p = 0.66). Rest MBF was higher in the regadenoson group compared to adenosine group (1.35±0.35 vs. 1.12±0.26 ml/min/g, p=0.07). MPR was non-significantly lower in regadenoson compared to adenosine 1.72±0.70 vs.1.89±0.53 ml/g/min, p=0.13). Conclusions: Based on fully quantitative perfusion using CMR, regadenoson and adenosine have similar vasodilator efficacy in subjects with risk factors for CMD. However, resting blood flows are slightly higher when regadenoson is used which may impact quantification of MPR.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".