Changes in myocardial perfusion after coronary sinus reducer implantation for refractory angina - assessment using fully automated quantitative stress perfusion cardiac MRI
Bibliographic record
Abstract
Abstract Introduction Previous reports show angina improvement after Coronary Sinus Reducer (CSR) implantation [1,2]. However, the mechanistic basis remains unconfirmed. Preliminary studies using semi-quantitative metrics derived from stress perfusion cardiac MRI (CMR), have suggested improved myocardial perfusion particularly in ischaemic segments [3]. To date, assessment by fully automated quantitative myocardial perfusion CMR has not been reported. Purpose To assess the effect of CSR implantation on quantitative regional myocardial blood flow in patients with refractory angina and advanced coronary artery disease (CAD). Methods Prospective cohort study of patients undergoing CSR implantation. CMR was performed at baseline and median 7 months follow-up. Automated segmentation into a 16-segment American Heart Association model was performed to quantify segmental rest and stress myocardial blood flow (MBF, ml/min/g) and myocardial perfusion reserve (MPR). Rest MBF was corrected for heart rate by dividing by the scan heart rate and multiplying by the mean resting heart rate among all subjects. Wilcoxon matched-pairs sign rank tests were used to compare paired global and segmental perfusion values. A linear mixed-effects model with random slopes and intercepts was used to assess the relationship between baseline segmental MPR and associated change in MPR (ΔMPR) after CSR implantation. Results 12 patients (10M:2F; mean age 67) were included. Median Canadian Cardiovascular Society class was 3. Globally, there was no change in rest (P=0.90), stress MBF (P=0.34) or MPR (P=0.72) from baseline to follow-up. However, ΔMPR was related to the degree of baseline ischaemia (panel A). Segments with baseline MPR<2.45 increased in MPR whereas segments with baseline MPR ≥2.45 experienced a decrease (P=0.003, conditional R2: 0.81). In segments with MPR<2.45 (n=138), median ΔMPR was +0.18 (15.4%; P<0.0001); whereas with MPR≥2.45 (n=52) it was -0.41 (-12.7%; P=0.03; panel B). When assessed by myocardial layer, significant increases in MPR were observed in both subendocardial (+0.19 [15.6%]; P<0.0001) and subepicardial (+0.19 [12.3%]; P<0.0002) segments with baseline MPR< 2.45 (panel C). Conversely, in segments with baseline MPR≥2.45, there was a significant reduction in MPR in the subendocardium (-0.43 [-15.9%]; P=0.04) but not in the subepicardium (-0.36 [-9.90%]; P=0.08; panel D). Conclusion To our knowledge, this is the first study showing changes in quantitative myocardial perfusion after CSR implantation by fully automated inline quantitative perfusion CMR. Our analysis shows a relationship between baseline MPR and change in MPR after CSR implantation, supporting redistribution of perfusion into both subendocardial and subepicardial layers as potential mechanisms of action of CSR. Further studies are needed to confirm these preliminary results.
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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 | 0.000 | 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".