Reversible myocardial perfusion defects in patients not suffering from obstructive epicardial coronary artery disease as assessed by coronary angiography
Bibliographic record
Abstract
In approximately 10-30% of patients presenting with angina complaints, normal or non-obstructive coronary arteries are found on angiography. In this review paper, available literature on the underlying pathophysiological substrate explaining these discrepancies is reviewed. Both histological studies as well as studies using intravascular ultrasound e.g. the PROSPECT trial, show that epicardial coronary vessel significant lumen stenosis may be delayed until a plaque occupies 40% of the internal elastic lamina area. Limited available data suggest that these angiographically undetectable plaques are associated with an abnormal vasodilation capacity of the coronary circulation and may results in reversible perfusion defects on myocardial perfusion imaging (MPI). Organic non-atherosclerotic causes of epicardial coronary artery disease such as anomalous coronary arteries that course between the aorta and pulmonary artery, myocardial bridging and coronary vasospasm may also contribute to MPI results suggesting the presence of ischemia in the presence of normal coronary arteries on coronary angiography. Additional causes of reversible perfusion defects on MPI in the presence of a normal coronary angiogram are intraventricular conduction disturbances. The existence of reversible perfusion defects in the anteroseptal region in most of the patients suffering from left bundle branch block (LBBB) on MPI following physical exercise as stressor is well documented. As the observed reduced septal uptake of both 201Tl and 99mTc-sestamibi/tetrofosmin in LBBB reflects coronary autoregulation in response to lower oxygen demands, not surprisingly, dipyridamole which uniformly exploits flow reserve, has proven more accurate for the diagnosis of coronary artery disease (CAD) in patients suffering from LBBB. Although patients with a permanent ventricular pacemaker have a similar conduction abnormality as patients presenting with a LBBB, most of the defects found on MPI imaging in this patient population (in up to 78% of patients with a normal coronary angiogram that area continuously paced) are localized in the inferoposterior (71%), apical (50%) and inferoseptal (28%) wall; coronary flow velocities in the left anterior descending (LAD) and dominant coronary artery and coronary flow reserve are also significantly lower when compared to a control group. Contrary to what is seen in LBBB patients, dipyridamole stress does not significantly reduce the incidence of abnormalities found but limits the defects to the inferior wall. Furthermore, the frequency of abnormalities found on MPI increases over time with right ventricular outflow tract pacing. Previous histologic studies have shown that microvessel disease is often accompanied by a slow-flow phenomenon reflecting decreased resting flow velocity. Thus, not surprisingly, MPI reversible abnormalities in the presence of a normal coronary angiogram have been reported in a wide variety of diseases characterized by microvessel disease such as diabetes, systemic lupus erythematosus, Behçet's disease and metabolic syndrome. In these patients, low adiponectin and high lipoprotein(a) levels are found which are known to be associated with endothelial dysfunction, atherosclerosis and coronary artery disease. Furthermore, in these patients, limited available data suggest that reversible perfusion defects on MPI confer a significantly poorer prognosis both in terms of hard event rate (MI and cardiac death) and total event rate (MI, cardiac death or late revascularization). It is thus suggested that MPI could discriminate patients with a more severe prognosis. Finally, physical training in patients with primary microvascular angina appears to be associated with reduction of myocardial perfusion abnormalities.
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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 | 0.001 |
| 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".