Optimal Use of Vasodilators for Diagnosis of Microvascular Angina in the Cardiac Catheterization Laboratory. (June 2020)

• Record Type: Journal Article
• Authors: Rahman, Haseeb; Demir, Ozan M.; Ryan, Matthew; McConkey, Hannah; Scannell, Cian; Ellis, Howard; Webb, Andrew; Chiribiri, Amedeo; Perera, Divaka
• Is Part Of: Circulation. Volume 13:Number 6(2020)
• Publication Date: 2020-06
• Subjects: coronary circulation -- endothelium -- magnetic resonance imaging -- microvascular angina -- myocardial ischemia; Cardiovascular system -- Surgery -- Periodicals; Cardiovascular system -- Diseases -- Treatment -- Periodicals; 616.105
• DOI: 10.1161/CIRCINTERVENTIONS.120.009019
• Languages: English
• ISSNs: 1941-7640

Abstract

Abstract : Background: Among patients with angina and nonobstructive coronary artery disease, those with coronary microvascular dysfunction have a poor outcome. Coronary microvascular dysfunction is usually diagnosed by assessing flow reserve with an endothelium-independent vasodilator like adenosine, but the optimal diagnostic threshold is unclear. Furthermore, the incremental value of testing endothelial function has never been assessed before. We sought to determine what pharmacological thresholds correspond to exercise pathophysiology and myocardial ischemia in patients with coronary microvascular dysfunction. Methods: Patients with angina and nonobstructive coronary artery disease underwent simultaneous acquisition of coronary pressure and flow during rest, supine bicycle exercise, and pharmacological vasodilatation with adenosine and acetylcholine. Adenosine and acetylcholine coronary flow reserve were calculated as vasodilator/resting coronary blood flow (CFR and AchFR, respectively). Coronary wave intensity analysis was used to quantify the proportion of accelerating wave energy; a normal exercise response was defined as an increase in accelerating wave energy from rest to peak exercise. Ischemia was assessed by quantitative 3-Tesla stress perfusion cardiac magnetic resonance imaging and dichotomously defined by a hyperemic endo-epicardial gradient <1.0. Results: Ninety patients were enrolled (58±10 years, 77% female). Area under the curve using receiver-operating characteristic analysis demonstrated optimal CFR and AchFR thresholds for identifying exercise pathophysiology and ischemia as 2.6 and 1.5, with positive and negative predictive values of 91% and 86%, respectively. Fifty-eight percent had an abnormal CFR (of which 96% also had an abnormal AchFR). Of those with a normal CFR, 53% had an abnormal AchFR, and 47% had a normal AchFR; ischemia rates were 83%, 63%, and 14%, respectively. Conclusions: The optimal CFR and AchFR diagnostic thresholds are 2.6 and 1.5, with high-positive and negative predictive values, respectively. A normal CFR value should prompt the measurement of AchFR. A stepwise algorithm incorporating both vasodilators can accurately identify an ischemic cause in patients with nonobstructive coronary artery disease.