Angiography-Derived Versus Coronary Guidewire-Derived Index of Microcirculatory Resistance in Patients With Ischemia With Nonobstructive Coronary Arteries

Abstract

Background: Coronary function testing (CFT) during invasive coronary angiography is guideline-recommended to identify coronary microvascular dysfunction (CMD) in patients with ischemia with nonobstructive coronary arteries (INOCA). Wire-free, angiography-derived index of microcirculatory resistance (IMR_angio) measurements have been developed to simplify assessment for CMD. We assessed the validity of IMR_angio compared with the conventional index of microcirculatory resistance (IMR) in a cohort of individuals with INOCA.

Methods: This single-center observational study prospectively enrolled adults aged >18 years who were referred for clinically indicated invasive coronary angiography for the evaluation of chest discomfort or an anginal equivalent and had no coronary artery lesions with ≥50% stenosis. Participants underwent invasive CFT using bolus thermodilution techniques to determine IMR and coronary flow reserve (CFR) in the left anterior descending artery. IMR_angio was calculated retrospectively, blinded to CFT results. CMD was defined by IMR ≥25 or CFR <2.5.

Results: Among 122 enrolled participants with INOCA (median age 62 years, 77% women), the median IMR in the left anterior descending artery was 20 (13-27), CFR was 3.95 (2.5-4.7), and 54 participants (44%) had CMD. IMR_angio did not correlate with IMR (r = 0.1; P = .14). Mean IMR_angio was not different among patients with and without IMR ≥25 (P = .21). IMR_angio ≥25 had a sensitivity of 44% and a specificity of 53% in identifying participants with CMD. In sensitivity analyses among participants with cineangiography at 10 to 15 frames per second (r = 0.37; P = .02) and limited to participants with both optimal angiographic view and frame rates ≥10 (r = 0.48; P = .03), we observed weak positive correlations between IMR_angio and IMR.

Conclusions: In patients with INOCA, correlations between IMR_angio and IMR were poor. IMR_angio appears unreliable for identifying CMD in patients with INOCA.

Keywords: coronary function testing; coronary microvascular dysfunction; diagnostics; ischemia with nonobstructive coronary arteries; microcirculation.

Figure 1

Frequency distributions index of microcirculatory resistance (IMR) in all participants. (A) Wire-based index of microcirculatory resistance (IMR) and (B) angiography-derived IMR (IMR_angio).

Central Illustration

In a real-world cohort of 122 patients with ischemia and nonobstructive coronary arteries, there was no correlation between wire-based index of microcirculatory resistance (IMR) and angiography-derived IMR (IMR_angio) (r = 0.10; P = .14). AUC, area under the receiver operating characteristic curve; QFR, quantitative flow ratio.

Figure 2

Diagnostic accuracy of angiography-derived index of microcirculatory resistance (IMR_angio) to predict the index of microcirculatory resistance (IMR). (A) Diagnostic accuracy in all participants (sensitivity = 51%, specificity = 56%). (B) Diagnostic accuracy in participants with optimal views (sensitivity = 62%, specificity = 51%). (C) Diagnostic accuracy in participants with frame rates of 10 or 15 frames per second (C) (sensitivity = 71%, specificity = 50%). (D) Diagnostic accuracy in participants with optimal views and frame rates ≥10 frames per second (sensitivity = 64%, specificity = 30%).

Figure 3

Receiver operating characteristic (ROC) curves for angiography-derived index of microcirculatory resistance (IMR_angio) to estimate abnormal index of microcirculatory resistance (IMR). (A) ROC curve for all participants (area under the ROC curve [AUC] = 0.57, P = .21) with an optimal dichotomous index of IMR_angio = 21.9 (sensitivity = 73%, specificity = 44%). (B) ROC curve for participants with optimal views (AUC = 0.63, P = .1) with an optimal dichotomous index of IMR_angio = 21.9 (sensitivity = 90%, specificity = 37%). (C) ROC curve in participants with frame rates of 15 or 10 frames per second (AUC = 0.66, P = .13) with an optimal dichotomous index of IMR_angio = 21.4 (sensitivity = 93%, specificity = 50%). (D) ROC curve in participants with both optimal views and frame rates ≥10 frames per second (AUC = 0.56, P = .62) with an optimal dichotomous index of IMR_angio = 19.8 (sensitivity = 91%, specificity = 30%).

Figure 4

Comparison of angiography-derived index of microcirculatory resistance (IMR_angio) in participants with normal and abnormal index of microcirculatory resistance (IMR). (A) Analysis of all participants demonstrating a median IMR_angio of 23.65 (n = 85) in participants with normal IMR and a median IMR_angio of 25.52 (n = 37) in participants with abnormal IMR (P = .21). (B) Analysis of only participants with optimal views demonstrating a median IMR_angio of 24.44 (n = 43) in participants with normal IMR and a median IMR_angio of 26.12 (n = 21) in participants with abnormal IMR (P = .1). (C) Analysis of participants with frame rates of 10 or 15 frames per second demonstrating a mean IMR_angio of 24.24 (n = 18) in participants with normal IMR and a mean IMR_angio of 31.41 (n = 14) in participants with abnormal IMR (P = .04). (D) Analysis of participants with both optimal views and frame rates ≥10 frames per second demonstrating a median IMR_angio of 27.1 (n = 10) in participants with normal IMR and a mean IMR_angio of 27.9 (n = 11) in participants with abnormal IMR (P = .39).

Figure 5

Comparison of angiography-derived index of microcirculatory resistance (IMR_angio) in participants with and without coronary microvascular dysfunction (CMD). Analysis demonstrating a median IMR_angio of 24.4 (n = 68) in patients without CMD and a median IMR_angio of 24.1 (n = 54) in patients with CMD (P = .31)

Figure 6

Receiver operating characteristic curves for angiography-derived index of microcirculatory resistance to estimate coronary microvascular dysfunction defined by abnormal index of microcirculatory resistance or abnormal coronary flow reserve. Area under the receiver operating characteristic curve = 0.53, P = .63.

Figure 7

Correlations between wire-based index of microcirculatory resistance (IMR) and angiography-derived IMR (IMR_angio). (A) In participants with optimal views (r = 0.17; P = .1); (B) in participants with frame rates of 10 or 15 frames per second (r = 0.37; P = .02); and (C) in participants with both optimal views and frame rates ≥10 frames per second (r = 0.48; P = .03).

Figure 8

Bland-Altman plot representing the difference between the index of microcirculatory resistance (IMR) and angiography-derived IMR (IMR_angio) vs the mean of IMR and IMR_angio. Mean difference, 5.1.