Non-invasive imaging of myocardial bridge by coronary computed tomography angiography: the value of transluminal attenuation gradient to predict significant dynamic compression. Eur Radiol. 2017;27:1971-1979. [PMID: 27565800 DOI: 10.1007/s00330-016-4544-7]

CT Fractional Flow Reserve for the Diagnosis of Myocardial Bridging-Related Ischemia: A Study Using Dynamic CT Myocardial Perfusion Imaging as a Reference Standard

Objective

To investigate the diagnostic performance of CT fractional flow reserve (CT-FFR) for myocardial bridging-related ischemia using dynamic CT myocardial perfusion imaging (CT-MPI) as a reference standard.

Materials and Methods

Dynamic CT-MPI and coronary CT angiography (CCTA) data obtained from 498 symptomatic patients were retrospectively reviewed. Seventy-five patients (mean age ± standard deviation, 62.7 ± 13.2 years; 48 males) who showed myocardial bridging in the left anterior descending artery without concomitant obstructive stenosis on the imaging were included. The change in CT-FFR across myocardial bridging (ΔCT-FFR, defined as the difference in CT-FFR values between the proximal and distal ends of the myocardial bridging) in different cardiac phases, as well as other anatomical parameters, were measured to evaluate their performance for diagnosing myocardial bridging-related myocardial ischemia using dynamic CT-MPI as the reference standard (myocardial blood flow < 100 mL/100 mL/min or myocardial blood flow ratio ≤ 0.8).

Results

ΔCT-FFR_systolic (ΔCT-FFR calculated in the best systolic phase) was higher in patients with vs. without myocardial bridging-related myocardial ischemia (median [interquartile range], 0.12 [0.08–0.17] vs. 0.04 [0.01–0.07], p < 0.001), while CT-FFR_systolic (CT-FFR distal to the myocardial bridging calculated in the best systolic phase) was lower (0.85 [0.81–0.89] vs. 0.91 [0.88–0.96], p = 0.043). In contrast, ΔCT-FFR_diastolic (ΔCT-FFR calculated in the best diastolic phase) and CT-FFR_diastolic (CT-FFR distal to the myocardial bridging calculated in the best diastolic phase) did not differ significantly. Receiver operating characteristic curve analysis showed that ΔCT-FFR_systolic had largest area under the curve (0.822; 95% confidence interval, 0.717–0.901) for identifying myocardial bridging-related ischemia. ΔCT-FFR_systolic had the highest sensitivity (91.7%) and negative predictive value (NPV) (97.8%). ΔCT-FFR_diastolic had the highest specificity (85.7%) for diagnosing myocardial bridging-related ischemia. The positive predictive values of all CT-related parameters were low.

Conclusion

ΔCT-FFR_systolic reliably excluded myocardial bridging-related ischemia with high sensitivity and NPV. Myocardial bridging showing positive CT-FFR results requires further evaluation.

Myocardial bridges: A meta-analysis

Myocardial bridges are anatomical entities characterized by myocardium covering segments of coronary arteries. In some patients, the presence of a myocardial bridge is benign and is only incidentally found on autopsy. In other patients, however, myocardial bridges can lead to compression of the coronary artery during systolic contraction and delayed diastolic relaxation, resulting in myocardial ischemia. This ischemia in turn can lead to myocardial infarction, ventricular arrhythmias and sudden cardiac death. Myocardial bridges have also been linked to an increased incidence of atherosclerosis, which has been attributed to increased shear stress and the presence of vasoactive factors. Other studies however, demonstrated the protective roles of myocardial bridges. In this study, using systematic review and a meta-analytical approach we investigate the prevalence and morphology of myocardial bridges in both clinical imaging and cadaveric dissections. We also discuss the pathophysiology, clinical significance, and management of these anatomical entities.

Myocardial bridge-related coronary heart disease: Independent influencing factors and their predicting value

BACKGROUND

Myocardial bridge (MB) will compress the mural coronary artery (MCA) during the systole and cause myocardial ischemia. In the diagnosis of coronary heart disease (CHD), because the structure of MB is difficult to be observed by coronary angiography (CAG), the clinical study of the influence of MB on CHD is lacking. With the advancement of computed tomography coronary angiography technology, detailed observations of the MB anatomy have realized.

AIM

To explore the main influencing factors of MB-related CHD and to find potential indicators for predicting MB-related CHD.

METHODS

A total of 1718 patients with suspected CHD due to the symptoms of myocardial ischemia were enrolled as subjects. Patients diagnosed with CHD were included in a CHD group, and patients with no significant abnormalities were included in a control group. In the CHD group, patients were divided into an MB-CHD subgroup if MB-related CHD was found. In the control group, patients were divided into a simple MB subgroup if MB was found. The patient's clinical data and MB-related indicators, including the branch of MB, MB type (superficial/deep type), MB length, MB thickness, systolic and diastolic compression of the MCA, and MCA systolic stenosis rate were recorded and compared. Logistic regression analysis was used to explore the independent influencing factors of MD-related CHD. ROC curve was used to analyze the diagnostic efficacy of potential indicators for MB-related CHD.

RESULTS

There were 1060 cases in the CHD group and 658 cases in the control group, and there were 236 cases in the MB-CHD subgroup and 52 cases in the simple MB subgroup. Multivariate logistic regression analysis showed that the combined MB had a significant effect on the occurrence of CHD (P < 0.05). MB thickness, systolic compression, diastolic compression, and MCA systolic stenosis rate had significant effects on the occurrence of MB-related CHD (P < 0.05). The area under the curve (AUC) of the combination of these influencing factors for the diagnosis of MB-related CHD was 0.959, which was significantly higher than the AUCs of the four indicators separately (P < 0.05). The sensitivity was 97.06% and the specificity was 87.63%.

CONCLUSION

MB thickness, systolic compression, diastolic compression, and MCA systolic stenosis are independent influencing factors for MB-related CHD. The combination of these factors has potential diagnostic value for MB-related CHD.