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The relationship between CTA performances and cardiac function indicators in myocardial bridge and mural coronary
Fuzhen Guo1, Junfen Yan2, Xiubin Xue3
1Department of Emergency, The First Hospital of Zhangjiakou Zhangjiakou 075000, Hebei, China.
Insights
Cardiac function indicators correlate with myocardial bridge and mural coronary artery (MB-MCA) severity. Combining indicators like cardiac output (CO) and left ventricular ejection fraction (LVEF) effectively predicts MB-MCA.
Area of Science:
- Cardiovascular Imaging and Diagnostics
- Interventional Cardiology
- Cardiac Physiology
Background:
- Myocardial bridge and mural coronary artery (MB-MCA) can affect coronary blood flow.
- Understanding the relationship between MB-MCA characteristics and cardiac function is crucial for patient management.
- Computed tomography angiography (CTA) is a key imaging modality for diagnosing MB-MCA.
Purpose of the Study:
- To investigate the correlation between CTA findings in MB-MCA patients and their cardiac function indicators.
- To evaluate the predictive performance of cardiac function indicators for MB-MCA severity.
Main Methods:
- Retrospective analysis of 60 MB-MCA patients who underwent CTA.
- Patients were grouped based on CTA-derived metrics: LAD stenosis, atherosclerosis presence, MB thickness, and LAD branch stenosis.
- Cardiac function indicators (ESV, EDV, SV, CO, LVEF) were analyzed for correlation with CTA findings; ROC curves assessed predictive value.
Main Results:
- Significant differences in cardiac function indicators (EDV, SV, CO, LVEF) were observed between groups with varying stenosis severity and atherosclerosis.
- Deeper myocardial bridges were associated with lower SV, CO, and LVEF.
- Combined cardiac function indicators demonstrated a high predictive value (AUC 0.907) for MB-MCA severity, outperforming single indicators.
Conclusions:
- Cardiac function indicators, particularly cardiac output (CO) and left ventricular ejection fraction (LVEF), are significantly correlated with CTA-assessed MB-MCA.
- A combined assessment of cardiac function indicators offers a robust approach for predicting the severity of MB-MCA.
Objective:
To investigate the relationship between computed tomography angiography (CTA) performances and cardiac function indicators in patients with myocardial bridge and mural coronary artery (MB-MCA).
Methods:
The clinical data of 60 patients with MB-MCA receiving CTA in the First Hospital of Zhangjiakou from January 2021 to February 2022 were analyzed retrospectively. The patients were divided into different groups based on CTA performances, including the degree of stenosis of the left anterior descending (LAD) MCA, whether there was atherosclerosis in the anterior segment of MB of LAD branch, the MB thickness, and the degree of stenosis of the LAD branch. The correlation between these TCA performances and cardiac function indicators including end-systolic volume (ESV), end-diastolic volume (EDV), stroke volume (SV), cardiac output (CO), and left ventricular ejection fraction (LVEF) was analyzed. Besides, the receiver operating characteristic (ROC) curve was used to analyze the predictive performance of cardiac function indicators for the severity of MB-MCA.
Results:
ESV, EDV, SV, CO and LVEF were statistically different between the moderate stenosis group and mild stenosis group (all P < 0.05). EDV, SV, CO, and LVEF were statistically different between the atherosclerosis group and non-atherosclerosis group (all P < 0.05). SV, CO, LVEF in the deep group were lower than that in the superficial group (all P < 0.05). EDV, CO, LVEF were different between the LAD moderate stenosis group and LAD mild stenosis group (all P < 0.05). The AUC (areas under the curve) of combined detection of ESV, EDV, SV, CO, and LVEF in predicting the severity of MB-MCA was 0.907, which was higher than the single indicator predictive effect.
Conclusions:
Cardiac function indicators, mainly CO and LVEF are correlated with the CTA performance of MB-MCA patients. The combination of cardiac function indicators has a good effect in predicting the severity of MB-MCA.
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