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Application of Model-Building Based on Arterial Ultrasound Imaging Evaluation to Predict CHD Risk
Xiaoya Chen1, Yinzhu Chu1, Xiaobo Hou2
1Department of Ultrasound, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, China.
Insights
Arterial ultrasound findings, like carotid plaque count, can independently predict coronary heart disease (CHD) risk. Combining these with traditional factors improves CHD prediction accuracy and severity assessment.
Area of Science:
- Cardiovascular Medicine
- Diagnostic Imaging
- Public Health
Background:
- Atherosclerosis is a systemic disease affecting multiple arteries, sharing risk factors and pathogenesis with coronary heart disease (CHD).
- Assessing atherosclerosis in various vascular beds may offer insights into systemic disease patterns and CHD risk.
Purpose of the Study:
- To explore the correlation between arterial ultrasound assessment data and coronary heart disease (CHD) lesions, severity, and branch involvement.
- To evaluate the predictive value of arterial ultrasound data, combined with traditional risk factors, for CHD risk.
Main Methods:
- 363 inpatients with suspected CHD underwent clinical, biochemical, and arterial ultrasound examinations (neck, abdominal, limb arteries).
- Data were analyzed to compare CHD and control groups, correlate ultrasound findings with CHD severity (Gensini score), and assess predictive value using logistic regression and ROC curves.
Main Results:
- Significant differences in lipids, CK-MB, hs-cTnI, BNP, and GGT were observed between groups.
- Carotid plaque count, abdominal aortic and inferior mesenteric artery velocities, and lower-extremity artery atherosclerosis were associated with CHD.
- Arterial ultrasound parameters, especially carotid plaque count, carotid artery atherosclerosis, and lower-extremity artery stenosis, significantly improved CHD prediction compared to traditional risk factors alone.
Conclusions:
- Arterial ultrasound findings like intima-media thickening, plaques, and stenosis provide valuable information on systemic atherogenesis.
- Carotid plaque count emerges as an independent predictor of CHD risk.
- Integrating arterial ultrasound data with traditional risk factors enhances the prediction of CHD, its severity, and lesion complexity.
Objective:
Atherosclerotic is a chronic systemic disease that may occur in multiple vascular beds, including the carotid arteries, renal arteries, lower limb arteries, and cerebral vessels. Coronary atherosclerosis shares similar risk factors, pathogenesis, and pathophysiological basis with the atherosclerotic lesions of arteries at these sites. Arterial ultrasound assessment data were used to explore the correlation of atherosclerotic disease with CHD lesions and their severity and the number of lesion branches, as well as to evaluate its value in predicting CHD risk, in combination with traditional risk factors.
Methods:
A total of 363 inpatients with suspected CHD in the Department of Cardiology of the First Hospital of Harbin Medical University from November 2017 to June 2021 were selected. Patient clinical data, blood biochemical examination results, and ultrasound examination of neck vessels, abdominal arteries, and limb arteries were collected to obtain atherosclerosis assessment data. We then compared the differences between the CHD group and the control group, analyzed their correlation with CHD lesions and severity and the number of lesion branches, and evaluated the correlation with the coronary Gensini score. After adjustment for traditional risk factors, logistic regression was applied to analyze the relationship between arterial ultrasound assessment data and the risk of CHD. In addition, ROC plots were drawn to evaluate the risk of arterial ultrasound assessment data, combined with traditional risk factors, to predict CHD.
Results:
With regard to abnormal blood biochemical index values, differences in lipids, HDL-C, FIB, CK-MB, hs-cTnI, BNP, and GGT were found between the CHD group and the control group. Carotid plaque count, abdominal aortic flow velocity, inferior mesenteric artery flow velocity, classification of the number of stenotic branches of abdominal aortic branch arteries, lower-extremity-artery plaque count, degree of lower-extremity-artery stenosis, and lower-extremity-artery AS were risk factors for arterial ultrasound assessment data of CHD. Carotid plaque count, carotid artery AS, inferior mesenteric artery flow velocity, abdominal aortic flow velocity, abdominal aortic plaque count, abdominal aortic branch artery stenosis branch classification, lower-extremity-artery plaque count, lower-extremity-artery stenosis branch classification, degree of lower-extremity-artery stenosis, and lower-extremity-artery AS, combined with traditional risk factors, were mostly more effective than traditional risk factor models in predicting CHD, its severity, and the number of branch lesions; moreover, the predictive value was higher. Specifically, carotid plaque count, carotid AS, lower-extremity-artery AS, the degree of stenosis of lower-extremity arteries, and abdominal aortic branch artery stenosis branch classification can be used as predictor variables for CHD risk. Among these variables, the carotid plaque count can be used as an independent predictor of CHD.
Conclusion:
The incidence of arterial intima-media thickening (IMT), plaques, and stenosis can provide a reference for understanding the pattern of systemic atherogenesis and the distribution of atherosclerosis.
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