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.
Abstract

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