The value of CCTA combined with machine learning for predicting angina pectoris in the anomalous origin of the right coronary artery.

Journal: Biomedical engineering online
PMID: 39267079

Abstract

BACKGROUND: Anomalous origin of coronary artery is a common coronary artery anatomy anomaly. The anomalous origin of the coronary artery may lead to problems such as narrowing of the coronary arteries at the beginning of the coronary arteries and abnormal alignment, which may lead to myocardial ischemia due to the compression of the coronary arteries. Clinical symptoms include chest tightness and dyspnea, with angina pectoris as a common symptom that can be life-threatening. Timely and accurate diagnosis of anomalous coronary artery origin is of great importance. Coronary computed tomography angiography (CCTA) can provide detailed information on the characteristics of coronary arteries. Therefore, we combined CCTA and artificial intelligence (AI) technology to analyze the CCTA image features and clinical features of patients with anomalous origin of the right coronary artery to predict angina pectoris and the relevance of different features to angina pectoris.

Authors

  • Ying Wang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Mengxing Wang
  • Mingyuan Yuan
    Department of Radiology, Affiliated Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China. zp_yuanmy@sumhs.edu.cn.
  • Wenxian Peng
    College of Medical Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China. pengwx@sumhs.edu.cn.

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