Coronary Artery Anomalies and Associated Radiologic Findings

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

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.

METHODS

In this retrospective analysis, we compiled data on 15 characteristics from 126 patients diagnosed with anomalous right coronary artery origins. The dataset encompassed both CCTA imaging attributes, such as the positioning of the right coronary artery orifices and the alignment of coronary arteries, and clinical parameters including gender and age. To identify the most salient features, we employed the Chi-square feature selection method, which filters features based on their statistical significance. We then focused on features yielding a Chi-square score exceeding a threshold of 1, thereby narrowing down the selection to seven key variables, including cardiac function and gender. Subsequently, we evaluated seven classifiers known for their efficacy in classification tasks. Through rigorous training and testing, we conducted a comparative analysis to identify the top three classifiers with the highest accuracy rates.

RESULTS

The top three classifiers in this study are Support Vector Machine (SVM), Ensemble Learning (EL), and Kernel Approximation Classifier. Among the SVM, EL and Kernel Approximation Classifier-based classifiers, the best performance is achieved for linear SVM, optimizable Ensembles Learning and SVM kernel, respectively. And the corresponding accuracy is 75.7%, 75.7%, and 73.0%, respectively. The AUC values are 0.77, 0.80, and 0.75, respectively.

CONCLUSIONS

Machine learning (ML) models can predict angina pectoris caused by the origin anomalous of the right coronary artery, providing valuable auxiliary diagnostic information for clinicians and serving as a warning to clinicians. It is hoped that timely intervention and treatment can be realized to avoid serious consequences such as myocardial infarction.

Multi-slice CT coronary angiography versus invasive coronary angiography in the assessment of graft patency after coronary artery bypasses graft surgery

BACKGROUND

The long-term patency of arterial and venous grafts is crucial for the success of CABG. This study was designed to investigate graft patency using 128-slice coronary computed tomography angiography (CCTA) and compared the results with those obtained using invasive coronary angiography (ICA). In this observational cross-sectional study, we included 40 symptomatic post-CABG patients underwent CCTA and ICA within the same month.

RESULTS

Fifty-five percent were aged more than 60 years, and 80% were males. 67.5% had diabetes, 90% had hypertension, and 30% were smokers. Mean body mass index was 28.89 ± 5.17 kg/m2. Mean duration since CABG was 5.25 ± 4.04 years. In total, 124 native vessels and 97 grafts were assessed using CCTA and ICA. CCTA delineated 8 non-cannulated venous grafts and 6 non-cannulated left internal mammary artery grafts. CCTA required a significantly lower radiation dose (1165.77 ± 123.54 vs. 47,589.78 ± 6967.53, p < 0.001).

CONCLUSION

CCTA can be as accurate as ICA in assessing bypass grafts with less radiation dose, providing a non-invasive reliable tool for evaluation.

A newly described variation of normal coronary: Dual origin of the circumflex artery from the main stem of the left coronary artery

BACKGROUND

The dual origin of the circumflex artery from the main stem of the left coronary artery is rare variation of normal coronary, which is not reported in previous literature. We report a case of old man with the dual origin of the circumflex artery from the main stem of the left coronary artery.

METHODS AND RESULTS

A 58-year-old man presented with chest pain and dyspnea. The echocardiogram and Laboratory examination are no obvious abnormalities. He was referred to coronary computed tomography angiography (CCTA). The CCTA showed the proximal circumflex artery forming a Y-shaped bifurcation with the dual origin of the main stem of the left coronary artery.

DISCUSSION

The dual origin of the circumflex artery is extremely rare variation of normal coronary. Though catheter angiography may be performed for preoperative identification of various coronary artery, it is limited in the description of the relationship of the coronary arteries to the cardiac structures and great vessels. CCTA can help in noninvasive characterization of coronary anomalies with respect to their origin, course, and spatial relations. The preoperative findings of various coronary artery are very important for achieving an accurate diagnosis and formulating the appropriate procedural planning and intraprocedural management.

CONCLUSION

CCTA findings of various CAAs are is important for achieving an accurate diagnosis and formulating the appropriate procedural planning and intraprocedural management.

State of the art of coronary computed tomography angiography

OBJECTIVES

The aim of this paper is to evaluate contrast media (CM) bolus geometry and opacification patterns in the coronary arteries with particular focus on patient, scanner and safety considerations during coronary computed tomography angiography (CCTA).

KEY FINDINGS

The rapid evolution of computed tomography (CT) technology has seen this imaging modality challenge conventional coronary angiography in the evaluation of coronary artery disease. Increases in spatial and temporal resolutions have enabled CCTA to become the modality of choice when evaluating the coronary vascular tree as an alternative in the diagnostic algorithm for acute chest pain. However, these new technologic improvements in scanner technology have imposed new challenges for the optimisation of CM delivery and image acquisition strategies.

CONCLUSION

Understanding basic CM-imaging principles is essential for designing optimal injection protocols according to each specific clinical scenario, independently of scanner technology.

IMPLICATIONS FOR PRACTICE

With rapid advances in CT scanner technology including faster scan acquisitions, the risk of poor opacification of coronary vasculature increases significantly. Therefore, awareness of CM delivery protocols is paramount to consistently provide optimal image quality at a low radiation dose.