Current and Future Applications of Artificial Intelligence in Cardiac CT.
Mugdha JoshiDiana Patricia MeloDavid OuyangPiotr J SlomkaMichelle C WilliamsDamini DeyPublished in: Current cardiology reports (2023)
Recent studies have shown that deep learning networks can be applied for rapid automated segmentation of coronary plaque from coronary CT angiography, with AI-enabled measurement of total plaque volume predicting future heart attack. AI has also been applied to automate assessment of coronary artery calcium on cardiac and ungated chest CT and to automate the measurement of epicardial fat. Additionally, AI-based prediction models integrating clinical and imaging parameters have been shown to improve prediction of cardiac events compared to traditional risk scores. Artificial intelligence applications have been applied in all aspects of cardiovascular CT - in image acquisition, reconstruction and denoising, segmentation and quantitative analysis, diagnosis and decision assistance and to integrate prognostic risk from clinical data and images. Further incorporation of artificial intelligence in cardiovascular imaging holds important promise to enhance cardiovascular CT as a precision medicine tool.
Keyphrases
- artificial intelligence
- deep learning
- big data
- convolutional neural network
- coronary artery
- image quality
- dual energy
- coronary artery disease
- machine learning
- computed tomography
- contrast enhanced
- left ventricular
- high resolution
- pulmonary artery
- positron emission tomography
- magnetic resonance imaging
- heart failure
- adipose tissue
- atrial fibrillation
- mass spectrometry
- pulmonary hypertension
- high throughput
- sensitive detection
- loop mediated isothermal amplification
- ejection fraction