Cardiothoracic Imaging AI for Cardiac Diseases

Abstract

Artificial intelligence (AI) has transformed medical imaging across disciplines. In cardiothoracic imaging, AI has the potential to impact all modalities, including chest radiography, echocardiography, computed tomography, magnetic resonance imaging, and nuclear cardiology. Use cases include automated structural and functional quantification of anatomic structures, lesion detection and characterization, and novel disease screening opportunities. Here, we discuss techniques and applications specific to cardiovascular diseases, including multimodal AI, coronary artery disease and coronary calcium detection, cardiac structural and functional evaluation, analysis of acute aortic syndromes, and evolving use cases such as pericardial disease evaluation and pulmonary hypertension assessment. We also discuss population health-related aspects of AI, model development challenges, and ethical considerations.