Current and Future Applications of Artificial Intelligence in Cardiac CT

Mugdha Joshi, Diana Patricia Melo, David Ouyang, Piotr J. Slomka, Michelle C. Williams, Damini Dey

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Purpose of Review
In this review, we aim to summarize state-of-the-art artificial intelligence (AI) approaches applied to cardiovascular CT and their future implications.

Recent Findings
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.
Original languageEnglish
Pages (from-to)109-117
JournalCurrent cardiology reports
Issue number3
Early online date28 Jan 2023
Publication statusPublished - 1 Mar 2023


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