The role of artificial intelligence in coronary CT angiography

Rudolf L.M. van Herten; Ioannis Lagogiannis; Tim Leiner; Ivana Išgum

doi:10.1007/s12471-024-01901-8

The role of artificial intelligence in coronary CT angiography

Rudolf L.M. van Herten^*
, Ioannis Lagogiannis
, Tim Leiner
, Ivana Išgum

^*Corresponding author for this work

Radiology

Research output: Contribution to journal › Review article › peer-review

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Abstract

Coronary CT angiography (CCTA) offers an efficient and reliable tool for the non-invasive assessment of suspected coronary artery disease through the analysis of coronary artery plaque and stenosis. However, the detailed manual analysis of CCTA is a burdensome task requiring highly skilled experts. Recent advances in artificial intelligence (AI) have made significant progress toward a more comprehensive automated analysis of CCTA images, offering potential improvements in terms of speed, performance and scalability. This work offers an overview of the recent developments of AI in CCTA. We cover methodological advances for coronary artery tree and whole heart analysis, and provide an overview of AI techniques that have shown to be valuable for the analysis of cardiac anatomy and pathology in CCTA. Finally, we provide a general discussion regarding current challenges and limitations, and discuss prospects for future research.

Original language	English
Pages (from-to)	417-425
Number of pages	9
Journal	Netherlands Heart Journal
Volume	32
Issue number	11
Early online date	10 Oct 2024
DOIs	https://doi.org/10.1007/s12471-024-01901-8
Publication status	Published - Nov 2024

Keywords

Artificial intelligence
Coronary artery disease
Coronary CT angiography
Deep learning

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title = "The role of artificial intelligence in coronary CT angiography",

abstract = "Coronary CT angiography (CCTA) offers an efficient and reliable tool for the non-invasive assessment of suspected coronary artery disease through the analysis of coronary artery plaque and stenosis. However, the detailed manual analysis of CCTA is a burdensome task requiring highly skilled experts. Recent advances in artificial intelligence (AI) have made significant progress toward a more comprehensive automated analysis of CCTA images, offering potential improvements in terms of speed, performance and scalability. This work offers an overview of the recent developments of AI in CCTA. We cover methodological advances for coronary artery tree and whole heart analysis, and provide an overview of AI techniques that have shown to be valuable for the analysis of cardiac anatomy and pathology in CCTA. Finally, we provide a general discussion regarding current challenges and limitations, and discuss prospects for future research.",

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doi = "10.1007/s12471-024-01901-8",

language = "English",

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T1 - The role of artificial intelligence in coronary CT angiography

AU - van Herten, Rudolf L.M.

AU - Lagogiannis, Ioannis

AU - Leiner, Tim

AU - Išgum, Ivana

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2024/11

Y1 - 2024/11

N2 - Coronary CT angiography (CCTA) offers an efficient and reliable tool for the non-invasive assessment of suspected coronary artery disease through the analysis of coronary artery plaque and stenosis. However, the detailed manual analysis of CCTA is a burdensome task requiring highly skilled experts. Recent advances in artificial intelligence (AI) have made significant progress toward a more comprehensive automated analysis of CCTA images, offering potential improvements in terms of speed, performance and scalability. This work offers an overview of the recent developments of AI in CCTA. We cover methodological advances for coronary artery tree and whole heart analysis, and provide an overview of AI techniques that have shown to be valuable for the analysis of cardiac anatomy and pathology in CCTA. Finally, we provide a general discussion regarding current challenges and limitations, and discuss prospects for future research.

AB - Coronary CT angiography (CCTA) offers an efficient and reliable tool for the non-invasive assessment of suspected coronary artery disease through the analysis of coronary artery plaque and stenosis. However, the detailed manual analysis of CCTA is a burdensome task requiring highly skilled experts. Recent advances in artificial intelligence (AI) have made significant progress toward a more comprehensive automated analysis of CCTA images, offering potential improvements in terms of speed, performance and scalability. This work offers an overview of the recent developments of AI in CCTA. We cover methodological advances for coronary artery tree and whole heart analysis, and provide an overview of AI techniques that have shown to be valuable for the analysis of cardiac anatomy and pathology in CCTA. Finally, we provide a general discussion regarding current challenges and limitations, and discuss prospects for future research.

KW - Artificial intelligence

KW - Coronary artery disease

KW - Coronary CT angiography

KW - Deep learning

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DO - 10.1007/s12471-024-01901-8

M3 - Review article

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VL - 32

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EP - 425

JO - Netherlands Heart Journal

JF - Netherlands Heart Journal

IS - 11

ER -

The role of artificial intelligence in coronary CT angiography

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