Application of AI in cardiovascular multimodality imaging

Giuseppe Muscogiuri; Valentina Volpato; Riccardo Cau; Mattia Chiesa; Luca Saba; Marco Guglielmo; Alberto Senatieri; Gregorio Chierchia; Gianluca Pontone; Serena Dell'Aversana; U. Joseph Schoepf; Mason G. Andrews; Paolo Basile; Andrea Igoren Guaricci; Paolo Marra; Denisa Muraru; Luigi P. Badano; Sandro Sironi

doi:10.1016/j.heliyon.2022.e10872

Application of AI in cardiovascular multimodality imaging

Giuseppe Muscogiuri^*, Valentina Volpato, Riccardo Cau, Mattia Chiesa, Luca Saba, Marco Guglielmo, Alberto Senatieri, Gregorio Chierchia, Gianluca Pontone, Serena Dell'Aversana, U. Joseph Schoepf, Mason G. Andrews, Paolo Basile, Andrea Igoren Guaricci, Paolo Marra, Denisa Muraru, Luigi P. Badano, Sandro Sironi

^*Corresponding author for this work

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

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Abstract

Technical advances in artificial intelligence (AI) in cardiac imaging are rapidly improving the reproducibility of this approach and the possibility to reduce time necessary to generate a report. In cardiac computed tomography angiography (CCTA) the main application of AI in clinical practice is focused on detection of stenosis, characterization of coronary plaques, and detection of myocardial ischemia. In cardiac magnetic resonance (CMR) the application of AI is focused on post-processing and particularly on the segmentation of cardiac chambers during late gadolinium enhancement. In echocardiography, the application of AI is focused on segmentation of cardiac chambers and is helpful for valvular function and wall motion abnormalities. The common thread represented by all of these techniques aims to shorten the time of interpretation without loss of information compared to the standard approach. In this review we provide an overview of AI applications in multimodality cardiac imaging.

Original language	English
Article number	e10872
Journal	Heliyon
Volume	8
Issue number	10
DOIs	https://doi.org/10.1016/j.heliyon.2022.e10872
Publication status	Published - Oct 2022

Keywords

Artificial intelligence
Cardiac computed tomography angiography
Cardiac magnetic resonance
Coronary plaque
echocardiography
Late gadolinium enhancement

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10.1016/j.heliyon.2022.e10872Licence: CC BY

PIIS2405844022021600Final published version, 1.9 MBLicence: CC BY

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Muscogiuri, G., Volpato, V., Cau, R., Chiesa, M., Saba, L., Guglielmo, M., Senatieri, A., Chierchia, G., Pontone, G., Dell'Aversana, S., Schoepf, U. J., Andrews, M. G., Basile, P., Guaricci, A. I., Marra, P., Muraru, D., Badano, L. P., & Sironi, S. (2022). Application of AI in cardiovascular multimodality imaging. Heliyon, 8(10), Article e10872. https://doi.org/10.1016/j.heliyon.2022.e10872

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abstract = "Technical advances in artificial intelligence (AI) in cardiac imaging are rapidly improving the reproducibility of this approach and the possibility to reduce time necessary to generate a report. In cardiac computed tomography angiography (CCTA) the main application of AI in clinical practice is focused on detection of stenosis, characterization of coronary plaques, and detection of myocardial ischemia. In cardiac magnetic resonance (CMR) the application of AI is focused on post-processing and particularly on the segmentation of cardiac chambers during late gadolinium enhancement. In echocardiography, the application of AI is focused on segmentation of cardiac chambers and is helpful for valvular function and wall motion abnormalities. The common thread represented by all of these techniques aims to shorten the time of interpretation without loss of information compared to the standard approach. In this review we provide an overview of AI applications in multimodality cardiac imaging.",

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AU - Muscogiuri, Giuseppe

AU - Volpato, Valentina

AU - Cau, Riccardo

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AU - Guglielmo, Marco

AU - Senatieri, Alberto

AU - Chierchia, Gregorio

AU - Pontone, Gianluca

AU - Dell'Aversana, Serena

AU - Schoepf, U. Joseph

AU - Andrews, Mason G.

AU - Basile, Paolo

AU - Guaricci, Andrea Igoren

AU - Marra, Paolo

AU - Muraru, Denisa

AU - Badano, Luigi P.

AU - Sironi, Sandro

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N2 - Technical advances in artificial intelligence (AI) in cardiac imaging are rapidly improving the reproducibility of this approach and the possibility to reduce time necessary to generate a report. In cardiac computed tomography angiography (CCTA) the main application of AI in clinical practice is focused on detection of stenosis, characterization of coronary plaques, and detection of myocardial ischemia. In cardiac magnetic resonance (CMR) the application of AI is focused on post-processing and particularly on the segmentation of cardiac chambers during late gadolinium enhancement. In echocardiography, the application of AI is focused on segmentation of cardiac chambers and is helpful for valvular function and wall motion abnormalities. The common thread represented by all of these techniques aims to shorten the time of interpretation without loss of information compared to the standard approach. In this review we provide an overview of AI applications in multimodality cardiac imaging.

AB - Technical advances in artificial intelligence (AI) in cardiac imaging are rapidly improving the reproducibility of this approach and the possibility to reduce time necessary to generate a report. In cardiac computed tomography angiography (CCTA) the main application of AI in clinical practice is focused on detection of stenosis, characterization of coronary plaques, and detection of myocardial ischemia. In cardiac magnetic resonance (CMR) the application of AI is focused on post-processing and particularly on the segmentation of cardiac chambers during late gadolinium enhancement. In echocardiography, the application of AI is focused on segmentation of cardiac chambers and is helpful for valvular function and wall motion abnormalities. The common thread represented by all of these techniques aims to shorten the time of interpretation without loss of information compared to the standard approach. In this review we provide an overview of AI applications in multimodality cardiac imaging.

KW - Artificial intelligence

KW - Cardiac computed tomography angiography

KW - Cardiac magnetic resonance

KW - Coronary plaque

KW - echocardiography

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VL - 8

JO - Heliyon

JF - Heliyon

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Application of AI in cardiovascular multimodality imaging

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