Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization

Gudigar, A; Nayak, S; Samanth, J; Raghavendra, U; Ashwal, AJ; Barua, PD; Hasan, N; Ciaccio, EJ; Tan, R-S; Acharya, UR

Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization

Gudigar, A Nayak, S Samanth, J Raghavendra, U Ashwal, AJ Barua, PD Hasan, N Ciaccio, EJ Tan, R-S Acharya, UR

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Publisher:: MDPI AG
Publication Type:: Journal Article
Citation:: International Journal of Environmental Research and Public Health, 2021, 18, (19), pp. 10003
Issue Date:: 2021-09-23

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Field	Value	Language
dc.contributor.author	Gudigar, A
dc.contributor.author	Nayak, S
dc.contributor.author	Samanth, J
dc.contributor.author	Raghavendra, U
dc.contributor.author	Ashwal, AJ
dc.contributor.author	Barua, PD
dc.contributor.author	Hasan, N
dc.contributor.author	Ciaccio, EJ
dc.contributor.author	Tan, R-S
dc.contributor.author	Acharya, UR
dc.date.accessioned	2022-02-16T02:18:48Z
dc.date.available	2022-02-16T02:18:48Z
dc.date.issued	2021-09-23
dc.identifier.citation	International Journal of Environmental Research and Public Health, 2021, 18, (19), pp. 10003
dc.identifier.issn	1661-7827
dc.identifier.issn	1660-4601
dc.identifier.uri	http://hdl.handle.net/10453/154586
dc.description.abstract	<jats:p>Coronary artery disease is a major cause of morbidity and mortality worldwide. Its underlying histopathology is the atherosclerotic plaque, which comprises lipid, fibrous and—when chronic—calcium components. Intravascular ultrasound (IVUS) and intravascular optical coherence tomography (IVOCT) performed during invasive coronary angiography are reference standards for characterizing the atherosclerotic plaque. Fine image spatial resolution attainable with contemporary coronary computed tomographic angiography (CCTA) has enabled noninvasive plaque assessment, including identifying features associated with vulnerable plaques known to presage acute coronary events. Manual interpretation of IVUS, IVOCT and CCTA images demands scarce physician expertise and high time cost. This has motivated recent research into and development of artificial intelligence (AI)-assisted methods for image processing, feature extraction, plaque identification and characterization. We performed parallel searches of the medical and technical literature from 1995 to 2021 focusing respectively on human plaque characterization using various imaging modalities and the use of AI-assisted computer aided diagnosis (CAD) to detect and classify atherosclerotic plaques, including their composition and the presence of high-risk features denoting vulnerable plaques. A total of 122 publications were selected for evaluation and the analysis was summarized in terms of data sources, methods—machine versus deep learning—and performance metrics. Trends in AI-assisted plaque characterization are detailed and prospective research challenges discussed. Future directions for the development of accurate and efficient CAD systems to characterize plaque noninvasively using CCTA are proposed.</jats:p>
dc.language	en
dc.publisher	MDPI AG
dc.relation.ispartof	International Journal of Environmental Research and Public Health
dc.relation.isbasedon	10.3390/ijerph181910003
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Toxicology
dc.title	Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization
dc.type	Journal Article
utslib.citation.volume	18
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	open_access	*
dc.date.updated	2022-02-16T02:18:27Z
pubs.issue	19
pubs.publication-status	Published online
pubs.volume	18
utslib.citation.issue	19

Abstract:

Coronary artery disease is a major cause of morbidity and mortality worldwide. Its underlying histopathology is the atherosclerotic plaque, which comprises lipid, fibrous and—when chronic—calcium components. Intravascular ultrasound (IVUS) and intravascular optical coherence tomography (IVOCT) performed during invasive coronary angiography are reference standards for characterizing the atherosclerotic plaque. Fine image spatial resolution attainable with contemporary coronary computed tomographic angiography (CCTA) has enabled noninvasive plaque assessment, including identifying features associated with vulnerable plaques known to presage acute coronary events. Manual interpretation of IVUS, IVOCT and CCTA images demands scarce physician expertise and high time cost. This has motivated recent research into and development of artificial intelligence (AI)-assisted methods for image processing, feature extraction, plaque identification and characterization. We performed parallel searches of the medical and technical literature from 1995 to 2021 focusing respectively on human plaque characterization using various imaging modalities and the use of AI-assisted computer aided diagnosis (CAD) to detect and classify atherosclerotic plaques, including their composition and the presence of high-risk features denoting vulnerable plaques. A total of 122 publications were selected for evaluation and the analysis was summarized in terms of data sources, methods—machine versus deep learning—and performance metrics. Trends in AI-assisted plaque characterization are detailed and prospective research challenges discussed. Future directions for the development of accurate and efficient CAD systems to characterize plaque noninvasively using CCTA are proposed.

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http://hdl.handle.net/10453/154586