Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence
| Autor(a) principal: | |
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| Data de Publicação: | 2021 |
| Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | http://hdl.handle.net/10362/133561 |
Resumo: | Funding Information: ADC is supported by a grant from the GW Heart and Vascular Institute. |
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Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligenceatherosclerosiscarotid artery diseasescomputed tomography angiographycoronary angiographydiagnostic imagingCardiology and Cardiovascular MedicineFunding Information: ADC is supported by a grant from the GW Heart and Vascular Institute.Objective The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT). Methods This is a post-hoc analysis of data from 303 subjects enrolled in the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial who were referred for invasive coronary angiography and subsequently underwent coronary computed tomographic angiography (CCTA). In this study, a blinded core laboratory analysing quantitative coronary angiography images classified lesions as obstructive (≥50%) or non-obstructive (<50%) while AI software quantified APCs including plaque volume (PV), low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), calcified plaque (CP), lesion length on a per-patient and per-lesion basis based on CCTA imaging. Plaque measurements were normalised for vessel volume and reported as % percent atheroma volume (%PAV) for all relevant plaque components. Data were subsequently stratified by age <65 and ≥65 years. Results The cohort was 64.4±10.2 years and 29% women. Overall, patients >65 had more PV and CP than patients <65. On a lesion level, patients >65 had more CP than younger patients in both obstructive (29.2 mm 3 vs 48.2 mm 3; p<0.04) and non-obstructive lesions (22.1 mm 3 vs 49.4 mm 3; p<0.004) while younger patients had more %PAV (LD-NCP) (1.5% vs 0.7%; p<0.038). Younger patients had more PV, LD-NCP, NCP and lesion lengths in obstructive compared with non-obstructive lesions. There were no differences observed between lesion types in older patients. Conclusion AI-QCT identifies a unique APC signature that differs by age and degree of stenosis and provides a foundation for AI-guided age-based approaches to atherosclerosis identification, prevention and treatment.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)Comprehensive Health Research Centre (CHRC) - pólo NMSRUNJonas, RebeccaEarls, JamesPinto Marques, HugoChang, Hyuk JaeChoi, Jung HyunDoh, Joon HyungHer, Ae YoungKoo, Bon KwonNam, Chang WookPark, Hyung BokShin, SanghoonCole, JasonGimelli, AlessiaKhan, Muhammad AkramLu, BinGao, YangNabi, FaisalNakazato, RyoSchoepf, U. JosephDriessen, Roel S.Bom, Michiel J.Thompson, Randall C.Jang, James J.Ridner, MichaelRowan, ChrisAvelar, ErickGénéreux, PhilippeKnaapen, PaulDe Waard, Guus A.Pontone, GianlucaAndreini, DanieleAl-Mallah, Mouaz H.Jennings, RobertCrabtree, Tami R.Villines, Todd C.Min, James K.Choi, Andrew D.2022-02-24T23:22:05Z2021-11-162021-11-16T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/133561eng2398-595XPURE: 35418905https://doi.org/10.1136/openhrt-2021-001832info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-10-21T01:36:16Zoai:run.unl.pt:10362/133561Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:30:45.389155Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence |
| title |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence |
| spellingShingle |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence Jonas, Rebecca atherosclerosis carotid artery diseases computed tomography angiography coronary angiography diagnostic imaging Cardiology and Cardiovascular Medicine |
| title_short |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence |
| title_full |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence |
| title_fullStr |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence |
| title_full_unstemmed |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence |
| title_sort |
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence |
| author |
Jonas, Rebecca |
| author_facet |
Jonas, Rebecca Earls, James Pinto Marques, Hugo Chang, Hyuk Jae Choi, Jung Hyun Doh, Joon Hyung Her, Ae Young Koo, Bon Kwon Nam, Chang Wook Park, Hyung Bok Shin, Sanghoon Cole, Jason Gimelli, Alessia Khan, Muhammad Akram Lu, Bin Gao, Yang Nabi, Faisal Nakazato, Ryo Schoepf, U. Joseph Driessen, Roel S. Bom, Michiel J. Thompson, Randall C. Jang, James J. Ridner, Michael Rowan, Chris Avelar, Erick Généreux, Philippe Knaapen, Paul De Waard, Guus A. Pontone, Gianluca Andreini, Daniele Al-Mallah, Mouaz H. Jennings, Robert Crabtree, Tami R. Villines, Todd C. Min, James K. Choi, Andrew D. |
| author_role |
author |
| author2 |
Earls, James Pinto Marques, Hugo Chang, Hyuk Jae Choi, Jung Hyun Doh, Joon Hyung Her, Ae Young Koo, Bon Kwon Nam, Chang Wook Park, Hyung Bok Shin, Sanghoon Cole, Jason Gimelli, Alessia Khan, Muhammad Akram Lu, Bin Gao, Yang Nabi, Faisal Nakazato, Ryo Schoepf, U. Joseph Driessen, Roel S. Bom, Michiel J. Thompson, Randall C. Jang, James J. Ridner, Michael Rowan, Chris Avelar, Erick Généreux, Philippe Knaapen, Paul De Waard, Guus A. Pontone, Gianluca Andreini, Daniele Al-Mallah, Mouaz H. Jennings, Robert Crabtree, Tami R. Villines, Todd C. Min, James K. Choi, Andrew D. |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.contributor.none.fl_str_mv |
NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM) Comprehensive Health Research Centre (CHRC) - pólo NMS RUN |
| dc.contributor.author.fl_str_mv |
Jonas, Rebecca Earls, James Pinto Marques, Hugo Chang, Hyuk Jae Choi, Jung Hyun Doh, Joon Hyung Her, Ae Young Koo, Bon Kwon Nam, Chang Wook Park, Hyung Bok Shin, Sanghoon Cole, Jason Gimelli, Alessia Khan, Muhammad Akram Lu, Bin Gao, Yang Nabi, Faisal Nakazato, Ryo Schoepf, U. Joseph Driessen, Roel S. Bom, Michiel J. Thompson, Randall C. Jang, James J. Ridner, Michael Rowan, Chris Avelar, Erick Généreux, Philippe Knaapen, Paul De Waard, Guus A. Pontone, Gianluca Andreini, Daniele Al-Mallah, Mouaz H. Jennings, Robert Crabtree, Tami R. Villines, Todd C. Min, James K. Choi, Andrew D. |
| dc.subject.por.fl_str_mv |
atherosclerosis carotid artery diseases computed tomography angiography coronary angiography diagnostic imaging Cardiology and Cardiovascular Medicine |
| topic |
atherosclerosis carotid artery diseases computed tomography angiography coronary angiography diagnostic imaging Cardiology and Cardiovascular Medicine |
| description |
Funding Information: ADC is supported by a grant from the GW Heart and Vascular Institute. |
| publishDate |
2021 |
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2021-11-16 2021-11-16T00:00:00Z 2022-02-24T23:22:05Z |
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info:eu-repo/semantics/publishedVersion |
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2398-595X PURE: 35418905 https://doi.org/10.1136/openhrt-2021-001832 |
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