Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.
Int J Cardiovasc Imaging
; 40(6): 1283-1303, 2024 Jun.
Article
em En
| MEDLINE
| ID: mdl-38678144
ABSTRACT
The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The participants in this study consisted of 459 individuals who had undergone coronary angiography, contrast-enhanced ultrasonography, and focused carotid B-mode ultrasound. Each patient was tracked for thirty days. The measurements on these patients consisted of maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (cIMT), and intraplaque neovascularization (IPN). CAD risk and CV event stratification were performed by applying eight types of DL-based models. Univariate and multivariate analysis was also conducted to predict the most significant risk predictors. The DL's model effectiveness was evaluated by the area-under-the-curve measurement while the CV event prediction was evaluated using the Cox proportional hazard model (CPHM) and compared against the DL-based concordance index (c-index). IPN showed a substantial ability to predict CV events (p < 0.0001). The best DL system improved by 21% (0.929 vs. 0.762) over the best ML system. DL-based CV event prediction showed a ~ 17% increase in DL-based c-index compared to the CPHM (0.86 vs. 0.73). CAD and CV incidents were linked to IPN and carotid imaging characteristics. For survival analysis and CAD prediction, the DL-based system performs superior to ML-based models.
Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Doença da Artéria Coronariana
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Doenças das Artérias Carótidas
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Valor Preditivo dos Testes
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Placa Aterosclerótica
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Espessura Intima-Media Carotídea
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Aprendizado Profundo
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Fatores de Risco de Doenças Cardíacas
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
País/Região como assunto:
America do norte
Idioma:
En
Revista:
Int J Cardiovasc Imaging
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Índia