Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.
Int J Cardiovasc Imaging
; 40(5): 951-966, 2024 May.
Article
en En
| MEDLINE
| ID: mdl-38700819
ABSTRACT
Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Enfermedad de la Arteria Coronaria
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Interpretación de Imagen Radiográfica Asistida por Computador
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Valor Predictivo de las Pruebas
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Angiografía Coronaria
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Vasos Coronarios
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Calcificación Vascular
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Aprendizaje Profundo
Límite:
Humans
Idioma:
En
Revista:
Int J Cardiovasc Imaging
/
Int. j. cardiovasc. imaging
/
International journal of cardiovascular imaging
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2024
Tipo del documento:
Article
País de afiliación:
Suiza