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Erschienen in: The International Journal of Cardiovascular Imaging 12/2020

02.07.2020 | Review Paper

From CT to artificial intelligence for complex assessment of plaque-associated risk

verfasst von: Diana Opincariu, Theodora Benedek, Monica Chițu, Nora Raț, Imre Benedek

Erschienen in: The International Journal of Cardiovascular Imaging | Ausgabe 12/2020

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Abstract

The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust information on the overall coronary circulation and luminal stenosis, also providing the ability to assess the composition, morphology, and vulnerability of atherosclerotic plaques. In addition, the perivascular adipose tissue (PVAT) has recently emerged as a marker of increased cardiovascular risk. The addition of PVAT quantification to standard CCTA imaging may provide the ability to extract information on local inflammation, for an individualized approach in coronary risk stratification. The development of image post-processing tools over the past several years allowed CCTA to provide a significant amount of data that can be incorporated into machine learning (ML) applications. ML algorithms that use radiomic features extracted from CCTA are still at an early stage. However, the recent development of artificial intelligence will probably bring major changes in the way we integrate clinical, biological, and imaging information, for a complex risk stratification and individualized therapeutic decision making in patients with CAD. This review aims to present the current evidence on the complex role of CCTA in the detection and quantification of vulnerable plaques and the associated coronary inflammation, also describing the most recent developments in the radiomics-based machine learning approach for complex assessment of plaque-associated risk.
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Metadaten
Titel
From CT to artificial intelligence for complex assessment of plaque-associated risk
verfasst von
Diana Opincariu
Theodora Benedek
Monica Chițu
Nora Raț
Imre Benedek
Publikationsdatum
02.07.2020
Verlag
Springer Netherlands
Erschienen in
The International Journal of Cardiovascular Imaging / Ausgabe 12/2020
Print ISSN: 1569-5794
Elektronische ISSN: 1875-8312
DOI
https://doi.org/10.1007/s10554-020-01926-1

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