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Review
. 2021 Jul 26;4(3):192-203.
doi: 10.1093/pcmedi/pbab018. eCollection 2021 Sep.

Understanding the predictive value and methods of risk assessment based on coronary computed tomographic angiography in populations with coronary artery disease: a review

Yiming Li  1 , Kaiyu Jia  1 , Yuheng Jia  1 , Yong Yang  1 , Yijun Yao  1 , Mao Chen  1 , Yong Peng  1
Affiliations
Review

Understanding the predictive value and methods of risk assessment based on coronary computed tomographic angiography in populations with coronary artery disease: a review

Yiming Li et al. Precis Clin Med. .

Abstract

Risk assessment in coronary artery disease plays an essential role in the early identification of high-risk patients. However, conventional invasive imaging procedures all require long intraprocedural times and high costs. The rapid development of coronary computed tomographic angiography (CCTA) and related image processing technology has facilitated the formulation of noninvasive approaches to perform comprehensive evaluations. Evidence has shown that CCTA has outstanding performance in identifying the degree of stenosis, plaque features, and functional reserve. Moreover, advancements in radiomics and machine learning allow more comprehensive interpretations of CCTA images. This paper reviews conventional as well as novel diagnostic and risk assessment tools based on CCTA.

Keywords: coronary artery disease; coronary computed tomographic angiography (CCTA); prediction value; risk assessment.

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Figures

Figure 1.
Figure 1.
The process from lesion to risk model based on radiomic and machine learning by Siemens (Healthineers, Forchheim, Germany).
Figure 2.
Figure 2.
Using coronary computed tomographic angiography to perform risk assessment in patients with coronary disease in multiple dimensions.
See this image and copyright information in PMC

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