☆ 4.4 Article

Society of Cardiovascular Computed Tomography / North American Society of Cardiovascular Imaging - Expert Consensus Document on Coronary CT Imaging of Atherosclerotic Plaque

JOURNAL OF CARDIOVASCULAR COMPUTED TOMOGRAPHY (2021)

Journal

JOURNAL OF CARDIOVASCULAR COMPUTED TOMOGRAPHY

Volume 15, Issue 2, Pages 93-109

Publisher

ELSEVIER SCIENCE INC

DOI: 10.1016/j.jcct.2020.11.002

Keywords

Atherosclerotic plaque; Prognosis; Acute coronary syndrome; High risk plaque; Prevention

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Abstract

Coronary computed tomographic angiography (CCTA) not only provides information on anatomical stenosis, but also identifies nonobstructive atherosclerosis and high-risk plaque features as precursors to coronary events. However, there is no consensus on how to identify and quantify these features or their use in clinical decision-making.

Coronary computed tomographic angiography (CCTA) provides a wealth of clinically meaningful information beyond anatomic stenosis alone, including the presence or absence of nonobstructive atherosclerosis and high-risk plaque features as precursors for incident coronary events. There is, however, no uniform agreement on how to identify and quantify these features or their use in evidence-based clinical decision-making. This statement from the Society of Cardiovascular Computed Tomography and North American Society of Cardiovascular Imaging addresses this gap and provides a comprehensive review of the available evidence on imaging of coronary atherosclerosis. In this statement, we provide standardized definitions for high-risk plaque (HRP) features and distill the evidence on the effectiveness of risk stratification into usable practice points. This statement outlines how this information should be communicated to referring physicians and patients by identifying critical elements to include in a structured CCTA report - the presence and severity of atherosclerotic plaque (descriptive statements, CAD-RADS (TM) categories), the segment involvement score, HRP features (e.g., low attenuation plaque, positive remodeling), and the coronary artery calcium score (when performed). Rigorous documentation of atherosclerosis on CCTA provides a vital opportunity to make recommendations for preventive care and to initiate and guide an effective care strategy for at-risk patients. (C) 2020 Published by Elsevier Inc. on behalf of Society of Cardiovascular Computed Tomography.

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Yan Huang, Jinzhu Yang, Yang Hou, Qi Sun, Shuang Ma, Chaolu Feng, Jin Shang

Summary: Cardiovascular disease is the leading cause of death worldwide, and acute coronary syndrome (ACS) is a common first manifestation. This study proposes a hybrid deep learning framework for predicting ACS by extracting coronary CT angiography (CCTA) imaging features of pericoronary adipose tissue (PCAT) and atherosclerotic plaques. The framework utilizes a two-stream CNN feature extraction module to extract the features, and a channel feature fusion module to explore feature correlations. Experimental results demonstrate the impressive performance of the proposed method in accurately predicting ACS, surpassing classical image classification networks and state-of-the-art medical image classification methods.

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