医学
无症状的
冠状动脉钙
冠状动脉疾病
风险评估
公制(单位)
心肌梗塞
疾病
弗雷明翰风险评分
内科学
放射科
运营管理
计算机安全
计算机科学
经济
作者
Amit Banwari Gupta,Kaustav Bera,Elias George Kikano,Jonathan D. Pierce,Jonathan M. Gan,Maharshi A. Rajdev,Leslie M. Ciancibello,Aekta Gupta,Sanjay Rajagopalan,Robert Gilkeson
出处
期刊:Radiographics
[Radiological Society of North America]
日期:2022-06-03
卷期号:42 (4): 947-967
被引量:118
摘要
Coronary artery calcium (CAC) scores obtained from CT scans have been shown to be prognostic in assessment of the risk for development of cardiovascular diseases, facilitating the prediction of outcome in asymptomatic individuals. Currently, several methods to calculate the CAC score exist, and each has its own set of advantages and disadvantages. Agatston CAC scoring is the most extensively used method. CAC scoring is currently recommended for use in asymptomatic individuals to predict the risk of developing cardiovascular diseases and the disease-specific mortality. In specific subsets of patients, the CAC score has also been recommended for reclassifying cardiovascular risk and aiding in decision making when planning primary prevention interventions such as statin therapy. The progression of CAC scores on follow-up images has been shown to be linked to risk of myocardial infarction and cardiovascular mortality. While the CAC score is a validated tool used clinically, several challenges, including various pitfalls associated with the acquisition, calculation, and interpretation of the score, prevent more widespread adoption of this metric. Recent research has been focused extensively on strategies to improve existing scoring methods, including measuring calcium attenuation, detecting microcalcifications, and focusing on extracoronary calcifications, and on strategies to improve image acquisition. A better understanding of CAC scoring approaches will help radiologists and other physicians better use and interpret these scores in their workflows. An invited commentary by S. Gupta is available online. Online supplemental material is available for this article. ©RSNA, 2022
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