医学
狭窄
计算机断层摄影术
易损斑块
表征(材料科学)
放射科
血管造影
人工智能
医学物理学
计算机科学
病理
纳米技术
材料科学
作者
Riccardo Cau,Adam E. Flanders,Lorenzo Mannelli,Carola Politi,Gavino Faa,Jasjit S. Suri,Luca Saba
标识
DOI:10.1016/j.ejrad.2021.109767
摘要
Cardiovascular disease (CVD) is associated with high mortality around the world. Prevention and early diagnosis are key targets in reducing the socio-economic burden of CVD. Artificial intelligence (AI) has experienced a steady growth due to technological innovations that have to lead to constant development. Several AI algorithms have been applied to various aspects of CVD in order to improve the quality of image acquisition and reconstruction and, at the same time adding information derived from the images to create strong predictive models. In computed tomography angiography (CTA), AI can offer solutions for several parts of plaque analysis, including an automatic assessment of the degree of stenosis and characterization of plaque morphology. A growing body of evidence demonstrates a correlation between some type of plaques, so-called high-risk plaque or vulnerable plaque, and cardiovascular events, independent of the degree of stenosis. The radiologist must apprehend and participate actively in developing and implementing AI in current clinical practice. In this current overview on the existing AI literature, we describe the strengths, limitations, recent applications, and promising developments of employing AI to plaque characterization with CT.
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