Cardiac computed tomography (CT) in 2020 is at the vanguard of cardiovascular prevention, structural interventions, machine learning and proven improvement in cardiovascular outcomes. There have been several notable trends in cardiovascular computed tomography that will advance the care of patients with heart disease.

Most notably, the findings from the recent ISCHEMIA trial, the recent 5-year outcomes data from the SCOT-HEART trial demonstrating a reduction in death or non-fatal myocardial infarction through a cardiac CT strategy and the updated 2019 European Society of Cardiology guidelines on chronic coronary syndromes continue to solidify the role of CT as a first line test for symptomatic patients with suspected CAD.

Moving from a paradigm of coronary artery stenosis to that of identification of high-risk atherosclerosis by qualitative and quantitative methods by cardiac CT remains an important trend. Several recent studies have demonstrated the benefits of treatment therapies such as statins, colchicine and direct oral anticoagulants in causing plaque inhibition or preventing plaque progression.

The inclusion of coronary artery calcium in the 2018 American College of Cardiology/American Heart Association cholesterol prevention guidelines for asymptomatic patients aged 40-75 years, without diabetes and at intermediate ASCVD risk caps years of research demonstrating prognostic significance and enhanced risk stratification. New frontiers in coronary artery calcium imaging extend to novel populations such as familial hyperlipidemia and use as an endpoint in clinical trials.

In structural heart disease, cardiac CT has become the gold standard in planning of transcatheter aortic valve interventions. In transcatheter mitral interventions, there are a number of important anatomic considerations that include annular sizing, identification of the mitral annulus to neighboring structures (eg risk stratification for left ventricular outflow tract obstruction), annular sizing, landing zone characterization and pre-determination of coaxial angiographic views best identified by CT. As transcatheter mitral valve repair evolves, CT will continue to be primary to successful treatment.

In the realm of machine learning the field asks whether the future has arrived for cardiovascular CT? In the current digital age, it is estimated that global healthcare data encompasses 153 exabytes/year. To put that in context, 1 exabyte = 1 billion gigabytes and 5 exabytes = all the words ever spoken by humans. Furthermore, it is estimated that the average cardiac imaging specialist reporting 8 CT scans per day must process 650 million voxels of day per day (source: Dr. James Min) to encompass both cardiac structures as well as quantitative atherosclerotic plaque types identified by cardiac CT. Novel machine learning technologies on the horizon may enable improved, more accurate and rapid identification and integration of these variables. This, in turn may enable physicians to focus less on data processing and more on direct patient care.

Lastly, improving access to cardiac CT through include new education training guidelines, ensuring appropriate use, and improving reimbursement remains an important goal of cardiac imaging societies. Recent efforts led by the leadership of the American College of Cardiology, Society of Cardiovascular CT and American College of Radiology aim to ensure that clinicians and patients have the ability to adopt many of the advancements discussed in this piece fully into daily clinical practice.

Social media, has provided a means of rapid dissemination of the latest in cardiac CT knowledge around the world. The horizon is vast for cardiac CT in 2020and beyond!