Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

Example of an automated artificial intelligence (AI) assessment of soft coronary plaque from a CT scan from the vendor Cleerly. The AI gives a very detailed report of all the plaque in all the coronary vessels. Some cardiology experts believe this may be the way of the future in screening patients for early coronary disease and monitoring the impact of prevention efforts such as statins to determine if more aggressive treatments are needed.

Medicare administrative contractors approve coverage of AI-enabled quantitative CT

Four of the seven Medicare Administrative Contractors (MACs) announced they will now cover artificial intelligence-enabled quantitative coronary tomography (AI-QCT) and coronary plaque analysis (AI-CPA). 

HeartFlow Plaque Analysis

CMS updates Medicare coverage for AI-powered coronary plaque assessments

The new policy goes into effect in November, improving Medicare coverage for a technology that has rapidly gained momentum in recent years.

Ron Blankstein, MD, Brigham and Womens Hospital, explains a study using AI opportunistic screening in non-cardiac CT scans looking for coronary artery disease.

Use of AI opportunistic screening in CT for cardiovascular disease

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

artificial intelligence in cardiology

FDA grants AI-powered ECG screening tool for aortic stenosis its breakthrough device designation

The FDA clearly sees significant potential in this new screening software from New York-based AccurKardia.

Left, coronary CT angiography of a vessel showing plaque heavy calcium burden. Right, image showing color code of various types of plaque morphology showing the complexity of these lesions. The right image was processed using the FDA cleared, AI-enabled plaque assessment from Elucid.

FDA clears new software for AI-powered CCTA assessments

Elucid's PlaqueIQ was trained to turn CCTA images into interactive 3D reports that help physicians visualize the presence of atherosclerosis.

Breast arterial calcifications (BACs) identified on screening mammograms may help identify women who face a heightened risk of developing cardiovascular disease (CVD), according to a new analysis published in Clinical Imaging.

Younger women with breast arterial calcifications are at markedly higher risk of major cardiovascular events

Currently, there is no standardized reporting requirement related to BACs, and ACR classifies reporting vascular calcifications on breast imaging as optional. 

voice audio recording smartphone

AI detects hypertension in voice recordings

A machine learning-powered smartphone app was trained to detect hundreds of biomarkers in the human voice, using even the tiniest detail to anticipate when patients may present with symptoms of hypertension. 

Harlan Krumholz, MD, SM, editor-in-chief of the Journal of the American College of Cardiology (JACC), and a cardiologist and the Harold H. Hines, Jr. Professor of Medicine at the Yale school Medicine, explains some of the key technology advances he is watching across cardiology.

JACC editor excited by progress during a 'very important moment' for cardiology

Harlan Krumholz, MD, editor-in-chief of the Journal of the American College of Cardiology, explains some of the key technology and treatment trends he has his eyes on.

Around the web

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.