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. 

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AI-powered ECG screening boosts patient outcomes—when clinicians give it a chance

New research out of Mayo Clinic found that clinicians who listened to AI-based treatment recommendations were more successful at identifying patients with low ejection fraction. 

AI-generated coronary tree from a patient's CT scan showing a color code of areas of interest for plaque burden from the Cleerly software shown at SCCT 2022.

VIDEO: The role of AI in cardiac imaging

Ed Nicol, MD, president-elect of the Society of Cardiovascular Computed Tomography, provided us with an exclusive look at how AI is expected to change cardiac imaging.

Left, HeartFlow's RoadMap analysis enables cardiac CT readers to identify stenoses in the major coronary arteries. The AI provides visualization and quantification of the location and severity of anatomic narrowings. Right image, HeartFlow's Plaque Analysis AI algorithm automates assessment of coronary plaque characteristics and volume on CCTA exams to greatly reduce the time it takes to manually assess and quantify these features.

HeartFlow gains FDA clearance for 2 new AI-powered imaging assessments

The solutions, Plaque Analysis and RoadMap Analysis, both use coronary CT angiography to provide clinicians with a noninvasive look at patients who present with coronary artery disease and face a heightened myocardial infarction risk.

AI model uses ECG data to identify new cases of AFib

“Our ultimate goal is to prevent strokes," one Mayo Clinic electrophysiologist said. "I believe the current study has brought us one step closer.”

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Biotronik announces collaboration with AliveCor as first in a series of strategic partnerships to disrupt cardiac digital health with AI-enabled solutions

BIOTRONIK has announced a new partnership with AliveCor.

Validation and testing of all artificial intelligence (AI) algorithms is needed to eliminate any biases in the data used to train the AI, according to HIMSS.

VIDEO: Understanding biases in healthcare AI

Validation and testing of all algorithms is needed to eliminate any biases in the data used to train the AI, according to Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America.

Impella Heart Pump Abiomed RECOVER IV RCT cardiogenic shock

Regulatory Roundup: FDA clears AI model for RV/LV ratios, approves calcium-blocking TAVR valve and much more

Read our review of some of the biggest FDA-related stories that have hit cardiology in the last month, including news from Viz.ai, Edwards Lifesciences, Abiomed and Medtronic. 

A study published this week in the Journal of the American College of Cardiology (JACC): Cardiovascular Imaging shows artificial intelligence (AI) algorithms can more rapidly and objectively determine calcium scores in computed tomographic (CT) and positron emission tomographic (PET) images than physicians.[1] The AI also performed well when the images were obtained from very-low-radiation CT attenuation scans. https://doi.org/10.1016/j.jcmg.2022.06.006

Artificial intelligence can objectively determine cardiac calcium scores faster than doctors

A new study shows artificial intelligence (AI) algorithms can more rapidly and objectively determine calcium scores in CT and PET/CT images than physicians.

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Around the web

Health Imaging
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.

Health Imaging
New imaging protocols proposed to curb rise of cardiovascular infections

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