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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Cardiologists ask popular AI model ChatGPT to answer questions about cardiology

Can ChatGPT discuss preventive cardiology with patients? Cardiologists with Cleveland Clinic and Stanford University put the popular AI model to the test, sharing their findings in JAMA.

DiA Imaging Analysis, an Israel-based healthcare technology company, has gained U.S. Food and Drug Administration (FDA) clearance for LVivo IQS, a new software solution designed to help users acquire high-quality echocardiography images.

FDA clears new AI-powered cardiac imaging solution

The newly approved software uses artificial intelligence to provide users with real-time feedback related to image quality.

An example of artificial intelligence (AI) automated detection of a intracranial hemorrhage (ICH) in. a CT scan used to send alerts to the stroke acute care team before a radiologist even sees the exam. Example shown by TeraRecon at RSNA 2022.

FDA has now cleared more than 500 healthcare AI algorithms

More than 500 clinical AI algorithms have now been cleared by the FDA, with the majority just in the past couple years.

An example of an FDA cleared radiology AI algorithm to automatically take a cardiac CT scan and identify, contour and quantify soft plaque in the coronary arteries. The Cleerly software then generates an automated report with images, measurements and a risk assessment for the patient. This type of quantification is too time consuming and complex for human readers to bother with, but AI assisted reports like this may become a new normal over the next decade. Example from Cleerly Imaging at SCCT 2022.

Legal considerations for artificial intelligence in radiology and cardiology

There are now more than 520 FDA-cleared AI algorithms and the majority are for radiology and cardiology, raising the question of who is liable if the AI gets something wrong.

Surgeons Operating On Patient

AI model predicts risk of post-operative AFib

Post-operative atrial fibrillation was once viewed as a fairly insignificant issue, but more recent research suggests it can increase a patient’s risk of multiple adverse events. 

New wearable device, no bigger than a stamp, uses AI to deliver on-the-go cardiac imaging

New stamp-sized wearable device uses AI to deliver on-the-go cardiac imaging

The device, designed to be worn for up to 24 hours at a time, uses ultrasound technology and artificial intelligence to track how much blood the user's heart is pumping.

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Cardiologists use video-based AI model to ID coronary artery disease

A team of specialists out of Cedars-Sinai developed the deep learning model using TTEs from nearly 3,000 patients.

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AI in cardiology: A step-by-step guide to developing high-quality algorithms

Overwhelmed or confused by AI and machine learning technology? A new analysis in European Heart Journal hopes to provide some clarity. 

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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.