Artificial intelligence predicts heart attack risk from cardiac MRI for the first time
For the first time, artificial intelligence has been proven to instantly measure blood flow and predict a patient’s risk of a heart attack, researchers revealed Friday.
Experts with University College London recently harnessed this new tool to quickly analyze cardiovascular magnetic resonance images. It then allowed them to accurately predict the chance of myocardial infarction, stroke and death, according to their results, published Feb. 14 in Circulation.
With heart disease the leading cause death worldwide, scientists believe their intervention has the potential to save thousands of lives in the not-too-distant future.
"The predictive power and reliability of the AI was impressive and easy to implement within a patient's routine care,” lead author Kristopher Knott, with the UCL Institute of Cardiovascular Science, said in a statement. “The calculations were happening as the patients were being scanned, and the results were immediately delivered to doctors."
Reduced blood flow is a common symptom of heart disease and is often treatable. But many such assessments are risky, invasive and time-consuming for doctors.
In this largest study of its kind, Knott and colleagues took cardiovascular MRI scans of more than 1,000 patients at two London hospitals. AI then analyzed the images and helped to instantaneously quantify blood flow to the heart and deliver measurements to the care team. Clinicians then compared these AI-created blood flow results with the health outcomes of each patient to determine their risk of such adverse events.
The study was funded by the British Heart Foundation and National Institute for Health Research, among others. NIH experts also assisted in developing the automated AI techniques used in the study, according to the announcement.
"This study demonstrates the growing potential of artificial intelligence-assisted imaging technology to improve the detection of heart disease and may move clinicians closer to a precision medicine approach to optimize patient care. We hope that this imaging approach can save lives in the future,” added Peter Kellman, MD, a study coauthor and director of the Medical Signal and Image Processing Program at the National Heart, Lung and Blood Institute, which is part of NIH.
Marty Stempniak has covered healthcare since 2012, with his byline appearing in the American Hospital Association's member magazine, Modern Healthcare and McKnight's. Prior to that, he wrote about village government and local business for his hometown newspaper in Oak Park, Illinois. He won a Peter Lisagor and Gold EXCEL awards in 2017 for his coverage of the opioid epidemic.