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AI measurements of heart scans more strongly linked to patient survival than clinician measurements

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AI measurements of heart scans more strongly linked to patient survival than clinician measurements

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Artificial intelligence (AI) measurements of heart function from MRI scans are more strongly linked to how long patients live after their scan than measurements made by clinicians, suggesting that AI could provide a useful first-line approach to measuring heart function. This is according to research led by City St George's, University of London and University College London, and published in The Lancet Digital Health.

The research focused on ejection fraction—the most important measure of heart function. It describes how effectively the heart pumps blood and acts as a "gatekeeper" for many treatments.

Ejection fraction is widely used by doctors to guide treatment decisions for people with heart disease. It helps doctors decide whether patients may benefit from specialist heart failure treatments, implanted heart devices and procedures to improve blood flow to the heart. It is used to gauge surgical risk and to monitor heart function during chemotherapy.

In the largest study of its kind, researchers analyzed heart MRI scans from 27,382 patients undergoing investigation for known or suspected heart conditions in the U.K. and United States. Patients were followed for an average of more than five years, during which 3,458 deaths occurred.

The team compared measurements of ejection fraction generated by an AI tool with those produced by experienced clinicians assessing cardiac MRI scans.

They found that AI-derived measurements of ejection fraction were slightly but significantly better at predicting which patients were at increased risk of death than clinician-derived measurements.


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