In a new study from Cedars-Sinai Medical Center, researchers show that an artificial intelligence (AI) tool could effectively identify and distinguish between two life-threatening heart conditions.
The two heart conditions are cardiac amyloidosis and hypertrophic cardiomyopathy. They are very easy to miss in health checks.
Cardiac amyloidosis often called “stiff heart syndrome” is a disorder caused by deposits of an abnormal protein (amyloid) in the heart tissue.
As amyloid builds up, it takes the place of the healthy heart muscle, making it difficult for the heart to work properly.
Hypertrophic cardiomyopathy is a disease that causes the heart muscle to thicken and stiffen.
As a result, it’s less able to relax and fill with blood, resulting in damage to heart valves, fluid buildup in the lungs, and abnormal heart rhythms.
Although separate and distinct conditions, cardiac amyloidosis and hypertrophic cardiomyopathy often look very similar to each other on an echocardiogram, the most commonly used cardiac imaging diagnostic.
Importantly, in the very early stages of the disease, each of these cardiac conditions can also mimic the appearance of a non-diseased heart that has progressively changed in size and shape with aging.
In the current study, the two-step, novel algorithm was used on over 34,000 cardiac ultrasound videos from Cedars-Sinai and Stanford Healthcare’s echocardiography laboratories.
When applied to these clinical images, the algorithm identified specific features—related to the thickness of heart walls and the size of heart chambers—to efficiently flag certain patients as suspicious for having potentially unrecognized cardiac diseases.
The AI tool picks up subtle cues on ultrasound videos that distinguish between heart conditions that can often look very similar to more benign conditions.
Researchers plan to soon launch clinical trials for patients flagged by the AI algorithm for suspected cardiac amyloidosis.
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The study was conducted by Grant Duffy et al., and published in JAMA Cardiology.
