Physician-researchers at Cedars-Sinai’s Smidt Heart Institute have created an artificial intelligence (AI) tool that can effectively identify and distinguish between two life-threatening heart conditions that are often easy to miss: hypertrophic cardiomyopathy and cardiac amyloidosis. The new findings were published in JAMA Cardiology.
“Both of these heart conditions are difficult to identify accurately, even for expert cardiologists, and patients often go years, even decades, before receiving a correct diagnosis,” said David Ouyang, MD, cardiologist at the Smidt Heart Institute. and lead author of the study. “Our AI algorithm can identify disease patterns that cannot be seen with the naked eye, then use those patterns to predict the correct diagnosis.”
The new two-step algorithm has been used on more than 34,000 cardiac ultrasound videos from Cedars-Sinai and Stanford Healthcare echocardiography labs. When applied to these clinical images, the algorithm identified specific features – related to the thickness of the heart walls and the size of the heart chambers – to effectively flag certain patients as suspects of having potentially unhealthy heart diseases. recognized.
“The algorithm identified high-risk patients more accurately than the well-trained eye of a clinical expert,” Ouyang said. “That’s because the algorithm picks up subtle cues on ultrasound videos that distinguish heart conditions that can often appear very similar to more benign conditions, as well as to each other, on initial examination.”
Without comprehensive testing, cardiologists struggle to distinguish between similar-looking diseases and changes in the shape and size of the heart that can sometimes be considered part of normal aging. This algorithm accurately distinguishes not only abnormal from normal, but also life-threatening underlying cardiac conditions that may be present – with warning signals that are now detectable long before the disease progresses clinically to the point where it can impact health outcomes. Obtaining an earlier diagnosis allows patients to start effective treatments sooner, prevent adverse clinical events and improve their quality of life.
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 healthy heart muscle, making it difficult for the heart to function properly. Cardiac amyloidosis often goes undetected because patients may show no symptoms or only show symptoms sporadically.
The disease tends to affect older black men or patients with cancer or diseases that cause inflammation. Many patients are from underserved communities, making the study results an important tool for improving healthcare equity, Ouyang said.
Hypertrophic cardiomyopathy is a disease that causes thickening and stiffening of the heart muscle. As a result, it is less able to relax and fill with blood, leading to heart valve damage, fluid buildup in the lungs, and abnormal heart rhythms.
Although separate and distinct conditions, cardiac amyloidosis and hypertrophic cardiomyopathy often look very similar on an echocardiogram, the most commonly used cardiac imaging diagnosis.
It is important to note that in the very early stages of the disease, each of these heart conditions can also mimic the appearance of a healthy heart that has gradually changed in size and shape with aging.
“One of the most important aspects of this AI technology is not only the ability to distinguish abnormal from normal, but also to distinguish these abnormal conditions, because the treatment and management of each heart disease is very different,” Ouyang said.
The hope, Ouyang said, is that this technology can be used to identify patients very early in the course of their disease. Indeed, clinicians know that sooner is always better to get the most out of the therapies available today, which can be very effective in preventing the worst possible outcomes, such as heart failure, hospitalizations and sudden death. .
The researchers plan to launch clinical trials soon for patients flagged by the AI algorithm for suspected cardiac amyloidosis. Patients enrolled in the trial will be seen by experts from the Cardiac Amyloidosis Program at the Smidt Heart Institute, one of the few West Coast programs dedicated to the disease.
A clinical trial for patients flagged by the algorithm for suspected hypertrophic cardiomyopathy has just begun at Cedars-Sinai.
“The use of artificial intelligence in cardiology has evolved rapidly and dramatically in a relatively short period of time,” said Susan Cheng, MD, MPH, director of the Healthy Aging Research Institute at Smidt Heart Institute Department of Cardiology and study co-lead author. “These remarkable advances – which span research and clinical care – can have a huge impact on the lives of our patients.