EchoNext leverages deep-learning analysis of standard ECGs to uncover hidden structural heart disease, potentially turning every routine cardiac test into an early-detection screening tool.
A routine, low-cost heart test may be on the verge of a transformative upgrade thanks to artificial intelligence.
With
advancements in artificial intelligence (AI), a common and affordable test used
in many medical clinics could soon help uncover hidden heart conditions.
Structural heart disease, which
includes problems like valve defects and congenital abnormalities that
interfere with how the heart functions, affects millions across the globe.
Unfortunately, because no cost-effective screening method exists, these
conditions often go unnoticed until they begin to cause serious damage.
“We have colonoscopies, we have
mammograms, but we have no equivalents for most forms of heart disease,” says
Pierre Elias, assistant professor of medicine and biomedical informatics at Columbia University Vagelos
College of Physicians and Surgeons and Medical Director for Artificial
Intelligence at NewYork-Presbyterian.
To address this gap, Elias and a team
of researchers from Columbia University and NewYork-Presbyterian created an
AI-based tool called EchoNext. This system examines data from standard
electrocardiograms (ECGs) to determine which patients might benefit from a
follow-up ultrasound (echocardiogram), a non-invasive imaging test that can
reveal structural heart issues.
According to a study published in Nature,
EchoNext was able to detect structural heart disease from ECG data more
reliably than cardiologists, even those who had access to AI-assisted
interpretation.
“EchoNext basically uses the cheaper
test to figure out who needs the more expensive ultrasound,” says Elias, who
led the study. “It detects diseases cardiologists can’t from an ECG. We think
that ECG plus AI has the potential to create an entirely new screening
paradigm.”
The (Echo)Next step in cardiovascular screening
The ECG is the most used cardiac test
in health care. The test, which measures electrical activity in the heart, is
typically used to detect abnormal heart rhythms, blocked coronary arteries, and
prior heart attack. ECGs are inexpensive, non-invasive, and often administered
to patients who are being treated for conditions unrelated to structural heart
disease.
While
ECGs have their uses, they also have limitations. “We were all taught in
medical school that you can’t detect structural heart disease from an
electrocardiogram,” Elias says.
Echocardiograms, which use ultrasound
to obtain images of the heart, can be used to definitively diagnose valve
disease, cardiomyopathy, pulmonary hypertension, and other structural heart
problems that require medication or surgical treatment.
EchoNext was designed to analyze
ordinary ECG data to determine when follow-up with cardiac ultrasound is
warranted. The deep learning model was trained on more than 1.2 million
ECG–echocardiogram pairs from 230,000 patients. In a validation study across
four hospital systems, including several NewYork-Presbyterian campuses, the
screening tool demonstrated high accuracy in identifying
structural heart problems, including heart failure due to cardiomyopathy, valve
disease, pulmonary hypertension, and severe thickening of the heart.
In a head-to-head comparison with 13
cardiologists on 3,200 ECGs, EchoNext accurately identified 77% of structural
heart problems. In contrast, cardiologists making a diagnosis with the ECG data
had an accuracy of 64%.
Finding undiagnosed structural heart problems
To see how well the tool worked in
the real world, the research team ran EchoNext in nearly 85,000 patients
undergoing ECG who had not previously had an echocardiogram. The AI tool
identified more than 7,500 individuals–9% –as high-risk for having undiagnosed
structural heart disease. The researchers then followed the patients over the
course of a year to see how many were diagnosed with structural heart disease.
(The patients’ physicians were not aware of the EchoNext deployment so they
were not influenced by its predictions).
Among the individuals deemed
high-risk by EchoNext, 55% went on to have their first echocardiogram. Of
those, nearly three-quarters were diagnosed with structural heart disease—twice
the rate of positivity when compared to all people having their first
echocardiogram without the benefit of AI.
At the same positivity rate, if all
the patients identified by EchoNext as high-risk had had an echocardiogram,
about 2,000 additional patients may have been diagnosed with a potentially
serious structural heart problem.
“You
can’t treat the patient you don’t know about,” Elias says. “Using our
technology, we may be able to turn the estimated 400 million ECGs that will be
performed worldwide this year into 400 million chances to screen for structural
heart disease and potentially deliver life-saving treatment at the most
opportune time,” Elias says.
Next steps
Elias and his team released a de-identified dataset to help other health systems improve screening for heart disease. The researchers have also launched a clinical trial to test EchoNext across eight emergency departments.
No comments:
Post a Comment