Echocardiography has long been considered a workhorse of cardiac imaging, and now it has become the natural training ground for artificial intelligence, Akhil Narang, MD, a cardiologist and director of the Electrocardiography Lab at Northwestern Medicine’s Bluhm Cardiovascular Institute in Chicago said in an episode of Becker’s “Cardiology + Heart Surgery Podcast.”
“Echo ends up being the natural training ground for AI in cardiology for a variety of reasons — the volume, variability and the nature of the data itself,” Dr. Narang said. “It’s cheaper than cardiac CT, more accessible than cardiac MRI, and it doesn’t carry the radiation or contrast concerns that some other modalities do. That ubiquity means there’s a massive, naturally occurring dataset — millions of studies throughout the country and the world each year, often paired with outcomes — and that simply doesn’t exist at the same scale for other modalities.”
Despite guidelines and recommendations, there can be a difference in how studies are interpreted based on the expertise of the interpreter, but with AI, “we can standardize outputs and reduce inconsistency,” Dr. Narang said.
The promise of enhanced efficiency comes with changes in how the workforce will handle patient volumes, Amogh Karnik, MD, a cardiologist at Bluhm Cardiovascular Institute, said in the podcast. AI-augmented echocardiography has the potential to automate measurements that traditionally would be performed manually by sonographers and echocardiographers. This would speed up the interpretation process, but also lead to higher patient volume.
“That has a real impact on the workforce, because it means individual sonographers and readers are dealing with more images and studies on a daily basis,” Dr. Karnik said. “How that evolves as these tools become more embedded in daily workflows is still to be determined. There’s more evidence needed on the actual impact on efficiency and workload — and on whether we’re placing too much stress on the system when it comes to burnout.”
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