The gold standard for assessing coronary artery disease—the leading cause of death in the United States—involves placing a thin tube into the heart to examine blood flow. Each year, over 1 million patients have this procedure, called catheterization, when they don’t really need it because the diagnostic imaging shows unreliable information.

Lardo, a professor in the Heart and Vascular Institute and the Department of Biomedical Engineering, along with Rajat Mittal, a mechanical engineering professor, patented a technology in 2014 to accurately and noninvasively predict, in minutes, who needs a catheterization and who does not.

The technology combines an algorithm, or formula calculated by a computer, and a CT scan. After injecting the patient with a contrast agent, the clinician performs a CT scan to see how the contrast agent disperses. The software then examines the 3-D CT scan and creates an information-rich map of the blood flow and pressure throughout the coronary vessels.

“No other noninvasive imaging modality can provide this type of information,” says Lardo. “It’s a unique intersection where medicine meets engineering to create a solution for a large unmet need. This is precisely the information that the physician needs.”

Initial validation studies of the technology are complete, and the next step will be human validation testing to assist in gaining approval from the Food and Drug Administration.