Kennesaw State researcher earns American Heart Association award for innovative study on heart disease diagnostics

(Press-News.org) Kennesaw State University researcher Chen Zhao has earned the 2025 American Heart Association Institutional Research Enhancement Award (AIREA) for his unique research on non-invasive blood flow prediction in cardiovascular disease diagnosis.

The $194,032 award will allow Zhao to continue developing technology aimed at evaluating Fractional Flow Reserve (FFR), a measurement used to diagnose coronary artery disease (CAD). According to the Centers for Disease Control and Prevention, CAD is the leading cause of death in the United States, with an average of 375,000 to 400,000 people perishing from it per year.

Traditional wired-FFR measurement methods are invasive, time-consuming, and costly, or rely on computational fluid dynamics-based methods, which often take hours to obtain results. Zhao’s research aims to build a non-invasive method for FFR evaluation while reducing the evaluation time to just seconds, making diagnoses faster and less risky for patients.

The technology Zhao is developing uses coronary computed tomography angiography (CCTA) scans to measure FFR. Traditionally, doctors measure FFR by inserting a wire into the artery to assess the pressure differences before and after a blockage. However, this method carries certain risks and can result in significant discomfort for patients.

“This research is not just about improving diagnosis; it’s about transforming the entire workflow in cardiovascular disease diagnosis,” said Zhao, an assistant professor of computer science in the College of Computing and Software Engineering. “By shortening the time it takes to predict blood pressure and blood flow and converting the invasive technique to non-invasive technique, we can provide real-time results to doctors, allowing them to make faster decisions. This could potentially save lives.”

CCSE Dean Sumanth Yenduri applauded Zhao for this groundbreaking research and his drive to help others.

"Dr. Zhao's research is a prime example of the transformative work happening within the College of Computing and Software Engineering,” Yenduri said. “His contributions bridge the gap between computer science and healthcare, showcasing the impact of our interdisciplinary approach." 

Zhao’s journey into heart research began during his doctoral studies, where he first started working with cardiovascular imaging techniques. During that time, he became fascinated with the potential to combine computer science with medical imaging to improve diagnostic processes.

The idea of using CCTA to predict FFR came from his desire to eliminate the risks associated with traditional invasive methods. While CCTA scans are commonly used to capture images of coronary arteries, calculating FFR from these images using traditional computational flow dynamics methods takes a lot of time and effort. Zhao saw the potential for deep learning and physics-informed neural network to revolutionize this process.

Zhao’s vision extends far beyond his current research. He hopes to push the boundaries of what AI can achieve in medical diagnostics. By refining his technology, he aims to not only improve heart disease diagnoses but also expand his work to other areas of medicine.

“We’re just scratching the surface with what we can do in medical imaging,” Zhao said. “I’m hopeful that this research can lead to breakthroughs in other areas as well. The ultimate goal is to improve patient outcomes and quality of life on a global scale.”

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