HeartFlow, Inc., a leader in revolutionizing precision heartcare, today announced new data which indicate that the information provided by the HeartFlow FFRct Analysis was a superior predictor of 10-year outcomes compared to the severity of a coronary stenosis shown on a coronary computed tomography angiogram (CTA). The 10-year results from the DISCOVER-FLOW trial were presented as a late-breaking trial during the virtual EuroPCR conference.

“When diagnosing and managing patients with coronary artery disease, physicians want to understand the impact of treatment. We want to be able to provide immediate symptom relief and have confidence that the treatment we are selecting, specifically the possible benefits of revascularization, will have a positive, long-lasting impact,” said Bon-Kwon Koo, MD, PhD, FACC, Professor of Internal Medicine, Seoul National University, and Director of the Cardiovascular Center and Chair of the Cardiology Division, Seoul National University Hospital. “The 10-year outcomes indicate that FFRct is a more useful non-invasive test than coronary CT alone as the information provided helps physicians with long-term risk stratification and treatment selection for patients with coronary artery disease.”

The DISCOVER-FLOW trial was the first-in-human trial evaluating the HeartFlow Analysis and enrolled 103 patients from 4 international hospitals. All patients received a HeartFlow Analysis following a coronary CT scan.

“It’s rare to have the opportunity to follow patients for 10 years in clinical trials and we were pleased to confirm the long-term prognostic value of FFRct through the DISCOVER-FLOW trial,” said Campbell Rogers, MD, FACC, Chief Medical Officer, HeartFlow. “These new data are a reflection of the company’s commitment to providing comprehensive clinical evidence on the diagnostic accuracy, safety, efficacy and utility of the HeartFlow Analysis to help clinicians engage patients in the decision-making process and confidently diagnose and optimize treatment for patients with coronary artery disease.”

About the HeartFlow FFRct Analysis

Starting with a standard coronary CTA, the HeartFlow Analysis leverages deep learning and highly trained analysts to create a digital, personalized 3D model of the heart. The HeartFlow Analysis then uses powerful computer algorithms to solve millions of complex equations to simulate blood flow and provides FFRct values along the coronary arteries. This information helps physicians evaluate the impact a blockage may be having on blood flow and determine the optimal course of treatment for each patient. A positive FFRct value (≤0.80) indicates that a coronary blockage may be impeding blood flow to the heart muscle to a degree which may warrant invasive management.

Data demonstrating the safety, efficacy and cost-effectiveness of the HeartFlow Analysis have been published in more than 425 peer-reviewed publications, including long-term data out to five years. The HeartFlow Analysis offers the highest diagnostic performance available from a non-invasive test.¹ To date, clinicians around the world have used the HeartFlow Analysis for more than 75,000 patients to aid in the diagnosis of heart disease.

About HeartFlow, Inc.

HeartFlow, Inc. is a leader in revolutionizing precision heartcare, uniquely combining human ingenuity with advanced technology. Our non-invasive HeartFlow FFRct Analysis leverages artificial intelligence to create a personalized 3D model of the heart. By using this model, clinicians can better evaluate the impact a blockage has on blood flow and determine the best treatment for patients. Our technology is reflective of our Silicon Valley roots and incorporates decades of scientific evidence with the latest advances in artificial intelligence. The HeartFlow FFRct Analysis is commercially available in the United States, Canada, Europe and Japan. For more information, visit www.heartflow.com.

1. Driessen, R., et al. Comparison of Coronary Computed Tomography Angiography, Fractional Flow Reserve, and Perfusion Imaging for Ischemia Diagnosis. J Am Coll Cardiol. 2019;73(2),161-73.

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