HeartFlow's AI-powered medical technology debuts on Nasdaq
Co-founded by NSF-funded researcher Charles Taylor, HeartFlow is now a publicly traded company, offering its innovative solution for diagnosing coronary artery disease using AI and medical imaging
Recent rapid advancements in artificial intelligence have led to the emergence of innovative interdisciplinary fields such as computational medicine — a domain that leverages AI's strength to identify diseases such as coronary artery disease (CAD).
CAD is a major health concern in the U.S., costing hundreds of billions of dollars every year. As the most common type of heart disease, CAD is characterized by plaque buildup in the coronary arteries — a condition that restricts or blocks blood flow to the heart. CAD is estimated to cause one heart attack every 40 seconds and one out of every five deaths. Furthermore, many of the estimated 18 million adults in the U.S. and 315 million people globally living with CAD either have no symptoms or symptoms that go unrecognized, making it a "silent killer."
Tackling this critical challenge is HeartFlow, a medical technology company cofounded by NSF-funded researcher Charles Taylor at The University of Texas at Austin. HeartFlow is transforming the way cardiovascular disease is diagnosed and treated. Its patented, noninvasive technologies provide unprecedented insights into coronary blood flow, helping to prevent heart attacks. Today, HeartFlow is recognized as the most widely adopted AI solution in U.S. health care.
Early NSF grant fuels research behind AI health care startup, HeartFlow
In the early 2000s, as analytics moved into complex simulation technology across various fields, including medicine, pioneering researchers like Taylor realized the significant impact it could have in diagnosing and treating diseases.
Recognizing the novelty and potential of Taylor's proposed research to understand cardiovascular disease, NSF awarded him (then at Stanford) and his team (collaborators at Rensselaer Polytechnic and The University of Texas at Austin, as well as multiple doctoral students and postdoctoral fellows at Stanford) roughly $3.7 million in 2002. This investment from the NSF Directorate for Computer and Information Science and Engineering supported a five-year project to develop the computational methods necessary to simulate blood flow in the cardiovascular system from medical imaging data, opening a new window into detecting and assessing CAD.
Leveraging this foundational research in complex simulations, Taylor cofounded Cardiovascular Simulation in 2007, later renamed HeartFlow in 2010. HeartFlow's first product, the Fractional Flow Reserve derived from Computed Tomography (FFRCT) analysis, was cleared by the U.S. Food and Drug Administration (FDA) and became commercially available in the U.S. in 2014.
This groundbreaking technology offered a noninvasive technique to test for and assess the severity of coronary artery disease. From standard coronary CT angiography (CCTA) images, FFRCT analysis generated a 3D model, or digital twin, of a patient's heart and simulated blood flow through it, revealing pressure differences in the arteries. This allowed physicians to visualize potential arterial blockages that could lead to a heart attack and provide a functional evaluation of coronary artery disease.
NSF renews funding for HeartFlow
In 2018, HeartFlow enhanced its technology by launching the FFRCT 2nd Generation, which featured a new Cloud-based infrastructure. This enhancement enabled the transfer of data to clinicians faster and more securely. It also allowed HeartFlow to utilize the data it received from its global community of clinicians and integrate this vast dataset into AI machine learning to continuously improve the technology.
HeartFlow's momentum continued, earning a spot on Fast Company's 2019 list of "The World's Most Innovative Companies." That same year, the NSF Partnerships for Innovation Program (now under the NSF Technology, Innovation and Partnerships Directorate) awarded a grant to Thomas Hughes at The University of Texas at Austin to partner with Taylor and his team at HeartFlow to develop a patient-specific prototype to detect, noninvasively, vulnerable plaques. These vulnerable plaques typically contain lipid pools in the artery walls and can rupture to cause blood clots. Vulnerable plaques are estimated to be the cause of approximately two-thirds of heart attacks.
New AI-driven platform is a game-changer for coronary artery disease
In 2021, HeartFlow released the 3rd Generation of FFRCT, followed by two new, AI-powered products: Plaque Analysis and Roadmap Analysis. Together, FFRCT, Plaque and Roadmap analyses make up HeartFlow's novel suite of FDA-approved technologies:
- Roadmap Analysis provides visualization and quantification of the location and severity of anatomic narrowings (stenoses) in coronary arteries based on CCTA images.
- FFRCT Analysis assesses the impact of these narrowings on coronary blood flow by creating a personalized 3D model of blood flow simulation.
- Plaque Analysis delivers critical information on the nature and volume of coronary plaque within the arteries.
Together, these three analyses make up an integrated platform to provide improved AI-powered risk scoring to identify both symptomatic and asymptomatic patients at risk of heart attack, from just a single CCTA scan.
HeartFlow leads the market in transforming cardiovascular care
Today, HeartFlow is one of the most successful digital health care companies in the world. It was recently named one of Fast Company's Most Innovative Companies in Medical Devices for 2025 and won the Innovation in Cardiac Imaging award at the 2025 Global Cardiovascular Awards.
For his pioneering work in the field of predictive, simulation-based medicine, Taylor was elected to the National Academy of Engineering class of 2024. This research forms the foundation of HeartFlow's award-winning, AI-based technologies, which equip clinicians with the tools to identify and diagnose CAD earlier, and patients better understand and manage their disease for the best possible health outcomes.
Reflecting on the impact of NSF's early support for his research, Taylor remarked, "This funding enabled me, my collaborators and my students to solve several of the most important scientific problems needed to model blood flow in patient-specific models of the cardiovascular system created from medical imaging data." He continued, "Since that initial NSF investment, HeartFlow has subsequently raised more than $1.2 billion of capital, and its products have been used at over 1,500 hospitals in the U.S. to diagnose heart disease in over 400,000 patients. On a personal level, I can honestly say that NSF funding not only created an entirely new (and better) way to diagnose heart disease but was instrumental in my career and that of all the students that worked on this project."
Reference to a company does not constitute an endorsement by the U.S. National Science Foundation.