Abstract
Patient-specific models of blood flow constructed from coronary CT angiography (cCTA) images and using computational fluid dynamics are poised to transform the diagnosis of heart disease by providing a safer, less expensive and more efficient procedure as compared to the standard of care that often involves nuclear imaging and invasive diagnostic cardiac catheterizations. Such image-based computations require an accurate segmentation of the coronary artery lumen from cCTA images and employ biologic principles relating form (anatomy) to function (physiology). Leveraging research originally performed at Stanford University, HeartFlow has developed a non-invasive test, FFRCT, based on computing flow and pressure in the coronary arteries . FFRCT has been validated against invasive pressure measurements in more than 800 patients and demonstrated to improve care in numerous clinical studies to date . At present, FFRCT has been used for more than 20,000 patients in routine practice for clinical decision making in the United States, Canada, Europe, and Japan. In the United States, the Centers for Medicare and Medicaid Services and the majority of private insurance companies reimburse physicians for using FFRCT. In the United Kingdom, the National Institute for Health and Care Excellence (NICE) evaluated FFRCT and concluded it was safe, accurate and cost-savings in the U.K. healthcare system. In April 2018 NHS England selected HeartFlow to receive NHS funding to enable clinical use of FFRCT through the Innovation and Technology Payment (ITP) program.
Patient data is uploaded to the HeartFlow application running on Amazon Web Services and then image analysis methods leveraging deep learning are used to create an initial patient-specific geometric model, which is inspected and corrected by a trained analyst. Next fully-automated mesh generation techniques are used to discretize the model. Computational fluid dynamic analysis is performed on AWS to compute the blood flow solution. Results are returned to the physicians through a web interface or mobile application. New developments including the possibility of planning treatments and evaluating risk of rupture of coronary plaques will be discussed.
Speaker Biography:
Charles A. Taylor received his B.S. degree in Mechanical Engineering in 1987, an M.S. degree in Mechanical Engineering in 1991 and his M.S. Degree in Mathematics in 1992 from Rensselaer Polytechnic Institute. He completed his Ph.D. in Mechanical Engineering at Stanford University in 1996 under the joint supervision of Thomas J.R. Hughes, Ph.D. and Christopher K. Zarins, M.D. He joined the faculty at Stanford in 1997 where he developed an internationally recognized research program focused on the development of computer modeling and imaging techniques for cardiovascular disease research, device design and surgery planning. He pioneered the field of image-based modeling by performing the first computer simulations of blood flow in patient-specific models derived from medical imaging data. He has published more than 140 peer-reviewed scientific papers in internationally refereed journals, more than 250 peer-reviewed conference abstracts and has more than 275 issued or pending patents. While on the full-time faculty at Stanford, he supervised 30 PhD students and Postdoctoral Fellows. Dr. Taylor co-founded HeartFlow, Inc. in 2007 where he serves as the Chief Technology Officer and leads the technology development effort. He is an Adjunct Professor of Bioengineering at Stanford University, a Part-time Professor of Biomedical Engineering, Technical University Eindhoven, and an Adjunct Professor of Computational Engineering and Sciences, University of Texas, Austin.