Personalized Blood Flow Simulation from an Image-Derived Model: Changing the Paradigm for Cardiovascular Diagnostics

Abstract: Coronary heart disease is the leading cause of mortality worldwide, accounting for 1/3 of all global deaths.  Treatment of stable coronary heart disease is typically performed by medication/lifestyle for a lower disease burden or PCI (stenting) for a greater disease  burden.  The choice between these treatments is best determined by an invasive diagnostic test that measures blood flow through a diseased area.  Unfortunately, this invasive diagnostic test is expensive, dangerous and usually finds a lower disease burden.  We are working to change the diagnostics paradigm with blood flow simulation in a personalized heart model that is derived from cardiac CT angiography images.  This simulation-based diagnostic is the first clinically available diagnostic that utilizes personalized simulation and is much safer and more comfortable for the patient as well as less expensive.  Our diagnostic depends on a hyperaccurate image segmentation of the coronary arteries, physiological modeling and accurate computational fluid dynamics.  In this talk I will discuss the algorithms that drive this technology, the machine learning that we’re doing with our database of segmented images and personalized hemodynamics, and the successful clinical trials that have proven the diagnostic accuracy and benefit to patients.

Bio: Leo Grady is the Vice President of Research and Development at HeartFlow since 2012.  Prior to joining HeartFlow, he worked at Siemens Corporate Research for nine years as a Principal Research Scientist following his PhD at Boston University.  His work has focused on a range of computer vision and medical imaging applications in image segmentation and machine learning.  He has written two books on computer vision and data analysis using graph theory, is an editor of several journals in computer vision and was recently inducted as a Fellow of the American Institute of Medical and Biomedical Engineers.