Developing a Cloud-Based Infrastructure to Accelerate Analysis of Coronary Bifurcation Lesion Intervention
DescriptionCoronary artery disease (CAD) is a highly prevalent type of heart disease in the US, causing more than 360,000 deaths in 2017 alone. In 20% of cases, these lesions occur at arterial bifurcations or branch points in the arterial tree. Determining how best to treat these lesions remains a particular challenge, as they may involve the main branch, the side branch, or both vessels and bifurcation stenting is associated with a higher risk for adverse cardiac events. However, it is unclear whether restoring blood flow in the main branch alleviates the disturbed hemodynamics in the side branch as well. This question becomes even more challenging due to the complex anatomic features of bifurcation lesions, such as the curvature, percentage stenosis, and length. To ascertain the influence of anatomic changes in bifurcation lesion geometries and how different stenting options affect resulting flow, we produced a synthetic database of 360 different bifurcation lesion morphologies. However, as each individual simulation is computationally costly methods employed to we developed methods to optimize parallel simulations of coronary interventions on NVIDIA-based GPU instances in the Microsoft Azure cloud computing platform. By establishing a cloud-based, high throughput framework for computing coronary flow, we were efficiently calculate flow for the full database and quantify the influence of lesion- and treatment-specific parameters on resulting flow. Here we will discuss the technical hurdles overcome to complete the large-scale fluid dynamics analysis using a cloud-based platform.
Event Type
Exhibitor Forum
TimeTuesday, 15 November 202211:30am - 12pm CST
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