03 Dec 2018, 11:00 - 12:00
Room 208,Wilfred Brown Building
12/03/2018 11:00 AM
12/03/2018 12:00 PM
Europe/London
Computational Modeling of Vascular Pathologies and Therapies: Toward Treatment's Customization
Departmental seminar
Room 208,Wilfred Brown Building
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A departmental talk by Stefano Casarin
Everyone is welcome to this exciting talk, part of the Departmental seminar series.
About the speaker
Stefano Casarin is a Postdoctoral fellow with the Center for Computational Surgery at Houston
Methodist Research Institute. He works under the supervision of Marc Garbey, PhD, where his
research focuses on the development of multiscale models to design effective therapies for vascular
and tumor diseases, as well as the improvement of surgical planning for virtual lumpectomy in
response to breast cancer.
About the talk
Peripheral Arterial Occlusive Disease (PAOD) is a chronic condition affecting at least 8 to 12 million people annually in the US, typically treated at surgical level with a Vein Graft Bypass (VGB) or through the deployment of a stent in order to restore the physiological circulation. Despite surgical and post-surgical advancements across the years, such interventions still suffer from a high rate of failure. VGBs experience restenosis phenomena on 12% of cases after just one month from original operation, while in-stent restenosis incidence ranges between 17 and 41%. Failure of peripheral endovascular treatments occurs at the intersection of vascular biology, biomechanics, and clinical decision making. It is our hypothesis that the majority of endovascular treatment approaches share the same driving mechanisms and that a deep understanding of their dynamics is pivotal in order to move toward a decisive improvement of the current techniques. Accordingly, our group of research focused on a two parallel streams of projects. On one end, we developed a series of computational models able to replicate the healing of a VGB during the post-surgical follow-up. Ranging from simple dynamical systems to more complex Agent-Based,
Partial Differential Equations models, the goal is to capture the several feedback loops that regulate the interaction between events at cellular/tissue level and mechano-environmental conditions. On the other end, a multiscale model able to cover the healing process in its full extent, from genetic to tissue level, allowed us to test virtual genetic therapies to be administered to the patient during the post-surgical follow-up in order to contain the restenosis events. The computational models developed are validated on experimental data from rabbit model and easily generalizable to be applied to the study of different endovascular treatments, such as the previously cited stent deployment. It is our belief that an approach of this kind will drive medical research across a sphere of treatments customized on the single patient, which is the key to move Medicine toward the future.