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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Keshav Kohli
BME PhD Defense Presentation
Date:2022-04-12
Time: 2PM-4PM ET
Location / Meeting Link: Emory University Hospital, Room D105A / https://emory.zoom.us/j/96568243063
Committee Members:
John Oshinski, Ph.D. (Advisor), Ajit Yoganathan, Ph.D. (Co-Advisor), Lakshmi Prasad Dasi, Ph.D., Vasilis Babaliaros, M.D., Carlo De Cecco, M.D., Ph.D.
Title: Image-based Modeling of Hemodynamics in Patients Undergoing Transcatheter Mitral Valve Replacement
Abstract: Mitral valve disease affects over 4 million people in the United States and is a debilitating condition if left untreated. Almost 50% of patients diagnosed with mitral valve disease are deemed at too high risk for conventional surgical options due to advanced age and/or comorbidities. These patients are candidates for a new procedure called transcatheter mitral valve replacement (TMVR) which has emerged as a potential alternative to surgery. During this procedure, a prosthetic mitral valve is implanted in place of the diseased valve through a minimally invasive approach without the need for cardiopulmonary bypass. While overall clinical results have been promising, up to 54% of patients can have a potentially fatal obstruction of blood flow ejecting from the heart. The mechanism of this obstruction is partial or complete blockage of the left ventricular outflow tract (LVOT) from the implanted mitral valve. This thesis focused on providing new insights into the mechanisms, modeling, and mitigation of this procedural complication. Computed tomography (CT) was first used to characterize the dynamic LVOT geometry and flow rate in patients who underwent TMVR and identify optimal predictors for LVOT obstruction. Next, a simplified in silico model was developed using CT in combination with computational fluid dynamics to model patient-specific blood flow in the heart after TMVR. Finally, this in silico model was used to conduct a virtual clinical study to evaluate the efficacy of a new interventional technique to mitigate LVOT obstruction. The outcomes of this thesis can help clinicians to improve their care of patients undergoing the TMVR procedure by better predicting and mitigating LVOT obstruction. This thesis also introduces new simulation methods for engineers to better design and test TMVR devices which are currently undergoing development.
