Software Development for Advanced TAVR-in-TAVR Surgical Planning
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Swamy, Kevin
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Abstract
Leaflets cannot open and close properly when an aortic valve has undergone calcification. If untreated, aortic stenosis will eventually cause heart failure. Transcatheter aortic valve replacement (TAVR) is a minimally invasive surgery used to treat aortic stenosis as opposed to traditional Surgical Aortic Valve Replacement (SAVR) surgery. TAVR is a surgical procedure used to replace a deceased, dilapidated aortic valve with an artificial valve. Due to its minimally invasive approach, TAVR has become the standard of care for low-risk patients and its popularity continues to grow across the world. However, there are growing apprehensions regarding valve deterioration in TAVR patients. A second TAVR surgery might be necessary. This is referred to as a TAVR-in-TAVR procedure. Such convoluted procedures require thorough pre-surgical evaluations based on cardiac CT scans.
High-fidelity computational simulations are performed to determine how a new TAVR would behave inside an existing TAVR, and evaluate for possible paravalvular leaks, patient mismatch, conduction abnormalities, further calcification risks, or thrombosis. However, such simulations require a high-resolution model of the existing stent geometry and the flow boundary condition for simulations, which are very difficult to procure. The stent is largely fabricated from metal wires and CT reconstructions are sometimes not feasible due to blooming artifacts. 4DCT scans contain left ventricle deformation during a cardiac cycle and such information can be utilized to calculate heart valve flow rates. I will use image registration and machine learning algorithms to obtain the aforementioned information and make it accessible for clinicians during pre-surgical planning. This application will be a user-friendly, easy-to-use tool for clinicians and physicians and will include a Graphical User Interface (GUI). The plan is to build a program that is intuitive and user-friendly to enable clinicians to input CT data, receive results, and gain the surgical insights needed to make informed decisions.
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Undergraduate Research Option Thesis