Aortic stenosis is a life-threatening heart condition that is a leading cause for invasive, valvular surgery in Western countries. Transcatheter aortic valve replacement (TAVR) is a non-invasive, alternative procedure that can curtail the risks involved in traditional open-heart surgeries, but careful prior interventions need to be planned beforehand using computed tomography (CT) to visualize the calcium deposit on the aortic valve. This has traditionally been a manual and qualitative process, in which doctors obtain a general understanding of the calcium distribution on the aortic valve, but we aim to introduce a more consistent, quantitative approach to quantify the calcium deposit. A current algorithm developed by previous researchers at the Edelman Lab uses 2D slices of the CT to identify and quantify the calcium, but non-calcium artifacts are difficult to distinguish at the 2D level. I will improve upon the current algorithm by incorporating 3D capabilities to capture the contiguous calcium deposit on the aortic valve and eliminate irrelevant artifacts. We expect to achieve a more accurate quantification of calcium deposits, which we will verify by comparing to the cohort of patient data manually analyzed by trained cardiologists.

Through SuperUROP, I want to combine my passion for technology and medicine, and contribute to this interdisciplinary study. I am excited to use the software skills I have developed to conduct clinical research.”