Issac Kim

Project

Systematic Electrophysiological Parameter Analysis for Determining Reentrant Driver Inducibility

Atrial fibrillation (AFib) is the most commonly sustained cardiac arrhythmia with significant global health implications. Currently, patient-specific computational models of the left atrium are being studied to predict the characteristics of reentrant activity that promote fibrillation. However, these models are limited in personalization, primarily focusing on anatomical structure and the distribution of disease-related remodeling. This lack of personalization can lead to inaccuracies in simulation outcomes, such as simulating AFib-like behavior in patients with atrial flutter (AFl), and vice versa. My project aims to derive cell-scale and tissue-scale parameter sets that favor the initiation of one type of arrhythmia or the other (AFib or AFl). If a strong relationship is established between model configurations and simulation outcomes, the data from the present study can guide future simulations to accurately tailor models to represent the arrhythmic state in patients predisposed to AFl.

What I learned

Through my research project, I not only gained proficiency in computational tools, critical thinking, and effective communication skills, but I also learned the importance of being surrounded by supportive peers and mentors from different fields. Working with a network of diverse individuals who contribute their unique experiences and scientific backgrounds to a single project enriched my research. It allowed me to gain new insights and broaden my perspective, emphasizing the value of interdisciplinary work which will undoubtedly benefit me in various ways in the future.

Advice for future applicants

Find your passion and partner with mentors who can guide you towards your fullest potential!

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