Discipline: Technology and Engineering
Subcategory: Biomedical Engineering
Justin Reed - University of Maryland Baltimore County
Co-Author(s): Seungik Baek, Michigan State University, East Lansing, MI
Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of death in the United States and is predicted to be the third leading cause of death world-wide by 2030 (World Health Organization). Despite this, the current primary diagnostic tool (the FEV1/FVC ratio test) tends to either under or over diagnose the disease. Our research objective was to develop an image-based assessment to assist in developing an improved diagnostic method. I used three CT scan image sets which included one healthy patient’s lungs, one patient’s lungs effected by COPD in March, and a progressed COPD in the same patient in November. I performed a segmentation analysis using MIMICS software, which can build the trees of multiple generations of bronchioles. From this segmentation analysis, I constructed three anatomical models which I used to compare a healthy versus COPD patient as well as COPD progression over 8 months. To improve the accuracy of the results I refined the models with 3MATIC software. With, 3MATIC I operated a smoothing and re-meshing tool to isolate the bronchioles to clearly depict the geometry of the models. Analysis of the geometric differences in our models allowed us to further comprehend the geometrical features that are associated with the COPD symptoms. After the findings are assessed, the geometric comparisons and analysis will provide us a better understanding of the disease progression and in turn aid to design a hypothesis-driven research.
Funder Acknowledgement(s): National Science Foundation
Faculty Advisor: Seungik Baek, email@example.com
Role: I completed the entire research by myself with the supervision of Seungik Baek.