Pulmonary Hypertension Assessed Using Mathematical Modeling Integrating Imaging and Time-Series Data
Department of Mathematics
NC State University
Cardiovascular disease management involves interpreting imaging data, time-series data, and single-valued markers often measured over several visits. While each data type provides insight into the disease state, these snapshots cannot easily be integrated to provide insight into disease predictions. In this talk, we demonstrate how to interpret the disease state using multiscale mathematical modeling integrating computed tomography (CT) images with blood pressure measurements from right heart categorization. We use these models to characterize patient-specific remodeling in the proximal and distal vasculature. We calculate patient-specific nominal parameter values using morphometric and invasively measured hemodynamic data, use sensitivity analysis to determine what parameters best inform the data, and a Bayesian approach to infer identifiable subject-specific parameters and propagate the uncertainty of pressure and flow predictions to all large vessels. We also validate frequency domain results assessing change in wave-propagation and wave-intensity with the disease. For the micro-vasculature, we conduct a morphometric analysis characterizing changes in the arterial networks' branching structure by extracting skeletonized networks from the micro-CT images and using a custom algorithm to represent the network as a connected graph. We determine subject-specific fractal parameters and analyze how these changes with PH. Our model and data analysis outcomes are combined to understand the link between spatially distributed etiologies and global hemodynamics and shed light on the prospect of combining the model and graph-based morphometric analysis of vascular trees.
Dr. Olufsen, Professor, has been associated with the NCSU Mathematics Department since 2001. She got her Ph.D. in Applied Mathematics from Roskilde University, Denmark in 2001, for which she developed a 1D systemic arterial model for use in an Anesthesia Simulator. After graduating, she spent three years at Boston University, working with Nancy Kopell and Ali Nadim.
At NCSU her main focus has been on developing patient-specific models for understanding the cardiovascular system and its control. Her recent work has focused on using modeling to understand pulmonary hypertension integrating imaging and time-series data. She has mentored more than 20 graduate students (two who are Assistant Professors at USC) and a large number of undergraduate students. She has published more than 100 manuscripts and organized numerous workshops and conferences including SIAM Life Sciences. She served as a scientific advisor for the Mathematical Biosciences Institute at Ohio State and is currently the director for the NCSU Research for Undergraduates Program.
Wednesday, September 30, 2020
A Zoom webinar invitation will be posted here.