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Mette Olufsen, Department of Mathematics, NCSU – Applied Mathematics Colloquium

April 13, 2018 @ 4:00 pm - 5:00 pm

332 Phillips Hall, 4:00 pm – 5:00 pm

Tea at 3:30 in 330 Phillips Hall

Title: Using 1D fluid dynamics to study pulmonary hypertension

Abstract: Pulmonary hypertension (PH) is a complex disorder manifested by high blood pressure in the pulmonary arteries emanating in the right heart going to the lungs. The disorder encompasses several disease categories diagnosed from a combination of imaging studies and invasive cauterization.  The disease cannot be diagnosed non-invasively, and the disease have no cure. As a result to monitor development in specific patients imaging/invasive pressure measurements are collected frequently. Yet few quantitative measures exist to describe how the disease propagates and it is difficult from available measurements to establish what parts of the system that has been remodeled. Generally, remodeling arises from three sources: narrowing and stiffening of small and/or large vessels, microvascular rarefaction (thinning of the network), and thrombus formation blocking specific vessels.  This talk will discuss how to study pulmonary hypertension using a 1D fluid mechanics modelto study wave propagation in the pulmonary vasculature, we illustrate how to use hyperelasticity to predict wall deformation and how to account for wall remodeling in both large and small vessels. We will discuss how changes in these properties impact flow and pressure predictions as well as wave propagation along the network. Second, we will show how to extract network geometry from micro CT images. With progression of PH, vessels remodel yet the basic network structure remains constant requiring robust algorithms mapping CT images to graphs. Specifically, we show how changes in thresholding and smoothness impact vessel segmentation, how to map segmented vessels to a graph and how variations from segmenting the same network multiple times randomly varying segmentation parameters impact fluid dynamics predictions.

Details

Date:
April 13, 2018
Time:
4:00 pm - 5:00 pm
Event Category: