Mitchel Colebank (North Carolina State University) - On the effects of vascular network size for hemodynamic parameter inference
Computational fluid dynamics (CFD) modeling is an emerging tool for understanding the prognosis and development of cardiovascular disease. Advances in image analysis and data acquisition has led to patient-specific CFD, whereby imaging data is directly used as the vascular domain for computational hemodynamic simulations. These techniques are underutilized in understanding pulmonary vascular disease, e.g., pulmonary hypertension (PH), which affect hundreds to thousands of pulmonary blood vessels. One-dimensional (1D) CFD models can predict wave propagation throughout a network of blood vessels, yet it is unclear how model predictions and parameter inference are affected by the size of the vascular network used. This talk investigates the effect of pulmonary arterial network size on model sensitivity, parameter inference, and model predictions in both normotensive and PH models, utilizing data from mice.
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336, VAT Registration Number GB 592 9507 00, and is acknowledged by the UK authorities as a “Recognised body” which has been granted degree awarding powers.
Any views expressed within media held on this service are those of the contributors, should not be taken as approved or endorsed by the University, and do not necessarily reflect the views of the University in respect of any particular issue.