Pulmonary Artery Hemodynamics Using MRI & CFD
This item will be available on: 2018-08-01
Pulmonary hypertension (PH), as defined by a mean pulmonary arterial pressure (mPAP) greater than 25 mmHg, is a life-threatening chronic disorder of the pulmonary circulation which leads to right ventricle failure and if untreated, death. The purpose of this work was to use both, magnetic resonance imaging (MRI) and computational fluid dynamics (CFD), to quantify changes in wall shear stress (WSS) throughout the pulmonary artery (PA) of a pulmonary hypertension (PH) population when compared to a normotensive control subject. With the future goal of this knowledge potentially being used to diagnose PH non-invasively. Patient's PA's were recreated using MRIs and MIMICS software. Velocity profiles were generated from the MRIs using MATLAB and CFD simulations were conducted using Fluent 17.0. Overall, the data followed a similar trend to published data where the control subject showed an approximately 1.5 to 3.5 times increase in WSS when compared to the PH subjects. The control subject showed a maximum of 5.596 dyn/cm2 while the PH subjects ranged from 1.521 to 3.151 dyn/cm2. This work can serve as the groundwork for further CFD simulations however, future work needs to be done with both a larger population size, potentially modeling further into the pulmonary vasculature as well as attempting different methods of data post-processing.
Rabidou, Jake. (July 2017). Pulmonary Artery Hemodynamics Using MRI & CFD (Master's Thesis, East Carolina University). Retrieved from the Scholarship. (http://hdl.handle.net/10342/6399.)
Rabidou, Jake. Pulmonary Artery Hemodynamics Using MRI & CFD. Master's Thesis. East Carolina University, July 2017. The Scholarship. http://hdl.handle.net/10342/6399. May 23, 2018.
Rabidou, Jake, “Pulmonary Artery Hemodynamics Using MRI & CFD” (Master's Thesis., East Carolina University, July 2017).
Rabidou, Jake. Pulmonary Artery Hemodynamics Using MRI & CFD [Master's Thesis]. Greenville, NC: East Carolina University; July 2017.
East Carolina University