  This study uses a one dimensional fluid dynamics arterial network model to
infer changes in hemodynamic quantities associated with pulmonary hypertension
in mice. Data for this study include blood flow and pressure measurements from
the main pulmonary artery for 7 control mice with normal pulmonary function and
5 hypertensive mice with hypoxia induced pulmonary hypertension. Arterial
dimensions for a 21 vessel network are extracted from micro-CT images of lungs
from a representative control and hypertensive mouse. Each vessel is
represented by its length and radius. Fluid dynamic computations are done
assuming that the flow is Newtonian, viscous, laminar, and has no swirl. The
system of equations is closed by a constitutive equation relating pressure and
area, using a linear model derived from stress-strain deformation in the
circumferential direction assuming that the arterial walls are thin, and also
an empirical nonlinear model. For each dataset, an inflow waveform is extracted
from the data, and nominal parameters specifying the outflow boundary
conditions are computed from mean values and characteristic time scales
extracted from the data. The model is calibrated for each mouse by estimating
parameters that minimize the least squares error between measured and computed
waveforms. Optimized parameters are compared across the control and the
hypertensive groups to characterize vascular remodeling with disease. Results
show that pulmonary hypertension is associated with stiffer and less compliant
proximal and distal vasculature with augmented wave reflections, and that
elastic nonlinearities are insignificant in the hypertensive animal.
