  Pulmonary hypertension (PH), defined by a mean pulmonary arterial blood
pressure above 20 mmHg, is a cardiovascular disease impacting the pulmonary
vasculature. PH is accompanied by vascular remodeling, wherein vessels become
stiffer, large vessels dilate, and smaller vessels constrict. Some types of PH,
including hypoxia-induced PH (HPH), lead to microvascular rarefaction. The goal
of this study is to analyze the change in pulmonary arterial network
morphometry in the presence of HPH. To do so, we use novel methods from
topological data analysis (TDA), employing persistent homology to quantify
arterial network morphometry for control and hypertensive mice. These methods
are used to characterize arterial trees extracted from micro-computed
tomography (micro-CT) images. To compare results between control and
hypertensive animals, we normalize generated networks using three pruning
algorithms. This proof-of-concept study shows that the pruning methods effects
the spatial tree statistics and complexities of the trees. Results show that
HPH trees have higher depth and that the directional complexities correlate
with branch number, except for trees pruned by vessel radius, where the left
and anterior complexity are lower compared to control trees. While more data is
required to make a conclusion about the overall effect of HPH on network
topology, this study provides a framework for analyzing the topology of
biological networks and is a step towards the extraction of relevant
information for diagnosing and detecting HPH.
