Circumferential wall stress as a mechanism for arteriolar rarefaction and proliferation in a network model.
Hypertension results in structural rarefaction of the microvascular arteriolar network while, conversely, decreasing pressure results in arteriolar proliferation. A remodeling mechanism capable of unifying these results remains elusive. A network model of a transverse arteriole tree was used to test whether adaptations to changes in mean circumferential wall stress (sigma theta) could produce realistic structural remodeling. Vessel diameters and network boundary pressures were assigned using experimental data, and control flows (Qij) and sigma theta ij for each vessel were calculated. Mean sigma theta ij in A2 (Strahler order) vessels (sigma m) was 6.62 x 10(4) dynes/cm2. Input pressure was increased by 35% in simulated one-kidney, one-clip (s1K1C) hypertension or decreased by 30% in simulated main feeder ligation (sMFL). Vessel diameters were adjusted iteratively until each Qij was restored, simulating autoregulation. Wall stresses decreased 15.9% for hypertension (sigma m = 5.57 x 10(4) dynes/cm2), but were elevated 60.9% for main feeder ligation (sigma m = 10.65 x 10(4) dynes/cm2), A stress-growth principle was applied, so that stresses above an upper threshold cause growth while stresses below a lower threshold cause resorption. Individual vessels with sigma theta ij < 5.24 x 10(4) dynes/cm2 were removed while new A2 segments were added to A2 vessels with sigma theta ij > 8.27 x 10(4) dynes/cm2. The network structure was adjusted until all sigma theta ij were within these stress thresholds. The number of A2s decreased 22% in s1K1C and increased 96% in sMFL in quantitative agreement with experimental data, consistent with the hypothesis that wall stress may be an important determinant of network remodeling. Arteriolar proliferation and rarefaction represent adaptations to different hemodynamic conditions, but may be governed by a common stress-growth principle.
Price
R J
RJ
Department of Biomedical Engineering, University of Virginia, Charlottesville 22908.
Skalak
T C
TC
D000222:Adaptation, Physiological; D000818:Animals; D001160:Arterioles / Q000473:pathology / Q000502:physiology*; D003198:Computer Simulation; D003250:Constriction; D004730:Endothelium, Vascular / Q000473:pathology / Q000502:physiology*; D006973:Hypertension / Q000473:pathology / Q000503:physiopathology; D008955:Models, Cardiovascular; D051381:Rats; D013314:Stress, Mechanical