Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?

Modern models that derive allometric relationships between metabolic rate and body mass are based on the architectural design of the cardiovascular system and presume sibling vessels are symmetric in terms of radius, length, flow rate, and pressure. Here, we study the cardiovascular structure of the...

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Main Authors: Elif Tekin, David Hunt, Mitchell G Newberry, Van M Savage
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-11-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC5130167?pdf=render
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author Elif Tekin
David Hunt
Mitchell G Newberry
Van M Savage
author_facet Elif Tekin
David Hunt
Mitchell G Newberry
Van M Savage
author_sort Elif Tekin
collection DOAJ
description Modern models that derive allometric relationships between metabolic rate and body mass are based on the architectural design of the cardiovascular system and presume sibling vessels are symmetric in terms of radius, length, flow rate, and pressure. Here, we study the cardiovascular structure of the human head and torso and of a mouse lung based on three-dimensional images processed via our software Angicart. In contrast to modern allometric theories, we find systematic patterns of asymmetry in vascular branching, potentially explaining previously documented mismatches between predictions (power-law or concave curvature) and observed empirical data (convex curvature) for the allometric scaling of metabolic rate. To examine why these systematic asymmetries in vascular branching might arise, we construct a mathematical framework to derive predictions based on local, junction-level optimality principles that have been proposed to be favored in the course of natural selection and development. The two most commonly used principles are material-cost optimizations (construction materials or blood volume) and optimization of efficient flow via minimization of power loss. We show that material-cost optimization solutions match with distributions for asymmetric branching across the whole network but do not match well for individual junctions. Consequently, we also explore random branching that is constrained at scales that range from local (junction-level) to global (whole network). We find that material-cost optimizations are the strongest predictor of vascular branching in the human head and torso, whereas locally or intermediately constrained random branching is comparable to material-cost optimizations for the mouse lung. These differences could be attributable to developmentally-programmed local branching for larger vessels and constrained random branching for smaller vessels.
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spelling doaj.art-b58ad1d470cb443095383710d56ffb1d2022-12-21T18:53:20ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-11-011211e100522310.1371/journal.pcbi.1005223Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?Elif TekinDavid HuntMitchell G NewberryVan M SavageModern models that derive allometric relationships between metabolic rate and body mass are based on the architectural design of the cardiovascular system and presume sibling vessels are symmetric in terms of radius, length, flow rate, and pressure. Here, we study the cardiovascular structure of the human head and torso and of a mouse lung based on three-dimensional images processed via our software Angicart. In contrast to modern allometric theories, we find systematic patterns of asymmetry in vascular branching, potentially explaining previously documented mismatches between predictions (power-law or concave curvature) and observed empirical data (convex curvature) for the allometric scaling of metabolic rate. To examine why these systematic asymmetries in vascular branching might arise, we construct a mathematical framework to derive predictions based on local, junction-level optimality principles that have been proposed to be favored in the course of natural selection and development. The two most commonly used principles are material-cost optimizations (construction materials or blood volume) and optimization of efficient flow via minimization of power loss. We show that material-cost optimization solutions match with distributions for asymmetric branching across the whole network but do not match well for individual junctions. Consequently, we also explore random branching that is constrained at scales that range from local (junction-level) to global (whole network). We find that material-cost optimizations are the strongest predictor of vascular branching in the human head and torso, whereas locally or intermediately constrained random branching is comparable to material-cost optimizations for the mouse lung. These differences could be attributable to developmentally-programmed local branching for larger vessels and constrained random branching for smaller vessels.http://europepmc.org/articles/PMC5130167?pdf=render
spellingShingle Elif Tekin
David Hunt
Mitchell G Newberry
Van M Savage
Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?
PLoS Computational Biology
title Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?
title_full Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?
title_fullStr Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?
title_full_unstemmed Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?
title_short Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?
title_sort do vascular networks branch optimally or randomly across spatial scales
url http://europepmc.org/articles/PMC5130167?pdf=render
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AT davidhunt dovascularnetworksbranchoptimallyorrandomlyacrossspatialscales
AT mitchellgnewberry dovascularnetworksbranchoptimallyorrandomlyacrossspatialscales
AT vanmsavage dovascularnetworksbranchoptimallyorrandomlyacrossspatialscales