Voronoi Polyhedra Analysis of Optimized Arterial Tree Models

AbstractTopological and metric properties of Voronoi polyhedra (VP) generated by the distal end points of terminal segments in arterial tree models grown by the method of constrained constructive optimization (CCO) are analyzed with the aim to characterize the spatial distribution of their supply sites relative to randomly distributed points as a reference model. The distributions of the number Nf of Voronoi cell faces, cell volume V, surface area S, area A of individual cell faces, and asphericity parameter α of the CCO models are all significantly different from the ones of random points, whereas the distributions of V, S, and α are also significantly different among CCO models optimized for minimum intravascular volume and minimum segment length (p < 0.0001). The distributions of Nf, V, and S of the CCO models are reasonably well approximated by two-parameter gamma distributions. We study scaling of intravascular blood volume and arterial cross-sectional area with the volume of supplied tissue, the latter being represented by the VP of the respective terminal segments. We observe scaling exponents from 1.20 ± 0.007 to 1.08 ± 0.005 for intravascular blood volume and 0.77 ± 0.01 for arterial cross-sectional area. Setting terminal flows proportional to the associated VP volumes during tree construction yields a relative dispersion of terminal flows of 37% and a coefficient of skewness of 1.12. © 2003 Biomedical Engineering Society. PAC2003: 8719Uv, 8710+e, 4720Ky, 0260Pn, 0230Oz

[1]  M. Fátima Vaz,et al.  Grain size distribution: The lognormal and the gamma distribution functions , 1988 .

[2]  C D Murray,et al.  The Physiological Principle of Minimum Work: I. The Vascular System and the Cost of Blood Volume. , 1926, Proceedings of the National Academy of Sciences of the United States of America.

[3]  C. Gans,et al.  Biomechanics: Motion, Flow, Stress, and Growth , 1990 .

[4]  R S Reneman,et al.  Propagation velocity and reflection of pressure waves in the canine coronary artery. , 1979, The American journal of physiology.

[5]  P. Jedlovszky Voronoi polyhedra analysis of the local structure of water from ambient to supercritical conditions , 1999 .

[6]  W Schreiner,et al.  The branching angles in computer-generated optimized models of arterial trees , 1994, The Journal of general physiology.

[7]  R. E. Miles,et al.  Monte carlo estimates of the distributions of the random polygons of the voronoi tessellation with respect to a poisson process , 1980 .

[8]  D'arcy W. Thompson On Growth and Form , 1945 .

[9]  Solvation of large dipoles A molecular dynamics study II. , 1978 .

[10]  K. Kubát,et al.  Variability of intercapillary distance estimated on histological sections of rat heart. , 1985, Advances in experimental medicine and biology.

[11]  Aneesur Rahman,et al.  Liquid Structure and Self‐Diffusion , 1966 .

[12]  R W Glenny,et al.  A computer simulation of pulmonary perfusion in three dimensions. , 1995, Journal of applied physiology.

[13]  James B. Bassingthwaighte,et al.  The Fractal Nature of Myocardial Blood Flow Emerges from a Whole-Organ Model of Arterial Network , 2000, Journal of Vascular Research.

[14]  R. Glenny,et al.  Fractal properties of pulmonary blood flow: characterization of spatial heterogeneity. , 1990, Journal of applied physiology.

[15]  H. Honda Description of cellular patterns by Dirichlet domains: the two-dimensional case. , 1978, Journal of theoretical biology.

[16]  José L. F. Abascal,et al.  The Voronoi polyhedra as tools for structure determination in simple disordered systems , 1993 .

[17]  B. Ripley Tests of 'Randomness' for Spatial Point Patterns , 1979 .

[18]  C. Seiler,et al.  Basic structure-function relations of the epicardial coronary vascular tree. Basis of quantitative coronary arteriography for diffuse coronary artery disease. , 1991 .

[19]  David P. Dobkin,et al.  The quickhull algorithm for convex hulls , 1996, TOMS.

[20]  G. Ruocco,et al.  Analysis of the network topology in liquid water and hydrogen sulphide by computer simulation , 1992 .

[21]  H Kurz,et al.  Structural and biophysical simulation of angiogenesis and vascular remodeling , 2001, Developmental dynamics : an official publication of the American Association of Anatomists.

[22]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[23]  W. Chilian,et al.  Microvascular pressures and resistances in the left ventricular subepicardium and subendocardium. , 1991, Circulation research.

[24]  Atsuyuki Okabe,et al.  Spatial Tessellations: Concepts and Applications of Voronoi Diagrams , 1992, Wiley Series in Probability and Mathematical Statistics.

[25]  T Togawa,et al.  Optimal branching structure of the vascular tree. , 1972, The Bulletin of mathematical biophysics.

[26]  M Zamir,et al.  Optimality principles in arterial branching. , 1976, Journal of theoretical biology.

[27]  W Schreiner,et al.  A three-dimensional model for arterial tree representation, generated by constrained constructive optimization , 1999, Comput. Biol. Medicine.

[28]  M. Woldenberg,et al.  Relation of branching angles to optimality for four cost principles. , 1986, Journal of theoretical biology.

[29]  J. Abascal,et al.  Ionic association in electrolyte solutions: A Voronoi polyhedra analysis , 1994 .

[30]  James B. Bassingthwaighte,et al.  Modeling Advection and Diffusion of Oxygen in Complex Vascular Networks , 2001, Annals of Biomedical Engineering.

[31]  Atsuyuki Okabe,et al.  Spatial Tessellations: Concepts and Applications of Voronoi Diagrams, Second Edition , 2000, Wiley Series in Probability and Mathematical Statistics.

[32]  M Zamir,et al.  Arterial bifurcations in the human retina , 1979, The Journal of general physiology.

[33]  G S Kassab,et al.  Morphometry of pig coronary arterial trees. , 1993, The American journal of physiology.

[34]  J. Bassingthwaighte,et al.  Fractal Nature of Regional Myocardial Blood Flow Heterogeneity , 1989, Circulation research.

[35]  S. Kurtz,et al.  Properties of a two-dimensional Poisson-Voronoi tesselation: A Monte-Carlo study , 1993 .

[36]  J. Bassingthwaighte,et al.  Fractal descriptions for spatial statistics , 2006, Annals of Biomedical Engineering.

[37]  Wolfgang Schreiner,et al.  Visualization Of Computer-generated ArterialModel Trees , 1970 .

[38]  A. N. Strahler Quantitative analysis of watershed geomorphology , 1957 .

[39]  Georges Voronoi Nouvelles applications des paramètres continus à la théorie des formes quadratiques. Deuxième mémoire. Recherches sur les parallélloèdres primitifs. , 1908 .

[40]  James H. Brown,et al.  A General Model for the Origin of Allometric Scaling Laws in Biology , 1997, Science.

[41]  J. Prothero,et al.  Scaling of blood parameters in mammals , 1980 .

[42]  Martin Neumann,et al.  Staged Growth of Optimized Arterial Model Trees , 2000, Annals of Biomedical Engineering.

[43]  K. Sandau,et al.  Modelling of vascular growth processes: A stochastic biophysical approach to embryonic angiogenesis , 1994, Journal of microscopy.

[44]  B. Zweifach,et al.  Methods for the simultaneous measurement of pressure differentials and flow in single unbranched vessels of the microcirculation for rheological studies. , 1977, Microvascular research.

[45]  S. K. Kurtz,et al.  Properties of a three-dimensional poisson-voronoi tesselation: A Monte Carlo study , 1993 .

[46]  M. Marcus,et al.  Redistribution of coronary microvascular resistance produced by dipyridamole. , 1989, The American journal of physiology.

[47]  A. Ziada,et al.  Angiogenesis in the heart and skeletal muscle. , 1986, The Canadian journal of cardiology.

[48]  C. Brooks Computer simulation of liquids , 1989 .

[49]  L. Heinrich On a test of randomness of spatial point patterns , 1984 .

[50]  Kevin Q. Brown,et al.  Voronoi Diagrams from Convex Hulls , 1979, Inf. Process. Lett..

[51]  E. vanBavel,et al.  Branching patterns in the porcine coronary arterial tree. Estimation of flow heterogeneity. , 1992, Circulation research.

[52]  C. Wang,et al.  Capillary supply regions. , 2001, Mathematical biosciences.

[53]  J B Bassingthwaighte,et al.  Regional myocardial flow heterogeneity explained with fractal networks. , 1989, The American journal of physiology.

[54]  R. Rosen Optimality Principles in Biology , 1967, Springer US.

[55]  W. Schreiner,et al.  Computer-optimization of vascular trees , 1993, IEEE Transactions on Biomedical Engineering.

[56]  H. Qian,et al.  A class of flow bifurcation models with lognormal distribution and fractal dispersion. , 2000, Journal of theoretical biology.

[57]  W Schreiner,et al.  Computer generation of complex arterial tree models. , 1993, Journal of biomedical engineering.

[58]  B. Hambly Fractals, random shapes, and point fields , 1994 .

[59]  G. L. Dirichlet Über die Reduction der positiven quadratischen Formen mit drei unbestimmten ganzen Zahlen. , 1850 .