Parameterisation of multi-scale continuum perfusion models from discrete vascular networks.

Experimental data and advanced imaging techniques are increasingly enabling the extraction of detailed vascular anatomy from biological tissues. Incorporation of anatomical data within perfusion models is non-trivial, due to heterogeneous vessel density and disparate radii scales. Furthermore, previ...

Descripción completa

Detalles Bibliográficos
Publicado en:Medical & Biological Engineering & Computing Vol. 51; no. 5; pp. 557 - 571
Autores principales: Hyde, Eoin R, Michler, Christian, Lee, Jack, Cookson, Andrew N, Chabiniok, Radek, Nordsletten, David A, Smith, Nicolas P
Formato: research Journal Article
Publicado: Springer Nature May2013
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109855813&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 109855813
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01400118
        PO0
      jtl: Medical & Biological Engineering & Computing
      issn: 01400118
      maglogo: N
    pubinfo:
      dt: May2013
      vid: 51
      iid: 5
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        109855813
        NLM23345008
        2012084103
        10.1007/s11517-012-1025-2
        NLM23345008
        PMC3627025
        109855813
      ppf: 557
      ppct: 14
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: Parameterisation of multi-scale continuum perfusion models from discrete vascular networks.
      aug:
        au:
          Hyde, Eoin R
          Michler, Christian
          Lee, Jack
          Cookson, Andrew N
          Chabiniok, Radek
          Nordsletten, David A
          Smith, Nicolas P
        affil: Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK.
      sug:
        subj:
          Blood Circulation Physiology
          Blood Vessels Anatomy and Histology
          Models, Biological
          Algorithms
          Animal Studies
          Blood Pressure Physiology
          Capillary Permeability Physiology
          Human
          Rats
      ab: Experimental data and advanced imaging techniques are increasingly enabling the extraction of detailed vascular anatomy from biological tissues. Incorporation of anatomical data within perfusion models is non-trivial, due to heterogeneous vessel density and disparate radii scales. Furthermore, previous idealised networks have assumed a spatially repeating motif or periodic canonical cell, thereby allowing for a flow solution via homogenisation. However, such periodicity is not observed throughout anatomical networks. In this study, we apply various spatial averaging methods to discrete vascular geometries in order to parameterise a continuum model of perfusion. Specifically, a multi-compartment Darcy model was used to provide vascular scale separation for the fluid flow. Permeability tensor fields were derived from both synthetic and anatomically realistic networks using (1) porosity-scaled isotropic, (2) Huyghe and Van Campen, and (3) projected-PCA methods. The Darcy pressure fields were compared via a root-mean-square error metric to an averaged Poiseuille pressure solution over the same domain. The method of Huyghe and Van Campen performed better than the other two methods in all simulations, even for relatively coarse networks. Furthermore, inter-compartment volumetric flux fields, determined using the spatially averaged discrete flux per unit pressure difference, were shown to be accurate across a range of pressure boundary conditions. This work justifies the application of continuum flow models to characterise perfusion resulting from flow in an underlying vascular network.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N