4.1 Article

Estimation of Blood Flow Rates in Large Microvascular Networks

Journal

MICROCIRCULATION
Volume 19, Issue 6, Pages 530-538

Publisher

WILEY-BLACKWELL
DOI: 10.1111/j.1549-8719.2012.00184.x

Keywords

hemodynamics; flow simulation; imaging; microvascular function

Funding

  1. NIH [HL 070657]
  2. EPSRC [EP/GOO7527/2]
  3. Wellcome Trust Medical Engineering Centre at King's College London
  4. European Commission [FP7-ICT-2007-224495: euHeart]

Ask authors/readers for more resources

Please cite this paper as: Fry BC, Lee J, Smith NP, Secomb TW. Estimation of blood flow rates in large microvascular networks. Microcirculation similar to 19: 530538, 2012. Abstract Objective: Recent methods for imaging microvascular structures provide geometrical data on networks containing thousands of segments. Prediction of functional properties, such as solute transport, requires information on blood flow rates also, but experimental measurement of many individual flows is difficult. Here, a method is presented for estimating flow rates in a microvascular network based on incomplete information on the flows in the boundary segments that feed and drain the network. Methods: With incomplete boundary data, the equations governing blood flow form an underdetermined linear system. An algorithm was developed that uses independent information about the distribution of wall shear stresses and pressures in microvessels to resolve this indeterminacy, by minimizing the deviation of pressures and wall shear stresses from target values. Results: The algorithm was tested using previously obtained experimental flow data from four microvascular networks in the rat mesentery. With two or three prescribed boundary conditions, predicted flows showed relatively small errors in most segments and fewer than 10% incorrect flow directions on average. Conclusions: The proposed method can be used to estimate flow rates in microvascular networks, based on incomplete boundary data, and provides a basis for deducing functional properties of microvessel networks.

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