4.5 Article

Computing the ankle-brachial index with parallel computational fluid dynamics

Journal

JOURNAL OF BIOMECHANICS
Volume 82, Issue -, Pages 28-37

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jbiomech.2018.10.007

Keywords

Hemodynamics; Computational fluid dynamics; Ankle-brachial index

Funding

  1. U.S. Department of Energy by LLNL [DE-AC52-07NA27344]
  2. LLNL Laboratory Directed Research and Development (LDRD) program
  3. Office of the Director, National Institutes of Health [DP50D019876]
  4. National Science Foundation [1512553]
  5. Big Data-Scientist Training Enhancement Program (BD-STEP) of the Department of Veterans Affairs
  6. Div Of Chem, Bioeng, Env, & Transp Sys
  7. Directorate For Engineering [1512553] Funding Source: National Science Foundation

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The ankle-brachial index (ABI), a ratio of arterial blood pressure in the ankles and upper arms, is used to diagnose and monitor circulatory conditions such as coarctation of the aorta and peripheral artery disease. Computational simulations of the ABI can potentially determine the parameters that produce an ABI indicative of ischemia or other abnormalities in blood flow. However, 0- and 1-D computational methods are limited in describing a 3-D patient-derived geometry. Thus, we present a massively parallel framework for computational fluid dynamics (CFD) simulations in the full arterial system. Using the lattice Boltzmann method to solve the Navier-Stokes equations, we employ highly parallelized and scalable methods to generate the simulation domain and efficiently distribute the computational load among processors. For the first time, we compute an ABI with 3-D CFD. In this proof-of-concept study, we investigate the dependence of ABI on the presence of stenoses, or narrowed regions of the arteries, by directly modifying the arterial geometry. As a result, our framework enables the computation a hemodynamic factor characterizing flow at the scale of the full arterial system, in a manner that is extensible to patient-specific imaging data and holds potential for treatment planning. (C) 2018 Elsevier Ltd. All rights reserved.

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