TY - JOUR
T1 - Computing the ankle-brachial index with parallel computational fluid dynamics
AU - Gounley, John
AU - Draeger, Erik W.
AU - Oppelstrup, Tomas
AU - Krauss, William D.
AU - Gunnels, John A.
AU - Chaudhury, Rafeed
AU - Nair, Priya
AU - Frakes, David
AU - Leopold, Jane A.
AU - Randles, Amanda
N1 - Funding Information:
Research reported in this publication was supported by the Office of the Director, National Institutes of Health under Award Number DP5OD019876. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This material is based upon work supported by the National Science Foundation under Grant No. 1512553 . Support was provided by the Big Data-Scientist Training Enhancement Program (BD-STEP) of the Department of Veterans Affairs.
Funding Information:
Research reported in this publication was supported by the Office of the Director, National Institutes of Health under Award Number DP5OD019876. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This material is based upon work supported by the National Science Foundation under Grant No. 1512553. Support was provided by the Big Data-Scientist Training Enhancement Program (BD-STEP) of the Department of Veterans Affairs.
Funding Information:
We thank Don Frederick and the Livermore Computing Operations team at Lawrence Livermore National Laboratory (LLNL) for helping with the full system runs on Vulcan. This work was performed under the auspices of the U.S. Department of Energy by LLNL under Contract DE-AC52-07NA27344. Computing support for this work came from the LLNL Institutional Computing Grand Challenge program. Support was also provided by the LLNL Laboratory Directed Research and Development (LDRD) program.Research reported in this publication was supported by the Office of the Director, National Institutes of Health under Award Number DP5OD019876. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This material is based upon work supported by the National Science Foundation under Grant No. 1512553. Support was provided by the Big Data-Scientist Training Enhancement Program (BD-STEP) of the Department of Veterans Affairs.
Funding Information:
We thank Don Frederick and the Livermore Computing Operations team at Lawrence Livermore National Laboratory (LLNL) for helping with the full system runs on Vulcan. This work was performed under the auspices of the U.S. Department of Energy by LLNL under Contract DE-AC52-07NA27344. Computing support for this work came from the LLNL Institutional Computing Grand Challenge program. Support was also provided by the LLNL Laboratory Directed Research and Development (LDRD) program.
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2019/1/3
Y1 - 2019/1/3
N2 - 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.
AB - 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.
KW - Ankle-brachial index
KW - Computational fluid dynamics
KW - Hemodynamics
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U2 - 10.1016/j.jbiomech.2018.10.007
DO - 10.1016/j.jbiomech.2018.10.007
M3 - Article
C2 - 30385003
AN - SCOPUS:85055628588
SN - 0021-9290
VL - 82
SP - 28
EP - 37
JO - Journal of Biomechanics
JF - Journal of Biomechanics
ER -