Computing the ankle-brachial index with parallel computational fluid dynamics.


Journal

Journal of biomechanics
ISSN: 1873-2380
Titre abrégé: J Biomech
Pays: United States
ID NLM: 0157375

Informations de publication

Date de publication:
03 01 2019
Historique:
received: 16 01 2018
revised: 09 10 2018
accepted: 10 10 2018
pubmed: 6 11 2018
medline: 14 6 2019
entrez: 3 11 2018
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 30385003
pii: S0021-9290(18)30772-3
doi: 10.1016/j.jbiomech.2018.10.007
pmc: PMC6666426
mid: NIHMS1511228
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

28-37

Subventions

Organisme : NIH HHS
ID : DP5 OD019876
Pays : United States

Informations de copyright

Copyright © 2018 Elsevier Ltd. All rights reserved.

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Auteurs

John Gounley (J)

Department of Biomedical Engineering, Duke University, Durham, NC, USA. Electronic address: john.gounley@duke.edu.

Erik W Draeger (EW)

Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, USA. Electronic address: draeger1@llnl.gov.

Tomas Oppelstrup (T)

Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, USA. Electronic address: oppelstrup2@llnl.gov.

William D Krauss (WD)

Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, USA. Electronic address: liam1@llnl.gov.

John A Gunnels (JA)

IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA. Electronic address: gunnels@us.ibm.com.

Rafeed Chaudhury (R)

Department of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA. Electronic address: rafeed@asu.edu.

Priya Nair (P)

Department of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA. Electronic address: pnair3@asu.edu.

David Frakes (D)

Department of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA. Electronic address: dfrakes@asu.edu.

Jane A Leopold (JA)

Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: jleopold@partners.org.

Amanda Randles (A)

Department of Biomedical Engineering, Duke University, Durham, NC, USA. Electronic address: amanda.randles@duke.edu.

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