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Research Papers

A Computational Method for Analyzing the Biomechanics of Arterial Bruits

[+] Author and Article Information
Chi Zhu

Department of Mechanical Engineering,
Johns Hopkins University,
3400 N. Charles Street,
Baltimore, MD 21218
e-mail: czhu19@jhu.edu

Jung-Hee Seo

Department of Mechanical Engineering,
Johns Hopkins University,
3400 N. Charles Street,
Baltimore, MD 21218
e-mail: jhseo@jhu.edu

Hani Bakhshaee

Department of Mechanical Engineering,
Johns Hopkins University,
3400 N. Charles Street,
Baltimore, MD 21218
e-mail: hbakhsh1@jhu.edu

Rajat Mittal

Professor
Department of Mechanical Engineering,
Johns Hopkins University,
3400 N. Charles Street,
Baltimore, MD 21218
e-mail: mittal@jhu.edu

1Corresponding author.

Manuscript received January 18, 2017; final manuscript received March 2, 2017; published online April 6, 2017. Assoc. Editor: Guy M. Genin.

J Biomech Eng 139(5), 051008 (Apr 06, 2017) (9 pages) Paper No: BIO-17-1028; doi: 10.1115/1.4036262 History: Received January 18, 2017; Revised March 02, 2017

A computational framework consisting of a one-way coupled hemodynamic–acoustic method and a wave-decomposition based postprocessing approach is developed to investigate the biomechanics of arterial bruits. This framework is then applied for studying the effect of the shear wave on the generation and propagation of bruits from a modeled stenosed artery. The blood flow in the artery is solved by an immersed boundary method (IBM) based incompressible flow solver. The sound generation and propagation in the blood volume are modeled by the linearized perturbed compressible equations, while the sound propagation through the surrounding tissue is modeled by the linear elastic wave equation. A decomposition method is employed to separate the acoustic signal into a compression/longitudinal component (curl free) and a shear/transverse component (divergence free), and the sound signals from cases with and without the shear modulus are monitored on the epidermal surface and are analyzed to reveal the influence of the shear wave. The results show that the compression wave dominates the detected sound signal in the immediate vicinity of the stenosis, whereas the shear wave has more influence on surface signals further downstream of the stenosis. The implications of these results on cardiac auscultation are discussed.

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Figures

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Fig. 1

Schematic of the constricted channel model and acoustic domain employed in the current study. The dimensions in the schematic are not to scale.

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Fig. 2

Time evolution of (a) nondimensionalized vorticity field and (b) nondimensionalized pressure field. 0/4T is the minimum flow rate phase and 2/4T is the maximum flow rate phase.

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Fig. 3

(a) Time histories and (b) the corresponding spectra of the nondimensionalized time-derivative of the pressure on the upper lumen at three different downstream locations

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Fig. 4

Spatial distribution of the spectral energy of the nondimensionalized pressure time-derivative along the upper lumen

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Fig. 5

Schematic of the computational domain with an acceleration point source located at (0D,0D) and two monitor points at (2D,0D) and (0D,2D)

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Fig. 6

Spectra of the nondimensionalized vertical acceleration signal collected at monitor point (a) (2D,0D) and (b) (0D,2D)

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Fig. 7

Instantaneous spatial distribution of (a) compression and (b) shear components of the nondimensionalized vertical acceleration

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Fig. 8

(a) Comparison of nondimensionalized vertical acceleration signal between the simulations with and without shear modulus on the epidermal surface at x=4.5D and (b) spectra of the components of the nondimensionalized vertical acceleration from the simulation with shear modulus at the same location

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Fig. 9

(a) Comparison of nondimensionalized vertical acceleration signal between the simulations with and without shear modulus on the epidermal surface at × 515D and (b) spectra of the components of the nondimensionalized vertical acceleration from the simulation with shear modulus at the same location

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Fig. 10

Spectral energy of the nondimensionalized vertical acceleration along the epidermal surface for simulations with and without the shear wave mechanism for tissue thickness of 9D

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Fig. 11

Spectral energy of the nondimensionalized vertical acceleration along the epidermal surface for simulations with and without the shear-wave mechanism for tissue thickness of 6D

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