Literature DB >> 29129332

Aerosol deposition predictions in computed tomography-derived skeletons from severe asthmatics: A feasibility study.

Shinjiro Miyawaki1, Eric A Hoffman2, Sally E Wenzel3, Ching-Long Lin4.   

Abstract

BACKGROUND: The authors numerically investigated the correlation between airway skeletons of severe asthmatic human subjects and predicted aerosol deposition to shed light on the effect of environmental factors on asthma risk. We hypothesized that there are asthmatic subjects whose airway skeletal structure can expose the subject to a risk of higher local aerosol deposition compared to subjects with a more common/normal branching pattern.
METHODS: From a population of severe asthmatics studied at total lung capacity via computed tomography we randomly selected 8 subjects whose Forced Expiratory Volume in 1s, percent predicted fell below 45% predicted. To simulate aerosol motion in the human lungs, we employed in-house three-dimensional eddy-resolving computational fluid dynamics and particle tracking models utilizing 3 of the 8 severe asthmatic subjects. One of the 3 subjects was found to have a distinct, localized airway narrowing chosen for further investigation. In the simulation, we controlled flow rate and luminal area, i.e., Reynolds and Stokes numbers, in each branch of the computed tomography-derived airway skeletons.
FINDINGS: We found a distinct enhancement of aerosol deposition associated with the narrowed branches of one subject even when the luminal area was numerically adjusted from its narrowed state to that of a non-asthmatic subject. The branching angle, freed of luminal narrowing persisted in demonstrating a marginally significant increase in local particle deposition compared with the subjects without the initial constriction.
INTERPRETATION: These results demonstrate the possibility that inherent airway structure may influence localized constriction found in severe asthmatics.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Branching angle; Geometric airway model; Luminal area; Numerical aerosol model; Subject-specific

Mesh:

Substances:

Year:  2017        PMID: 29129332      PMCID: PMC5934349          DOI: 10.1016/j.clinbiomech.2017.10.020

Source DB:  PubMed          Journal:  Clin Biomech (Bristol, Avon)        ISSN: 0268-0033            Impact factor:   2.063


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