Literature DB >> 29079097

Assessing the relationship between movement and airflow in the upper airway using computational fluid dynamics with motion determined from magnetic resonance imaging.

Alister J Bates1, Andreas Schuh2, Gabriel Amine-Eddine3, Keith McConnell4, Wolfgang Loew5, Robert J Fleck6, Jason C Woods7, Charles L Dumoulin5, Raouf S Amin4.   

Abstract

BACKGROUND: Computational fluid dynamics simulations of respiratory airflow in the upper airway reveal clinically relevant information, including sites of local resistance, inhaled particle deposition, and the effect of pathological constrictions. Unlike previous simulations, which have been performed on rigid anatomical models from static medical imaging, this work utilises ciné imaging during respiration to create dynamic models and more closely represent airway physiology.
METHODS: Airway movement maps were obtained from non-rigid image registration of fast-cine MRI and applied to high-spatial-resolution airway surface models. Breathing flowrates were recorded simultaneously with imaging. These data formed the boundary conditions for large eddy simulation computations of the airflow from exterior mask to bronchi. Simulations with rigid geometries were performed to demonstrate the resulting airflow differences between airflow simulations in rigid and dynamic airways.
FINDINGS: In the analysed rapid breathing manoeuvre, incorporating airway movement significantly changed the findings of the CFD simulations. Peak resistance increased by 19.8% and occurred earlier in the breath. Overall pressure loss decreased by 19.2%, and the proportion of flow in the mouth increased by 13.0%. Airway wall motion was out-of-phase with the air pressure force, demonstrating the presence of neuromuscular motion. In total, the anatomy did 25.2% more work on the air than vice versa. INTERPRETATIONS: Realistic movement of the airway is incorporated into CFD simulations of airflow in the upper airway for the first time. This motion is vital to producing clinically relevant computational models of respiratory airflow and will allow novel analysis of dynamic conditions, such as sleep apnoea.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  CFD; Image registration; MRI; Movement; Sleep apnoea; Upper airways

Mesh:

Year:  2017        PMID: 29079097     DOI: 10.1016/j.clinbiomech.2017.10.011

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


  12 in total

Review 1.  Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration.

Authors:  Haythem Rehouma; Rita Noumeir; Sandrine Essouri; Philippe Jouvet
Journal:  Sensors (Basel)       Date:  2020-12-17       Impact factor: 3.576

Review 2.  Magnetic resonance imaging of obstructive sleep apnea in children.

Authors:  Robert J Fleck; Sally R Shott; Mohamed Mahmoud; Stacey L Ishman; Raouf S Amin; Lane F Donnelly
Journal:  Pediatr Radiol       Date:  2018-08-04

3.  The effect of airway motion and breathing phase during imaging on CFD simulations of respiratory airflow.

Authors:  Chamindu C Gunatilaka; Andreas Schuh; Nara S Higano; Jason C Woods; Alister J Bates
Journal:  Comput Biol Med       Date:  2020-11-01       Impact factor: 4.589

4.  Quantitative Assessment of Regional Dynamic Airway Collapse in Neonates via Retrospectively Respiratory-Gated 1 H Ultrashort Echo Time MRI.

Authors:  Alister J Bates; Nara S Higano; Erik B Hysinger; Robert J Fleck; Andrew D Hahn; Sean B Fain; Paul S Kingma; Jason C Woods
Journal:  J Magn Reson Imaging       Date:  2018-09-25       Impact factor: 4.813

5.  Imaging the breastfeeding swallow: Pilot study utilizing real-time MRI.

Authors:  Nikki Mills; Anna-Maria Lydon; David Davies-Payne; Melissa Keesing; Donna T Geddes; Seyed Ali Mirjalili
Journal:  Laryngoscope Investig Otolaryngol       Date:  2020-05-20

Review 6.  Computational fluid dynamics modelling of human upper airway: A review.

Authors:  W M Faizal; N N N Ghazali; C Y Khor; Irfan Anjum Badruddin; M Z Zainon; Aznijar Ahmad Yazid; Norliza Binti Ibrahim; Roziana Mohd Razi
Journal:  Comput Methods Programs Biomed       Date:  2020-06-26       Impact factor: 5.428

Review 7.  A Review of Respiratory Anatomical Development, Air Flow Characterization and Particle Deposition.

Authors:  Mohammad S Islam; Gunther Paul; Hui X Ong; Paul M Young; Y T Gu; Suvash C Saha
Journal:  Int J Environ Res Public Health       Date:  2020-01-07       Impact factor: 3.390

8.  Effect of tube length on the buckling pressure of collapsible tubes.

Authors:  M Amin F Zarandi; Kevin Garman; John S Rhee; B Tucker Woodson; Guilherme J M Garcia
Journal:  Comput Biol Med       Date:  2021-07-28       Impact factor: 6.698

9.  Molecular Binding Contributes to Concentration Dependent Acrolein Deposition in Rat Upper Airways: CFD and Molecular Dynamics Analyses.

Authors:  Jinxiang Xi; Qin Hu; Linlin Zhao; Xiuhua April Si
Journal:  Int J Mol Sci       Date:  2018-03-27       Impact factor: 5.923

10.  Nasal sprayed particle deposition in a human nasal cavity under different inhalation conditions.

Authors:  Hadrien Calmet; Kiao Inthavong; Beatriz Eguzkitza; Oriol Lehmkuhl; Guillaume Houzeaux; Mariano Vázquez
Journal:  PLoS One       Date:  2019-09-06       Impact factor: 3.240

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