The effect of including dynamic imaging derived airway wall motion in CFD simulations of respiratory airflow in patients with OSA

Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid dynamics (CFD) simulations allow non-invasive assessment of clinically relevant metrics such as total pressure loss (TPL) in patients with OSA...

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Vydáno v:	Scientific reports Ročník 14; číslo 1; s. 17242 - 11
Hlavní autoři:	Xiao, Qiwei, Gunatilaka, Chamindu, McConnell, Keith, Bates, Alister
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 26.07.2024 Nature Publishing Group Nature Portfolio
Témata:	639/166/985 639/705/1042 639/766/189 Adult Allergic diseases Apnea Boundary conditions Computational fluid dynamics Computer Simulation Female Fluid dynamics Humanities and Social Sciences Humans Hydrodynamics Inhalation Magnet resonance imaging Magnetic Resonance Imaging - methods Male Middle Aged multidisciplinary Obstructive sleep apnea Patient-specific Physiology Pulmonary Ventilation - physiology Respiration Respiratory airflow Respiratory tract diseases Science Science (multidisciplinary) Simulation Sleep apnea Sleep Apnea, Obstructive - diagnostic imaging Sleep Apnea, Obstructive - physiopathology Sleep disorders Upper airway Respiratory airflow Patient-specific Computational fluid dynamics Magnet resonance imaging Obstructive sleep apnea Upper airway
ISSN:	2045-2322, 2045-2322
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Abstract	Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid dynamics (CFD) simulations allow non-invasive assessment of clinically relevant metrics such as total pressure loss (TPL) in patients with OSA. However, most of such studies use static airway geometries, which neglect physiological airway motion. This study aims to quantify how much the airway moves during the respiratory cycle, and to determine how much this motion affects CFD pressure loss predictions. Motion of the airway wall was quantified using cine MRI data captured over a single respiratory cycle in three subjects with OSA. Synchronously-measured respiratory airflow was used as the flow boundary condition for all simulations. Simulations were performed for full respiratory cycles with 5 different wall boundary conditions: (1) a moving airway wall, and static airway walls at (2) peak inhalation, (3) end inhalation, (4) peak exhalation, and (5) end exhalation. Geometric analysis exposed significant local airway cross-sectional area (CSA) variability, with local CSA varying as much as 300%. The comparative CFD simulations revealed the discrepancies between dynamic and static wall simulations are subject-specific, with TPL differing by up to 400% between static and dynamic simulations. There is no consistent pattern to which static wall CFD simulations overestimate or underestimate the airway TPL. This variability underscores the complexity of accurately modeling airway physiology and the importance of considering dynamic anatomical factors to predict realistic respiratory airflow dynamics in patients with OSA.
AbstractList	Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid dynamics (CFD) simulations allow non-invasive assessment of clinically relevant metrics such as total pressure loss (TPL) in patients with OSA. However, most of such studies use static airway geometries, which neglect physiological airway motion. This study aims to quantify how much the airway moves during the respiratory cycle, and to determine how much this motion affects CFD pressure loss predictions. Motion of the airway wall was quantified using cine MRI data captured over a single respiratory cycle in three subjects with OSA. Synchronously-measured respiratory airflow was used as the flow boundary condition for all simulations. Simulations were performed for full respiratory cycles with 5 different wall boundary conditions: (1) a moving airway wall, and static airway walls at (2) peak inhalation, (3) end inhalation, (4) peak exhalation, and (5) end exhalation. Geometric analysis exposed significant local airway cross-sectional area (CSA) variability, with local CSA varying as much as 300%. The comparative CFD simulations revealed the discrepancies between dynamic and static wall simulations are subject-specific, with TPL differing by up to 400% between static and dynamic simulations. There is no consistent pattern to which static wall CFD simulations overestimate or underestimate the airway TPL. This variability underscores the complexity of accurately modeling airway physiology and the importance of considering dynamic anatomical factors to predict realistic respiratory airflow dynamics in patients with OSA.Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid dynamics (CFD) simulations allow non-invasive assessment of clinically relevant metrics such as total pressure loss (TPL) in patients with OSA. However, most of such studies use static airway geometries, which neglect physiological airway motion. This study aims to quantify how much the airway moves during the respiratory cycle, and to determine how much this motion affects CFD pressure loss predictions. Motion of the airway wall was quantified using cine MRI data captured over a single respiratory cycle in three subjects with OSA. Synchronously-measured respiratory airflow was used as the flow boundary condition for all simulations. Simulations were performed for full respiratory cycles with 5 different wall boundary conditions: (1) a moving airway wall, and static airway walls at (2) peak inhalation, (3) end inhalation, (4) peak exhalation, and (5) end exhalation. Geometric analysis exposed significant local airway cross-sectional area (CSA) variability, with local CSA varying as much as 300%. The comparative CFD simulations revealed the discrepancies between dynamic and static wall simulations are subject-specific, with TPL differing by up to 400% between static and dynamic simulations. There is no consistent pattern to which static wall CFD simulations overestimate or underestimate the airway TPL. This variability underscores the complexity of accurately modeling airway physiology and the importance of considering dynamic anatomical factors to predict realistic respiratory airflow dynamics in patients with OSA. Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid dynamics (CFD) simulations allow non-invasive assessment of clinically relevant metrics such as total pressure loss (TPL) in patients with OSA. However, most of such studies use static airway geometries, which neglect physiological airway motion. This study aims to quantify how much the airway moves during the respiratory cycle, and to determine how much this motion affects CFD pressure loss predictions. Motion of the airway wall was quantified using cine MRI data captured over a single respiratory cycle in three subjects with OSA. Synchronously-measured respiratory airflow was used as the flow boundary condition for all simulations. Simulations were performed for full respiratory cycles with 5 different wall boundary conditions: (1) a moving airway wall, and static airway walls at (2) peak inhalation, (3) end inhalation, (4) peak exhalation, and (5) end exhalation. Geometric analysis exposed significant local airway cross-sectional area (CSA) variability, with local CSA varying as much as 300%. The comparative CFD simulations revealed the discrepancies between dynamic and static wall simulations are subject-specific, with TPL differing by up to 400% between static and dynamic simulations. There is no consistent pattern to which static wall CFD simulations overestimate or underestimate the airway TPL. This variability underscores the complexity of accurately modeling airway physiology and the importance of considering dynamic anatomical factors to predict realistic respiratory airflow dynamics in patients with OSA. Abstract Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid dynamics (CFD) simulations allow non-invasive assessment of clinically relevant metrics such as total pressure loss (TPL) in patients with OSA. However, most of such studies use static airway geometries, which neglect physiological airway motion. This study aims to quantify how much the airway moves during the respiratory cycle, and to determine how much this motion affects CFD pressure loss predictions. Motion of the airway wall was quantified using cine MRI data captured over a single respiratory cycle in three subjects with OSA. Synchronously-measured respiratory airflow was used as the flow boundary condition for all simulations. Simulations were performed for full respiratory cycles with 5 different wall boundary conditions: (1) a moving airway wall, and static airway walls at (2) peak inhalation, (3) end inhalation, (4) peak exhalation, and (5) end exhalation. Geometric analysis exposed significant local airway cross-sectional area (CSA) variability, with local CSA varying as much as 300%. The comparative CFD simulations revealed the discrepancies between dynamic and static wall simulations are subject-specific, with TPL differing by up to 400% between static and dynamic simulations. There is no consistent pattern to which static wall CFD simulations overestimate or underestimate the airway TPL. This variability underscores the complexity of accurately modeling airway physiology and the importance of considering dynamic anatomical factors to predict realistic respiratory airflow dynamics in patients with OSA.
ArticleNumber	17242
Author	McConnell, Keith Xiao, Qiwei Gunatilaka, Chamindu Bates, Alister
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Cites_doi	10.1089/jamp.2023.0023 10.1016/j.clinbiomech.2017.10.011 10.1016/j.resp.2007.02.006 10.1002/fld.1805 10.1016/j.jbiomech.2019.07.014 10.1016/J.CMPB.2024.108064 10.1002/alr.21319 10.1164/rccm.202208-1574IM 10.1152/japplphysiol.00071.2023 10.1063/5.0053326 10.1111/j.1440-1843.2006.00862.x 10.1007/s11517-008-0420-1 10.1016/j.compbiomed.2020.104099 10.1097/MCP.0b013e3283130f66 10.1016/j.jbiomech.2022.111304 10.1002/cnm.3144 10.1016/j.medengphy.2015.05.014 10.1093/sleep/zsaa071 10.1164/ajrccm/148.5.1385 10.14814/phy2.14099 10.7150/ijms.76495 10.1371/journal.pone.0256460 10.1213/ane.0b013e3181adc506 10.1016/j.resp.2016.09.002 10.1007/s10439-019-02410-1 10.1016/j.cmpb.2020.105627 10.1016/j.jbiomech.2011.08.019 10.3390/acoustics5040060 10.1016/j.neuroimage.2006.01.015 10.1017/S0022215117001906 10.1007/s00405-021-06942-y 10.1016/j.jbiomech.2015.08.017 10.1164/AJRCCM-CONFERENCE.2021.203.1_MEETINGABSTRACTS.A4677
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Snippet	Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid... Abstract Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific...
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SubjectTerms	639/166/985 639/705/1042 639/766/189 Adult Allergic diseases Apnea Boundary conditions Computational fluid dynamics Computer Simulation Female Fluid dynamics Humanities and Social Sciences Humans Hydrodynamics Inhalation Magnet resonance imaging Magnetic Resonance Imaging - methods Male Middle Aged multidisciplinary Obstructive sleep apnea Patient-specific Physiology Pulmonary Ventilation - physiology Respiration Respiratory airflow Respiratory tract diseases Science Science (multidisciplinary) Simulation Sleep apnea Sleep Apnea, Obstructive - diagnostic imaging Sleep Apnea, Obstructive - physiopathology Sleep disorders Upper airway
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Title	The effect of including dynamic imaging derived airway wall motion in CFD simulations of respiratory airflow in patients with OSA
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