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Article: Computational fluid dynamics analysis on the upper airways of obstructive sleep apnea using patient - specific models

TitleComputational fluid dynamics analysis on the upper airways of obstructive sleep apnea using patient - specific models
Authors
KeywordsComputational Fluid Dynamics
Obstructive Sleep Apnea
Patient Specific Model
Upper Airway
Issue Date2011
PublisherNewswood Ltd. The Journal's web site is located at http://www.iaeng.org/IJCS/index.html
Citation
Iaeng International Journal Of Computer Science, 2011, v. 38 n. 4, p. 401-408 How to Cite?
AbstractObstructive Sleep Apnea Syndrome (OSAS) is a common sleep disorder. It is characterized by repeated occlusion of upper airway and discontinuation of sleep. The breathing pauses and starts again with a loud snort. There may even be an abrupt interruption of sleep to maintain the patency of the airway. The pressure drop along the pharyngeal pathway should be a good indicator to show the severity of the pathological airways. Computational Fluid Dynamics (CFD) has become an important tool in investigating the internal flow dynamics of the respiratory system, especially for the upper airway. It provides a non-invasive environment for the analysis of the biological flow. Employing such technology, this study will provide insight for a male patient with severe OSAS. This patient also underwent surgical procedures to improve the size of the airway. The pre-operative and post-operative CT scans were reconstructed and converted to two patient-specific, three-dimensional models suitable for numerical simulations. The inhalation process was simulated using a constant volume flow rate, 0.3 liter per second (L s -1), at the nostrils for both cases. An index, the 'resistance of the airway', was defined as the pressure drop per unit flow rate to estimate the tendency of airway collapse. The pressure distribution from the velopharynx to hypopharynx was investigated. The pressure drops were 12.1 Pascal (Pa) and 7.3 Pascal before and after surgical treatment respectively. The resistance of airway changed from 40 Pa s L -1 to 24 Pa s L -1, a 40% reduction. The results showed that the pressure drop along the upper airway was reduced significantly after the surgical procedure. This decreased the collapsibility of the airway and consequently improved the sleep quality.
Persistent Identifierhttp://hdl.handle.net/10722/157156
ISSN
2023 SCImago Journal Rankings: 0.278
References

 

DC FieldValueLanguage
dc.contributor.authorFan, Yen_US
dc.contributor.authorCheung, LKen_US
dc.contributor.authorChong, MMen_US
dc.contributor.authorChua, HDen_US
dc.contributor.authorChow, KWen_US
dc.contributor.authorLiu, CHen_US
dc.date.accessioned2012-08-08T08:45:34Z-
dc.date.available2012-08-08T08:45:34Z-
dc.date.issued2011en_US
dc.identifier.citationIaeng International Journal Of Computer Science, 2011, v. 38 n. 4, p. 401-408en_US
dc.identifier.issn1819-656Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/157156-
dc.description.abstractObstructive Sleep Apnea Syndrome (OSAS) is a common sleep disorder. It is characterized by repeated occlusion of upper airway and discontinuation of sleep. The breathing pauses and starts again with a loud snort. There may even be an abrupt interruption of sleep to maintain the patency of the airway. The pressure drop along the pharyngeal pathway should be a good indicator to show the severity of the pathological airways. Computational Fluid Dynamics (CFD) has become an important tool in investigating the internal flow dynamics of the respiratory system, especially for the upper airway. It provides a non-invasive environment for the analysis of the biological flow. Employing such technology, this study will provide insight for a male patient with severe OSAS. This patient also underwent surgical procedures to improve the size of the airway. The pre-operative and post-operative CT scans were reconstructed and converted to two patient-specific, three-dimensional models suitable for numerical simulations. The inhalation process was simulated using a constant volume flow rate, 0.3 liter per second (L s -1), at the nostrils for both cases. An index, the 'resistance of the airway', was defined as the pressure drop per unit flow rate to estimate the tendency of airway collapse. The pressure distribution from the velopharynx to hypopharynx was investigated. The pressure drops were 12.1 Pascal (Pa) and 7.3 Pascal before and after surgical treatment respectively. The resistance of airway changed from 40 Pa s L -1 to 24 Pa s L -1, a 40% reduction. The results showed that the pressure drop along the upper airway was reduced significantly after the surgical procedure. This decreased the collapsibility of the airway and consequently improved the sleep quality.en_US
dc.languageengen_US
dc.publisherNewswood Ltd. The Journal's web site is located at http://www.iaeng.org/IJCS/index.htmlen_US
dc.relation.ispartofIAENG International Journal of Computer Scienceen_US
dc.subjectComputational Fluid Dynamicsen_US
dc.subjectObstructive Sleep Apneaen_US
dc.subjectPatient Specific Modelen_US
dc.subjectUpper Airwayen_US
dc.titleComputational fluid dynamics analysis on the upper airways of obstructive sleep apnea using patient - specific modelsen_US
dc.typeArticleen_US
dc.identifier.emailCheung, LK:lkcheung@hkucc.hku.hken_US
dc.identifier.emailChow, KW:kwchow@hku.hken_US
dc.identifier.emailLiu, CH:chliu@hkucc.hku.hken_US
dc.identifier.authorityCheung, LK=rp00013en_US
dc.identifier.authorityChow, KW=rp00112en_US
dc.identifier.authorityLiu, CH=rp00152en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-81255170157en_US
dc.identifier.hkuros210118-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-81255170157&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume38en_US
dc.identifier.issue4en_US
dc.identifier.spage401en_US
dc.identifier.epage408en_US
dc.publisher.placeHong Kongen_US
dc.identifier.scopusauthoridFan, Y=20734044200en_US
dc.identifier.scopusauthoridCheung, LK=7102302747en_US
dc.identifier.scopusauthoridChong, MM=54383142600en_US
dc.identifier.scopusauthoridChua, HD=10838799100en_US
dc.identifier.scopusauthoridChow, KW=13605209900en_US
dc.identifier.scopusauthoridLiu, CH=36065161300en_US
dc.identifier.issnl1819-656X-

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