Evaluation of human obstructive sleep apnea using computational fluid dynamics

Obstructive sleep apnea (OSA) severity might be correlated to the flow characteristics of the upper airways. We aimed to investigate the severity of OSA based on 3D models constructed from CT scans coupled with computational fluid dynamics (CFD) simulations. The CT scans of seven adult patients diag...

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Published inCommunications biology Vol. 2; no. 1; p. 423
Main Authors Taherian, Shahab, Rahai, Hamid, Lopez, Samuel, Shin, Jamie, Jafari, Behrouz
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 21.11.2019
Nature Publishing Group
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ISSN2399-3642
2399-3642
DOI10.1038/s42003-019-0668-z

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Summary:Obstructive sleep apnea (OSA) severity might be correlated to the flow characteristics of the upper airways. We aimed to investigate the severity of OSA based on 3D models constructed from CT scans coupled with computational fluid dynamics (CFD) simulations. The CT scans of seven adult patients diagnosed with OSA were used to reconstruct the 3D models of the upper airways and CFD modeling and analyses were performed. Results from the fluid simulations were compared with the apnea-hypopnea index. Here we show a correlation between a CFD-based parameter, the adjusted pressure coefficient (Cp*), and the respective apnea-hypopnea index (Pearson’s r = 0.91, p = 0.004), which suggests that the anatomical-based model coupled with CFD could provide functional and localized information for different regions of the upper airways. Taherian et al. show a correlation between the severity of apnea-hypopnea and the adjusted pressure coefficient. This study suggests that anatomy-based models coupled with computational fluid dynamics may serve to identify biomarkers that report the severity of sleep obstruction.
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ISSN:2399-3642
2399-3642
DOI:10.1038/s42003-019-0668-z