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Published on: December 6, 2016
Computational fluid dynamics study in children with obstructive sleep apnea
Wei-Chung Hsu1,2,3, Kun-Tai Kang1,4,5, Yunn-Jy Chen3,6
1Department of Otolaryngology, National Taiwan University Hospital, Taipei, Taiwan.
Insights
Computational fluid dynamics (CFD) can identify airway differences in children with obstructive sleep apnea (OSA). Higher airway pressure and resistance in OSA patients suggest CFD is a valuable diagnostic tool.
Area of Science:
- Pediatric Pulmonology
- Medical Imaging
- Biomedical Engineering
Background:
- Obstructive sleep apnea (OSA) is a common condition in children.
- Accurate diagnosis of OSA relies on objective measures of upper airway patency.
- Image-based computational fluid dynamics (CFD) offers a non-invasive method to assess airway dynamics.
Purpose of the Study:
- To identify distinct image-based computational fluid dynamics (CFD) characteristics in children diagnosed with obstructive sleep apnea (OSA).
- To evaluate the utility of CFD in differentiating between children with OSA and those with primary snoring.
Main Methods:
- A diagnostic study involving a hospital-based cohort of children with symptoms suggestive of OSA.
- Three-dimensional CFD models were generated from cone-beam computed tomography (CBCT) scans.
- Polysomnography was used to diagnose OSA and categorize participants based on apnea-hypopnea index (AHI).
Main Results:
- Children with moderate-to-severe OSA (AHI > 5) exhibited significantly higher total airway pressure, total airway resistance, and velocity at minimal cross-sectional area compared to those with primary snoring (AHI < 1).
- Optimal cut-off points for identifying moderate-to-severe OSA were determined for total airway pressure (46.2 Pa), total airway resistance (2373 Nm), and velocity at minimal cross-sectional area (12.6 m/s).
- Conditional logistic regression confirmed that these CFD parameters were significantly associated with an increased risk of moderate-to-severe OSA.
Conclusions:
- Image-based computational fluid dynamics (CFD) is a promising tool for assessing upper airway patency in pediatric OSA.
- CFD parameters like airway pressure, resistance, and velocity can aid in the diagnosis and risk stratification of OSA in children.
- Further research can explore the integration of CFD into routine clinical practice for OSA evaluation.
Objectives:
This study aims to identify characteristics in image-based computational fluid dynamics (CFD) in children with obstructive sleep apnea (OSA).
Design:
Diagnostic study.
Setting:
Hospital-based cohort.
Participants:
Children with symptoms suggestive of OSA were recruited and underwent polysomnography.
Main Outcome Measures:
Three-dimensional models of computational fluid dynamics were derived from cone-beam computed tomography.
Results:
A total of 68 children participated in the study (44 boys; mean age: 7.8 years), including 34 participants having moderate-to-severe OSA (apnea-hypopnea index [AHI] greater than 5 events/h), and 34 age, gender, and body mass index percentile matched participants having primary snoring (AHI less than 1). Children with moderate-to-severe OSA had a significantly higher total airway pressure (166.3 vs. 39.1 Pa, p = .009), total airway resistance (9851 vs. 2060 Newton-metre, p = .004) and velocity at a minimal cross-sectional area (65.7 vs. 8.8 metre per second, p = .017) than those with primary snoring. The optimal cut-off points for moderate-to-severe OSA were 46.2 Pa in the total airway pressure (area under the curve [AUC] = 73.2%), 2373 Newton-metre in the total airway resistance (AUC = 72.5%) and 12.6 metres per second in the velocity at a minimal cross-sectional area (AUC = 70.5%). The conditional logistic regression model revealed that total airway pressure, total airway resistance and velocity at minimal cross-sectional area were significantly associated with an increased risk of moderate-to-severe OSA.
Conclusions:
This study demonstrates that CFD could be a useful tool for evaluating upper airway patency in children with OSA.
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