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Functional respiratory imaging as a tool to assess upper airway patency in children with obstructive sleep apnea
C Van Holsbeke1, W Vos, K Van Hoorenbeeck
1FluidDA, Edegem, Belgium.
Insights
3D airway models from CT scans better predict obstructive sleep apnea (OSA) severity in children than clinical markers. Functional imaging parameters show strong correlations with OSA severity, aiding treatment assessment.
Area of Science:
- Pediatric Pulmonology
- Medical Imaging
- Computational Fluid Dynamics
Background:
- Obstructive sleep apnea (OSA) is a common condition in children.
- Current methods for assessing OSA severity rely on clinical markers and polysomnography.
- Predicting OSA severity and treatment response can be challenging.
Purpose of the Study:
- To evaluate if 3D airway models derived from CT scans can predict OSA severity more accurately than standard clinical assessments.
- To explore the correlation between anatomical and functional airway properties and OSA severity.
Main Methods:
- Children with suspected OSA underwent polysomnography, clinical evaluation, and awake CT scans.
- 3D reconstructions of the pharyngeal airway were created from CT data.
- Computational fluid dynamics (CFD) modeling was used to analyze low inspiratory flow.
Main Results:
- Children with OSA showed significantly lower airway volumes and cross-sectional areas in the tonsil-adenoid overlap region compared to controls.
- Upper airway conductance derived from CFD modeling strongly correlated with OSA severity (apnea-hypopnea index).
- Clinical parameters of airway patency did not show significant correlations with OSA severity.
Conclusions:
- Functional imaging parameters derived from 3D CT models are powerful predictors of OSA severity in children.
- These imaging-based parameters are superior to traditional clinical scores for assessing OSA severity.
- Preliminary findings suggest these parameters may help identify patients who do not benefit from local airway treatments.
Objective:
We aim to investigate if anatomical and functional properties of the upper airway using computerized 3D models derived from computed tomography (CT) scans better predict obstructive sleep apnea (OSA) severity than standard clinical markers.
Methods:
Consecutive children with suspected OSA underwent polysomnography, clinical assessment of upper airway patency, and a CT scan while awake. A three-dimensional (3D) reconstruction of the pharyngeal airway was built from these images, and computational fluid dynamics modeling of low inspiratory flow was performed using open-source software.
Results:
Thirty-three children were included (23 boys; mean age, was 6.0±3.2y). OSA was diagnosed in 23 patients. Children with OSA had a significantly lower volume of the overlap region between tonsils and the adenoids (median volume, 1408 mm compared to 2173 mm; p=0.04), a lower mean cross-sectional area at this location (median volume, 69.3mm(2) compared to 114.3mm2; p=0.04), and a lower minimal cross-sectional area (median volume, 17.9 mm2 compared to 25.9 mm2; p=0.05). Various significant correlations were found between several imaging parameters and the severity of OSA, most pronounced for upper airway conductance (r=-0.46) (p<0.01) for correlation between upper airway conductance and the apnea-hypopnea index. No differences or significant correlations were observed with clinical parameters of upper airway patency. Preliminary data after treatment showed that none of the patients with residual OSA had their smallest cross-sectional area located in segment 3, and this frequency was significantly lower than in their peers whose sleep study normalized (64%; p=0.05).
Conclusion:
Functional imaging parameters are highly correlated with OSA severity and are a more powerful correlate than clinical scores of upper airway patency. Preliminary data also showed that we could identify differences in the upper airway of those subjects who did not benefit from a local upper airway treatment.
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