title: Functional respiratory imaging as a tool to assess upper airway patency in children with obstructive sleep apnea.
abstract: 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).
  
  
  CONCLUSIONS
  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.
authors.affiliation: FluidDA, Edegem, Belgium.
authors.forename: C
authors.initials: C
authors.lastname: Van Holsbeke
authors.forename: W
authors.initials: W
authors.lastname: Vos
authors.forename: K
authors.initials: K
authors.lastname: Van Hoorenbeeck
authors.forename: A
authors.initials: A
authors.lastname: Boudewyns
authors.forename: R
authors.initials: R
authors.lastname: Salgado
authors.forename: P R
authors.initials: PR
authors.lastname: Verdonck
authors.forename: J
authors.initials: J
authors.lastname: Ramet
authors.forename: J
authors.initials: J
authors.lastname: De Backer
authors.forename: W
authors.initials: W
authors.lastname: De Backer
authors.forename: S L
authors.initials: SL
authors.lastname: Verhulst
mesh_terms: D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D006984:Hypertrophy; D021621:Imaging, Three-Dimensional / Q000379:methods; D008297:Male; D009296:Nasal Cavity / Q000000981:diagnostic imaging* / Q000473:pathology; D015508:Nasal Obstruction / Q000000981:diagnostic imaging* / Q000473:pathology; D014066:Palatine Tonsil / Q000000981:diagnostic imaging / Q000473:pathology; D017286:Polysomnography; D012720:Severity of Illness Index; D020181:Sleep Apnea, Obstructive / Q000000981:diagnostic imaging* / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods*