title: Correlation between severity of sleep apnea and upper airway morphology based on advanced anatomical and functional imaging.
abstract: Determination of the apnea hypopnea index (AHI) as a measure of the severity of obstructive sleep apnea/hypopnea syndrome (OSAHS) is a widely accepted methodology. However, the outcome of such a determination depends on the method used, is time consuming and insufficient for prediction of the effect of all treatment modalities. For these reasons more methods for evaluating the severity of OSAHS, based on different imaging modalities, have been looked into and recent studies have shown that anatomical properties determined from three-dimensional (3D) computed tomography (CT) images are good markers for the severity of the OSAHS. Therefore, we correlated anatomical measurements of a 3D reconstruction of the upper airway together with flow simulation results with the severity of OSAHS in order to find a combination of variables to indicate the severity of OSAHS in patients. The AHI of 20 non-selected, consecutive patients has been determined during a polysomnography. All patients also underwent a CT scan from which a 3D model of the upper airway geometry was reconstructed. This 3D model was used to evaluate the anatomical properties of the upper airway in OSAHS patients as well as to perform computational fluid dynamics (CFD) computations to evaluate the airflow and resistance of this upper airway. It has been shown that a combination of the smallest cross-sectional area and the resistance together with the body mass index (BMI) form a set of markers that predict very well the severity of OSAHS in patients within this study. We believe that these markers can be used to evaluate the outcome of an OSAHS treatment.
authors.affiliation: Department of Pulmonology, University Hospital Antwerp, Wilrijkstraat 10, 2650 Edegem, Belgium. Wim.Vos@student.ua.ac.be
authors.forename: W
authors.initials: W
authors.lastname: Vos
authors.forename: J
authors.initials: J
authors.lastname: De Backer
authors.forename: A
authors.initials: A
authors.lastname: Devolder
authors.forename: O
authors.initials: O
authors.lastname: Vanderveken
authors.forename: S
authors.initials: S
authors.lastname: Verhulst
authors.forename: R
authors.initials: R
authors.lastname: Salgado
authors.forename: P
authors.initials: P
authors.lastname: Germonpre
authors.forename: B
authors.initials: B
authors.lastname: Partoens
authors.forename: F
authors.initials: F
authors.lastname: Wuyts
authors.forename: P
authors.initials: P
authors.lastname: Parizel
authors.forename: W
authors.initials: W
authors.lastname: De Backer
mesh_terms: D003198:Computer Simulation; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D007830:Larynx / Q000000981:diagnostic imaging / Q000473:pathology* / Q000503:physiopathology*; D008297:Male; D010614:Pharynx / Q000000981:diagnostic imaging / Q000473:pathology* / Q000503:physiopathology*; D011237:Predictive Value of Tests; D012720:Severity of Illness Index; D020181:Sleep Apnea, Obstructive / Q000000981:diagnostic imaging / Q000473:pathology* / Q000503:physiopathology* / Q000628:therapy; D014057:Tomography, X-Ray Computed