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.

Introduction

Obstructive sleep apnea/hypopnea syndrome (OSAHS) is considered as sleep-disordered breathing phenomenon (Levy et al., 2006). Patients suffering from OSAHS are characterized by recurrent episodes of partial or complete upper airway collapse at the end expiratory phase during sleep (De Backer et al., 2005a; Xu et al., 2004). The collapse is highlighted by a reduction in or complete cessation of airflow despite ongoing inspiratory efforts. The events are caused by multiple factors like high extraluminal pressure, i.e. obesity, decreased dilator and increased constrictor activity, low tracheal traction, Bernoulli effects, etc. (Schafer, 2006). Due to the lack of adequate alveolar ventilation that results from upper airway narrowing, oxygen saturation may drop and partial pressure of CO₂ may occasionally rise. Minimal diagnostic criteria are defined for OSAHS. Patients should have excessive daytime sleepiness that is not better explained by other factors and/or two or more of the following symptoms that also are not better explained by other factors: choking or gasping during sleep, recurrent awakenings from sleep, unrefreshing sleep, daytime fatigue and impaired concentration. More than five obstructed breathing events per hour during sleep should be present (De Backer, 2006). The potentially severe consequences of OSAHS include hypertension and atherosclerosis. This may lead to stroke and even heart failure, resulting in an increased prevalence of cardiovascular morbidity and mortality (De Backer, 2006).

Over the years, several treatment methods for OSAHS have been developed reaching from continuous positive airway pressure, over oral devices, to surgical interventions (Boudewyns and Van de Heyning, 2006; Marklund, 2006; Randerath, 2006; Schichtl and Pfeifer, 2006; Smith, 2006).

The severity of OSAHS is usually expressed by the apnea hypopnea index (AHI). The AHI is a measurement for the collapsibility of the upper airway and is a combined magnitude for the amount of collapses and near collapses, or flow limitations, of the upper airway during 1 h of sleep. Different methods in the determination of the AHI (Farre et al., 2004) are known to give different results (De Backer, 2006; Epstein et al., 2000; Series and Marc, 1999). This methodology-dependent character and the relative complexity (duration, equipment, etc.) in the determination of the AHI and the need for better methods to predict treatment response have initiated a search for a methodology that has the potential to quantify OSAHS severity by means of different imaging modalities that more directly reflect the status of the upper airway (Pinto Basto and Rodenstein, 2006; Schwab, 1998). Recent studies have shown that anatomical properties determined from three-dimensional (3D) computed tomography (CT) images do correlate well with the AHI and thus with the severity of the OSAHS (Li et al., 2003, Li et al., 2005).

Converting traditional 3D CT images into computer-aided design (CAD) models does not only allow visual data to be extracted, but also an additional functional imaging of the upper airway can be performed by means of computational fluid dynamics (CFD) calculations (De Backer et al., 2005a, De Backer et al., 2005b). The aim of this study was to investigate the correlation between 3D CAD model measurements, CFD computations and the AHI in OSAHS patients. The finding could subsequently be used to identify markers to predict and evaluate OSAHS treatment for the individual patient.