Computed Tomography Imaging of Patients With Obstructive Sleep Apnea

Anatomy and physiology of the upper airway

The nose is the major portal of air exchange between the internal and external environment. The nose participates in the vital functions of conditioning inspired air toward a temperature of 37°C and 100% relative humidity, providing local defense and filtering inhaled particulate matter and gases. It also functions in olfaction, which provides both a defense and pleasure for the individual. Understanding normal physiology provides the basis for recognizing abnormalities.

Correlation between severity of sleep apnea and upper airway morphology: Cephalometry and MD-CT study during awake and sleep states

CONCLUSION

The data show that the evaluation of obstruction site in patients with obstructive sleep apnea (OSA) should be performed in the sleep state rather than in wakefulness.

OBJECTIVE

The aim of this study was to identify correlation between severity of OSA as measured by the apnea-hypopnea index (AHI) and upper airway morphology examined by cephalometry and dynamic multidetector computed tomography (MD-CT) in awake and sleep states.

METHODS

Polysomnography and cephalometry were performed in 94 patients with snoring or OSA. Among them, 64 patients underwent MD-CT study. Thirteen cephalometric variables were measured. We analyzed the correlations between AHI and MD-CT measurements - minimal cross-sectional area (mCSA) and collapsibility index (CI) in high retropalate (HRP), low retropalate (LRP), high retroglossal (HRG), and low retroglossal (LRG) areas.

RESULTS

Statistically significant correlations between the AHI and inferior displacement of the hyoid bone and pharyngeal length were identified in the cephalometric study. In wakefulness, AHI had a negative correlation with mCSA in the LRP area and a significant correlation with CI in LRP and HRG in MD-CT measurements. However, in the sleep state, the AHI had a negative correlation with mCSA in LRP, HRG, and LRG areas and a meaningful correlation with CI for the whole upper airway (HRP, LRP, HRG, and LRG).

Differences of Upper Airway Morphology According to Obesity: Study with Cephalometry and Dynamic MD-CT

Objectives

We investigated difference of parameters of polysomnography, cephalometry and dynamic multi-detector computerized tomography (MD-CT) in wake and sleep states according to obesity.

Methods

We evaluated 93 patients who underwent polysomnography and cephalometry. MD-CT was performed in 68 of these 93 patients. Fifty-nine and 34 patients were classified as obese and non-obese, with obesity defined as BMI ≥25. Cephalometry results were analyzed for 12 variables. Using the MD-CT, we evaluated dynamic upper airway morphology in wake and sleep states and divided the upper airway into four parts named as high retropalatal (HRP), low retropalatal (LRP), high retroglossal (HRG), and low retroglossal (LRG). A minimal cross sectional area (mCSA) and collapsibility index (CI) were calculated for each airway level.

Results

Diastolic blood pressure (P=0.0005), neck circumference (P<0.0001), and apnea-hypopnea index (P<0.0001) were statistically significantly different between the obese and non-obese group. Among 12 cephalometric variables, there was a significant difference in only the distance from mandibular plane to hyoid bone (P=0.003). There was statistical difference in CI of HRG and LRG in sleep state (P=0.0449, 0.0281) but no difference in mCSA in wake and sleep states.

Conclusion

The obese group had more severe sleep apnea than the non-obese group. We believe that the increased severity of apnea in the obese group may be have been due to increased collapsibility of the upper airway rather than decreased size of the upper airway.

Obstructive sleep apnea: preoperative assessment

Obstructive sleep apnea is the most prevalent breathing disturbance in sleep. It is linked to a host of preexisting medical conditions, and associated with poorer postoperative outcomes. Screening and vigilance during the preoperative assessment identifies patients at high risk of obstructive sleep apnea. Further diagnostic tests may be performed, and plans can be made for tailored intraoperative care. The STOP and the STOP-Bang questionnaires are useful screening tools. Patients with a known diagnosis of obstructive sleep apnea should be seen in the preoperative clinic, where risk stratification and optimization may be done before surgery. This review article presents functional algorithms for the perioperative management of obstructive sleep apnea based on limited clinical evidence, and a collation of expert knowledge and practices. These recommendations may be used to assist the anesthesiologist in decision-making when managing the patient with obstructive sleep apnea.