Use of cone beam computed tomography imaging for airway measurement to predict obstructive sleep apnea

Upper Airway Characteristics and Morphological Changes by Different MADs in OSA Adult Subjects Assessed by CBCT 3D Imaging

This study aimed to analyse the effectiveness of four different designs of the Mandibular Advancement Device (MAD) and the morphological changes on upper airway characteristics of Obstructive Sleep Apnea (OSA) patients inducted by each of them, detected by Cone Beam Computer Tomography (CBCT) 3D imaging. Twenty-two patients were recruited after an OSA diagnosis with PSG. Four different customised and titratable MADs were used and an initial CBCT scan was obtained for each patient. Six months after the end of the MAD titration phase, all the subjects performed a second PSG with the MAD in situ; the second PSG showed an Apnoea-Hypopnoea Index (AHI) of <5 or a decrease of 50% in AHI when compared with the initial AHI. Moreover, a second CBCT scan with the MAD in situ was performed. DICOM files were imported into the airway analysis software programme and the pharyngeal area around the oropharynx was highlighted. The area and volume of the oropharynx with and without the device was evaluated. A considerable improvement of the airway was observed (+33.76%), and a significant difference in the enlargement ratio between the posterior soft palate (+32.41%) and the posterior tongue (+36.96%) region was also found. The greatest increase in airway volume was achieved in patients treated with the MAD Forward and TAP (+42.77% and +41.63%, respectively). MAD therapy is effective to treat moderate to severe OSA with an increased upper airway volume. The design of the MAD can influence the effectiveness of the treatment.

The Usefulness of Modified Mallampati Score and CT Upper Airway Volume Measurements in Diagnosing OSA among Patients with Breathing-Related Sleep Disorders

Background: Obstructive sleep apnea (OSA) is a condition causing restriction of the airflow through the upper airways during sleep, despite preserved inspiratory muscle activity. This may lead to the development of secondary hypertension, ischemic heart disease, myocardial infarction, and arrhythmia. Moreover, the prevalence of OSA is on the rise. Methods: Comparison of scores from the Berlin Questionnaire, modified Mallampati scores (MMP), pulse oximetry readings and Upper Airway Volume (UAV) data obtained from CBCT (Cone Beam Computed Tomography). The study group of 129 patients of both sexes reporting sleep-related breathing problems completed the Berlin Questionnaire, had their oxygen saturation (SpO2) measured with a PO40 pulse oximeter, and oropharyngeal tissues assessed according to MMP. CBCT scans were put into 3D Amira TM 3D computer analysisto obtain UAV values. Results: Snoring was associated with significantly higher BMI compared to non-snoring patients. Furthermore, snoring patients had higher heart rate, modified Mallampati score, and lower UAV than the non-snoring group. The multifactorial analysis showed MMP as a useful indicator of the risk of snoring (OR = 7.468 (3863–14, 507, p < 0.001)). Conclusions: The composition of MMP together with UAV and the Berlin questionnaire might be reliable indicators to assess the risk of snoring.

Simple and Unbiased OSA Prescreening: Introduction of a New Morphologic OSA Prediction Score

PURPOSE

An early prescreening in suspected obstructive sleep apnea (OSA) patients is desirable to expedite diagnosis and treatment. However, the accuracy and applicability of current prescreening tools is insufficient. We developed and tested an unbiased scoring system based solely on objective variables, which focuses on the diagnosis of severe OSA and exclusion of OSA.

PATIENTS AND METHODS

The OSA prediction score was developed (n = 150) and validated (n = 50) within German sleep center patients that were recruited as part of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Six objective variables that were easy to assess and highly correlated with the apnea-hypopnea index were chosen for the score, including some known OSA risk factors: body-mass index, neck circumference, waist circumference, tongue position, male gender, and age (for women only). To test the predictive ability of the score and identify score thresholds, the receiver-operating characteristics (ROC) and curve were calculated.

RESULTS

A score ≥8 for predicting severe OSA resulted in an area under the ROC curve (ROC-AUC) of 90% (95% confidence interval: 84%, 95%), test accuracy of 82% (75%, 88%), sensitivity of 82% (65%, 93%), specificity of 82% (74%, 88%), and positive likelihood ratio of 4.55 (3.00, 6.90). A score ≤5 for predicting the absence of OSA resulted in a ROC-AUC of 89% (83%, 94%), test accuracy of 80% (73%, 86%), sensitivity of 72% (55%, 85%), specificity of 83% (75%, 89%), and positive likelihood ratio of 4.20 (2.66, 6.61). Performance characteristics were comparable in the small validation sample.

CONCLUSION

We introduced a novel prescreening tool combining easily obtainable objective measures with predictive power and high general applicability. The proposed tool successfully predicted severe OSA (important due to its high risk of cardiovascular disease) and the exclusion of OSA (rarely a feature of previous screening instruments, but important for better differential diagnosis and treatment).