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DOI: 10.1055/s-0039-1686789
Can the therapy outcome of Upper Airway Stimulation (UAS) be predicted by a preoperative MRI?
In the recent years UAS has been established as a second line therapy for Obstructive Sleep Apnea (OSA) in case of CPAP failure. Its efficacy has been shown over several years in large cohort studies. For a good therapy response a selection of patients is needed whereby the drug induced sleep endoscopy (DISE) is of major importance for excluding a complete concentric collapse of the soft palate. The significance of preoperative radiologic cross sectional imaging is still unclear. Based on the lack of radiation and the good ways of assessing soft tissue, the MRI seems to be suitable for preoperative evaluation of potential UAS patients.
We performed a retrospective analysis including 25 patients who were treated with UAS and had received a preoperative MRI examination of the neck. The ratio of the anterior- posterior diameter to the latero-lateral diameter on both velum and tongue base level were determined. The assumption was that a larger value coincides with a worse therapy outcome as it hints at a concentric respectively lateral collapse pattern. Therapy success was defined as an AHI < 15/h, so that 60% (n = 15, responder) were successfully and 40% (n = 10, non-responder) were unsuccessfully treated. The average AHI came down from initially 27,9/h to 14,2/h. Both groups were similar regarding average BMI. Differences in the ratio on retropalatel and retrolingual level were not significant (average: retropalatal: 0,37 vs. 0,34; retrolingual: 0,5 vs. 0,54).
Therefor, the MRI does not seem to be suitable as a screening method for the therapy outcome before UAS.
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Armin Steffen: Study investigator, Consultant, Reisekostenerstattung sowie Vergütung für eingeladene Vorträge durch Inspire Medical, Inc.
Katrin Hasselbacher, Maria V. Suurna: Reisekostenerstattung durch Inspire Medical, Inc.
Publication History
Publication Date:
23 April 2019 (online)
© 2019. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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