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Projekt Druckansicht

Identifizierung von oropharyngealen und Kraniofazialen Risikofaktoren bei obstruktiven Schlafapnoe.

Antragstellerinnen / Antragsteller Amro Daboul, Ph.D.; Professorin Dr. Tatyana Ivanovska
Fachliche Zuordnung Medizinische Physik, Biomedizinische Technik
Förderung Förderung von 2018 bis 2021
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 414051770
 
Erstellungsjahr 2023

Zusammenfassung der Projektergebnisse

The objective of this project was the development of an approach to measure and integrate the anatomical structures (Craniofacial characteristics and Oropharyngeal structures) in obstructive sleep apnea (OSA) patients with the presence and severity of the disease. The identification of the strongest risk factors of OSA in a particular population will help in understanding the etiology, and selecting the most suitable and efficient diagnostic and therapeutic approaches. We capitalized on the the availability of magnetic resonance images collected within the different cohorts of the study of health in Pomerania SHIP, the abundance of the sleep and medical examinations performed and the international research interest in the data. The project was carried out on subjects aged between 20-80 years old (n = 701) who underwent both an overnight sleep laboratory examination and a whole-body MRI scan. At first, we provided reliable and reproducible quantifications of oropharyngeal structures and anthropometric measurements of the craniofacial complex on a subsample of the main cohort, which were later used to develop and train a series of deep learning approaches (including 2D and 3D networks) for the fully automated segmentation of those structures on the main cohort. Thereafter, the most successful network architectures were applied to numerous MRI datasets to extract the structures of interest. Later, the required linear and volumetric measurements of oropharyngeal structures (including parapharyngeal fat pads) were extracted. We then utilized the generated data in combination with other datasets from SHIP to analyze possible associations with OSA presence and severity. We applied quantile regression and logistic regression analyses to asses associations between multiple oropharyngeal measurements and the severity of OSA. The most remarkable association emerged between pharyngeal length and OSA severity, and to a lesser degree the soft palate length. Moreover, we applied Procrustes-based 3D geometric morphometrics (PGM) to investigate the associations between craniofacial morphology and OSA, which showed that craniofacial morphology is associated with the severity of OSA, although the effect was moderate and influenced by age-related variation. In conclusion, through combined technical, epidemiological and medical approaches, this work presented a reliable method to extract morphological data from population-based MRI, and then standardize, validate and utilize this data to obtain epidemiological evidence on OSA risk factors.

Projektbezogene Publikationen (Auswahl)

 
 

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