Abstract
Obstructive sleep apnea (OSA) is a chronic breathing disorder that most of the time people are oblivious of the symptoms which may delay the diagnosis and may lead to long-term health consequences such as cardiovascular and cerebrovascular diseases. Ultrasonography is currently used to discern the real behavior of the upper airway (UA) in patients with OSA. However, previous methods were not enough to reveal the possible pathophysiology and biomechanics of the human UA. The aim of this study is to use the modified optical flow (OF)-based method in tracking the dynamic tongue base motion, utilizing nine tracking points, to effectively classify which group each subject belongs to. The classification groups are normal, mild, moderate, and severe OSA. A total of 82 participants were enrolled in this study. All of them had their B-mode ultrasound image sequences obtained for 10 s. The first 5 s was recorded during eupneic breathing, and the latter part was during the performance of the Müller Maneuver (MM), a simulation of the collapse of the UA while inducing negative pressure. The results demonstrate that the four classifications are significantly different (p < 0.05). The normal group has the largest displacement, while the severe OSA group has the smallest. The normal group has the smallest tongue base area (TBA), while the severe OSA group has the largest. Both instances were also observed during the MM. Tongue area measurement during the eupneic breathing for the four groups are 18.63 ± 2.595, 20.25 ± 2.366, 20.34 ± 3.207, and 21.75 ± 2.764, respectively. During the MM, the measurements were 18.54 ± 2.701, 20.16 ± 2.428, 20.32 ± 3.190, and 21.78 ± 2.820, respectively. Noninvasive sonographic evaluation using dynamic tongue motion tracking and tongue area measurements provides quantitative assessments that can be used by the clinician to indicate individualized treatment plan for each OSA patients.
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Acknowledgment
This study was supported by the Ministry of Science and Technology of the Republic of China (Taiwan) under grant MOST 106-2314-B-567-001 and, in part, funded by Cardinal Tien Hospital under grant CTH-107B-2A28 and CTH108B-2A33. No additional external funding was received for this study. The authors are grateful for administrative assistance on this project provided by Chiu-Ping Wang, Shu-Hwei Fan and Po-Cheng Yang. The authors also thank the staff of the Center for Sleep Disorders, Division of Pulmonary Medicine and Department of Medical Imaging of Catholic Cardinal Tien Hospital, for their technical support. They received no additional compensation for their contributions.
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Manlises, C.O., Chen, JW., Huang, CC. (2020). Ultrasonography Classification of Obstructive Sleep Apnea (OSA) Through Dynamic Tongue Base Motion Tracking and Tongue Area Measurements. In: Lin, KP., Magjarevic, R., de Carvalho, P. (eds) Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices. ICBHI 2019. IFMBE Proceedings, vol 74. Springer, Cham. https://doi.org/10.1007/978-3-030-30636-6_14
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DOI: https://doi.org/10.1007/978-3-030-30636-6_14
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