Stanley Yung-Chuan Liu1,2, Leh-Kiong Huon2,3,4, Men-Tzung Lo5, Yi-Chung Chang5, Robson Capasso1, Yunn-Jy Chen6, Tiffany Ting-Fang Shih7, Pa-Chun Wang3,4,8. 1. Division of Sleep Surgery, Department of Otolaryngology-Head & Neck Surgery, Stanford University Medical Center, Stanford, CA, USA. 2. School of Medicine, Stanford University, Stanford, CA, USA. 3. Department of Otolaryngology-Head &Neck Surgery, Cathay General Hospital, Taipei, Taiwan. 4. School of Medicine, Fu Jen Catholic University, Taipei, Taiwan. 5. Department of Biomedical Sciences and Engineering, National Central University, Taoyuan, Taiwan. 6. Department of Dental Medicine, National Taiwan University Hospital, Taipei, Taiwan. 7. Department of Medical Imaging, National Taiwan University, Taipei, Taiwan. 8. Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan.
Abstract
OBJECTIVES: Using sleep MRI, we aimed to identify static craniofacial measurements and dynamic upper airway collapse patterns associated with severe obstructive sleep apnoea (OSA) during natural sleep in age and BMI-matched patients. DESIGN: Nested case-control study. SETTING: Sleep MRI images (3.0 Tesla scanner) and synchronised acoustic recording were used to observe patterns of dynamic airway collapse in subjects with mild and severe OSA. Midsagittal images were also used for static craniofacial measurements. PARTICIPANTS: Fifteen male subjects with severe OSA (mean AHI 70.3 ± 23 events/h) were matched by age and BMI to 15 subjects with mild OSA (mean AHI 7.8 ± 1.4 events/h). Subjects were selected from a consecutive sleep MRI study cohort. MAIN OUTCOME MEASURES: Static craniofacial measurements selected a priori included measurements that represent maxillomandibular relationships and airway morphology. Axial, sagittal and coronal views of the airway were rated for dynamic collapse at retropalatal, retroglossal and lateral pharyngeal wall regions by blinded reviewers. Bivariate analysis was used to correlate measures associated with severity of OSA using AHI. Statistical significance was set at P < 0.01. RESULTS: Lateral pharyngeal wall collapse from dynamic sleep MRI (β = 51.8, P < 0.001) and upper airway length from static MRI images (β = 27.2, P < 0.001) positively correlated with severity of OSA. CONCLUSIONS: Lateral pharyngeal wall collapse and upper airway length are significantly associated with severe OSA based on sleep MRI. Assessment of these markers can be readily translated to routine clinical practice, and their identification may direct targeted surgical treatment.
OBJECTIVES: Using sleep MRI, we aimed to identify static craniofacial measurements and dynamic upper airway collapse patterns associated with severe obstructive sleep apnoea (OSA) during natural sleep in age and BMI-matched patients. DESIGN: Nested case-control study. SETTING: Sleep MRI images (3.0 Tesla scanner) and synchronised acoustic recording were used to observe patterns of dynamic airway collapse in subjects with mild and severe OSA. Midsagittal images were also used for static craniofacial measurements. PARTICIPANTS: Fifteen male subjects with severe OSA (mean AHI 70.3 ± 23 events/h) were matched by age and BMI to 15 subjects with mild OSA (mean AHI 7.8 ± 1.4 events/h). Subjects were selected from a consecutive sleep MRI study cohort. MAIN OUTCOME MEASURES: Static craniofacial measurements selected a priori included measurements that represent maxillomandibular relationships and airway morphology. Axial, sagittal and coronal views of the airway were rated for dynamic collapse at retropalatal, retroglossal and lateral pharyngeal wall regions by blinded reviewers. Bivariate analysis was used to correlate measures associated with severity of OSA using AHI. Statistical significance was set at P < 0.01. RESULTS: Lateral pharyngeal wall collapse from dynamic sleep MRI (β = 51.8, P < 0.001) and upper airway length from static MRI images (β = 27.2, P < 0.001) positively correlated with severity of OSA. CONCLUSIONS: Lateral pharyngeal wall collapse and upper airway length are significantly associated with severe OSA based on sleep MRI. Assessment of these markers can be readily translated to routine clinical practice, and their identification may direct targeted surgical treatment.
Authors: Viktória Molnár; András Molnár; Zoltán Lakner; Dávid László Tárnoki; Ádám Domonkos Tárnoki; Zsófia Jokkel; László Kunos; László Tamás Journal: Sleep Breath Date: 2022-03-30 Impact factor: 2.816