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Predicting sleep apnea from three-dimensional face photography
Journal article

Predicting sleep apnea from three-dimensional face photography

Peter Eastwood, Syed Zulqarnain Gilani, Nigel McArdle, David Hillman, Jennifer Walsh, Kathleen Maddison, Mithran Goonewardene and Ajmal Mian
Journal of clinical sleep medicine, Vol.16(4), pp.493-502
2020
PMID: 32003736
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Published (Version of Record)

Abstract

3dMD craniofacial anatomy linear discriminant analysis obstructive sleep apnea polysomnography Raine Study three-dimensional photography
STUDY OBJECTIVES: Craniofacial anatomy is recognized as an important predisposing factor in the pathogenesis of obstructive sleep apnea (OSA). This study used three-dimensional (3D) facial surface analysis of linear and geodesic (shortest line between points over a curved surface) distances to determine the combination of measurements that best predicts presence and severity of OSA. METHODS: 3D face photographs were obtained in 100 adults without OSA (apnea-hypopnea index [AHI] < 5 events/h), 100 with mild OSA (AHI 5 to < 15 events/h), 100 with moderate OSA (AHI 15 to < 30 events/h), and 100 with severe OSA (AHI ≥ 30 events/h). Measurements of linear distances and angles, and geodesic distances were obtained between 24 anatomical landmarks from the 3D photographs. The accuracy with which different combinations of measurements could classify an individual as having OSA or not was assessed using linear discriminant analyses and receiver operating characteristic analyses. These analyses were repeated using different AHI thresholds to define presence of OSA. RESULTS: Relative to linear measurements, geodesic measurements of craniofacial anatomy improved the ability to identify individuals with and without OSA (classification accuracy 86% and 89% respectively, P < .01). A maximum classification accuracy of 91% was achieved when linear and geodesic measurements were combined into a single predictive algorithm. Accuracy decreased when using AHI thresholds ≥ 10 events/h and ≥ 15 events/h to define OSA although greatest accuracy was always achieved using a combination of linear and geodesic distances. CONCLUSIONS: This study suggests that 3D photographs of the face have predictive value for OSA and that geodesic measurements enhance this capacity.

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Collaboration types
Domestic collaboration
Citation topics
1 Clinical & Life Sciences
1.137 Sleep Science & Circadian Systems
1.137.382 Obstructive Sleep Apnea
Web Of Science research areas
Clinical Neurology
ESI research areas
Neuroscience & Behavior
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