Predicting sleep apnea from three-dimensional face photography

Abstract

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.

RAS ID

31833

Document Type

Journal Article

Date of Publication

1-1-2020

School

School of Science

Grant Number

NHMRC Number : 1021859

Copyright

subscription content

Publisher

American Academy of Sleep Medicine

Comments

Eastwood, P., Gilani, S. Z., McArdle, N., Hillman, D., Walsh, J., Maddison, K., ... & Mian, A. (2020). Predicting sleep apnea from three-dimensional face photography. Journal of Clinical Sleep Medicine, 16(4), 493-502. https://doi.org/10.5664/jcsm.8246

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Link to publisher version (DOI)

10.5664/jcsm.8246