Upper Airway Volume Predicts Brain Structure and Cognition in Adolescents.
Authors
Affiliations (8)
Affiliations (8)
- University of Maryland Baltimore, Otorhinolaryngology, Baltimore, Maryland, United States.
- University of Maryland Institute for Health Computing , Bethesda, Maryland, United States.
- St Jude Children's Research Hospital, Memphis, Tennessee, United States.
- University of Maryland Baltimore, Diagnostic Radiology and Nuclear Medicine, Baltimore, Maryland, United States.
- Harvard Pilgrim Health Care Institute and Harvard Medical School, Department of Population Medicine, Boston, Massachusetts, United States.
- Brigham and Women's Hospital, Division of Sleep and Circadian Disorders, Boston, Massachusetts, United States.
- Harvard Medical School, Division of Sleep Medicine, Boston, Massachusetts, United States.
- University of Maryland Institute for Health Computing , Bethesda, Maryland, United States; [email protected].
Abstract
One in ten children experiences sleep-disordered breathing (SDB). Untreated SDB is associated with poor cognition, but the underlying mechanisms are less understood. We assessed the relationship between magnetic resonance imaging (MRI)-derived upper airway volume and children's cognition and regional cortical gray matter volumes. We used five-year data from the Adolescent Brain Cognitive Development study (n=11,875 children, 9-10 years at baseline). Upper airway volumes were derived using a deep learning model applied to 5,552,640 brain MRI slices. The primary outcome was the Total Cognition Composite score from the National Institutes of Health Toolbox (NIH-TB). Secondary outcomes included other NIH-TB measures and cortical gray matter volumes. The habitual snoring group had significantly smaller airway volumes than non-snorers (mean difference=1.2 cm<sup>3</sup>; 95% CI, 1.0-1.4 cm<sup>3</sup>; P<0.001). Deep learning-derived airway volume predicted the Total Cognition Composite score (estimated mean difference=3.68 points; 95% CI, 2.41-4.96; P<0.001) per one-unit increase in the natural log of airway volume (~2.7-fold raw volume increase). This airway volume increase was also associated with an average 0.02 cm<sup>3</sup> increase in right temporal pole volume (95% CI, 0.01-0.02 cm<sup>3</sup>; P<0.001). Similar airway volume predicted most NIH-TB domain scores and multiple frontal and temporal gray matter volumes. These brain volumes mediated the relationship between airway volume and cognition. We demonstrate a novel application of deep learning-based airway segmentation in a large pediatric cohort. Upper airway volume is a potential biomarker for cognitive outcomes in pediatric SDB, offers insights into neurobiological mechanisms, and informs future studies on risk stratification. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).