{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T02:51:54Z","timestamp":1785552714369,"version":"3.56.0"},"reference-count":54,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T00:00:00Z","timestamp":1769817600000},"content-version":"vor","delay-in-days":91,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["R01HL167012"],"award-info":[{"award-number":["R01HL167012"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000026","name":"National Institute on Drug Abuse","doi-asserted-by":"publisher","award":["U01DA041117"],"award-info":[{"award-number":["U01DA041117"]}],"id":[{"id":"10.13039\/100000026","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["R01HL167012"],"award-info":[{"award-number":["R01HL167012"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Institute on Drug Abuse","doi-asserted-by":"publisher","award":["U01DA041117"],"award-info":[{"award-number":["U01DA041117"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.atsjournals.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Rationale<\/jats:title>\n                    <jats:p>One in 10 children experiences sleep-disordered breathing (SDB). Untreated SDB is associated with poor cognition, but the underlying mechanisms are less understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>We assessed the relationship between magnetic resonance imaging\u2013derived upper airway volume and children\u2019s cognition and regional cortical gray matter volumes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used 5-year data from the Adolescent Brain Cognitive Development study (N\u2009=\u200911,875 children; 9\u201310 yr old at baseline). Upper airway volumes were derived using a deep learning model applied to 5,552,640 brain magnetic resonance imaging slices. The primary outcome was the Total Cognition Composite score from the NIH Toolbox (NIH-TB). Secondary outcomes included other NIH-TB measures and cortical gray matter volumes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Measurements and Main Results<\/jats:title>\n                    <jats:p>The habitual snoring group had significantly smaller airway volumes than nonsnorers (mean difference, 1.2 cm\u00b3; 95% confidence interval [CI], 1.0\u20131.4 cm\u00b3; P\u2009&amp;lt;\u20090.001). Deep learning\u2013derived airway volume predicted the Total Cognition Composite score (estimated mean difference, 3.68 points; 95% CI, 2.41\u20134.96 points; P\u2009&amp;lt;\u20090.001) per one-unit increase in the natural log of airway volume (\u223c2.7-fold raw volume increase). This airway volume increase was also associated with an average 0.02-cm\u00b3 increase in right temporal pole volume (95% CI, 0.01\u20130.02 cm\u00b3; P\u2009&amp;lt;\u20090.001). 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We demonstrate a novel application of deep learning\u2013based 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1164\/rccm.202409-1748oc","type":"journal-article","created":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T16:48:25Z","timestamp":1749833305000},"page":"2105-2116","update-policy":"https:\/\/doi.org\/10.1164\/crossmarkpolicies","source":"Crossref","is-referenced-by-count":8,"title":["Upper Airway Volume Predicts Brain Structure and Cognition in Adolescents"],"prefix":"10.1093","volume":"211","author":[{"given":"Adway","family":"Kanhere","sequence":"first","affiliation":[{"name":"Department of Otorhinolaryngology\u2014Head and Neck Surgery"},{"name":"University of Maryland Institute for Health Computing, Bethesda, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nithya","family":"Navarathna","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology\u2014Head and Neck Surgery"},{"name":"University of Maryland Institute for Health Computing, Bethesda, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul H.","family":"Yi","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Imaging, St. Jude Children\u2019s Research Hospital, Memphis, Tennessee"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vishwa S.","family":"Parekh","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology and Nuclear Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jerrah","family":"Pickle","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology\u2014Head and Neck Surgery"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christine C.","family":"Cloak","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology and Nuclear Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Ernst","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology and Nuclear Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linda","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology and Nuclear Medicine"},{"name":"Department of Neurology, and"},{"name":"Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongdong","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts"},{"name":"Department of Biostatistics, Harvard T. 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