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Image-Based 3-Dimensional Characterization of Laryngotracheal Stenosis in Children.
Article in OTO open. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Application of numerical simulation of upper airway flow field in pediatric obstructive sleep apnea with adenoid hypertrophy.Quantitative imaging in medicine and surgery · 2026Article
- 1.5-T MR imaging of organic laryngotracheal stenosis in a pediatric cohort predominantly younger than 7 years: protocol optimization and diagnostic performance.European radiology · 2026Article
- Endoscopic Preoperative Assessment, Classification of Stenosis, Decision-Making.Frontiers in pediatrics · 2019Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesDescribe a technique for the description and classification of laryngotracheal stenosis in children using 3-dimensional reconstructions of the airway from computed tomography (CT) scans. STUDY
designCross-sectional.
settingAcademic tertiary care children's hospital. SUBJECTS AND
methodsThree-dimensional models of the subglottic airway lumen were created using CT scans from 54 children undergoing imaging for indications other than airway disease. The base lumen models were deformed in software to simulate subglottic airway segments with 0%, 25%, 50%, and 75% stenoses for each subject. Statistical analysis of the airway geometry was performed using metrics extracted from the lumen centerlines. The centerline analysis was used to develop a system for subglottic stenosis assessment and classification from patient-specific airway imaging.
resultsThe scaled hydraulic diameter gradient metric derived from intersectional changes in the lumen can be used to accurately classify and quantitate subglottic stenosis in the airway based on CT scan imaging. Classification is most accurate in the clinically relevant 25% to 75% range of stenosis.
conclusionsLaryngotracheal stenosis is a complex diagnosis requiring an understanding of the airway lumen configuration, anatomical distortions of the airway framework, and alterations of respiratory aerodynamics. Using image-based airway models, we have developed a metric that accurately captures subglottis patency. While not intended to replace endoscopic evaluation and existing staging systems for laryngotracheal stenosis, further development of these techniques will facilitate future studies of upper airway computational fluid dynamics and the clinical evaluation of airway disease.
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