Evidence map›Paper›PMID 30480204›Full record

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Image-Based 3-Dimensional Characterization of Laryngotracheal Stenosis in Children.

Lee S McDaniel, William J Poynot, Keith A Gonthier, Michael E Dunham, And Tyler W Crosby

Abstract read
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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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lee S McDanielSchool of Public Health, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA.
William J PoynotDepartment of Mechanical & Industrial Engineering, Louisiana State University, Baton Rouge, Louisiana, USA.
Keith A GonthierDepartment of Mechanical & Industrial Engineering, Louisiana State University, Baton Rouge, Louisiana, USA.
Michael E DunhamDepartment of Otolaryngology-Head and Neck Surgery, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA.
And Tyler W CrosbyDepartment of Otolaryngology-Head and Neck Surgery, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

3-dimensional modelinglaryngotracheal stenosismedical image processingpediatric airway

Identifiers

PMID30480204
PMCPMC6239028

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.