Dynamic programming and automated segmentation of optical coherence tomography images of the neonatal subglottis: enabling efficient diagnostics to manage subglottic stenosis.

Konrad M Kozlowski,Joseph C Jing,Giriraj K Sharma,Kathryn Osann,Gurpreet S Ahuja,Phil-Sang Chung,Li Qi,Andrew E Heidari,Brian J.-F Wong,Jason J Chen,Zhongping Chen,Sehwan Kim

doi:10.1117/1.jbo.24.9.096001

Abstract

.Subglottic stenosis (SGS) is a challenging disease to diagnose in neonates. Long-range optical coherence tomography (OCT) is an optical imaging modality that has been described to image the subglottis in intubated neonates. A major challenge associated with OCT imaging is the lack of an automated method for image analysis and micrometry of large volumes of data that are acquired with each airway scan (1 to 2 Gb). We developed a tissue segmentation algorithm that identifies, measures, and conducts image analysis on tissue layers within the mucosa and submucosa and compared these automated tissue measurements with manual tracings. We noted small but statistically significant differences in thickness measurements of the mucosa and submucosa layers in the larynx (), subglottis (), and trachea (). The automated algorithm was also shown to be over 8 times faster than the manual approach. Moderate Pearson correlations were found between different tissue texture parameters and the patient’s gestational age at birth, age in days, duration of intubation, and differences with age (mean age 17 days). Automated OCT data analysis is necessary in the diagnosis and monitoring of SGS, as it can provide vital information about the airway in real time and aid clinicians in making management decisions for intubated neonates.

Highlights

Subglottic stenosis (SGS) in the neonatal population poses a significant diagnostic and management challenge
Analysis was conducted on data acquired from a previous study of intubated neonates, which examined the use of optical coherence tomography (OCT) on the neonatal laryngotracheal airway.[19]
Each neonate was imaged in the neonatal intensive care unit (NICU) at either the University of California Irvine (UCI) or Children’s Hospital of Orange County (CHOC)

Summary

Introduction

Subglottic stenosis (SGS) in the neonatal population poses a significant diagnostic and management challenge. Injury to the delicate subglottic epithelium in neonates can result from a myriad of causative factors, including cyclical micromotion of the ventilation circuit, bacterial infection, biofilm formation, and direct interfacing of the endotracheal tube (ETT) with the subglottic mucosa.[1] Following acute mucosal inflammation, edema and fibrosis can lead to SGS, which in some cases can be progressive and life threatening. SGS has a contemporary incidence between 0% and 2% per year in these patients, with the mean total charge in discharges from hospitalization being upward of $110,000.2–4 While direct laryngoscopy and bronchoscopy remain the diagnostic gold standard for SGS, this procedure requires general anesthesia and poses considerable risk of airway compromise.[5] there exists a critical need for a less invasive and practical means for neonatologists.

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Conclusion