# Predicting the Need for Surgery in Pediatric Subglottic Stenosis using Airway Elastography Derived from Endoscopic OCT and Intraluminal Pressure Measurement

> **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $797,092

## Abstract

Project Abstract
 Subglottic stenosis (SGS) is one of the most common life-threatening airway disorders in infants and
children. Current treatment methods are based on airway endoscopy, which provides only qualitative
information. Surgical treatment failures for the most severe grades of SGS range toward 50%, often due to
post-operative airway collapse in new, unpredicted locations. Treatment planning could be improved if
evidence-based, quantitative, physiologic or anatomic metrics were available.
 To address this need, we propose to advance anatomic optical coherence tomography (aOCT) for high-
resolution, high-speed imaging of the airway. Endoscopic aOCT and intraluminal pressure catheters will be
used simultaneously to inform models of airway wall viscoelasticity (VE). In combination with simulated surgery
and computational fluid dynamics (CFD), this constitutes a powerful new clinical tool to predict airway collapse
and airflow resistance in children with SGS. Our ultimate goal is to develop an aOCT-informed pipeline to
model tissue VE, perform simulated surgery, predict outcomes from a variety of surgical plans and, ultimately,
reduce treatment failures. This will leverage existing infrastructure at UNC, including the Virtual Pediatric
Airways Workbench for simulated surgery, the Pediatric Airway Atlas of normal airways, and fluid-structure
interaction (FSI) modeling of the dynamic interplay between airway wall VE, airway deformation, and
intraluminal pressure to accurately model and predict airway collapse.
 Our first Aim is to verify that geometric and pressure-related metrics that correlate with whether children
receive surgery for SGS, previously established using CT, can be obtained from endoscopic aOCT, thereby
avoiding ionizing radiation exposure. Our second Aim is technical development of dynamic (4 dimensional, 4D)
aOCT imaging to quantify airway wall VE, validated against CINE CT in pigs. Our final Aim is to create 4D
models of the airway in children with SGS including VE properties using aOCT, perform simulated surgery to
predict patient-specific post-surgical outcomes, and compare these to post-surgical aOCT models created from
routine post-operative surveillance endoscopies. In addition to the development of a new tool, these
experiments will also provide new data on longitudinal changes in VE wall properties before and after surgery.
Achievement of these goals will provide improved metrics for decision-making and enable evaluation of the
dynamic airway without radiation exposure. Our long-term goals are to: 1) validate this approach clinically at
multiple institutions; 2) evaluate the ability of these methods to improve outcomes; and 3) use the tool to study
other airway diseases, such as obstructive sleep apnea (~10% of the population), in children and adults.

## Key facts

- **NIH application ID:** 10249350
- **Project number:** 5R01HL154429-02
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Amy L Josefsberg
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $797,092
- **Award type:** 5
- **Project period:** 2020-09-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10249350

## Citation

> US National Institutes of Health, RePORTER application 10249350, Predicting the Need for Surgery in Pediatric Subglottic Stenosis using Airway Elastography Derived from Endoscopic OCT and Intraluminal Pressure Measurement (5R01HL154429-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10249350. Licensed CC0.

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