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

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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.