Predictive Modeling for Treatment of Upper Airway Obstruction in Young Children

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DESCRIPTION (provided by applicant): Infants and children with abnormalities of the upper airway are at risk for hypoxia, respiratory insufficiency and long term morbidity. Multiple levels of airway obstruction encountered in these disorders lead to life threatening difficulties in air exchange, problems with coordination of swallowing, growth, and speech development. In these airway disorders, therapy is typically directed by the clinician's experience and preference, rather than on normalized physiologic or anatomic metrics. Quantitative methods of evaluating and determining optimal management of these upper airway anomalies would be of tremendous benefit for improved clinical care and outcomes. New research tools can now measure computational fluid dynamics. These fluid-structure interaction models allow for the merger of dynamic anatomy with physiologic measures by creating a virtual model of the airway with computed measures of airflow, wall shear stress, pressure distribution, and airway wall shape change. This computational model can be virtually modified to reflect medical intervention, surgical techniques, and normal growth, which can predict changes in airway wall compliance, new airflow patterns, pressure distribution, and other physiologic variables to yield expected clinical results prior to intervention. Improvements in outcomes when computational modeling tools are used in pediatric upper airway intervention planning is enormous, particularly in complicated clinical scenarios. For purposes of model development, we focus on two very specific, commonly encountered, high risk anomalies encountered at our center, Pierre Robin sequence and subglottic stenosis. Normative data regarding growth and development of the upper airway will be studied. We hypothesize that a functional computational model that simulates the mechanical and aerodynamic behavior of the upper airway in children with Pierre Robin sequence and laryngeal lesions (e.g. subglottic stenosis) can be used as an effective diagnostic and treatment planning tool, reducing failures of initial treatment and avoiding potentially unnecessary future complications and interventions. Specific aims for this proposal are to: (1a) develop a functional computational model of the pediatric upper airway which can be used for diagnosis and to predict treatment outcomes in children < 10 years of age with Pierre Robin sequence and subglottic stenosis; data and modeling of normal airways will be obtained to help develop a Pediatric Airway Anatomical Atlas describing the aging airway; an integrated Virtual Pediatric Airway Workbench will also be developed (1b) validate the functional computational model using anatomic and physiologic measures that assess airway patency and airflow limitation in the upper airway in children < 10 years of age with Pierre Robin Sequence and subglottic stenosis and (2) apply the computational model to children being evaluated for Pierre Robin Sequence and subglottic stenosis, and determine the ability of the model to accurately predict results of various potential interventions on anatomic and physiologic metrics.