Improving Outcomes in Pediatric Obstructive Sleep Apnea With Computational Fluid Dynamics

Study Summary

To create a validated computational tool to predict surgical outcomes for pediatric patients with obstructive sleep apnea (OSA). The first line of treatment for children with OSA is to remove their tonsils and adenoids; however, these surgeries do not always cure the patient. Another treatment, continuous positive airway pressure (CPAP) is only tolerated by 50% of children. Therefore, many children undergo surgical interventions aimed at soft tissue structures surrounding the airway, such as tonsils, tongue, and soft palate, and/or the bony structures of the face. However, the success rates of these surgeries is surprisingly low. Therefore, there a need for a tool to improve the efficacy and predict which surgical option is going to benefit each individual patient most effectively. Computational fluid dynamics (CFD) simulations of respiratory airflow in the upper airways can provide this predictive tool, allowing the effects of various surgical options to be compared virtually and the option most likely to improve the patient's condition to be chosen. Previous CFD simulations have been unable to provide information about OSA as they were based on rigid geometries, or did not include neuromuscular motion, a key component in OSA. This project uses real-time magnetic resonance imaging (MRI) to provide the anatomy and motion of the airway to the CFD simulation, meaning that the exact in vivo motion is modeled for the first time. Furthermore, since the modeling is based on MRI, a modality which does not use ionizing radiation, it is suitable for longitudinal assessment of patients before and after surgical procedures. In vivo validation of these models will be achieved for the first time through comparison of CFD-based airflow velocity fields with those generated by phase-contrast MRI of inhaled hyperpolarized 129Xe gas. This research is based on data obtained from sleep MRIs achieved with the subject under sedation. While sedating the patient post-operatively is slightl

Primary Outcome

To solve the equations governing flow (the Navier-Stokes Equations), the airway model will be divided into 3-5 million cells using Star-CCM+ (Siemens PLM Software, Plano, TX). The inlet flow boundary condition for CFD simulations will be the respiratory flow rate as measured by an MRI-compatible pneumotach,83 which records flow rates synchronously with MRI. The flow solver (also Star-CCM+) will compute the pressure and velocity fields down to the resolution of the cells. The influence of flow fe

Conditions Studied

Interventions

• DRUG 129-Xe

Study Locations (1)