In Silico Modeling of Resistances and Dosimetry in Sarcoidosis Patients with Airway Disease

Abstract

Background: Sarcoidosis is a multisystem granulomatous disease that often impacts the lungs with mucosal inflammation, cobblestoning of the central airways, obstruction, and small airway disease. Airway involvement is often under-reported and not well understood, despite likely having implications for the work of breathing and particle dosimetry. Methods: To shed light on sarcoidosis disease with airway involvement, we performed patient-specific computational fluid dynamics and particle transport simulations in three subjects, for a few generations of the large conducting airways, with various presentations of airway disease. While Patient A had peripheral obstruction as identified from pulmonary function tests (PFTs), airway models created from computed tomography (CT) scans highlighted lower left lobe central airway abnormalities. Patient B presented with airway obstruction and diffusive stenosis throughout all five lobes while Patient C had normal PFTs and CT scans. Results: Localized central airway remodeling in Patient A resulted in localized elevation in dosimetry but no changes in total dosimetry or airway resistances, as also seen in Patient C. The subject with diffusive remodeling had abnormally high airway resistances and central airway deposition within the 3D-modeled airways. Conclusions: Results from this pilot study suggest that patients with diffuse remodeling may have enhanced susceptibility to environmental pollutants due to increased aerosol dosimetry. For aerosol medication treatment, the subject with diffusive airway remodeling may not receive adequate therapeutic dose if the goal is to deliver medication to the lung periphery. This study provides the first glimpse of airflow, resistances, and particle dosimetry in sarcoidosis subjects. Future studies should focus on phenotyping airway abnormalities in a larger sarcoidosis cohort and performing whole lung dosimetry modeling.

Keywords: aerosol deposition; airways; computational fluid dynamics; computed tomography; lung disease; patient-specific simulations.