Diagnosing obstructive respiratory diseases using exhaled aerosol fingerprints: A feasibility study

In this study, the feasibility of breath tests with inert tracer aerosols has been assessed to diagnose obstructive respiratory diseases. The hypothesis is that each airway structure has a signature exhaled aerosol pattern (aerosol fingerprint), which can be used to detect and localize airway structure modifications due to the diseases. The objective of this study was to evaluate the sensitivity of exhaled aerosol patterns to geometrical variations in four mouth–lung models with computational modeling. Specifically, one benign and three malign conditions were considered, which include a tracheal carina tumor, a bronchial tumor, and asthma. Aerosols ranging from 0.4 μm to 10 μm were simulated to be inhaled under normal breathing conditions and then exhaled, with exhaled distributions being recorded at the mouth of the computational model. Large eddy simulations coupled with a well-tested Lagrangian tracking model were used to simulate the respiratory airflow and aerosol dynamics. Apparent discrepancies in exhaled aerosol distributions were observed among the four models. Each structure abnormality gave a unique aerosol pattern that was clearly suggestive of the disease location and extent. For any given disease, this pattern persists for different particle sizes considered. Results of this study show that aerosol-fingerprint based breath tests are sensitive and robust enough to be a practical tool for diagnosis of specific lung diseases, and can disclose clues about the site and severity of the disease. Personalized delivery protocol can be devised that precisely targets medications at the disease site with severity-relevant dosage.