Visualization of local deposition of nebulized aerosols in a human upper respiratory tract model

Knowing aerosol deposition distribution (ADD) in the respiratory tract is crucial in assessing dose–response relationship and optimizing inhalation therapy. However, characterization of ADD inside the airway is challenging, due to its inaccessibility to standard measurement instruments. Radioactive imaging techniques such as gamma scintigraphy, SPECT, and PET are capable of characterizing ADD and have proven valuable in drug-device designs, but these techniques are costly, complex-to-use, and pose radiation risks to patients. The objective of this study is to develop and validate a simple and practical technique to visualize nebulized aerosol deposition in a human airway model. An anatomically accurate mouth–lung airway model was used in both experiments and numerical simulations for validation purpose. A sectional hollow cast replica was developed and fabricated using 3D printing. Sar-Gel was utilized to visualize the aerosol deposition distribution on the inner walls of the upper respiratory airway. Computational simulations were conducted to understand the underlying mechanisms of particle transport and deposition. The deposition distribution obtained from the Sar-Gel experiments and numerical simulations resembled each other to a high degree. Specifically, the deposition hot spots in the upper trachea were nearly identical between experiment and simulation, suggesting that the computational model is adequate in capturing the mechanisms of particle transport and deposition. Considering the inhalation effect, more drug particles were delivered to the lungs at 10 L/min than at 30 L/min. The Sar-Gel based method in combination with sectional upper airway casts appears to be a practical approach to visualize regional depositions with nebulizers. Computational modeling and Sar-Gel tests can be used as complementary in optimizing inhalation therapies.