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Updated: May 8, 2026

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
Published on: November 11, 2020
Gravity-driven ventilation heterogeneity shapes aerosol deposition: a full-scale digital lung modeling study
Jiahuan Meng1, Chen Ma1, Zhong Ni1
1Department of Respiratory and Critical Care Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Sichuan University, No. 2222 Xin Chuan Road, Chengdu 610200, China.
Abstract:
Exposure to hazardous aerosol represent critical driver of chronic and acute pulmonary diseases. Conventional inhalation risk assessments frequently rely on mean deposition indices and simplified mechanical models, failing to reproduce ventilatory heterogeneity, thereby masking regional difference in aerosol deposition. To elucidate the correlation between regional airflow dynamics and tissue vulnerability, we developed an anatomically full-scale digital lung model that incorporates nonlinear compliance and gravity-driven pleural pressure gradients to simulate particle deposition during quiet, up-right breathing in healthy adults. Numerical simulations of aerosol particles (0.1-10 µm) over a complete respiratory cycle revealed a distinct gravity-dependent heterogenous deposition pattern: The highest deposition intensity was observed in the right lower lobe and left lower lobe, while the lowest occurred in the right upper lobe. Three deposition hotspots were identified: two in the right lower lobe (0.53 %/m2) and left lower lobe (0.51 %/m2), spanning generations G21-G23 and enriched with particles of 3 µm in diameter, and one in the right lower lobe (0.48 %/m2), spanning generations G7-G10 and enriched with particles of 10 µm in diameter. Additionally, we use wielding fume as an example to demonstrate how to quantitatively calculate the regional surface deposition density and exposure time required to reach cytotoxicity thresholds, highlighting the model's ability to translate regional deposition patterns into biologically meaningful risk metrics. In conclusion, our full-scale digital lung model replicates human-specific airway branching and ventilation dynamics, offering a non-invasive digital platform for temporospatial evaluation of inhalation risks from hazardous aerosol.
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