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Updated: Apr 13, 2026
Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
Published on: November 11, 2020
Validating CFD Predictions of Pharmaceutical Aerosol Deposition with In Vivo Data
Geng Tian1, Michael Hindle2, Sau Lee3
1Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, 401 West Main Street, P.O. Box 843015, Richmond, Virginia, 23284-3015, USA.
Purpose:
CFD provides a powerful approach to evaluate the deposition of pharmaceutical aerosols; however, previous studies have not compared CFD results of deposition throughout the lungs with in vivo data.
Methods:
The in vivo datasets selected for comparison with CFD predictions included fast and slow clearance of monodisperse aerosols as well as 2D gamma scintigraphy measurements for a dry powder inhaler (DPI) and softmist inhaler (SMI). The CFD model included the inhaler, a characteristic model of the mouth-throat (MT) and upper tracheobronchial (TB) airways, stochastic individual pathways (SIPs) representing the remaining TB region, and recent CFD-based correlations to predict pharmaceutical aerosol deposition in the alveolar airways.
Results:
For the monodisperse aerosol, CFD predictions of total lung deposition agreed with in vivo data providing a percent relative error of 6% averaged across aerosol sizes of 1-7 μm. With the DPI and SMI, deposition was evaluated in the MT, central airways (bifurcations B1-B7), and intermediate plus peripheral airways (B8 through alveoli). Across these regions, CFD predictions produced an average relative error <10% for each inhaler.
Conclusions:
CFD simulations with the SIP modeling approach were shown to accurately predict regional deposition throughout the lungs for multiple aerosol types and different in vivo assessment methods.
