Patient-specific time-resolved mapping of airway flow and aerosol deposition using CT-derived geometries

Accurate prediction of aerosol transport and deposition in human airways is crucial for both inhalation exposure assessment and targeted aerosol drug delivery. Conventional computational studies often rely on idealized sinusoidal or quasi-steady breathing profiles, which fail to capture the transient dynamics of real respiratory cycles and can alter deposition estimates. Here, we compare time-dependent airflow and aerosol deposition under spirometry-derived and idealized sinusoidal breathing waveforms in a subject-specific CT-derived airway geometry. Unsteady airflow and Lagrangian particle transport were simulated across multiple tracheo-bronchial generations for particle sizes of 1, 5, and 10 μm, with continuous tracking over one complete inspiratory-expiratory cycle. Under the prescribed conditions, the spirometry-derived waveform yielded lower one-cycle deposition fractions and different peak deposition times than the sinusoidal waveform, while 7–9% of injected particles deposited during exhalation. Deposition patterns were strongly particle-size dependent, with larger particles favoring extra-thoracic regions, intermediate sizes depositing in central airways, and smaller particles reaching distal bronchi. Comparisons with MPPD predictions revealed size-dependent differences in regional deposition fractions, reflecting differences in anatomical representation, domain coverage, and modeling assumptions. For the CT-reconstructed airway geometry examined here, the results demonstrate differences in one-cycle aerosol deposition between spirometry-derived and sinusoidal breathing conditions, highlighting the importance of considering the prescribed breathing profile and inspired volume when interpreting deposition predictions.