Improved aerosol deposition predictions in human upper respiratory tract using coupled mesh phantom-based computational model.

Abstract

Aerosol deposition in the human respiratory tract significantly impacts drug delivery, pollutant exposure, and radiological protection. While existing models, such as the Multiple-Path Particle Dosimetry (MPPD) and the Human Respiratory Tract Model (HRTM) from International Commission on Radiological Protection (ICRP) provide valuable insights, their reliance on simplified geometries and flow dynamics, limits their ability to accurately predict particle deposition within realistic anatomies. This study integrates Mesh-type Reference Computational Phantoms (MRCPs) with computational fluid-particle dynamics (CFPD) to address these limitations. Our simulations reveal the influence of complex anatomical features, including nasal cavity, trachea, and bronchial regions, on aerosol deposition patterns. For ambient aerosol particles in the diffusion-dominated regime (< 0.5 μm), CFPD results reveal enhanced nasal deposition fractions than ICRP predictions, while, above this size, the ICRP semi-empirical model shows overestimations. In the extrathoracic (ET) airways, deposition distribution varied significantly between ET₁ and ET₂, with ET₂ receiving 65-75% of deposits (near the junction of ET₁ and ET₂) under certain flow conditions. In the bronchial bifurcation (BB₁), deposition efficiency varies with Stokes number and Reynolds number, revealing localized preferential deposition. These findings enhance our understanding of aerosol behaviour and paves the way for more accurate therapeutic and safety models in radiological protection.