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

Area of Science:

• Respiratory physiology
• Computational modeling
• Aerosol science

Background:

• Aerosol deposition impacts drug delivery, pollutant exposure, and radiological protection.
• Existing models (MPPD, ICRP HRTM) use simplified geometries, limiting accuracy in realistic human respiratory tracts.

Purpose of the Study:

• To integrate Mesh-type Reference Computational Phantoms (MRCPs) with computational fluid-particle dynamics (CFPD) for precise aerosol deposition prediction.
• To investigate the influence of complex airway anatomy on aerosol deposition patterns.

Main Methods:

• Utilized Mesh-type Reference Computational Phantoms (MRCPs).
• Employed computational fluid-particle dynamics (CFPD) simulations.
• Compared CFPD results with International Commission on Radiological Protection (ICRP) predictions.

Main Results:

• CFPD revealed enhanced nasal deposition for sub-0.5 μm particles compared to ICRP.
• ICRP models overestimated deposition for particles >0.5 μm.
• Significant deposition variations observed in extrathoracic (ET) airways (ET2: 65-75%) and bronchial bifurcations (BB1) based on flow dynamics and particle properties.

Conclusions:

• CFPD with MRCPs offers superior accuracy for aerosol deposition modeling in complex respiratory anatomies.
• Findings improve understanding of aerosol behavior for targeted drug delivery and enhanced radiological protection strategies.