Image-based modelling of inhaler deposition during respiratory exacerbation

Abstract

For many of the one billion sufferers of respiratory diseases worldwide, managing their disease with inhalers improves their ability to breathe. Poor disease management and rising pollution can trigger exacerbations which require urgent relief. Higher drug deposition in the throat instead of the lungs limits the impact on patient symptoms. To optimise delivery to the lung, patient-specific computational studies of aerosol inhalation can be used. However in many studies, inhalation modelling does not represent an exacerbation, where the patient's breath is much faster and shorter. Here we compare differences in deposition of inhaler particles in the airways of a healthy male, female lung cancer and child cystic fibrosis patient. We aimed to evaluate deposition differences during an exacerbation with image-based healthy and diseased patient models. We found that during an exacerbation, particles progressing to the lower airways were distributed similarly to those inhaled during healthy breathing, but fewer in quantity. Throat deposits were halved in the healthy patient compared to the diseased patients under extreme inhalation, due to changes in the detailed shape of the throat. Our results identify that the modelled upper airway must be patient-specific, and an exacerbating profile tested for optimal measurement of reliever inhaler deposition.

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks

“…The deposition simulations in this study were performed using OpenFOAM v6 [94] using our custom solver deepLungMPPICFoam [95]. Briefly summarised, we solved mass and momentum conservation equations for transport of an incompressible fluid (air).…”