Effect of morphology on nanoparticle transport and deposition in human upper tracheobronchial airways. (June 2018)

• Record Type: Journal Article
• Authors: Shang, Yidan; Tian, Lin; Fan, Yaming; Dong, Jingliang; Inthavong, Kiao; Tu, Jiyuan
• Is Part Of: Journal of computational multiphase flows. Volume 10:Number 2(2018)
• Page Start: 83
• Page End: 96
• Publication Date: 2018-06
• Subjects: Airway morphology -- nanoparticles -- transport and deposition -- tracheobronchial tree -- computational fluid dynamics; Multiphase flow -- Data processing -- Periodicals; 620.106
• DOI: 10.1177/1757482X18756012
• Languages: English
• ISSNs: 1757-482X

Abstract

Aerosol transport and deposition in human lungs has attracted considerable attention in the past few years, as it has significant value to the study of toxicity consequence as well as therapeutic potential in occupational health and medical applications. In reproducing human tracheobronchial airways, two approaches were frequently taken: (1) anatomical realistic reconstruction through image scans (e.g. CT and MRI) or cadaver casts and (2) mathematical description using simplified models. Strengths and limitations are primarily focused on accuracy, resolution, repeatability, and computational\physical expenses. While both approaches were reported in literature, detailed comparison of aerosol transport and deposition in the two representations were scarcely performed, largely due to the challenge to acquire comprehensive data from the irregular structured airway replicas (approach 1). To fill the gap, the current study performed a numerical comparison of nanoparticle transport and deposition in human upper tracheobronchial airways by using an anatomical realistic reconstruction (through CT scans) and a mathematically simplified airway model. As the first step, the current study was focused on the variation in breathing airflow pattern and the effect towards fate of the inhaled nanoparticles in human upper tracheobronchial airways. The study provided important information to understand geometric sensitivity of nanoparticle modeling in the human tracheobronchial tree and is of significant value to predict the whole lung uptake of inhaled nanoparticles in the human respiratory system.