The Effectiveness of An Averaged Airway Model in Predicting the Airflow and Particle Transport Through the Airway

Toshihiro Sera, Hiroaki Kuninaga, Kazuaki Fukasaku, Hideo Yokota, Masao Tanaka

Research output: Contribution to journalArticle

Abstract

Background: In this study, we proposed an averaged airway model design based on four healthy subjects and numerically evaluated its effectiveness for predicting the airflow and particle transport through an airway. Methods: Direct-Averaged models of the conducting airways of four subjects were restored by averaging the three-dimensional (3D) skeletons of four healthy airways, which were calculated using an inverse 3D thinning algorithm. We simulated the airflow and particle transport in the individual and the averaged airway models using computational fluid dynamics. Results: The bifurcation geometry differs even among healthy subjects, but the averaged model retains the typical geometrical characteristics of the airways. The Reynolds number of the averaged model varied within the range found in the individual subject models, and the averaged model had similar inspiratory flow characteristics as the individual subject models. The deposition fractions at almost all individual lobes ranged within the variation observed in the subjects, however, the deposition fraction was higher in only one lobe. The deposition distribution at the main bifurcation point differed among the healthy subjects, but the characteristics of the averaged model fell within the variation observed in the individual subject models. On the contrary, the deposition fraction of the averaged model was higher than that of the average of the individual subject models and deviated from the range observed in the subject models. Conclusion: These results indicate that the direct-Averaged model may be useful for predicting the individual airflow and particle transport on a macroscopic scale.

Original languageEnglish
Pages (from-to)278-292
Number of pages15
JournalJournal of Aerosol Medicine and Pulmonary Drug Delivery
Volume32
Issue number5
DOIs
Publication statusPublished - Oct 2019

All Science Journal Classification (ASJC) codes

  • Pulmonary and Respiratory Medicine
  • Pharmaceutical Science
  • Pharmacology (medical)

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