Topological analysis of particle transport in lung airways: Predicting particle source and destination

Ali Farghadan, Filippo Coletti, Amirhossein Arzani

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Particle transport in lung airways can induce respiratory disease and play a vital role in aerosol drug delivery. Herein, we present dynamical systems features that influence airflow and particle transport in the tracheobronchial trees. Computational fluid dynamics (CFD) was used to solve for unsteady airflow in a patient-specific model. Particle tracking simulations were performed for micron-size particles. The destination map that connects the particle final location to the initial location and injection time was constructed. Finite-time Lyapunov exponent (FTLE) fields were calculated to identify inertial Lagrangian coherent structures (ILCS), topological features that act as separatrices. Our results demonstrated that these topological features control the destination map at the trachea. The temporal evolution of ILCS influenced the sensitivity of particle transport fate to injection time, whereas the emergence of new ILCS with an increased integration time controlled transport to different generations of airways. Additionally, particles starting at the ILCS were shown to mostly deposit at the airway walls. Finally, an innovative source inversion strategy was introduced to integrate the Maxey–Riley equation backward in time and identify the origin of dispersed particles. Our study explores novel dynamical systems tools that improve our understanding of particle transport and deposition in the airways and could be used to guide future targeted drug delivery studies.

Original languageEnglish (US)
Article number103497
JournalComputers in Biology and Medicine
StatePublished - Dec 2019
Externally publishedYes


  • Aerosol
  • Airflow
  • Computational fluid dynamics
  • FTLE
  • Lagrangian coherent structures
  • Particle tracking
  • Source inversion

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications


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