Non-uniform central airways ventilation model based on vascular segmentation

G. Ibrahim, A. Rona*, S. V. Hainsworth

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Improvements in the understanding of the physiology of the central airways require an appropriate representation of the non-uniform ventilation at its terminal branches. This paper proposes a new technique for estimating the non-uniform ventilation at the terminal branches by modelling the volume change of their distal peripheral airways, based on vascular segmentation. The vascular tree is used for sectioning the dynamic CT-based 3D volume of the lung at 11 time points over the breathing cycle of a research animal. Based on the mechanical coupling between the vascular tree and the remaining lung tissues, the volume change of each individual lung segment over the breathing cycle was used to estimate the non-uniform ventilation of its associated terminal branch. The 3D lung sectioning technique was validated on an airway cast model of the same animal pruned to represent the truncated dynamic CT based airway geometry. The results showed that the 3D lung sectioning technique was able to estimate the volume of the missing peripheral airways within a tolerance of 2%. In addition, the time-varying non-uniform ventilation distribution predicted by the proposed sectioning technique was validated against CT measurements of lobar ventilation and showed good agreement. This significant modelling advance can be used to estimate subject-specific non-uniform boundary conditions to obtain subject-specific numerical models of the central airway flow.

Original languageEnglish
Pages (from-to)137-145
Number of pages9
JournalComputers in Biology and Medicine
Volume65
DOIs
Publication statusPublished - 1 Oct 2015

Bibliographical note

© 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

  • Bronchial flow modelling
  • CT image processing
  • Non-uniform ventilation
  • Physiological boundary conditions
  • Vascular segmentation

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