Whitfield, C.A., Latimer, P., Horsley, A. et al. (3 more authors) (2020) Spectral graph theory efficiently characterizes ventilation heterogeneity in lung airway networks. Journal of the Royal Society Interface, 17 (168). 20200253. ISSN 1742-5689
Abstract
This paper introduces a linear operator for the purposes of quantifying the spectral properties of transport within resistive trees, such as airflow in lung airway networks. The operator, which we call the Maury matrix, acts only on the terminal nodes of the tree and is equivalent to the adjacency matrix of a complete graph summarizing the relationships between all pairs of terminal nodes. We show that the eigenmodes of the Maury operator have a direct physical interpretation as the relaxation, or resistive, modes of the network. We apply these findings to both idealized and image-based models of ventilation in lung airway trees and show that the spectral properties of the Maury matrix characterize the flow asymmetry in these networks more concisely than the Laplacian modes, and that eigenvector centrality in the Maury spectrum is closely related to the phenomenon of ventilation heterogeneity caused by airway narrowing or obstruction. This method has applications in dimensionality reduction in simulations of lung mechanics, as well as for characterization of models of the airway tree derived from medical images.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
Keywords: | network; resistance; lung; spectral graph theory; airways; respiratory medicine |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Sheffield Teaching Hospitals |
Funding Information: | Funder Grant number MEDICAL RESEARCH COUNCIL MR/M008894/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Oct 2020 12:38 |
Last Modified: | 05 Oct 2020 12:38 |
Status: | Published |
Publisher: | The Royal Society |
Refereed: | Yes |
Identification Number: | 10.1098/rsif.2020.0253rsif20200253 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165643 |