Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/102289
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dc.contributor.authorStahr, C.-
dc.contributor.authorSamarage, C.-
dc.contributor.authorDonnelley, M.-
dc.contributor.authorFarrow, N.-
dc.contributor.authorMorgan, K.-
dc.contributor.authorZosky, G.-
dc.contributor.authorBoucher, R.-
dc.contributor.authorSiu, K.-
dc.contributor.authorMall, M.-
dc.contributor.authorParsons, D.-
dc.contributor.authorDubsky, S.-
dc.contributor.authorFouras, A.-
dc.date.issued2016-
dc.identifier.citationScientific Reports, 2016; 6(1):29438-1-29438-10-
dc.identifier.issn2045-2322-
dc.identifier.issn2045-2322-
dc.identifier.urihttp://hdl.handle.net/2440/102289-
dc.descriptionPublished: 27 July 2016-
dc.description.abstractComputed tomography (CT) and spirometry are the mainstays of clinical pulmonary assessment. Spirometry is effort dependent and only provides a single global measure that is insensitive for regional disease, and as such, poor for capturing the early onset of lung disease, especially patchy disease such as cystic fibrosis lung disease. CT sensitively measures change in structure associated with advanced lung disease. However, obstructions in the peripheral airways and early onset of lung stiffening are often difficult to detect. Furthermore, CT imaging poses a radiation risk, particularly for young children, and dose reduction tends to result in reduced resolution. Here, we apply a series of lung tissue motion analyses, to achieve regional pulmonary function assessment in β-ENaC-overexpressing mice, a well-established model of lung disease. The expiratory time constants of regional airflows in the segmented airway tree were quantified as a measure of regional lung function. Our results showed marked heterogeneous lung function in β-ENaC-Tg mice compared to wild-type littermate controls; identified locations of airway obstruction, and quantified regions of bimodal airway resistance demonstrating lung compensation. These results demonstrate the applicability of regional lung function derived from lung motion as an effective alternative respiratory diagnostic tool.-
dc.description.statementofresponsibilityCharlene S. Stahr, Chaminda R. Samarage, Martin Donnelley, Nigel Farrow, Kaye S. Morgan, Graeme Zosky, Richard C. Boucher, Karen K. W. Siu, Marcus A. Mall, David W. Parsons, Stephen Dubsky and Andreas Fouras-
dc.language.isoen-
dc.publisherNature Publishing Group-
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/-
dc.source.urihttp://dx.doi.org/10.1038/srep29438-
dc.subjectLung-
dc.subjectNeutrophils-
dc.subjectAnimals-
dc.subjectMice, Inbred C3H-
dc.subjectMice, Inbred C57BL-
dc.subjectMice, Transgenic-
dc.subjectMice-
dc.subjectLung Diseases-
dc.subjectTomography, X-Ray Computed-
dc.subjectRadiography-
dc.subjectRespiratory Function Tests-
dc.subjectSpirometry-
dc.subjectAlgorithms-
dc.subjectMotion-
dc.subjectX-Rays-
dc.subjectComputer Simulation-
dc.subjectFemale-
dc.subjectMale-
dc.titleQuantification of heterogeneity in lung disease with image-based pulmonary function testing-
dc.typeJournal article-
dc.identifier.doi10.1038/srep29438-
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/626863-
dc.relation.granthttp://purl.org/au-research/grants/arc/DE120102571-
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1022721-
pubs.publication-statusPublished-
dc.identifier.orcidDonnelley, M. [0000-0002-5320-7756]-
dc.identifier.orcidFarrow, N. [0000-0002-2289-1268]-
dc.identifier.orcidParsons, D. [0000-0003-1746-3290]-
Appears in Collections:Aurora harvest 7
Paediatrics publications

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