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Quantification of muco-obstructive lung disease variability in mice via laboratory X-ray velocimetry

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posted on 2023-05-20, 15:52 authored by Werdiger, F, Donnelley, M, Dubsky, S, Murrie, RP, Carnibella, RP, Samarage, CR, How, YY, Graeme ZoskyGraeme Zosky, Fouras, A, Parsons, DW, Morgan, KS
To effectively diagnose, monitor and treat respiratory disease clinicians should be able to accurately assess the spatial distribution of airflow across the fine structure of lung. This capability would enable any decline or improvement in health to be located and measured, allowing improved treatment options to be designed. Current lung function assessment methods have many limitations, including the inability to accurately localise the origin of global changes within the lung. However, X-ray velocimetry (XV) has recently been demonstrated to be a sophisticated and non-invasive lung function measurement tool that is able to display the full dynamics of airflow throughout the lung over the natural breathing cycle. In this study we present two developments in XV analysis. Firstly, we show the ability of laboratory-based XV to detect the patchy nature of cystic fibrosis (CF)-like disease in β-ENaC mice. Secondly, we present a technique for numerical quantification of CF-like disease in mice that can delineate between two major modes of disease symptoms. We propose this analytical model as a simple, easy-to-interpret approach, and one capable of being readily applied to large quantities of data generated in XV imaging. Together these advances show the power of XV for assessing local airflow changes. We propose that XV should be considered as a novel lung function measurement tool for lung therapeutics development in small animal models, for CF and for other muco-obstructive diseases.

History

Publication title

Scientific Reports

Volume

10

Article number

10859

Number

10859

Pagination

1-12

ISSN

2045-2322

Department/School

Tasmanian School of Medicine

Publisher

Nature Publishing Group

Place of publication

United Kingdom

Rights statement

Copyright 2020 The Authors Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) Attribution 4.0 International (CC BY 4.0)

Repository Status

  • Open

Socio-economic Objectives

Clinical health not elsewhere classified

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