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Regional measures of lung function in the β-ENaC cystic fibrosis mouse model obtained using four-dimensional X-ray velocimetry : An image-based pulmonary function test for localising and quantifying disease

posted on 26.04.2018, 02:42 by Charlene Shia Ying Stahr
This thesis provides an overview of the relevance of lung mechanics to lung function, with particular context to cystic fibrosis lung disease, and presents an implementation of a 4-dimensional in vivo image-based method to measure regional lung motion as an indicator of lung disease.

In this study β-ENaC transgenic mice and littermate controls were employed as a model for cystic fibrosis lung disease. Four-dimensional particle image velocimetry was applied to synchrotron tomographic reconstructions of live, mechanically ventilated subjects to measure regional lung tissue motion, and determine regional ventilation throughout breathing. Regional airflow was calculated by associating the regional ventilation measurements to an airway tree extracted from the CT reconstruction. Regional lung function was classified using the expiratory time constant of the regional airflow.

The assessment yielded maps of lung function at high spatial and temporal resolution across the entire lung during breathing. The study successfully demonstrated the quantification of lung disease heterogeneity, identifying airway obstruction, and regions of bimodal airway resistance. The regional measures were more sensitive in detecting functional deficits in the β-ENaC transgenic mice compared to global measures, relative to littermate controls.

This thesis demonstrates the ability of regional lung function derived from in vivo lung imaging as an effective tool to assess obstructive diseases of the lung, such as cystic fibrosis. It showed that image- based calculation of regional lung function allows the quantification and localisation of cystic fibrosis-like lung disease, which are not currently available using global lung function tests such as spirometry.


Campus location


Principal supervisor

Andreas Fouras

Additional supervisor 1

Karen Kit Wan Siu

Year of Award


Department, School or Centre

Mechanical and Aerospace Engineering


Master of Engineering Science (Research)

Degree Type



Faculty of Engineering