Title: Image-based measurement of alveoli volume expansion in an animal model of a diseased lung
Authors: Christopher E. Hann, Darren Hewett, J. Geoffrey Chase, Timon Rabczuk, Ashwath Sundaresan, XiaoQi Chen, Wenhui Wang, Geoffrey M. Shaw
Addresses: Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. ' Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. ' Department of Intensive Care, Christchurch Hospital, Christchurch, New Zealand
Abstract: This research aims to improve ventilation protocols in critical care by using appropriate computer models that take into account the essential lung mechanics. This paper automatically tracks the boundary of individual or groups of alveoli, and converts this into a pressure volume curve for three different types of alveoli. Schiller et al. investigate the inflation and deflation of alveoli in a surfactant deactivation model of lung injury in pigs. Three different types of alveoli were tracked using dynamic ventilation data from Schiller et al. The boundaries of all the tracked alveoli compared well visually to the movies. Pressure versus area curves were derived for both inflation and deflation, they captured the expected physiological behaviour, and were qualitatively similar to the quasi-static pressure area curves derived by Schiller et al. Quantitative differences are due to the dynamic effects of ventilation which were not investigated by Schiller et al.
Keywords: mechanical ventilation; critical care; computer models; dynamic alveoli tracking; tracking algorithm; animal modelling; diseased lungs; lung mechanics; surfactant deactivation; pigs; lung injury.
DOI: 10.1504/IJCAT.2010.034731
International Journal of Computer Applications in Technology, 2010 Vol.39 No.1/2/3, pp.58 - 65
Published online: 18 Aug 2010 *
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