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Abstract #0297

Feasibility of MRI-based lung tissue mechanics computational models of the paediatric lung

Megan Soo1, Haribalan Kumar1,2,3, Daniel Cornfeld3, Paul Condron3,4, Taylor Emsden3,4, Leigh Potter3,5, Samantha Holdsworth3,4, Merryn H. Tawhai1, and Ho-Fung Chan1,3
1Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand, 2GE Healthcare Australia and New Zealand, Auckland, New Zealand, 3Mātai Medical Research Institute, Gisborne, New Zealand, 4Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand, 5Ngāti Porou, Ngāti Kahungungu, Rongomaiwahine, Rongowhakaata; Tūranganui-a-Kiwa, Tairāwhiti, New Zealand

Synopsis

Keywords: Lung, Lung

Motivation: There is a scarcity of personalised computational physiology models of the paediatric lung because most models have previously been derived for the adult lung from CT images.

Goal(s): We aim to derive personalised computational models of the paediatric lung from novel structure-function lung MRI techniques.

Approach: In this feasibility study, lung ZTE MR images from healthy children were used to create finite element soft tissue deformation mechanics models.

Results: Simulations of regional supine lung tissue densities were shown to be similar to lung ZTE MRI densities, demonstrating the strong potential for developing computational paediatric lung models from MR images.

Impact: A computational physiology model of soft tissue deformation was created from lung ZTE MR images of healthy children, demonstrating the potential of using novel regional lung structure-function information for personalised paediatric computational models.

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Keywords