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Both the development of accurate models of lung function and their quantitative validation can be significantly enhanced by the use of functional imaging techniques. The advent of hyperpolarized noble gas magnetic resonance imaging (MRI) technology has increased the amount of local, functional information we can obtain from the lung. In particular, application of (3)He to measure apparent diffusion coefficients has enabled some measure of lung microstructure and airspace size within the lung. Models mimicking image acquisition in hyperpolarized gas MRI can improve understanding of the relationship between image findings and lung structure, and can be used to improve the definition of imaging protocols. In this paper, we review the state of the art in hyperpolarized gas MRI modelling. We also present our own results, obtained using a Monte Carlo approach and a realistic alveolar sac geometry, which has previously been applied in functional lung studies. In this way, we demonstrate the potential for models combining lung function and image acquisition, which could provide valuable tools in both basic studies and clinical practice.

Original publication




Journal article


Philos Trans A Math Phys Eng Sci

Publication Date





2347 - 2369


Computational Biology, Humans, Magnetic Resonance Imaging, Monte Carlo Method, Pulmonary Alveoli, Pulmonary Disease, Chronic Obstructive