Pulmonary MRI provides strong evidence of ventilation abnormalities that are temporally and spatially persistent; this has generated a paradigm shift in our understanding of asthma as a spatially and temporally heterogeneous, non-stochastic disease. Based on these findings, here our objective was to develop image-processing methods to estimate and mathematically describe the spatial probability distribution of MRI-derived ventilation defects. To accomplish this, we generated functional lung MRI atlases based on asthmatics who were evaluated before and post-methacholine using hyperpolarized 3He static-ventilation MRI. This proof-of-concept evaluation showed that in asthmatics, ventilation abnormalities are not diffuse nor stochastic, but heterogeneous and deterministic.
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