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Abstract #3681

Feasibility of Dynamic Inhaled Gas MRI-based Measurements using Acceleration Factors of 10 and 14

Matthew S Fox1,2, Elise Woodward3, Marcus Couch4, Tao Li5, Iain Ball6, and Alexei V Ouriadov1,2
1Lawson Health Research Institute, London, ON, Canada, 2Physics and Astronomy, The University of Western Ontario, London, ON, Canada, 3The University of Western Ontario, London, ON, Canada, 4Montrel Neuro Institute, Montreal, QC, Canada, 5Thunder Bay Regional Research Institute,, Thunder Bay, ON, Canada, 6Philips Australia & New Zealand, North Ryde, Australia

We hypothesize that the SEM equation can be adapted for fitting the gas-density dependence of the MR signal similar to fitting time or b-value dependences S(n)=exp[-(nR)β], where 0<β<1, n is the image number and R is the apparent-fractional-ventilation parameter. This interpretation allows us to consider the signal-intensity variation as reflection of the underlying gas-density variation and hence, reconstruction of the under-sampled k-space using the adapted SEM equation. Lung fractional-ventilation maps have been generated using reconstructed images. We have demonstrated the feasibility of our approach using retrospective under-sampling mimicking acceleration factors of 10 and 14 in a small animal cohort.

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