Abstract #3681

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

Matthew S Fox^1,2, Elise Woodward³, Marcus Couch⁴, Tao Li⁵, Iain Ball⁶, and Alexei V Ouriadov^1,2

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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