Abstract #4462

Highly Accelerated Dynamic Acquisition of 3D Grid-Tagged He-3 Lung Images Using Compressed Sensing

William J Garrison¹, Kun Qing², Sina Tafti³, John P Mugler^1,2, Y Michael Shim⁴, Jaime F Mata², Gordon D Cates^2,3, Eduard E de Lange², Craig H Meyer^1,2, Jing Cai⁵, and G Wilson Miller^1,2

¹Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, ²Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, United States, ³Department of Physics, University of Virginia, Charlottesville, VA, United States, ⁴Department of Medicine, University of Virginia, Charlottesville, VA, United States, ⁵Department of Health Technology and Informatics, Hong Kong Polytechnic University, Kowloon, Hong Kong

Radiotherapy in the context of lung cancer can become less effective if lung biomechanics are not well-characterized. MRI of grid-tagged, inhaled hyperpolarized He-3 gas provides images with strong signal at the tag locations, allowing time-resolved tracking of regional lung motion that can be used to inform strategies for precision radiotherapy. The present work demonstrates rapid acquisition of high-quality 3D grid-tagged images obtained with 8-fold under-sampling and reconstructed using compressed sensing. The dramatic imaging acceleration inherent in this technique allows multiple 3D image sets to be acquired during a single breath-hold, effectively permitting 4D-MRI of lung motion during exhalation.

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