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Abstract #3877

Application of 3D-Dictionary Learning Compressed Sensing Reconstruction En Route to Isotropic Submillimeter Spatial Resolution Sodium (23Na) In Vivo MRI of the Human Eye at 7.0 Tesla

Daniel Wenz1, Nicolas G.R. Behl2, Armin M. Nagel2,3, Mark E. Ladd2, and Thoralf Niendorf1,4

1Berlin Ultrahigh Field Facility, Max Delbrueck Centrum, Berlin, Germany, 2Division of Medical Physics in Radiology, German Research Centre (DKFZ), Heidelberg, Germany, 3Institute of Radiology, Unviersity Hospital Erlangen, Erlangen, Germany, 4MRI.TOOLS GmbH, Berlin, Germany

Sodium ion (Na+) is a very important factor in the physiology of the human eye. However sodium (23Na) MRI is limited by its low sensitivity. Compressed sensing provides means to overcome this challenge. This work demonstrates the feasibility of high spatial resolution (1mm isotropic) 23Na in vivo MRI of the eye using a dedicated six-channel transceiver array in conjunction with a 3D dictionary learning compressed sensing algorithm. This approach showed distinct noise reduction along with substantial reduction in total acquisition time if benchmarked against conventional reconstruction employing standard gridding.

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