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. Nagel^2,3, Mark E. Ladd², and Thoralf Niendorf^1,4

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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