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Abstract #2157

Accelerated 3DPCASL Using Compressed Sensing

Li Zhao1, Samuel W. Fielden1, Xiao Chen1, John P. Mugler, III2, Josef Pfeuffer3, Manal Nicolas-Jilwan2, Max Wintermark2, Craig H. Meyer1

1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States; 2Radiology, University of Virginia, Charlottesville, VA, United States; 3Siemens, Erlangen, Germany

Low SNR in ASL limits the achievable spatial resolution and the accuracy of perfusion maps. Dynamic ASL is time-consuming and also suffers from low SNR. Compressed sensing can improve image quality by enforcing spatial-domain sparsity. Compressed sensing can also enforce time-domain sparsity in dynamic ASL. Volunteer data are shown to demonstrate CS performance on single PLD PCASL images and multiple dynamic frames. The results show image SNR and image quality improvement. More importantly, the estimated CBF becomes more accurate and stable with compressed sensing image reconstruction.