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Abstract #2497

Undersampling strategies for compressed sensing accelerated MR spectroscopic imaging

Nutandev Bikkamane Jayadev1, Christopher Lawhorn1, John Chang2, and Vikram Kodibagkar1

1SBHSE, Arizona State University, Tempe, AZ, United States, 2Department of Radiology and Medical Imaging, Banner MD Anderson Cancer Center, Glibert, AZ, United States

Magnetic Resonance Spectroscopic Imaging (MRSI) is an invaluable tool in cancer diagnosis due to its specificity but long scan times makes it less popular for routine clinical use. Clinical integration of accelerating methods such as compressed sensing (CS) can improve patient throughput. Two different undersampling strategies were implemented and statistical fidelity was tested to obtain a five-fold reduction is acquisition time; 1) a conventional variable density pseudorandom undersampling and 2) an a priori information based strategy that exploits anatomical scans. Statistical results from in vivo studies show the feasibility of using CS accelerated MRSI without loss of data fidelity.

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