Abstract #3485

Accelerated Echo Planar J-Resolved Spectroscopic Imaging in Prostate Cancer and A Hybrid Dictionary Learning-Total Variation Reconstruction

Ajin Joy¹, Rajakumar Nagarajan¹, Andres Saucedo¹, Zohaib Iqbal¹, Manoj K Sarma¹, Neil E Wilson¹, Ely R Felker¹, Robert E Reiter², Steven S Raman¹, and M Albert Thomas¹

¹Radiological Sciences, University of California-Los Angeles, Los Angeles, CA, United States, ²Urology, University of California-Los Angeles, Los Angeles, CA, United States

Synopsis

Prospectively undersampled 5D echo-planar J-resolved spectroscopic imaging (EP-JRESI) data were acquired in 9 prostate cancer patients and 3 healthy controls. The 5D data was reconstructed using Dictionary learning (DL), Total Variation (TV), Perona-Malik (PM) and a hybrid DLTV method combining DL and TV. DLTV uses the gradient sparsity of TV and the learned dictionary-based sparsity of DL to further increase the transform sparsity of the data. The DLTV method unambiguously resolved 2D J-resolved peaks including myo-inositol, citrate, creatine, spermine and choline with an improved reconstruction that facilitates higher acceleration factors, leading to significant reduction in scan time.

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