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Abstract #1878

High Resolution DTI Using Highly Undersampled Variable Desnity Acquisition and ICORNOL Reconstruction

Wenchuan Wu1, Sheng Fang2, Chun Yuan3, 4, Hua Guo4

1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine,, Tsinghua University, Beijing, China; 2Institute of nuclear and new energy technology, Tsinghua Univerisity, Beijing, China; 3Department of Radiology, University of Washington, Seattle, WA, United States; 4Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China

Combined variable density spiral (VDS) and improved CORNOL was proposed to acquire high spatio-temporal resolution diffusion tensor images. The oversampled data from VDS central k space provides self-navigation capability, thus they can be used to correct motion induced phase error induced by motion sensitive diffusion gradients. Additionally, VDS is a suitable candidate for nonlinear reconstruction as the undersampling artifacts are incoherent. CORNOL is a kind of nonlinear reconstruction methods that can effectively suppress incoherent aliasing artifacts while maintaining image structure details for highly undersampled data. Preliminary results show that with a reduction factor of 4, VDS and CORNOL combination for high resolution diffusion tensor imaging has less artifacts and better structure details compared to CG-SENSE.

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Keywords

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