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.