Diffusion Tensor Imaging with HighlY constrained backPRojection ( HYPR )

Diffusion tensor imaging (DTI) and other DW imaging methods are typically applied using echo-planar imaging (EPI) methods, which are highly efficient and insensitive to motion, but are prone to significant artifacts including image distortion, blurring and ghosting. Conversely, diffusion-weighted projection reconstruction imaging (DW-PRI) methods [1-4] demonstrate significantly reduced image artifacts; however, the scans are significantly slower and much less noise efficient. The imaging time requirements of DW-PRI are particularly prohibitive for DW scans using a large number diffusion encoding directions, such as q-ball imaging (QBI) and diffusion spectrum imaging (DSI) [5]. In this study, a novel image reconstruction method, HYPR (highly constrained backprojection) [6], was used to reconstruct diffusion tensor images from a set of highly undersampled DW PRI data. HYPR is a method in which a series of angularly undersampled images are obtained in projection mode. For each image in the series a highly constrained back projection technique is used in which the backprojected signal is deposited only in those locations provided by a composite image that is formed from the set of all interleaved sets of projections acquired in the entire scan [6].