Diffusion tensor imaging (DTI) provides information about the organization of white matter tracts in the central and peripheral nervous systems. DTI has been successfully applied to tractography of the brain, and has potential usefulness in early diagnosis of white matter disorders. Early changes in diffusion tensors may precede white matter changes visible on conventional MRI scans in diseases such as multiple sclerosis. However, limitations in current DTI techniques have prevented its use in much of the brain and in the spinal cord, optic nerves, and peripheral nerves, where early changes of MS may be manifest. Diffusion tensor imaging requires long data acquisitions and is therefore susceptible to image artifacts arising from field inhomogeneity and patient motion. These artifacts are reduced with faster imaging. Single- shot diffusion tensor imaging methods have been developed to image with greater speed, thus reducing motion and inhomogeneity artifacts, at the cost of image resolution. Multi-shot methods have been developed to attain higher resolution, but these methods are subject to artifacts caused by phase inconsistencies between multiple acquisitions. We have developed a novel DTI technique, three-dimensional single shot diffusion weighted imaging with stimulated echo acquisition (3D ss-DWSTEPI) which obtains diffusion information in a single shot acquisition over a limited imaging volume. To our knowledge, this is the first report on singleshot acquisition of three dimensional volume. This technique has the potential to overcome limitations of currently used DTI techniques. Three-dimensional imaging can give improved SNR and no loss of signal at the slice boundary in comparison with two-dimensional imaging. The use of volume-selective excitation to create interleaved three-dimensional subvolumes will allow faster imaging with optimal echo train lengths. In this project, realtime navigation is proposed to monitor any excessive motion related error which may reduce DTI measurement accuracy, and reject/reacquire the specific data. The proposed technique has the potential to make DTI possible in important areas such as the spinal cord, peripheral nerves, optic nerves, and regions of the brain not currently accessible by current DTI methods, allowing earlier diagnosis of white matter diseases such as multiple sclerosis. ? ? ?
