The diffusion anisotropy (DA) in the brain measured by diffusion weighted MRI (DW-MRI) is known to be related to the local white matter (WM) structure and therefore can be used as an indicator for changes associated with degenerative WM diseases. The estimation of DA is also a necessary precursor to all fiber tract mapping methods, which hold the potential for understanding brain connectivity when used in conjunction with functional MRI (fMRI) studies. The current standard method for measuring DA is diffusion tensor imaging (DTI) in which magnetic field variations along multiple directions encode complex patterns of microscopic water motion. Signal variations as a function of the diffusion encoding direction are related to the local tissue diffusion (LTD) from which DA is estimated based upon a simplified model for tissue diffusion that require only a few encoding directions. However, recent studies have shown that the complexity of LTD is not necessarily well fit by the standard model and high angular resolution diffusion (HARD) measurements are needed to better characterize LTD. This poses two significant problems: An increase in imaging time, making clinical applications more difficult, and no general analysis scheme by which to characterize anisotropy. Ultimately, the assessment of LTD and DA requires the development of more accurate physical models for tissue diffusion that incorporate boundaries and restrictions and increasingly sensitive methods of measurement. The primary goal of this work is to further investigate our recently proposed solutions to these two problems. We have generalized the analysis currently used for DTI to incorporate more a general physical model, for diffusion. This method, called the spherical harmonic decomposition (SHD), has been employed in a rapid numerical implementation efficient for clinical applications. The first specific aim is to extend our SHD approach to an even more general applicable to multiple b-values that we have developed, called the spherical wave decomposition (SWD). Secondly, we have described a novel DW-MRI method based on the recently introduced concept of hyperechoes (HE) that has the potential to dramatically increased the diffusion sensitivity per unit time of standard clinical applications, thereby facilitating the extension to HARD measurements with minimal time penalty but greatly increased DA sensitivity. While hyperecho DW-MRI has a clear theoretical advantage over traditional DW-MRI acquisition methods, it is prone to unique technical difficulties in its implementation that will be addressed as our second specific aim to make it a clinically viable methodology. Both these two aims will be used in the development of our third specific aim, which is to establish experimentally, through the use of variations of HE-HARD, in conjunction with SWD, the sensitivity of DW MRI to the structure of complex tissues. Motivated by our recent work showing changes in WM DA in alcoholic patients, our proposal focuses on increasing the sensitivity of DW-MRI to DA, our ultimate long term goal is to utilize these methods in a clinical environment, specifically in our ongoing assessment of degenerate white matter diseases such as Alzheimer's, AIDS, and, in particular, alcoholism.
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