Diffusion-Weighted and Diffusion Tensor Imaging in MR Tomography - Sequence Development and Optimization Focusing on Clinical Applications

The importance of Magnetic Resonance Tomography (MRT) arises from the high frequency of water protons in living tissue, the non-invasiveness of the technique and the straightforward spatial encoding of protons by means of additional locally varying magnetic field gradients. During the last two decades, diffusion-weighted imaging (DWI) has added an essential contribution to clinical MR tomography of structural T1- and T2-weighted imaging and to mapping of physiological processes like perfusion and functional activity. DWI uses the self-diffusion (Brownian motion) of water molecules in an inhomogeneous static magnetic field that can be encoded by locally dependent gradient fields. The key feature and importance of MR-DWI results from the fact that the random translatory motion of molecules scans the microscopic tissue structures far beyond the spatial resolution of MR imaging techniques. Furthermore, diffusion as a physical process is independent of magnetic resonance phenomena, but offers similar advantages like high contrast and spatial resolution. The intent of this dissertation covers projects of sequence development and optimization of clinical DWI applications that illustrate the fast evolving development of DWI in medical MR imaging. One focus is set on the combination of DW echo-planar imaging (EPI) and the fluid-attenuated inversion recovery (FLAIR) prepa¬ration. After technical validation, issues of measurement accuracy and signal-to-noise ratio and their implications on estimated contrast parameters like diffusion anisotropy are discussed. A proposed correction term enables immediate acquisition and comparison of standard DW-EPI and FLAIR-DWI in volunteer and patient studies. A preliminary study on patients with astrocytoma reveals the advantages of FLAIR-prepared DW imaging protocols. The second topic of this dissertation explores the extension of the linear diffusion tensor model to high angular resolution DWI (HARDI). The high complexity of white matter fiber structures limits the linear DTI model and requires improved acquisition schemes as well as enhanced quantitative estimates. An approach for visualizing deviations from the linear DT model by means of 2D polar and contour plots is proposed. Additionally, four examples of clinical protocols are described in detail showing important current contribu¬tions of methodological developments in DW and DT imaging. Neurological diagnostic questions concerning early stroke dynamics, transient global amnesia, and side effects of electroconvulsive therapy require a robust DWI strategy that is independent of diffusion anisotropy, whereas the directional information of diffusion tensor imaging enables the delineation of main white matter fiber tracts and a reliable description of small focal lacunar infarct lesions. This adds important diagnostic details to the patient s symptoms and prognosis. The stimulus to improvements and innovations in the field of DW MRI and all post-processing disciplines is still unbowed. Improved technical aspects of MR scanners like higher field strength, parallel acquisition techniques and development of alternative effective sampling strategies allow continuously improving image quality, stronger diffusion weighting and/or the realization of theoretically desired DW schemes of pulsed, short and strong DW gradients. On the other side, recent progress and increased benefits of post-processing strategies contribute essentially to the visualization of processed diffusion tensor data. The techniques of tracking algorithms, formerly based on the linear DT model and today extended to tensors of higher order and probabilistic algorithms, suggest the visualization of structural connectivity across fiber tracts. Merging these analyses with functional connectivity studies and other physiological data assigns DTI a small, yet important role in the investigation of human brain structure and function