|Title:||Diffusion tensor imaging and fiber tractography in the human brain|
|Authors :||Järmann, Thomas|
|Advisors / Reviewers :||Bösinger, Peter|
|Publisher / Ed. Institution :||ETH Zürich|
|Language :||Deutsch / German|
|Subject (DDC) :||616.8: Neurologie, Krankheiten des Nervensystems|
|Abstract:||The dysfunction of the human brain’s network is responsible for a variety of diseases. Its complexity on the cognitive as well as on the structural level makes neuroscience a challenging venture. Since the introduction of Diffusion Tensor Imaging (DTI) a decade ago, progress has been made in the non-invasive depiction of the neuronal organization. DTI allows to probe the tissue micro structure by characterizing the local mobility of water molecules in all three spatial dimensions. As an auspicious application, the so-called fiber tractography technique connects tiny, virtual brain segments in direction of the main diffusion, representing axonal pathways in three dimensions. The key problems of DTI consist in the low signal-to-noise ratio (SNR) and the poor image quality: As it is sensitive to motion, the underlying diffusion-weighted images are preferably acquired from a single radio frequency excitation. Single-shot experiments suffer from an increased susceptibility to magnetic field inhomogeneities, leading to image distortions, and a restricted spatial resolution due to spin relaxation processes. The limited image quality affects also the performance of reconstructing fiber trajectories. Misleading pathways may result. The present dissertation is dedicated to the development of new concepts for improving DTI and fiber tracking. With the advent of the parallel imaging technique SENSitivity Encoding (SENSE) and the initiation of high-field magnets, major advances in Magnetic Resonance Imaging have been achieved. A focus of the presented work is the implementation and investigation of SENSE-DTI at a high magnetic field strength. It is shown that the application of SENSE at 3 Tesla exploits the increased SNR of the main magnetic field while diminishing artifacts based on susceptibility variations. As a result of the reduced number of spatial encoding steps, the point spread function narrows, thus yielding data with an enhanced intrinsic spatial resolution. High-quality DTI with an in-plane resolution in the sub-millimeter range has been achieved in volunteers and patients. Furthermore, the increase of SNR resulting from the use of SENSE has been studied in detail. The non-destructive investigation of the occipital gray matter structure is essential to bridge the gap between anatomy and function. It requires very high SNR since the cortical anisotropy is relatively poor. Therefore, a sensitive miniature phased array detector, consisting of up to five surface coils, has been developed. The dedicated setup together with an optimal parallel acquisition strategy has enabled to resolve the matrix-like structure of the gray matter. In addition, axonal trajectories have been reconstructed which penetrate the cortical ribbon, where their radial arrangement represents the vertical organization of the occipital cortex. Fiber tractography using high-quality SENSE-DTI data provides a promising method for exploring the neuronal connectivity of the brain. It is crucial, however, to be aware of the intrinsic limitations of the technique. Standard procedures fail in brain regions where nerve bundles branch or intersect. To overcome this obstacle, an algorithm has been developed based on the Fast Marching method. Simulations as well as in-vivo results confirm the progress in reconstructing complex brain areas. In a patient study, the sensitivity of SENSE-DTI to the disease-related characteristics in Multiple Sclerosis (MS) has been examined. Preliminary results demonstrate the ability of fiber tractography to assess changes between affected white matter tracts and the contra-lateral normal appearing white matter. This may have prognostic and functional implications for differentiation of the form of MS amongst clinical subgroups with consequences on planning early treatment. In conclusion, the presented methods contribute to a better access and depiction of the brain’s neuronal architecture. This is of importance for an improved understanding of its functionality, both in physiological and pathological conditions.|
|Further description :||Diss., Naturwissenschaften ETH Zürich, Nr. 15994, 2005.|
|Departement:||School of Engineering|
|Publication type:||Dissertation / Doctoral Thesis|
|License (according to publishing contract) :||Lizenz gemäss Verlagsvertrag / Licence according to publishing contract|
|Appears in Collections:||Publikationen School of Engineering|
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