Diffusion tensor imaging is a quantitative magnetic resonance imaging method, which probes the anisotropic diffusion properties of white matter in the brain. Furthermore, it is possible to generate fiber tracts from these diffusion tensors, which are non-invasive visual representations of nerve fiber bundles. However, most methods for diffusion tensor imaging and tractography are time consuming and require extensive user interaction. Therefore, this thesis demonstrates the implementation of TRACULA, a technique for the automatic identification and reconstruction of 18 fiber tracts, and its evaluation based on results from 213 healthy probands and 27 Patients. Changes in tract reconstructions and tract-specific diffusion properties were found for healthy subjects, regarding image resolution, number of diffusion directions and age. Amyotrophic lateral sclerosis patients showed an increase in mean and radial diffusivity for bilateral corticospinal tracts. Furthermore, fractional anisotropy was decreased for ambilateral corticospinal tracts and superior longitudinal fasciculus parietal. These results are in agreement with the literature and emphasize the stability and reliability of TRACULA, as well as its potential in clinical use.
|Qualification||Master of Science|
|Publication status||Published - 2018|
- Diffusion Tensor Imaging