Diffusion Tensor Imaging: Evaluation of Tractography Algorithm Performance Using Ground Truth Phantoms

(Abstract) Diffusion Tensor Magnetic Resonance Imaging (DT-MRI), also known as Diffusion Tensor Imaging (DTI), is a unique medical imaging modality that provides non-invasive estimates of White Matter (WM) connectivity based on local principal directions of anisotropic water diffusion. DTI tractography estimates are a macroscopically sampled description of underlying microscopic structure, and are therefore of limited validity. The under-sampling of underlying white matter structure in DTI data gives rise to Intra-Voxel Orientational Heterogeneity (IVOH), a condition in which white matter structures of multiple different orientations are averaged into a single DTI voxel sample, causing a loss of validity in the diffusion tensor model. Fast Marching Tractography (FMT) algorithms based on fast marching level set methods have been proposed to better handle the presence of IVOH in DTI data when compared to older Streamline Tractography (SLT) methods. However, the actual performance advantage of any tractography algorithm over another cannot be conclusively stated until a ground truth standard of comparison is developed. This work develops an optimized version of the FMT algorithm that is dubbed the Front Propagation Tractography (FPT) algorithm. The FPT algorithm includes unique approaches to the speed function, connectivity estimation, and likelihood estimation components of the FMT framework. The performance of the FPT algorithm is compared against the SLT algorithm using ground truth software phantom data and human brain data. Software phantom ground truth experiments compare the performance of each algorithm in single tract and crossing tract structures for varying levels of diffusion tensor field perturbation. Human brain estimates in the corpus callosum yield qualitative comparisons from inspection of 3D visualizations. A final area of exploration is the construction and analysis of a ground truth physical DTI phantom manifesting IVOH. throughout the course of my research. Dr. Wyatt's technical ability and down to earth kindness was vital to the completion of this project. I realize that very few professors would have allowed me such freedom in choosing the course of my research, and for that freedom I am thankful. My next big thank you is to the Via family and the Bradley Department of Electrical and Computer Engineering for awarding me with the Bradley Fellowship during my graduate studies. I greatly appreciate being given the opportunity to complete my research distracted by work or financial worries. I hope that the Bradley Fellowship will continue far into the future and allow other fortunate students to pursue their own research visions. I …