The retinogeniculate visual pathway (RGVP) conveys visual information from the retina to the lateral geniculate nucleus. Anatomically, the RGVP can be separated into four subdivisions, including two decussating and two non-decussating fiber pathways, which cannot be identified by conventional magnetic resonance imaging (MRI). Diffusion MRI tractography has the potential to trace these subdivisions and is increasingly used to study the anatomy of the RGVP. However, it is not yet known which fiber tracking strategy is most suitable for tractographic reconstruction of the RGVP. In this study, four different tractography algorithms, including constrained spherical deconvolution (CSD) model based probabilistic (iFOD1) and deterministic (SD-Stream) methods, and multi-fiber (UKF-2T) and single-fiber (UKF-1T) unscented Kalman filter (UKF) tractography methods, are compared for reconstruction of the RGVP. Experiments are performed using diffusion MRI data of 57 subjects in the Human Connectome Project. The RGVP is identified using regions of interest created by two clinical experts. Anatomical measurements are used to assess the advantages and limitations of the four tracking strategies, including the reconstruction rate of the four RGVP subdivisions, the percentage of decussating fibers, the correlation between volumes of the traced RGVPs and a T1w-based RGVP segmentation, and an expert judgment to rank the anatomical appearance of the reconstructed RGVPs. Overall, we conclude that UKF-2T and iFOD1 produce the best RGVP reconstruction results. The iFOD1 method can better quantitatively estimate the percentage of decussating fibers, while the UKF-2T method produces reconstructed RGVPs that are judged to better correspond to the known anatomy.
bioRxiv Subject Collection: Neuroscience