Three-Dimensional Interactive and Stereotactic Human Brain Atlas of White Matter Tracts

Abstract

We present a human brain atlas of white matter (WM) tracts containing 40 major tracts, which is three-dimensional (3D), segmented, labeled, interactive, stereotactic and correlated to structure and vasculature. We consider: (1) WM accuracy by correlating WM tracts to underlying neuroanatomy and quantifying them; (2) balance between realism and completeness by processing a sequence of track volumes generated for various parameters with the increasing track number to enable a tract "shape convergence". MPRAGE and DTI in 64 directions of the same subject were acquired on 3 Tesla. The method has three steps: DTI-MPRAGE registration, 3D tract generation from DTI, to WM reconstruction from MPRAGE to parcellation into 17 components. 82 track volumes were generated for a wide spectrum of parameter values: Fractional Anisotropy threshold in [0.0125, 0.55] and trajectory angle lower than 45°, 60°, 65°, 70°, 75°, 80°, 85°, 90°. For each tract, a sequence of track volumes was processed to create/edit contours delineating this tract to achieve its shape convergence. The parcellated tracts were grouped into commissures, associations, projections and posterior fossa tracts, and labeled following Terminologia Anatomica. To facilitate that, a dedicated tract editor is developed which processes multiple track volumes, handles tracts in three representations (tracks, contours, envelopes); provides editing/visualization simultaneously on axial, coronal, sagittal planes; enables tract labeling and coloring; and provides numerous tools (track counting, smoothing and length thresholding; representation conversion and saving; structural atlas support). A stereotactic tract atlas along with parcellated WM was developed to explore in real-time any individual tract or their groups along with surrounding neuroanatomy.

Cortical Somatosensory Reorganization in Children with Spastic Cerebral Palsy: A Multimodal Neuroimaging Study

“…Ideally, the MEG-defined ROIs should be used for the determination of ROIs in the DTI analysis. However, fiber tracking has limitations in determining the thalamocortical SS radiations and the motor tracts for the hand areas due to its well-known weakness to handle crossing fibers at the centrum semiovale level (Nowinski et al, 2012). Here, we were not able to reconstruct fibers passing from the MEG-defined ROIs to the thalamus.…”

The value of neurosurgical and intraoperative magnetic resonance imaging and diffusion tensor imaging tractography in clinically integrated neuroanatomy modules: A cross‐sectional study

“…A 3D physical modeling activity has been reported by Estevez et al () as an effective method for teaching the spatial relationships of brain anatomy with the aim of better preparing students for the visualization of 3D neuroanatomy, a skill essential for higher education in neuroscience, neurology, and neurosurgery. Besides, a very useful and complete 3D atlas was introduced to permit neuroanatomy browsing, user self‐testing, automatic student assessment, preparing materials, and localization in clinical neurology (Nowinski et al, ).…”

A hitchhiker's guide to diffusion tensor imaging

“…These factors are compounded by a multitude of preprocessing and analysis methods in several software packages. Several papers and books describing the main technical issues and pitfalls related to DTI studies have been published (Basser and Jones, 2002; Moritani et al, 2005; Le Bihan et al, 2006; Mukherjee et al, 2008b; Bammer et al, 2009; Jones, 2010a,b,c; Jones and Cercignani, 2010; Chung et al, 2011; Hasan et al, 2011) which are complemented by available neuroanatomical WM atlas (Jellison et al, 2004; Wakana et al, 2004; Catani and Thiebaut De Schotten, 2008; Lawes et al, 2008; Oishi et al, 2008, 2010; Zhang et al, 2010; Bazin et al, 2011; Nowinski et al, 2012). However, given the constant methodological advances and the increase in DTI applicability across clinical and research domains, we have here compiled a practical hitchhiker's guide of critical information and main references to consider in setting up DTI studies, optimizing data quality, and interpreting results.…”