title: Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification.
abstract: Diffusion tensor imaging (DTI) is an exciting new MRI modality that can reveal detailed anatomy of the white matter. DTI also allows us to approximate the 3D trajectories of major white matter bundles. By combining the identified tract coordinates with various types of MR parameter maps, such as T2 and diffusion properties, we can perform tract-specific analysis of these parameters. Unfortunately, 3D tract reconstruction is marred by noise, partial volume effects, and complicated axonal structures. Furthermore, changes in diffusion anisotropy under pathological conditions could alter the results of 3D tract reconstruction. In this study, we created a white matter parcellation atlas based on probabilistic maps of 11 major white matter tracts derived from the DTI data from 28 normal subjects. Using these probabilistic maps, automated tract-specific quantification of fractional anisotropy and mean diffusivity were performed. Excellent correlation was found between the automated and the individual tractography-based results. This tool allows efficient initial screening of the status of multiple white matter tracts.
authors.affiliation: Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
authors.forename: Kegang
authors.initials: K
authors.lastname: Hua
authors.forename: Jiangyang
authors.initials: J
authors.lastname: Zhang
authors.forename: Setsu
authors.initials: S
authors.lastname: Wakana
authors.forename: Hangyi
authors.initials: H
authors.lastname: Jiang
authors.forename: Xin
authors.initials: X
authors.lastname: Li
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Reich
authors.forename: Peter A
authors.initials: PA
authors.lastname: Calabresi
authors.forename: James J
authors.initials: JJ
authors.lastname: Pekar
authors.forename: Peter C M
authors.initials: PC
authors.lastname: van Zijl
authors.forename: Susumu
authors.initials: S
authors.lastname: Mori
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000166:cytology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008959:Models, Neurological; D015233:Models, Statistical; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D009434:Neural Pathways / Q000033:anatomy & histology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity