title: Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy.
abstract: Tractography based on diffusion tensor imaging (DTI) is widely used to quantitatively analyze the status of the white matter anatomy in a tract-specific manner in many types of diseases. This approach, however, involves subjective judgment in the tract-editing process to extract only the tracts of interest. This process, usually performed by manual delineation of regions of interest, is also time-consuming, and certain tracts, especially the short cortico-cortical association fibers, are difficult to reconstruct. In this paper, we propose an automated approach for reconstruction of a large number of white matter tracts. In this approach, existing anatomical knowledge about tract trajectories (called the Template ROI Set or TRS) were stored in our DTI-based brain atlas with 130 three-dimensional anatomical segmentations, which were warped non-linearly to individual DTI data. We examined the degree of matching with manual results for selected fibers. We established 30 TRSs to reconstruct 30 prominent and previously well-described fibers. In addition, TRSs were developed to delineate 29 short association fibers that were found in all normal subjects examined in this paper (N=20). Probabilistic maps of the 59 tract trajectories were created from the normal subjects and were incorporated into our image analysis tool for automated tract-specific quantification.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
authors.forename: Yajing
authors.initials: Y
authors.lastname: Zhang
authors.forename: Jiangyang
authors.initials: J
authors.lastname: Zhang
authors.forename: Kenichi
authors.initials: K
authors.lastname: Oishi
authors.forename: Andreia V
authors.initials: AV
authors.lastname: Faria
authors.forename: Hangyi
authors.initials: H
authors.lastname: Jiang
authors.forename: Xin
authors.initials: X
authors.lastname: Li
authors.forename: Kazi
authors.initials: K
authors.lastname: Akhter
authors.forename: Pedro
authors.initials: P
authors.lastname: Rosa-Neto
authors.forename: G Bruce
authors.initials: GB
authors.lastname: Pike
authors.forename: Alan
authors.initials: A
authors.lastname: Evans
authors.forename: Arthur W
authors.initials: AW
authors.lastname: Toga
authors.forename: Roger
authors.initials: R
authors.lastname: Woods
authors.forename: John C
authors.initials: JC
authors.lastname: Mazziotta
authors.forename: Michael I
authors.initials: MI
authors.lastname: Miller
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; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008953:Models, Anatomic; D008959:Models, Neurological; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D009434:Neural Pathways / Q000033:anatomy & histology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity