title: Quantitative analysis along the pyramidal tract by length-normalized parameterization based on diffusion tensor tractography: application to patients with relapsing neuromyelitis optica.
abstract: In this study, we introduced a length-normalized parameterization method to establish anatomical correspondence of white matter fiber tracts across subjects and applied this method to investigate the presence of abnormal diffusion along the pyramidal tract (PYT) of relapsing neuromyelitis optica (RNMO) patients without visible brain lesions. In this approach, the part of the PYT between the lowest slice of the cerebral peduncle and the uppermost slice of the lateral ventricle was reconstructed to establish the anatomical correspondence across subjects using diffusion tensor tractography. Then it was parameterized by normalizing its length and dividing equally the normalized length into a certain number of segments, so that the comparability of each segment across subjects along the PYT was established. Tract-specific diffusion indices, including directionally averaged diffusivity (D(av)), fractional anisotropy (FA), primary diffusivity (lambda(1)) and transverse diffusivity (lambda(23)), were obtained from each segment. Thus, the distribution maps of these indices along the PYT were obtained. The distribution maps of D(av), FA, and lambda(23) of RNMO patients were significantly different from those of healthy controls, especially in the lower part of the PYT. The differences may be caused by secondary degeneration to lesions in the spinal cord. In conclusion, a length-normalized parameterization method is proposed to establish anatomical correspondence for the PYT. Compared with existed methods, a major merit of our method is to provide comparability across subjects along the PYT on the basis of diffusion tensor tractography and to make it possible for the quantitative analysis along the fiber tract. This method can also be used to quantitatively analyze other white matter fiber tracts between two definite anatomic landmarks in many neurological or psychiatric diseases.
authors.affiliation: National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, People's Republic of China.
authors.forename: Fuchun
authors.initials: F
authors.lastname: Lin
authors.forename: Chunshui
authors.initials: C
authors.lastname: Yu
authors.forename: Tianzi
authors.initials: T
authors.lastname: Jiang
authors.forename: Kuncheng
authors.initials: K
authors.lastname: Li
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Li
authors.forename: Wen
authors.initials: W
authors.lastname: Qin
authors.forename: Hong
authors.initials: H
authors.lastname: Sun
authors.forename: Piu
authors.initials: P
authors.lastname: Chan
mesh_terms: D000328:Adult; D000465:Algorithms; D016880:Anisotropy; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D020547:Lateral Ventricles / Q000033:anatomy & histology; D008279:Magnetic Resonance Imaging; D008297:Male; D008636:Mesencephalon / Q000033:anatomy & histology; D008875:Middle Aged; D009412:Nerve Fibers / Q000502:physiology; D009471:Neuromyelitis Optica / Q000473:pathology*; D011712:Pyramidal Tracts / Q000033:anatomy & histology* / Q000166:cytology; D012008:Recurrence