title: Surface-based vertexwise analysis of morphometry and microstructural integrity for white matter tracts in diffusion tensor imaging: With application to the corpus callosum in Alzheimer's disease.
abstract: In this article, we present a unified statistical pipeline for analyzing the white matter (WM) tracts morphometry and microstructural integrity, both globally and locally within the same WM tract, from diffusion tensor imaging. Morphometry is quantified globally by the volumetric measurement and locally by the vertexwise surface areas. Meanwhile, microstructural integrity is quantified globally by the mean fractional anisotropy (FA) and trace values within the specific WM tract and locally by the FA and trace values defined at each vertex of its bounding surface. The proposed pipeline consists of four steps: (1) fully automated segmentation of WM tracts in a multi-contrast multi-atlas framework; (2) generation of the smooth surface representations for the WM tracts of interest; (3) common template surface generation on which the localized morphometric and microstructural statistics are defined and a variety of statistical analyses can be conducted; (4) multiple comparison correction to determine the significance of the statistical analysis results. Detailed herein, this pipeline has been applied to the corpus callosum in Alzheimer's disease (AD) with significantly decreased FA values and increased trace values, both globally and locally, being detected in patients with AD when compared to normal aging populations. A subdivision of the corpus callosum in both hemispheres revealed that the AD pathology primarily affects the body and splenium of the corpus callosum. Validation analyses and two multiple comparison correction strategies are provided. Hum Brain Mapp 38:1875-1893, 2017. © 2017 Wiley Periodicals, Inc.
authors.affiliation: Sun Yat-sen University-Carnegie Mellon University (SYSU-CMU) Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China.|Sun Yat-sen University-Carnegie Mellon University (SYSU-CMU) Shunde International Joint Research Institute, Shunde, Guangdong, China.|School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, Guangdong, China.
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Tang
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Qin
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
authors.forename: Wenzhen
authors.initials: W
authors.lastname: Zhu
authors.affiliation: Center for Imaging Science, Johns Hopkins University, Baltimore, Maryland.|Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland.|Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
authors.forename: Michael I
authors.initials: MI
authors.lastname: Miller
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000473:pathology*; D016880:Anisotropy; D001931:Brain Mapping; D060825:Cognitive Dysfunction / Q000000981:diagnostic imaging / Q000473:pathology; D003337:Corpus Callosum / Q000000981:diagnostic imaging* / Q000473:pathology; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D066127:White Matter / Q000000981:diagnostic imaging* / Q000473:pathology
keywords: diffusion tensor imaging; microstructural integrity; morphometry; multiple comparison correction; statistical mapping; surface map; white matter tract