The voxel differences of fractional anisotropy (FA), λ1, λ2, and λ3 values between mild HI group and control group were analyzed in preterm and full term neonates respectively. Forty-one full term neonates (24 normal controls and 17 with mild HI injury) and 31 preterm neonates (20 normal controls and 11 with mild HI injury) underwent T1 weighted imaging, T2 weighted imaging and diffusion tensor imaging (DTI) within 28 days after birth. ![]() Each subject's aligned FA data was then projected onto this skeleton and the resulting data fed into voxelwise cross-subject statistics.The aim of this study is to employ tract-based spatial statistics (TBSS) to analyze the voxel-wise differences in DTI parameters between normal and mild hypoxic-ischemic (HI) neonatal brains. Next, the mean FA image was created and thinned to create a mean FA skeleton which represents the centres of all tracts common to the group. All subjects' FA data were then aligned into a common space using the nonlinear registration tool FNIRT, which uses a b-spline representation of the registration warp field. First, FA images were created by fitting a tensor model to the raw diffusion data using FDT, and then brain-extracted using BET. More detailed summary text: "Voxelwise statistical analysis of the FA data was carried out using TBSS (Tract-Based Spatial Statistics, ), part of FSL. TBSS projects all subjects' FA data onto a mean FA tract skeleton, before applying voxelwise cross-subject statistics." For your convenience, we provide example text (short and more detailed versions), which you are welcome to use in your methods description.īrief summary text: "Voxelwise statistical analysis of the FA data was carried out using TBSS (Tract-Based Spatial Statistics, ), part of FSL. If you use TBSS in your research, please make sure that you reference at least the first of the articles listed below, and ideally the complete list. TBSS aims to improve the sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies. TBSS aims to solve these issues via a) carefully tuned nonlinear registration, followed by b) projection onto an alignment-invariant tract representation (the "mean FA skeleton"). Furthermore, the arbitrariness of the choice of spatial smoothing extent has not been resolved. However, optimal analysis is compromised by the use of standard registration algorithms there has not been a satisfactory solution to the question of how to align FA images from multiple subjects in a way that allows for valid conclusions to be drawn from the subsequent voxelwise analysis. ![]() Many imaging studies are starting to use FA images in voxelwise statistical analyses, in order to localise brain changes related to development, degeneration and disease. One of the measures most commonly derived from diffusion data is fractional anisotropy (FA), which quantifies how strongly directional the local tract structure is. ![]() There is much recent interest in using magnetic resonance diffusion imaging to provide information about anatomical connectivity in the brain, by measuring the anisotropic diffusion of water in white matter tracts. Research Overview - Tract-Based Spatial Statistics ![]() Research Overview - Tract-Based Spatial Statistics.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |