Dataset Information

Longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging.

ABSTRACT: Relatively little is known about reliability of longitudinal diffusion-tensor imaging (DTI) measurements despite growing interest in using DTI to track change in white matter structure. The purpose of this study is to quantify within- and between session scan-rescan reliability of DTI-derived measures that are commonly used to describe the characteristics of neural white matter in the context of neural plasticity research. DTI data were acquired from 16 cognitively healthy older adults (mean age 68.4). We used the Tract-Based Spatial Statistics (TBSS) approach implemented in FSL, evaluating how different DTI preprocessing choices affect reliability indices. Test-Retest reliability, quantified as ICC averaged across the voxels of the TBSS skeleton, ranged from 0.524 to 0.798 depending on the specific DTI-derived measure and the applied preprocessing steps. The two main preprocessing steps that we found to improve TBSS reliability were (a) the use of a common individual template and (b) smoothing DTI data using a 1-voxel median filter. Overall our data indicate that small choices in the preprocessing pipeline have a significant effect on test-retest reliability, therefore influencing the power to detect change within a longitudinal study. Furthermore, differences in the data processing pipeline limit the comparability of results across studies.

SUBMITTER: Madhyastha T

PROVIDER: S-EPMC6869410 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging.

Madhyastha Tara T Mérillat Susan S Hirsiger Sarah S Bezzola Ladina L Liem Franziskus F Grabowski Thomas T Jäncke Lutz L

Human brain mapping 20140403 9

Relatively little is known about reliability of longitudinal diffusion-tensor imaging (DTI) measurements despite growing interest in using DTI to track change in white matter structure. The purpose of this study is to quantify within- and between session scan-rescan reliability of DTI-derived measures that are commonly used to describe the characteristics of neural white matter in the context of neural plasticity research. DTI data were acquired from 16 cognitively healthy older adults (mean age ...[more]

PMID: 24700773

Similar Datasets

Project description:Although often clinically indistinguishable in the early stages, Parkinson's disease (PD), Multiple System Atrophy (MSA) and Progressive Supranuclear Palsy (PSP) have distinct neuropathological changes. The aim of the current study was to identify white matter tract neurodegeneration characteristic of each of the three syndromes. Tract-based spatial statistics (TBSS) was used to perform a whole-brain automated analysis of diffusion tensor imaging (DTI) data to compare differences in fractional anisotropy (FA) and mean diffusivity (MD) between the three clinical groups and healthy control subjects. Further analyses were conducted to assess the relationship between these putative indices of white matter microstructure and clinical measures of disease severity and symptoms. In PSP, relative to controls, changes in DTI indices consistent with white matter tract degeneration were identified in the corpus callosum, corona radiata, corticospinal tract, superior longitudinal fasciculus, anterior thalamic radiation, superior cerebellar peduncle, medial lemniscus, retrolenticular and anterior limb of the internal capsule, cerebral peduncle and external capsule bilaterally, as well as the left posterior limb of the internal capsule and the right posterior thalamic radiation. MSA patients also displayed differences in the body of the corpus callosum corticospinal tract, cerebellar peduncle, medial lemniscus, anterior and superior corona radiata, posterior limb of the internal capsule external capsule and cerebral peduncle bilaterally, as well as the left anterior limb of the internal capsule and the left anterior thalamic radiation. No significant white matter abnormalities were observed in the PD group. Across groups, MD correlated positively with disease severity in all major white matter tracts. These results show widespread changes in white matter tracts in both PSP and MSA patients, even at a mid-point in the disease process, which are not found in patients with PD.

Project description:BACKGROUND AND PURPOSE:Patients with type 2 diabetes mellitus have considerably higher risk of developing cognitive impairment and dementia. WM changes in these patients have been reported. Our aim was to demonstrate that gradual and continuous WM change and the associated cognitive decline in patients with type 2 diabetes mellitus can be captured by DTI parameters, which can be used to complement neuropsychological test scores in identifying patients with type 2 diabetes mellitus with and without mild cognitive impairment. MATERIALS AND METHODS:Forty-two patients with type 2 diabetes mellitus, divided into a group with mild cognitive impairment (n = 20) and a group with normal cognition (n = 22), were enrolled with age-, sex-, and education-matched healthy controls (n = 26). 3T DTI followed by Tract-Based Spatial Statistics analysis was used to investigate the differences in fractional anisotropy, mean diffusivity, axial diffusivity (?1), and radial diffusivity (?23) among the groups. A receiver operating characteristic analysis assessed the performance of DTI parameters for separating the 2 groups with type 2 diabetes mellitus. RESULTS:The whole-brain Tract-Based Spatial Statistics analysis revealed that 7.3% and 24.9% of the WM exhibited decreased fractional anisotropy and increased mean diffusivity (P < .05), respectively, between the diabetes mellitus with mild cognitive impairment and the diabetes mellitus with normal cognition groups, while considerably larger WM regions showed fractional anisotropy (36.6%) and mean diffusivity (58.8%) changes between the diabetes mellitus with mild cognitive impairment and the healthy control groups. These changes were caused primarily by an elevated radial diffusivity observed in the patients with diabetes mellitus with mild cognitive impairment. Radial diffusivity also exhibited subtle but statistically significant changes between the diabetes mellitus with normal cognition and the healthy control groups. Analyses on individual fiber tracts showed pronounced fractional anisotropy reduction and mean diffusivity elevation in regions related to cognitive functions. The receiver operating characteristic analysis on the right cingulum (hippocampus) showed that fractional anisotropy produced a larger area under the curve (0.832) than mean diffusivity (0.753) for separating mild cognitive impairment from normal cognition among patients with type 2 diabetes mellitus. When fractional anisotropy was combined with mean diffusivity, the area under the curve was further improved to 0.857. CONCLUSIONS:DTI parameters can show a substantial difference between patients with type 2 diabetes mellitus with and without mild cognitive impairment, suggesting their potential use as an imaging marker for detecting cognitive decline in patients with type 2 diabetes mellitus. More important, DTI parameters may capture gradual and continuous WM changes that can be associated with early stages of cognitive decline in patients with type 2 diabetes mellitus before they can be diagnosed clinically by using conventional neuropsychological tests.

Project description:BackgroundThe core symptoms of autism spectrum disorder (ASD) are widely theorized to result from altered brain connectivity. Diffusion-weighted magnetic resonance imaging (DWI) has been a versatile method for investigating underlying microstructural properties of white matter (WM) in ASD. Despite phenotypic and etiological heterogeneity, DWI studies in majority male samples of older children, adolescents, and adults with ASD have largely reported findings of decreased fractional anisotropy (FA) across several commissural, projection, and association fiber tracts. However, studies in preschool-aged children (i.e., < 30-40 months) suggest individuals with ASD have increased measures of WM FA earlier in development.MethodsWe analyzed 127 individuals with ASD (85♂, 42♀) and 54 typically developing (TD) controls (42♂, 26♀), aged 25.1-49.6 months. Voxel-wise effects of ASD diagnosis, sex, age, and their interaction on DWI measures of FA, mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were investigated using tract-based spatial statistics (TBSS) while controlling mean absolute and relative motion.ResultsCompared to TD controls, males and females with ASD had significantly increased measures of FA in eight clusters (threshold-free cluster enhancement p < 0.05) that incorporated several WM tracts including regions of the genu, body, and splenium of the corpus callosum, inferior frontal-occipital fasciculi, inferior and superior longitudinal fasciculi, middle and superior cerebellar peduncles, and corticospinal tract. A diagnosis by sex interaction was observed in measures of AD across six significant clusters incorporating areas of the body, genu, and splenium of the corpus collosum. In these tracts, females with ASD showed increased AD compared to TD females, while males with ASD showed decreased AD compared to TD males.ConclusionsThe current findings support growing evidence that preschool-aged children with ASD have atypical measures of WM microstructure that appear to differ in directionality from alterations observed in older individuals with the condition. To our knowledge, this study represents the largest sample of preschool-aged females with ASD to be evaluated using DWI. Microstructural differences associated with ASD largely overlapped between sexes. However, differential relationships of AD measures indicate that sex likely modulates ASD neuroanatomical phenotypes. Further longitudinal study is needed to confirm and quantify the developmental relationship of WM structure in ASD.

Dataset Information

Longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging.

Publications

Longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets