Multicenter stability of diffusion tensor imaging measures: A European clinical and physical phantom study (original) (raw)
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NeuroImage, 2014
Brain diffusion tensor imaging Reproducibility Reliability Tract-based spatial statistics Multi-center Multi-site MRI Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3 T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3 T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm 3 , b = 700 s/mm 2 , 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.
Neurobiology of Aging, 2011
We aimed to explore the changes in fractional anisotropy (FA) in subjects with mild cognitive impairment (MCI) and Alzheimer's disease (AD) by analyzing diffusion tensor imaging (DTI) data using the Tract-Based Spatial Statistics (TBSS). DTI data were collected from 17 AD patients, 27 MCI subjects and 19 healthy controls. Voxel-based analysis with TBSS was used to compare FA among the three groups. Additionally, guided by TBSS findings, a region of interest (ROI)-based analysis along the TBSS skeleton was performed on group-level and the accuracy of the method was assessed by the back-projection of ROIs to the native space FA. Neurofiber tracts with decreased FA included: the parahippocampal white matter, cingulum, uncinate fasciculus, inferior and superior longitudinal fasciculus, corpus callosum, fornix, tracts in brain stem, and cerebellar tracts. Quantitative ROI-analysis further demonstrated the significant decrease on FA values in AD patients relative to controls whereas FA values of MCI patients were found in between the controls and AD patients. We conclude that TBSS is a promising method in examining the degeneration of neurofiber tracts in MCI and AD patients.
Korean Journal of Radiology
Objective: To evaluate the inter-vendor and inter-session reliability of diffusion tensor imaging (DTI) and relevant parameters. Materials and Methods: This prospective study included 10 healthy subjects (5 women and 5 men; age range, 25−33 years). Each subject was scanned twice using 3T magnetic resonance scanners from three different vendors at two different sites. A voxel-wise statistical analysis of diffusion data was performed using Tract-Based Spatial Statistics. Fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) values were calculated for each brain voxel using FMRIB's Diffusion Toolbox. Results: A repeated measures analysis of variance revealed that there were no significant differences in FA values across the vendors or between sessions; however, there were significant differences in MD values between the vendors (p = 0.020). Although there were no significant differences in inter-session MD and inter-session/inter-vendor RD values, a significant group x factor interaction revealed differences in MD and RD values between the 1st and 2nd sessions conducted by the vendors (p = 0.004 and 0.006, respectively). Conclusion: Although FA values exhibited good inter-vendor and inter-session reliability, MD and RD values did not show consistent results. Researchers using DTI should be aware of these limitations, especially when implementing DTI in multicenter studies.
Regional distribution of measurement error in diffusion tensor imaging
Psychiatry Research: Neuroimaging, 2006
The characterization of measurement error is critical in assessing the significance of diffusion tensor imaging (DTI) findings in longitudinal and cohort studies of psychiatric disorders. We studied 20 healthy volunteers each one scanned twice (average interval between scans of 51 ± 46.8 days) with a single shot echo planar DTI technique. Inter-session variability for fractional anisotropy (FA) and Trace (D) was represented as absolute variation (standard deviation within subjects: SDw), percent coefficient of variation (CV) and intra-class correlation coefficient (ICC). The values from the two sessions were compared for statistical significance with repeated measures ANOVA or a nonparametric equivalent of a paired t-test. The results show good reproducibility for both FA and Trace (CVs below 10% and ICCs at or above 0.70 in most regions of interest) and evidence of systematic global changes in Trace between scans. The regional distribution of reproducibility described here has implications for interpretation of regional findings and for rigorous pre-processing. The regional distribution of reproducibility measures was different for SDw, CV and ICC. Each one of these measures reveals complementary information that needs to be taken into consideration when performing statistical operations on groups of DTI images.
Magnetic resonance in medicine, 2017
In diffusion MRI (dMRI), fractional anisotropy derived from the single-tensor model (FA(DTI) ) is the most widely used metric to characterize white matter (WM) microarchitecture, despite known limitations in regions with crossing fibers. Due to time constraints when scanning patients in clinical settings, high angular resolution diffusion imaging acquisition protocols, often used to overcome these limitations, are still rare in clinical population studies. However, the tensor distribution function (TDF) may be used to model multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors. We compared the ability of standard FA(DTI) and TDF-derived FA (FA(TDF) ), calculated from a range of dMRI angular resolutions (41, 30, 15, and 7 gradient directions), to profile WM deficits in 251 individuals from the Alzheimer's Disease Neuroimaging Initiative and to detect associations with 1) Alzheimer's disease diagnosis, 2) Clinical Dementia Ratin...
Validation of the anisotropy index ellipsoidal area ratio in diffusion tensor imaging
Magnetic Resonance Imaging, 2010
A new diffusion anisotropy index, ellipsoidal area ratio (EAR), was described recently and proved to be less noise-sensitive than fractional anisotropy (FA) by theory and simulation. Here we show that EAR has higher signal-to-noise ratios than FA in average diffusion tensor imaging data from 40 normal subjects. EAR was also more sensitive than FA in detecting white matter abnormalities in a patient with widespread diffuse axonal injury. Monte Carlo simulation showed that EAR's mean values are more biased by noise than FA when anisotropy is small, both for single fiber tracts and when fiber tracts cross. However, the improved signal-to-noise ratio of EAR relative to FA suggests that EAR may be a superior measure of anisotropy both in quantifying both deep white matter with relatively uniform fiber tracts and pericortical white matter structure with relatively low anisotropy and fiber crossings.
The Neuroradiology Journal, 2012
This study evaluated the damage to the extensive range of white matter tracts in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Thirty-four patients with AD (mean age 71.5 yrs, MMSE 17.6), 23 patients with MCI (mean age 66 yrs, MMSE 27.4) and 15 normal controls (mean age 69 yrs, MMSE 29.8) were enrolled. Diffusion tensor imaging (DTI) was performed in 25 directions on 1.5 T MR scanner. Fractional anisotropy (FA) values were obtained with a small ROI method in several association tracts including posterior cingulum fibers, in commissural tracts (genu and splenium of corpus callosum) and projection tracts (middle cerebellar peduncles and posterior limbs of internal capsules). In MCI significant reductions of FA were found in the inferior longitudinal fascicles, left superior longitudinal fascicle and posterior cingulum fibers compared to normal controls. In AD significantly decreased FA values were detected in the same fascicles as in MCI and additiona...
대한자기공명의과학회지, 2012
Purpose : To evaluate white matter abnormalities on diffusion tensor imaging (DTI) in patients with mild Alzheimer disease (AD) and mild cognitive impairment (MCI), using tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM). Materials and Methods: DTI was performed in 21 patients with mild AD, in 13 with MCI and in 16 old healthy subjects. A fractional anisotropy (FA) map was generated for each participant and processed for voxel-based comparisons among the three groups using TBSS. For comparison, DTI data was processed using the VBM method, also. Results: TBSS showed that FA was significantly lower in the AD than in the old healthy group in the bilateral anterior and right posterior corona radiata, the posterior thalamic radiation, the right superior longitudinal fasciculus, the body of the corpus callosum, and the right precuneus gyrus. VBM identified additional areas of reduced FA, including both uncinates, the left parahippocampal white matter, and the right cingulum. There were no significant differences in FA between the AD and MCI groups, or between the MCI and old healthy groups. Conclusion: TBSS showed multifocal abnormalities in white matter integrity in patients with AD compared with old healthy group. VBM could detect more white matter lesions than TBSS, but with increased artifacts.
European Radiology, 2006
Fractional anisotropy and mean diffusivity measurements on normal human brain: comparison between low-and high-resolution diffusion tensor imaging sequences Abstract Non-invasive in vivo visualization of white matter fiber tracts is currently feasible by means of diffusion tensor imaging (DTI) techniques. DTI-derived metrics, like fractional anisotropy (FA) and mean diffusivity (MD), have the potential to improve tissue characterization. Technical optimization of diffusion tensor sequences, including signal-to-noise ratio and spatial resolution, was performed for 20 normal subjects. Highand low-resolution DTI sequences were applied on all subjects and FA, MD parametric maps were reconstructed for both protocols. Voxelbased statistical analysis revealed regions with significantly different FA and MD values between the two sequences, while the same type of analysis was performed to illustrate regions with significantly different signal-to-noise ratio. In conclusion, optimized DTI sequences may be applied routinely in clinical practice with a standard MR scanner, while accurate quantification of FA and MD may improve lesion characterization.