Intercenter Differences in Diffusion Tensor MRI Acquisition

Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Scientific Institute and University Hospital San Raffaele, 20132 Milan, Italy.
Journal of Magnetic Resonance Imaging (Impact Factor: 3.21). 06/2010; 31(6):1458-68. DOI: 10.1002/jmri.22186
Source: PubMed


To assess the effect on diffusion tensor (DT) magnetic resonance imaging (MRI) of acquiring data with different scanners.
Forty-four healthy controls and 36 multiple sclerosis patients with low disability were studied using eight MR scanners with acquisition protocols that were as close to a standard protocol as possible. Between 7 and 13 subjects were studied in each center. Region-of-interest (ROI) and histogram-based analyses of fractional anisotropy (FA), axial (D(ax)), radial (D(rad)), and mean diffusivity (MD) were performed. The influence of variables such as the acquisition center and the control/patient group was determined with an analysis of variance (ANOVA) test.
The patient/control group explained approximately 25% of data variability of FA and D(rad) from midsagittal corpus callosum (CC) ROIs. Global FA, MD, and D(rad) in the white matter differentiated patients from controls, but with lower discriminatory power than for the CC. In the gray matter, MD discriminated patients from controls (30% of variability explained by group vs. 17% by center).
Significant variability of DT-MRI data can be attributed to the acquisition center, even when a standardized protocol is used. The use of appropriate segmentation methods and statistical models allows DT-derived metrics to differentiate patients from healthy controls.

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    • "Use of a global scaling factor was shown to reduce the inter-site CoV to the range of intra-site CoV (Vollmar et al., 2010). Another study (Pagani et al., 2010) demonstrated that statistical adjustments for scanner manufacturer, field strength and number of diffusion-weighted directions was sufficient for discrimination of patients from healthy controls in a cross-sectional study. It has also been shown that weighing diffusion metrics based on their within scan variability, as evaluated by wild bootstrap analysis, can reduce the intra-and inter-site variability in phantom and human data (Zhu et al., 2011). "
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    ABSTRACT: Diffusion tensor imaging (DTI) measures are commonly used as imaging markers to investigate individual differences in relation to behavioral and health-related characteristics. However, the ability to detect reliable associations in cross-sectional or longitudinal studies is limited by the reliability of the diffusion measures. Several studies have examined reliability of diffusion measures within (i.e. intra-site) and across (i.e. inter-site) scanners with mixed results. Our study compares the test-retest reliability of diffusion measures within and across scanners and field strengths in cognitively normal older adults with a follow-up interval less than 2.25 years. Intra-class correlation (ICC) and coefficient of variation (CoV) of fractional anisotropy (FA) and mean diffusivity (MD) were evaluated in sixteen white matter and twenty-six gray matter bilateral regions. The ICC for intra-site reliability (0.32 to 0.96 for FA and 0.18 to 0.95 for MD in white matter regions; 0.27 to 0.89 for MD and 0.03 to 0.79 for FA in gray matter regions) and inter-site reliability (0.28 to 0.95 for FA in white matter regions, 0.02 to 0.86 for MD in gray matter regions) with longer follow-up intervals were similar to earlier studies using shorter follow-up intervals. The reliability of across field strengths comparisons was lower than intra- and inter-site reliability. Within and across scanner comparisons showed that diffusion measures were more stable in larger white matter regions (>1500 mm(3)). For gray matter regions, the MD measure showed stability in specific regions and was not dependent on region size. Linear correction factor estimated from cross-sectional or longitudinal data improved the reliability across field strengths. Our findings indicate that investigations relating diffusion measures to external variables must consider variable reliability across the distinct regions of interest and that correction factors can be used to improve consistency of measurement across field strengths. An important result of this work is that inter-scanner and field strength effects can be partially mitigated with linear correction factors specific to regions of interest. These data-driven linear correction techniques can be applied in cross-sectional or longitudinal studies. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 07/2015; 119. DOI:10.1016/j.neuroimage.2015.06.078 · 6.36 Impact Factor
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    • "Obtaining reproducible quantitative results from DTI data is not trivial given that the final results are sensitive to a large number of acquisition and analysis factors (Jones and Cercignani, 2010). Various aspects of DTI reproducibility have been investigated , including basic reproducibility measures of different populations (Bonekamp et al., 2007; Ciccarelli et al., 2003; Heiervang et al., 2006; Marenco et al., 2006), evaluation of the effects of region of interest (ROI) drawing protocols (Wakana et al., 2007), effects of signal averaging (Farrell et al., 2007), head motion effects (Yendiki et al., 2013), as well as the effects of various acquisition parameters like for example b-value (Bisdas et al., 2008), diffusion weighting scheme (Landman et al., 2007; Vaessen et al., 2010), voxel size (Papinutto et al., 2013), and MRI scanner effects (Brander et al., 2010; Pagani et al., 2010; Pfefferbaum et al., 2003; Vollmar et al., 2010; White et al., 2011; Zhu et al., 2011). However, despite the wide use of DTI as a tool to assess white matter integrity in 3 T MRI studies, across-session test–retest reliability of diffusion measures on subjects in stable conditions has not been thoroughly investigated using multiple MRI systems. "
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    ABSTRACT: 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 3T 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 3T 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 (2x2x2 mm(3), b=700s/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 (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 range 2-4% 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 protocol used are appropriate for multi-site experimental scenarios.
    NeuroImage 07/2014; 101C. DOI:10.1016/j.neuroimage.2014.06.075 · 6.36 Impact Factor
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    • "Such large variations were not initially expected since water diffusion as measured by MRI is mainly a physical characteristic of the tissue itself that should not be related to MR properties. However, significant effects related to the use of different scanners and/or imaging sequences on diffusion measures were previously reported in a small number of healthy volunteers[25]–[28]. These studies showed that ADC measures are significantly influenced by more or less important changes of hardware often performed over a long period in a clinical setting. "
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    ABSTRACT: Diffusion tensor imaging (DTI) histogram metrics are correlated with clinical parameters in cerebral small vessel diseases (cSVD). Whether ADC histogram parameters derived from simple diffusion weighted imaging (DWI) can provide relevant markers for long term studies of cSVD remains unknown. CADASIL patients were evaluated by DWI and DTI in a large cohort study overa6-year period. ADC histogram parameters were compared to those derived from mean diffusivity (MD) histograms in 280 patients using intra-class correlation and Bland-Altman plots. Impact of image corrections applied to ADC maps was assessed and a mixed effect model was used for analyzing the effects of scanner upgrades. The results showed that ADC histogram parameters are strongly correlated to MD histogram parameters and that image corrections have only limited influence on these results. Unexpectedly, scanner upgrades were found to have major effects on diffusion measures with DWI or DTI that can be even larger than those related to patients' characteristics. These data support that ADC histograms from daily used DWI can provide relevant parameters for assessing cSVD, but the variability related to scanner upgrades as regularly performed in clinical centers should be determined precisely for longitudinal and multicentric studies using diffusion MRI in cSVD.
    PLoS ONE 05/2014; 9(5):e97173. DOI:10.1371/journal.pone.0097173 · 3.23 Impact Factor
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