Multi-site voxel-based morphometry — Not quite there yet

Focke, Niels K.; Helms, Gunther; Kaspar, Susanne; Diederich, Christine; Toth, Vera; Dechent, Peter; Mohr, Alexander T.; Paulus, Walter

doi:10.1016/j.neuroimage.2011.02.029

Cited by 89 publications

(77 citation statements)

References 28 publications

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“…Third, participants were scanned using 2 different scanners. Although the reliability of multiscanner VBM has proven to be good when adding scanner as a covariate, 45,46 including scan site as a covariate may have lowered the statistical power of detecting between-group differences. Therefore, we repeated the analyses without including any covariates, which did not change the results.…”

Section: Limitationsmentioning

confidence: 99%

Grey matter, an endophenotype for schizophrenia? A voxel-based morphometry study in siblings of patients with schizophrenia

Velde

Gromann

Swart

et al. 2015

jpn

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IntroductionThe liability for schizophrenia is heritable, 1 with siblings of patients with schizophrenia being at increased risk (about a 10-fold increase) for the disorder.2 Structural brain abnormalities in patients with schizophrenia have been consistently reported. For example, patients show reduced grey matter in the frontal, temporal and thalamic regions (see the meta-analyses by Fornito and colleagues 3 and Haijma and colleagues 4 ). Previous studies have suggested that part of these grey matter abnormalities might not be related to the illness state, but rather to the genetic risk, and have proposed these abnormalities to be an endophenotype for schizophrenia. [5][6][7] Consistent with this proposal, 4 recent meta-analyses reported grey matter reductions in relatives of patients compared with controls. [8][9][10][11] Although the aims of these meta-analyses differed, all of them compared individuals at genetic high risk with controls. However, the results of these meta-analyses differed substantially, and the thresholds applied were rather low (p < 0.05, p < 0.005 and p < 0.001, uncorrected). Two meta-analyses showed grey matter reductions in relatives compared with controls in the lentiform nucleus 9,11 and medial prefrontal cortex, 9 whereas another meta-analysis reported higher levels of grey matter in the medial prefrontal cortex in siblings.11 Furthermore, reductions in the parahippompal gyrus and anterior cingulate have been reported, 8 while others reported reductions in the amygdala and hippocampus.10 Besides these contradictory reports, the 3 largest voxel-based morphometry (VBM) studies in siblings 12-14 did not report any significant differences in whole brain grey matter between siblings and controls.In a recent review, several hypotheses were proposed to explain these differences. 5 The first explanation was that many studies included participants who were already past the critical ages for schizophrenia developing. The onset of Background: Grey matter, both volume and concentration, has been proposed as an endophenotype for schizophrenia given a number of reports of grey matter abnormalities in relatives of patients with schizophrenia. However, previous studies on grey matter abnormalities in relatives have produced inconsistent results. The aim of the present study was to examine grey matter differences between controls and siblings of patients with schizophrenia and to examine whether the age, genetic loading or subclinical psychotic symptoms of selected individuals could explain the previously reported inconsistencies. Methods: We compared the grey matter volume and grey matter concentration of healthy siblings of patients with schizophrenia and healthy controls matched for age, sex and education using voxel-based morphometry (VBM). Furthermore, we selected subsamples based on age (< 30 yr), genetic loading and subclinical psychotic symptoms to examine whether this would lead to different results. Results: We included 89 siblings and 69 controls in our study. The results showed that sibl...

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Section: Limitationsmentioning

confidence: 99%

Grey matter, an endophenotype for schizophrenia? A voxel-based morphometry study in siblings of patients with schizophrenia

Velde

Gromann

Swart

et al. 2015

jpn

View full text Add to dashboard Cite

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“…As with ROI analyses, for subtle genetic effects there is therefore a need to pool voxelwise TBM data from multiple sites to achieve power and adequate sample sizes. However, it is not immediately clear how to relate these features and spatially normalize data across multiple sites, imaging acquisitions and datasets [8][9][10]. Inaccurate alignment across sites may further limit the power to detect localized effects.…”

Section: Introductionmentioning

confidence: 99%

Comparison of template registration methods for multi-site meta-analysis of brain morphometry

et al. 2016

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Neuroimaging consortia such as ENIGMA can significantly improve power to discover factors that affect the human brain by pooling statistical inferences across cohorts to draw generalized conclusions from populations around the world. Voxelwise analyses such as tensor-based morphometry also allow an unbiased search for effects throughout the brain. Even so, such consortium-based analyses are limited by a lack of high-powered methods to harmonize voxelwise information across study populations and scanners. While the simplest approach may be to map all images to a single standard space, the benefits of cohort-specific templates have long been established. Here we studied methods to pool voxel-wise data across sites using templates customized for each cohort but providing a meaningful common space across all studies for voxelwise comparisons. As non-linear 3D MRI registrations represent mappings between images at millimeter resolution, we need to consider the reliability of these mappings. To evaluate these mappings, we calculated test-retest statistics on the volumetric maps of expansion and contraction. Further, we created study-specific brain templates for ten T1-weighted MRI datasets, and a common space from four study-specific templates. We evaluated the efficacy of using a two-step registration framework versus a single standard space. We found that the two-step framework more reliably mapped subjects to a common space.

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“…Higher field strength also results in increased magnetic susceptibility artifacts (Bernstein et al, 2006). The brainstem is particularly prone to these artifacts (Focke et al, 2011), which can cause geometric distortions, signal loss as well as influence the effective excitation field and flip angle, thus affecting contrast in T 1 -weighted images (Truong et al, 2006). Inversion time is typically chosen in line with T 1 -relaxation (and hence field strength) as it determines the magnetization before excitation in each tissue, and thus the T 1 -contrast.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, even in single-site studies a scanner will likely undergo hardware exchanges or software upgrades over time, making it difficult to keep the status consistent over the period of a longer study. Previous work revealed scanning effects resulting from a number of factors, including static magnetic field inhomogeneity, imaging gradient nonlinearity and difference in subject positioning (Focke et al, 2011; Jovicich et al, 2006; Littmann et al, 2006; Vovk et al, 2007). On the other hand, it is also noted that these scanning effects may be orthogonal to and not necessarily interfere with the true effect of interest (Segall et al, 2009; Stonnington et al, 2008), or that statistical modeling (Fennema-Notestine et al, 2007) and scanner-specific segmentation (Moorhead et al, 2009) will ameliorate the scanning effects.…”

Section: Introductionmentioning

confidence: 99%

Exploration of scanning effects in multi-site structural MRI studies

Chen

Liu

Calhoun

et al. 2014

Journal of Neuroscience Methods

120

107

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Background Pooling of multi-site MRI data is often necessary when a large cohort is desired. However, different scanning platforms can introduce systematic differences which confound true effects of interest. One may reduce multi-site bias by calibrating pivotal scanning parameters, or include them as covariates to improve the data integrity. New method In the present study we use a source-based morphometry (SBM) model to explore scanning effects in multi-site sMRI studies and develop a data-driven correction. Specifically, independent components are extracted from the data and investigated for associations with scanning parameters to assess the influence. The identified scanning-related components can be eliminated from the original data for correction. Results A small set of SBM components captured most of the variance associated with the scanning differences. In a dataset of 1460 healthy subjects, pronounced and independent scanning effects were observed in brainstem and thalamus, associated with magnetic field strength-inversion time and RF-receiving coil. A second study with 110 schizophrenia patients and 124 healthy controls demonstrated that scanning effects can be effectively corrected with the SBM approach. Comparison with existing method(s) Both SBM and GLM correction appeared to effectively eliminate the scanning effects. Meanwhile, the SBM-corrected data yielded a more significant patient versus control group difference and less questionable findings. Conclusions It is important to calibrate scanning settings and completely examine individual parameters for the control of confounding effects in multi-site sMRI studies. Both GLM and SBM correction can reduce scanning effects, though SBM’s data-driven nature provides additional flexibility and is better able to handle collinear effects.

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Multi-site voxel-based morphometry — Not quite there yet

Cited by 89 publications

References 28 publications

Grey matter, an endophenotype for schizophrenia? A voxel-based morphometry study in siblings of patients with schizophrenia

Grey matter, an endophenotype for schizophrenia? A voxel-based morphometry study in siblings of patients with schizophrenia

Comparison of template registration methods for multi-site meta-analysis of brain morphometry

Exploration of scanning effects in multi-site structural MRI studies

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