Prospective multi-centre Voxel Based Morphometry study employing scanner specific segmentations: Procedure development using CaliBrain structural MRI data

Abstract

BackgroundStructural Magnetic Resonance Imaging (sMRI) of the brain is employed in the assessment of a wide range of neuropsychiatric disorders. In order to improve statistical power in such studies it is desirable to pool scanning resources from multiple centres. The CaliBrain project was designed to provide for an assessment of scanner differences at three centres in Scotland, and to assess the practicality of pooling scans from multiple-centres.MethodsWe scanned healthy subjects twice on each of the 3 scanners in the CaliBrain project with T1-weighted sequences. The tissue classifier supplied within the Statistical Parametric Mapping (SPM5) application was used to map the grey and white tissue for each scan. We were thus able to assess within scanner variability and between scanner differences. We have sought to correct for between scanner differences by adjusting the probability mappings of tissue occupancy (tissue priors) used in SPM5 for tissue classification. The adjustment procedure resulted in separate sets of tissue priors being developed for each scanner and we refer to these as scanner specific priors.ResultsVoxel Based Morphometry (VBM) analyses and metric tests indicated that the use of scanner specific priors reduced tissue classification differences between scanners. However, the metric results also demonstrated that the between scanner differences were not reduced to the level of within scanner variability, the ideal for scanner harmonisation.ConclusionOur results indicate the development of scanner specific priors for SPM can assist in pooling of scan resources from different research centres. This can facilitate improvements in the statistical power of quantitative brain imaging studies.

The neuro/PsyGRID calibration experiment

“…Analysis of variance modeled within-and between-center factors, with within-center reliability being relatively much greater, and enumerated the between-center differences in a number of key metrics. Other calibration studies have been reported [Costafreda et al, 2007;Deoni et al, 2008;Gountouna et al, 2009;Moorhead et al, 2009;Suckling et al, 2008], with similar outcomes from comparable analyses.…”

Effect of scanner in longitudinal diffusion tensor imaging studies

“…In volumetric studies, several groups have analyzed the effects of different scanners on cross-sectional or longitudinal morphometric results [Briellmann et al, 2001;Dickerson et al, 2008;Ewers et al, 2006;Fennema-Notestine et al, 2007;Fjell et al, 2009;Han et al, 2006;Ho et al, 2010;Huppertz et al, 2010;Jovicich et al, 2009;Kruggel et al, 2010;Meda et al, 2008;Moorhead et al, 2009;Pardoe et al, 2008;Schnack et al, 2004;Stonnington et al, 2008;Walhovd et al, 2009]. Usually, inter-scanner variability of volumetric measures is larger than intra-scanner variability.…”

HIV Distal Neuropathic Pain Is Associated with Smaller Ventral Posterior Cingulate Cortex

“…Since we did not collect skin biopsies, we cannot confirm that the DNP individuals without signs of neuropathy have HIV small fiber peripheral neuropathy. Finally, using brain structural MRI images from different scanners may introduce systematic noise [54][55][56][57] which could have contributed to why brain volumes for cortical pain processing regions (such as the anterior cingulate cortex, insula cortex, and prefrontal cortex) were not smaller for individuals with DNP compared to individuals without DNP.…”

“…Thus, their inclusion in the model may in fact help to increase the power of our comparisons of interest. To control for bias resulting from inter-scanner variability [54][55][56][57], we controlled for scanner as a covariate in the adjusted analysis.…”