A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS).

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages.

Improving data availability for brain image biobanking in healthy subjects: Practice-based suggestions from an international multidisciplinary working group.

Brain imaging is now ubiquitous in clinical practice and research. The case for bringing together large amounts of image data from well-characterised healthy subjects and those with a range of common brain diseases across the life course is now compelling. This report follows a meeting of international experts from multiple disciplines, all interested in brain image biobanking. The meeting included neuroimaging experts (clinical and non-clinical), computer scientists, epidemiologists, clinicians, ethicists, and lawyers involved in creating brain image banks. The meeting followed a structured format to discuss current and emerging brain image banks; applications such as atlases; conceptual and statistical problems (e.g. defining 'normality'); legal, ethical and technological issues (e.g. consents, potential for data linkage, data security, harmonisation, data storage and enabling of research data sharing). We summarise the lessons learned from the experiences of a wide range of individual image banks, and provide practical recommendations to enhance creation, use and reuse of neuroimaging data. Our aim is to maximise the benefit of the image data, provided voluntarily by research participants and funded by many organisations, for human health. Our ultimate vision is of a federated network of brain image biobanks accessible for large studies of brain structure and function.

Computational meta-analysis of statistical parametric maps in major depression.

OBJECTIVE: Several neuroimaging meta-analyses have summarized structural brain changes in major depression using coordinate-based methods. These methods might be biased toward brain regions where significant differences were found in the original studies. In this study, a novel voxel-based technique is implemented that estimates and meta-analyses between-group differences in grey matter from individual MRI studies, which are then applied to the study of major depression. METHODS: A systematic review and meta-analysis of voxel-based morphometry studies were conducted comparing participants with major depression and healthy controls by using statistical parametric maps. Summary effect sizes were computed correcting for multiple comparisons at the voxel level. Publication bias and heterogeneity were also estimated and the excess of heterogeneity was investigated with metaregression analyses. RESULTS: Patients with major depression were characterized by diffuse bilateral grey matter loss in ventrolateral and ventromedial frontal systems extending into temporal gyri compared to healthy controls. Grey matter reduction was also detected in the right parahippocampal and fusiform gyri, hippocampus, and bilateral thalamus. Other areas included parietal lobes and cerebellum. There was no evidence of statistically significant publication bias or heterogeneity. CONCLUSIONS: The novel computational meta-analytic approach used in this study identified extensive grey matter loss in key brain regions implicated in emotion generation and regulation. Results are not biased toward the findings of the original studies because they include all available imaging data, irrespective of statistically significant regions, resulting in enhanced detection of additional areas of grey matter loss.

The Neuro/PsyGRID calibration experiment: identifying sources of variance and bias in multicenter MRI studies.

Calibration experiments precede multicenter trials to identify potential sources of variance and bias. In support of future imaging studies of mental health disorders and their treatment, the Neuro/PsyGRID consortium commissioned a calibration experiment to acquire functional and structural MRI from twelve healthy volunteers attending five centers on two occasions. Measures were derived of task activation from a working memory paradigm, fractal scaling (Hurst exponent) from resting fMRI, and grey matter distributions from T(1) -weighted sequences. At each intracerebral voxel a fixed-effects analysis of variance estimated components of variance corresponding to factors of center, subject, occasion, and within-occasion order, and interactions of center-by-occasion, subject-by-occasion, and center-by-subject, the latter (since there is no intervention) a surrogate of the expected variance of the treatment effect standard error across centers. A rank order test of between-center differences was indicative of crossover or noncrossover subject-by-center interactions. In general, factors of center, subject and error variance constituted >90% of the total variance, whereas occasion, order, and all interactions were generally <5%. Subject was the primary source of variance (70%-80%) for grey-matter, with error variance the dominant component for fMRI-derived measures. Spatially, variance was broadly homogenous with the exception of fractal scaling measures which delineated white matter, related to the flip angle of the EPI sequence. Maps of P values for the associated F-tests were also derived. Rank tests were highly significant indicating the order of measures across centers was preserved. In summary, center effects should be modeled at the voxel-level using existing and long-standing statistical recommendations.

Grey matter differences in bipolar disorder: a meta-analysis of voxel-based morphometry studies.

OBJECTIVE: Several neuroimaging studies have reported structural brain differences in bipolar disorder using automated methods. While these studies have several advantages over those using region of interest techniques, no study has yet estimated a summary effect size or tested for between-study heterogeneity. We sought to address this issue using meta-analytic techniques applied for the first time in bipolar disorder at the level of the individual voxel. METHODS: A systematic review identified 16 voxel-based morphometry (VBM) studies comparing individuals with bipolar disorder with unaffected controls, of which eight were included in the meta-analysis. In order to take account of heterogeneity, summary effect sizes were computed using a random-effects model with appropriate correction for multiple testing. RESULTS: Compared with controls, subjects with bipolar disorder had reduced grey matter in a single cluster encompassing the right ventral prefrontal cortex, insula, temporal cortex, and claustrum. Study heterogeneity was widespread throughout the brain; though the significant cluster of grey matter reduction remained once these extraneous voxels had been removed. We found no evidence of publication bias (Eggers p = 0.63). CONCLUSIONS: Bipolar disorder is consistently associated with reductions in right prefrontal and temporal lobe grey matter. Reductions elsewhere may be obscured by clinical and methodological heterogeneity.

Do brain image databanks support understanding of normal ageing brain structure? A systematic review.

OBJECTIVE: To document accessible magnetic resonance (MR) brain images, metadata and statistical results from normal older subjects that may be used to improve diagnoses of dementia. METHODS: We systematically reviewed published brain image databanks (print literature and Internet) concerned with normal ageing brain structure. RESULTS: From nine eligible databanks, there appeared to be 944 normal subjects aged ≥60 years. However, many subjects were in more than one databank and not all were fully representative of normal ageing clinical characteristics. Therefore, there were approximately 343 subjects aged ≥60 years with metadata representative of normal ageing, but only 98 subjects were openly accessible. No databank had the range of MR image sequences, e.g. T2*, fluid-attenuated inversion recovery (FLAIR), required to effectively characterise the features of brain ageing. No databank supported random subject retrieval; therefore, manual selection bias and errors may occur in studies that use these subjects as controls. Finally, no databank stored results from statistical analyses of its brain image and metadata that may be validated with analyses of further data. CONCLUSION: Brain image databanks require open access, more subjects, metadata, MR image sequences, searchability and statistical results to improve understanding of normal ageing brain structure and diagnoses of dementia. KEY POINTS: • We reviewed databanks with structural MR brain images of normal older people. • Among these nine databanks, 98 normal subjects ≥60 years were openly accessible. • None had all the required sequences, random subject retrieval or statistical results. • More access, subjects, sequences, metadata, searchability and results are needed. • These may improve understanding of normal brain ageing and diagnoses of dementia.

Rationale and design of the brain magnetic resonance imaging protocol for FutureMS: a longitudinal multi-centre study of newly diagnosed patients with relapsing-remitting multiple sclerosis in Scotland.

Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. Magnetic resonance imaging (MRI) can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. This paper provides an overview of MRI data acquisition, management and processing in FutureMS. FutureMS is registered with the Integrated Research Application System (IRAS, UK) under reference number 169955. Methods and analysis: MRI is performed at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. Conclusions: FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland.

Impact of cannabis use on thalamic volume in people at familial high risk of schizophrenia.

BACKGROUND: No longitudinal study has yet examined the association between substance use and brain volume changes in a population at high risk of schizophrenia. AIMS: To examine the effects of cannabis on longitudinal thalamus and amygdala-hippocampal complex volumes within a population at high risk of schizophrenia. METHOD: Magnetic resonance imaging scans were obtained from individuals at high genetic risk of schizophrenia at the point of entry to the Edinburgh High-Risk Study (EHRS) and approximately 2 years later. Differential thalamic and amygdala-hippocampal complex volume change in high-risk individuals exposed (n = 25) and not exposed (n = 32) to cannabis in the intervening period was investigated using repeated-measures analysis of variance. RESULTS: Cannabis exposure was associated with bilateral thalamic volume loss. This effect was significant on the left (F = 4.47, P = 0.04) and highly significant on the right (F= 7.66, P= 0.008). These results remained significant when individuals using other illicit drugs were removed from the analysis. CONCLUSIONS: These are the first longitudinal data to demonstrate an association between thalamic volume loss and exposure to cannabis in currently unaffected people at familial high risk of developing schizophrenia. This observation may be important in understanding the link between cannabis exposure and the subsequent development of schizophrenia.

Assessment of the impact of the scanner-related factors on brain morphometry analysis with Brainvisa.

BACKGROUND: Brain morphometry is extensively used in cross-sectional studies. However, the difference in the estimated values of the morphometric measures between patients and healthy subjects may be small and hence overshadowed by the scanner-related variability, especially with multicentre and longitudinal studies. It is important therefore to investigate the variability and reliability of morphometric measurements between different scanners and different sessions of the same scanner. METHODS: We assessed the variability and reliability for the grey matter, white matter, cerebrospinal fluid and cerebral hemisphere volumes as well as the global sulcal index, sulcal surface and mean geodesic depth using Brainvisa. We used datasets obtained across multiple MR scanners at 1.5 T and 3 T from the same groups of 13 and 11 healthy volunteers, respectively. For each morphometric measure, we conducted ANOVA analysis and verified whether the estimated values were significantly different across different scanners or different sessions of the same scanner. The between-centre and between-visit reliabilities were estimated from their contribution to the total variance, using a random-effects ANOVA model. To estimate the main processes responsible for low reliability, the results of brain segmentation were compared to those obtained using FAST within FSL. RESULTS: In a considerable number of cases, the main effects of both centre and visit factors were found to be significant. Moreover, both between-centre and between-visit reliabilities ranged from poor to excellent for most morphometric measures. A comparison between segmentation using Brainvisa and FAST revealed that FAST improved the reliabilities for most cases, suggesting that morphometry could benefit from improving the bias correction. However, the results were still significantly different across different scanners or different visits. CONCLUSIONS: Our results confirm that for morphometry analysis with the current version of Brainvisa using data from multicentre or longitudinal studies, the scanner-related variability must be taken into account and where possible should be corrected for. We also suggest providing some flexibility to Brainvisa for a step-by-step analysis of the robustness of this package in terms of reproducibility of the results by allowing the bias corrected images to be imported from other packages and bias correction step be skipped, for example.

Rationale and design of a longitudinal study of cerebral small vessel diseases, clinical and imaging outcomes in patients presenting with mild ischaemic stroke: Mild Stroke Study 3.

BACKGROUND: Cerebral small vessel disease is a major cause of dementia and stroke, visible on brain magnetic resonance imaging. Recent data suggest that small vessel disease lesions may be dynamic, damage extends into normal-appearing brain and microvascular dysfunctions include abnormal blood-brain barrier leakage, vasoreactivity and pulsatility, but much remains unknown regarding underlying pathophysiology, symptoms, clinical features and risk factors of small vessel disease.Patients and Methods: The Mild Stroke Study 3 is a prospective observational cohort study to identify risk factors for and clinical implications of small vessel disease progression and regression among up to 300 adults with non-disabling stroke. We perform detailed serial clinical, cognitive, lifestyle, physiological, retinal and brain magnetic resonance imaging assessments over one year; we assess cerebrovascular reactivity, blood flow, pulsatility and blood-brain barrier leakage on magnetic resonance imaging at baseline; we follow up to four years by post and phone. The study is registered ISRCTN 12113543. SUMMARY: Factors which influence direction and rate of change of small vessel disease lesions are poorly understood. We investigate the role of small vessel dysfunction using advanced serial neuroimaging in a deeply phenotyped cohort to increase understanding of the natural history of small vessel disease, identify those at highest risk of early disease progression or regression and uncover novel targets for small vessel disease prevention and therapy.

Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task.

Multicentre MRI studies offer great potential to increase study power and flexibility, but it is not yet clear how reproducible the results from multiple centres may be. Here we present results from the multicentre study 'CaliBrain', examining the reproducibility of fMRI data within and between three sites. Fourteen subjects were scanned twice on three 1.5 T GE scanners using an identical scanning protocol. We present data from a motor task with three conditions, sequential and random finger tapping and rest. Similar activation maps were obtained for each site and visit; brain areas consistently activated during the task included the premotor, primary motor and supplementary motor areas, the striatum and cerebellum. Reproducibility was evaluated within and between sites by comparing the extent and spatial agreement of activation maps at both the subject and group levels. The results were within the range previously reported for similar tasks on single scanners and both measures were found to be comparable within and between sites, with between site reproducibility similar to the within site measures. A variance components analysis was used to examine the effects of site, subject and visit. The contributions of site and visit were small and reproducibility was similar between and within sites, whereas the variance between subjects, and unexplained variance was large. These findings suggest that we can have confidence in combined results from multicentre fMRI studies, at least when a consistent protocol is followed on similar machines in all participating scanning sites and care is taken to select homogeneous subject groups.

Power calculations for multicenter imaging studies controlled by the false discovery rate.

Magnetic resonance imaging (MRI) is widely used in brain imaging research (neuroimaging) to explore structural and functional changes across dispersed neural networks visible only via multisubject experiments. Multicenter investigations are an effective way to increase recruitment rates. This article describes image-based power calculations for a two-group, cross-sectional design specified by the mean effect size and its standard error, sample size, false discovery rate (FDR), and size of the network (i.e., proportion of image locations) that truly demonstrates an effect. Minimum sample size (for fixed effect size) and the minimum effect size (for fixed sample size) are calculated by specifying the acceptable power threshold. Within-center variance was estimated in five participating centers by repeat MRI scanning of 12 healthy participants from whom distributions of gray matter were estimated. The effect on outcome measures when varying FDR and the proportion of true positives is presented. Their spatial patterns reflect within-center variance, which is consistent across centers. Sample sizes 3-6 times larger are needed when detecting effects in subcortical regions compared to the neocortex. Hypothesized multicenter studies of patients with first episode psychosis and control participants were simulated with varying proportions of the cohort recruited at each center. There is little penalty to sample size for recruitment at five centers compared to the center with the lowest variance alone. At 80% power 80 participants per group are required to observe differences in gray matter in high variance regions.

Functional magnetic resonance imaging of BDNF val66met polymorphism in unmedicated subjects at high genetic risk of schizophrenia performing a verbal memory task.

Multiple strands of evidence suggest a role for Brain Derived Neurotrophic Factor (BDNF) in the pathophysiology of schizophrenia. It is not yet clear, however, how BDNF may contribute to altered brain function seen in the disorder, or in those at high genetic risk. The current study examines functional imaging correlates of the BDNF val66met polymorphism in a population at high genetic risk of schizophrenia. Subjects at high genetic risk for the disorder (n=58) provided both BDNF genotyping and fMRI data while performing a verbal memory task. During encoding, participants were presented with a word and asked to make a 'living'/'non-living' classification. During retrieval, individuals were requested to make an 'old'/'new' word classification. For encoding, we report decreased activation of the inferior occipital cortex and a trend in the cingulate cortex in Val homozygote individuals relative to Met carriers. For retrieval, we report decreases in activation in the prefrontal, cingulate cortex and bilateral posterior parietal regions in Val homozygote individuals versus Met carriers. These findings add to previous evidence suggesting that genetic variation in the BDNF gene modulates prefrontal and limbic functioning and suggests that it may contribute to differences in brain function seen in those at high risk of the disorder.

Between- and within-scanner variability in the CaliBrain study n-back cognitive task.

Psychiatric neuroimaging techniques are likely to improve understanding of the brain in health and disease, but studies tend to be small, based in one imaging centre and of unclear generalisability. Multicentre studies have great appeal but face problems if functional magnetic resonance imaging (fMRI) data from different centres are to be combined. Fourteen healthy volunteers had two brain scans on different days at three scanners. Considerable effort was first made to use similar scanning sequences and standardise task implementation across centres. The n-back cognitive task was used to investigate between- and within-scanner reproducibility and reliability. Both the functional imaging and behavioural results were in good accord with the existing literature. We found no significant differences in the activation/deactivation maps between scanners, or between repeat visits to the same scanners. Between- and within-scanner reproducibility and reliability was very similar. However, the smoothness of images from the scanners differed, suggesting that smoothness equalization might further reduce inter-scanner variability. Our results for the n-back task suggest it is possible to acquire fMRI data from different scanners which allows pooling across centres, when the same field strength scanners are used and scanning sequences and paradigm implementations are standardised.

A neuregulin 1 variant associated with abnormal cortical function and psychotic symptoms.

NRG1, encoding neuregulin 1, is a susceptibility gene for schizophrenia, but no functional mutation causally related to the disorder has yet been identified. Here we investigate the effects of a variant in the human NRG1 promoter region in subjects at high risk of schizophrenia. We show that this variant is associated with (i) decreased activation of frontal and temporal lobe regions, (ii) increased development of psychotic symptoms and (iii) decreased premorbid IQ.

Effects of the BDNF val66met polymorphism on prefrontal brain function in a population at high genetic risk of schizophrenia.

A single nucleotide polymorphism (val66met) in the brain derived neurotrophic factor (BDNF) gene has been shown to be a risk factor for a number of psychiatric disorders, including schizophrenia. This polymorphism has also been shown to have effects on prefrontal brain morphology and function. This study aims to clarify the effects of the val66met polymorphism on prefrontal brain function in a population at high genetic risk for schizophrenia. The Edinburgh High Risk Study has followed young individuals who had one first- or second-degree relative with schizophrenia and a minimum of one further genetic relative with the illness. A sample of 62 individuals provided both genetic and functional imaging data using the Hayling sentence completion task. Individuals with the BDNF ValVal (presumed risk) genotype (n = 41) showed relatively increased activation of the anterior cingulate cortex in relation to Met carrier individuals (n = 21) during sentence completion conditions versus baseline, against a background of similar levels of task performance. It appeared from further investigation that this relatively increased activation was attributable to a failure to disengage or suppress activation in the high risk ValVal group during the task condition, suggesting that BDNF may contribute to the abnormal default network reported in schizophrenia. These results suggest that this gene affects prefrontal brain function in those at high genetic risk for the disorder, unconfounded by medication effects. BDNF may therefore be one of the heritable factors involved in the development of abnormal prefrontal function in schizophrenia. © 2010 Wiley-Liss, Inc.

White matter abnormalities in bipolar disorder and schizophrenia detected using diffusion tensor magnetic resonance imaging.

OBJECTIVES: Strong qualitative and quantitative evidence exists of white matter abnormalities in both schizophrenia and bipolar disorder (BD). Diffusion tensor imaging (DTI) studies suggest altered connectivity in both disorders. We aim to address the diagnostic specificity of white matter abnormalities in these disorders. METHODS: DTI was used to assess white matter integrity in clinically stable patients with familial BD (n = 42) and familial schizophrenia (n = 28), and in controls (n = 38). Differences in fractional anisotropy (FA) were measured using voxel-based morphometry and automated region of interest analysis. RESULTS: Reduced FA was found in the anterior limb of the internal capsule (ALIC), anterior thalamic radiation (ATR), and in the region of the uncinate fasciculus in patients with BD and those with schizophrenia compared with controls. A direct comparison between patient groups found no significant differences in these regions. None of the findings were associated with psychotropic medication. CONCLUSIONS: Reduced integrity of the ALIC, uncinate fasciculus, and ATR regions is common to both schizophrenia and BD. These results imply an overlap in white matter pathology, possibly relating to risk factors common to both disorders.

Structural abnormalities of ventrolateral and orbitofrontal cortex in patients with familial bipolar disorder.

OBJECTIVES: Abnormalities of ventral prefrontal function have been widely reported in bipolar disorder, but reports of structural abnormalities in the same region are less consistent. We examined the presence and location of ventral prefrontal abnormalities in a large sample of individuals with bipolar disorder and their relationship to gender, psychotic symptoms, and age. METHODS: Structural magnetic resonance imaging brain scans were carried out on 66 individuals with bipolar disorder, type I, and 66 controls. Voxel-based morphometry was used to examine differences in grey and white matter density between the groups and their relationship with a lifetime occurrence of psychotic symptoms and age. RESULTS: Reductions in grey matter density were seen in the left and right lateral orbital gyri and the right inferior frontal gyrus, while white matter density reductions were seen in the corona radiata and the left temporal stem. In contrast, hallucinations and positive symptoms were associated with grey matter reduction in the left middle temporal gyrus. Age was more strongly associated with the right inferior frontal gyrus grey matter reductions in the bipolar group than in the controls, but not with any other finding. CONCLUSION: Abnormalities of the ventral prefrontal cortex are likely to be involved in the aetiopathology of bipolar disorder, while hallucinations appear to be more closely associated with temporal lobe abnormality, extending earlier work in schizophrenia. Further prospective studies are required to comprehensively address the trajectory of these findings.

Genetic variation in the G72 (DAOA) gene affects temporal lobe and amygdala structure in subjects affected by bipolar disorder.

BACKGROUND: Variation in the G72 (DAOA) gene is understood to convey susceptibility for bipolar disorder through an uncertain mechanism. Little is known about the structural brain phenotypes associated with this gene. We hypothesised that reductions in temporal lobe and amygdala gray matter would be associated with variation at two loci in the gene for which evidence of genetic linkage has been repeatedly demonstrated. METHODS: We examined the temporal lobe and amygdala gray matter associations of the risk variants M23 and M24 at the 5' end of the gene encoding G72 in 81 controls and 38 people with bipolar disorder. RESULTS: Genetic variation at both the M23 and M24 loci in G72 were associated with decreased gray matter density within the left temporal pole in people with bipolar disorder. M23 was also associated with reductions in right amygdala gray matter density. The genetic imaging associations were found only in patients with bipolar disorder. CONCLUSIONS: Genetic variation at single nucleotide polymorphisms in the G72 gene previously associated with bipolar disorder is related to reductions in temporal pole and amygdala gray matter structure in people with bipolar disorder.

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

BACKGROUND: Structural 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. METHODS: We 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. RESULTS: Voxel 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. CONCLUSION: Our 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.