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

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• 作者：T William J Moorhead (1) (6) <br> Viktoria-Eleni Gountouna (1) (6) <br> Dominic E Job (1) (6) <br> Andrew M McIntosh (1) (6) <br> Liana Romaniuk (1) (6) <br> G Katherine S Lymer (4) (6) <br> Heather C Whalley (1) (6) <br> Gordon D Waiter (2) (6) <br> David Brennan (3) (6) <br> Trevor S Ahearn (2) (6) <br> Jonathan Cavanagh (5) (6) <br> Barrie Condon (3) (6) <br> J Douglas Steele (2) (6) <br> Joanna M Wardlaw (4) (6) <br> Stephen M Lawrie (1) (6) <br>
• 刊名：BMC Medical Imaging
• 出版年：2009
• 出版时间：December 2009
• 年：2009
• 卷：9
• 期：1
• 全文大小：802KB
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Moorhead TW, Job DE, Whalley HC, Sanderson TL, Johnstone EC, Lawrie SM: Voxel-based morphometry of comorbid schizophrenia and learning disability: analyses in normalized and native spaces using parametric and nonparametric statistical methods. / Neuroimage 2004,22(1):188鈥?02. CrossRef <br> 10. Job DE, Whalley HC, McIntosh AM, Owens DG, Johnstone EC, Lawrie SM: Grey matter changes can improve the prediction of schizophrenia in subjects at high risk. / BMC Med 2006, 4:29. CrossRef <br> 11. Spencer MD, Moorhead TW, Gibson RJ, McIntosh AM, Sussmann JE, Owens DG, Lawrie SM, Johnstone EC: Low birthweight and preterm birth in young people with special educational needs: a magnetic resonance imaging analysis. / BMC Med 2008, 6:1. CrossRef <br> 12. Wilke M, Holland SK, Altaye M, Gaser C: Template-O-Matic: a toolbox for creating customized pediatric templates. / Neuroimage 2008,41(3):903鈥?3. CrossRef <br> 13. Shen S, Szameitat AJ, Sterr A: VBM lesion detection depends on the normalization template: a study using simulated atrophy. / Magn Reson Imaging 2007,25(10):1385鈥?6. CrossRef <br> 14. VanHaren NEM, Cahn W, Hulshoff Pol HE, Schnack HG, Caspers E, Lemstra A, Sitskoorn MM, Wiersma D, Bosch RJ, Dingemans PM, Schene AH, Kahn RS: Brain volumes as predictor of outcome in recent-onset schizophrenia: a multi-center MRI study. / Schizophr Res 2003,64(1):41鈥?2. CrossRef <br> 15. Schnack HG, van Haren NEM, Hulshoff Pol HE, Picchioni M, Weisbrod M, Sauer H, Cannon T, Huttunen M, Murray R, Kahn RS: Reliability of brain volumes from multicenter MRI acquisition: a calibration study. / Hum Brain Mapp 2004,22(4):312鈥?0. bm.20040">CrossRef <br> 16. Fischl B, Salat DH, Kouwe AJ, Makris N, S茅gonne F, Quinn BT, Dale AM: Sequence-independent segmentation of magnetic resonance images. / Neuroimage 2004,23(Suppl 1):S69鈥?4. CrossRef <br> 17. Han X, Fischl B: Atlas renormalization for improved brain MR image segmentation across scanner platforms. / IEEE Trans Med Imaging 2007,26(4):479鈥?6. CrossRef <br> 18. Hua X, Leow AD, Parikshak N, Lee S, Chiang MC, Toga AW, Jack CR Jr, Weiner MW, Thompson PM, The Alzheimer's Disease Neuroimaging Initiative: Tensor-based morphometry as a neuroimaging biomarker for Alzheimer's disease: An MRI study of 676 AD, MCI, and normal subjects. / Neuroimage 2008,43(3):458鈥?9. CrossRef <br> 19. Jack CR Jr, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, Borowski B, Britson PJ, L Whitwell J, Ward C, Dale AM, Felmlee JP, Gunter JL, Hill DL, Killiany R, Schuff N, Fox-Bosetti S, Lin C, Studholme C, DeCarli CS, Krueger G, Ward HA, Metzger GJ, Scott KT, Mallozzi R, Blezek D, Levy J, Debbins JP, Fleisher AS, Albert M, Green R, Bartzokis G, Glover G, Mugler J, Weiner MW: The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. / J Magn Reson Imaging 2008,27(4):685鈥?1. CrossRef <br> 20. Leow AD, Klunder AD, Jack CR Jr, Toga AW, Dale AM, Bernstein MA, Britson PJ, Gunter JL, Ward CP, Whitwell JL, Borowski BJ, Fleisher AS, Fox NC, Harvey D, Kornak J, Schuff N, Studholme C, Alexander GE, Weiner MW, Thompson PM, ADNI Preparatory Phase Study: Longitudinal stability of MRI for mapping brain change using tensor-based morphometry. / Neuroimage 2006,31(2):627鈥?0. CrossRef <br> 21. The pre-publication history for this paper can be accessed here:biomedcentral.com/1471-2342/9/8/prepub" class="a-plus-plus">http://www.biomedcentral.com/1471-2342/9/8/prepub <br>
• 作者单位：T William J Moorhead (1) (6) <br> Viktoria-Eleni Gountouna (1) (6) <br> Dominic E Job (1) (6) <br> Andrew M McIntosh (1) (6) <br> Liana Romaniuk (1) (6) <br> G Katherine S Lymer (4) (6) <br> Heather C Whalley (1) (6) <br> Gordon D Waiter (2) (6) <br> David Brennan (3) (6) <br> Trevor S Ahearn (2) (6) <br> Jonathan Cavanagh (5) (6) <br> Barrie Condon (3) (6) <br> J Douglas Steele (2) (6) <br> Joanna M Wardlaw (4) (6) <br> Stephen M Lawrie (1) (6) <br><br>1. The Division of Psychiatry, Centre for Clinical Brain Sciences (CCBS), School of Molecular and Clinical Medicine, University of Edinburgh, Edinburgh, UK <br> 6. Centre for Neuroscience, Division of Medical Sciences, University of Dundee, Dundee, UK <br> 4. SFC Brain Imaging Research Centre, SINAPSE Collaboration http://www.sinapse.ac.uk, Division of Clinical NeurosciencesUniversity of Edinburgh, Western General Hospital, Edinburgh, UK <br> 2. Aberdeen Biomedical Imaging Centre, Division of Applied Medicine University of Aberdeen, Aberdeen, UK <br> 3. The Department of Clinical Physics and Bioengineering, NHS Greater Glasgow South University Hospitals Division, Glasgow, UK <br> 5. Sackler Institute of Psychological Research, Faculty of Medicine, University of Glasgow, Glasgow, UK <br>

文摘

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 T1b>-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.