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

BMC Medical Imaging

Research Article

John Suckling¹  Anna Barnes¹  Steven CR Williams²  David Brennan³  Barrie Condon³  Mahsa Shokouhi⁴  Tiago Reis Marques⁵  Paola Dazzan⁵  Dominic Job⁶  Thomas WJ Moorhead⁶  Stephen M Lawrie⁶  Clare MacKay⁷  Steve R Williams⁸  Bill Deakin⁹  Shane McKie⁹  Katherine Lymer^1,10 

[1] Brain Mapping Unit, Department of Psychiatry and Behavioural and Clinical Neurosciences Institute, University of Cambridge, UK;Centre for Neuroimaging Sciences, Institute of Psychiatry, Kings College London, UK;Department of Clinical Physics and Bioengineering, Institute of Neurological Science, Southern General Hospital, Glasgow, UK;Department of Clinical Physics and Psychological Medicine, College of Medicine, Veterinary and Life Sciences, University of Glasgow, UK;Department of Psychosis Studies, Institute of Psychiatry, Kings College London, UK;Division of Psychiatry, Centre for Clinical Brain Sciences, School of Molecular and Clinical Medicine, University of Edinburgh, UK;FMRIB Centre, University of Oxford, Oxford, UK;Imaging Science and Biomedical Engineering, University of Manchester, UK;Neuroscience and Psychiatry Unit, University of Manchester, UK;SFC Brain Imaging Research Centre, Division of Clinical Neurosciences, University of Edinburgh, UK;

关键词: Grey Matter;    Bias Correction;    Morphometric Measure;    White Matter Volume;    Brain Segmentation;   

DOI  :  10.1186/1471-2342-11-23

 received in 2011-04-28, accepted in 2011-12-21,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundBrain 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.MethodsWe 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.ResultsIn 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.ConclusionsOur 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.

【 授权许可】

CC BY   
© Shokouhi et al.; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.