Aribisala, Benjamin

Bastin, Mark

Cox, Simon

Deary, Ian

Ferguson, Karen

Maclullich, Alasdair

MacPherson, Sarah E

Royle, Natalie

Valdes Hernandez, Maria

Wardlaw, Joanna

Edinburgh Research Explorer

     Edinburgh Research Explorer                                      Comparative analysis of atlas-based and manual prefrontal brainparcellation in an ageing cohortCitation for published version:Aribisala, B, Cox, S, MacPherson, SE, Maclullich, A, Ferguson, K, Royle, N, Valdes Hernandez, M, Bastin,M, Deary, I & Wardlaw, J 2012, 'Comparative analysis of atlas-based and manual prefrontal brainparcellation in an ageing cohort' 18th Annual Meeting of the Organization for Human Brain MappingMeeting, Beijing, China, 10/06/12 - 14/06/12, .Link:Link to publication record in Edinburgh Research ExplorerDocument Version:Publisher's PDF, also known as Version of recordPublisher Rights Statement:© Aribisala, B., Cox, S., MacPherson, S. E., Maclullich, A., Ferguson, K., Royle, N., Valdes Hernandez, M.,Bastin, M., Deary, I., & Wardlaw, J. (2012). Comparative analysis of atlas-based and manual prefrontal brainparcellation in an ageing cohort. Poster session presented at 18th Annual Meeting of the Organization forHuman Brain Mapping Meeting, Beijing, China.General rightsCopyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)and / or other copyright owners and it is a condition of accessing these publications that users recognise andabide by the legal requirements associated with these rights.Take down policyThe University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorercontent complies with UK legislation. If you believe that the public display of this file breaches copyright pleasecontact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately andinvestigate your claim.Download date: 28. Apr. 2017Comparative Analysis of Atlas-Based and Manual Prefrontal Brain Parcellation in an Ageing Cohort Benjamin Aribisala1,2,7*,  Simon Cox1,2*, Sarah MacPherson2,3, Alasdair  MacLullich2,4,5, Karen Ferguson2,5, Natalie Royle1,2,7 , Maria Valdés Hernández1,2,7,  Mark Bastin1,2,7,  Ian Deary2,3, Joanna Wardlaw1,2,7 * Joint first authors. Introduction Row Fogo Charitable TrustReferences 1. Heckemann RA et al.,  Neuroimage 2010, 51(1):221-227 2. Cabezas M, et al.,  Computer methods and programs in biomedicine 2011 3.  Deary et al., BMC Geriatr 2007, 7(28) 4.  Wardlaw et al., Int. J. Stroke, 2011 5.  Ardekani BA, et al.,  J Neurosci Methods 2005, 142(1):67-76. 6.. Aljabar et al. (2009),   Neuroimage, 2009,  46(3), 726-738. 1Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK 2Centre for  Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; 3Department of Psychology, University of Edinburgh, UK;  4Endocrinology Unit, University of Edinburgh, UK; 5Geriatric Medicine Unit, University of Edinburgh, Edinburgh, UK;  6Clinical Research Imaging Centre, University of Edinburgh, UK; 7Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, UK Regions of interest (ROI) definition is an important step in the analysis of many MR images  Manual Definition of Region of Interest Time Consuming User Bias and Issues with Reproducibility  Atlas based Method Requires standardization to normalise variation in brain sizes and shapes Non-linear registration matches boundaries better than linear Single atlas cannot account for anatomical diversity Multi-atlases1 performs well in young adults      Challenge To compare the performance of both single- and multi-atlas parcellation with manual segmentation using brain MRI of older men Also to investigate the choice of atlas(es) selection for both single- and multi-atlas approaches Purpose Ninety scans of men selected from 700 members of Lothian Birth Cohorts 19363 Community dwelling, Mean age 72.7+/-0.7 years Non-demented, Non depressed and Not taking any anti-depressant  T1W scan (resolution 1x1x1.3 mm)4, 1.5 T GE scanner Manual Segmentation  Frontal gyri segmented anterior to the coronal appearance of precentral sulcus. Single Atlas Parcellation  Representative atlases selected based on: Study-based ageing brains Intracranial volume (ICV) Total Brain volume (TBV) Frontal lobe volume (lobe) Non-study-based brain Young male adult Atlases transformation to target brain used  ART5 Multi Atlas Parcellation  Atlases selected based on Normalised Mutual Information (mutual) Normalised correlation coefficient (corr) Cross validation based on leave-one-out method  Atlases transformation to target brain used ART5 Atlases combination used image fusion6 Post-processed to remove CSF  Results  The atlas based on TBV performed best of the single atlases For multi-atlas Correlation and mutual information gave equal performance Multi-atlas performed better than single atlas CSF removal improved performance Single-Atlas Multi-Atlas Multi-Atlas post-proc. Volumetric: Bland Altman Spatial Comparison: Dice Coefficient Single-Atlas Multi-Atlas Multi-Atlas post-proc. Conclusion Atlas-based parcellation method performed reasonably well in the ageing men. However, brain shape and particularly the effects of age-related atrophy could reduce its performance, hence there is need for visual assessment and some manual editing. The performance of any parcellation scheme should be assessed, not only by volumetrically, but also visually and by measure of spatial concordance. Future work should investigate incorporating atrophy metric into atlas selection Subjects Age-related changes pose a significant challenge to any automatic method2 E.g. Atrophy    Skull Thickening      Lesions       Prefrontal brain  High degree of inter-subject sulcal pattern variation Highly susceptible to age-related changes e.g. atrophy   Performance of atlas based parcellation in ageing has not been investigated Manual Multi-Atlas Multi-Atlas post-proc. Single-Atlas Sagittal (top row) and coronal (bottom row) planes.  From left to right, manual, single-, multi- and multi-atlas after  CSF removal For single atlas, local patterns of gyrification were not well-matched   For multi-atlas, prior to CSF removal, voxels in lateral (orange arrows) and medial aspects (orange box) were classified as brain tissue.  Single-atlas, representative brain selected based on the  total brain tissue volume  Multi-atlas, atlases selection used normalised correlation coefficient  Visual Assessment 

Comparative analysis of atlas-based and manual prefrontal brain parcellation in an ageing cohort

Comparative analysis of atlas-based and manual prefrontal brain parcellation in an ageing cohort

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