Whole brain magnetic resonance image atlases: a systematic review of existing atlases and caveats for use in population imaging

Dickie, D. A. , Shenkin, S. D., Anblagan, D., Lee, J., Blesa Cabez, M., Rodriguez, D., Boardman, J. P., Waldman, A., Job, D. E. and Wardlaw, J. M. (2017) Whole brain magnetic resonance image atlases: a systematic review of existing atlases and caveats for use in population imaging. Frontiers in Neuroinformatics, 11, 1. (doi: 10.3389/fninf.2017.00001) (PMID:28154532) (PMCID:PMC5244468)

Abstract

Brain MRI atlases may be used to characterize brain structural changes across the life course. Atlases have important applications in research, e.g., as registration and segmentation targets to underpin image analysis in population imaging studies, and potentially in future in clinical practice, e.g., as templates for identifying brain structural changes out with normal limits, and increasingly for use in surgical planning. However, there are several caveats and limitations which must be considered before successfully applying brain MRI atlases to research and clinical problems. For example, the influential Talairach and Tournoux atlas was derived from a single fixed cadaveric brain from an elderly female with limited clinical information, yet is the basis of many modern atlases and is often used to report locations of functional activation. We systematically review currently available whole brain structural MRI atlases with particular reference to the implications for population imaging through to emerging clinical practice. We found 66 whole brain structural MRI atlases world-wide. The vast majority were based on T1, T2, and/or proton density (PD) structural sequences, had been derived using parametric statistics (inappropriate for brain volume distributions), had limited supporting clinical or cognitive data, and included few younger (>5 and <18 years) or older (>60 years) subjects. To successfully characterize brain structural features and their changes across different stages of life, we conclude that whole brain structural MRI atlases should include: more subjects at the upper and lower extremes of age; additional structural sequences, including fluid attenuation inversion recovery (FLAIR) and T2* sequences; a range of appropriate statistics, e.g., rank-based or non-parametric; and detailed cognitive and clinical profiles of the included subjects in order to increase the relevance and utility of these atlases.

• Item Type: Articles
• Additional Information: This work was carried out in The University of Edinburgh Brain Research Imaging Centre (BRIC; http://www.bric.ed.ac.uk/) within the Department of Neuroimaging Sciences. BRIC is part of the Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) collaboration (http://www.sinapse.ac.uk/), funded by the Scottish Funding Council, Scottish Executive Chief Scientist Office, and the six collaborator Universities. Professor JW was funded by the Scottish Funding Council and Scottish Executive Chief Scientist Office through the SINAPSE collaboration. DAD was funded by a SINAPSE industrial collaboration (SPIRIT) Ph.D. scholarship, a Medical Research Council (MRC) scholarship, and the Tony Watson Scholarship bequest to The University of Edinburgh; and is currently funded by Innovate UK. Dr. DJ was funded by Wellcome Trust Grant 007393/Z/05/Z. Funding from Edinburgh and Lothians Health Foundation 53/311 and BBSRC Sparking Impact SI 2013-0210 is gratefully acknowledged. The University of Edinburgh Centre for Cognitive Aging and Cognitive Epidemiology (SS) is part of the cross council Lifelong Health and Wellbeing Initiative (G0700704/84698). Funding from the Biotechnology and Biological Sciences Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Medical Research Council is also gratefully acknowledged.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Dickie, Dr David Alexander
• Authors: Dickie, D. A., Shenkin, S. D., Anblagan, D., Lee, J., Blesa Cabez, M., Rodriguez, D., Boardman, J. P., Waldman, A., Job, D. E., and Wardlaw, J. M.
• College/School: College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
• Journal Name: Frontiers in Neuroinformatics
• Publisher: Frontiers Media
• ISSN: 1662-5196
• ISSN (Online): 1662-5196
• Copyright Holders: Copyright © 2017 Dickie, Shenkin, Anblagan, Lee, Blesa Cabez, Rodriguez, Boardman, Waldman, Job and Wardlaw
• First Published: First published in Frontiers in Neuroinformatics 11:1
• Publisher Policy: Reproduced under a Creative Commons License