Brain Images of Normal Subjects

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■ News

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■ Research Data and Face Recognition

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■ BRAINS atlases available

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■ BRAINS paper published 2016

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■ Nuffield Placement 2015

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■ Press coverage of Brain Atlas paper

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■ Brain Image Bank Meeting 2014

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■ Visiting Students, Summer 2014

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Development of Human Brain Image Banks and Age-Specific Normative Atlases (28th-29th August)

SFC SINAPSE SPIRIT Programme of Knowledge Exchange in Imaging

Resources pack for Brain Image Bank and Brain Atlas Workshop

Current and emerging brain image banks and atlases

a) MNI: Alan Evans

• Evans AC, Janke AL, Collins DL, Baillet S. Brain templates and atlases Neuroimage. 2012 Aug 15;62(2):911-22. doi: 10.1016/j.neuroimage.2012.01.024.

• K Amunts et al, BigBrain: An Ultrahigh-Resolution 3D Human Brain Model Science 2013: Vol. 340 no. 6139 pp. 1472-1475 DOI: 10.1126/science.1235381

• S Das, AP Zijdenbos, J Harlap, D Vins, AC Evans LORIS: a web-based data management system for multi-center studies Front Neuroinform. 2011; 5: 37. doi: 10.3389/fninf.2011.00037

b) ENIGMA: Paul Thompson

• ENIGMA Consortium Website http://enigma.ini.usc.edu

• ENIGMA Consortium - Video: http://www.youtube.com/watch?v=VZbxLbzN5vk

• Thomspon P et al. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data Brain Imaging Behav. 2014; 8: 153–182. doi: 10.1007/s11682-013-9269-5; http://enigma.ini.usc.edu/wp-content/uploads/2014/01/Thompson_ENIGMA_Consortium_BIBreview.pdf

c) GIN: Bernard Mazoyer

• http://www.three-city-study.com; http://www.i-share.fr/frontpage

• http://www.gin.cnrs.fr/?lang=en

• http://www.i-share.fr/frontpage

• 3C study group (2003) Vascular factors and risk of dementia: design of the Three-City Study and baseline characteristics of the study population. Neuroepidemiology 22 :316-325.

• Dufouil C, Chalmers J, Coskun O, Besancon V, Bousser MG, Guillon P, MacMahon, S, Mazoyer B, Neal B, Woodward M, Tzourio-Mazoyer N, Tzourio C (2005); PROGRESS MRI Substudy Investigators. Effects of blood pressure lowering on cerebral white matter hyperintensities in patients with stroke: the PROGRESS (Perindopril Protection Against Recurrent Stroke Study) Magnetic Resonance Imaging Substudy. Circulation 12:1644-50.

• Lemaitre H, Crivello F, Grassiot B, Alperovitch A, Tzourio C, Mazoyer B (2005). Age- and sex-related effects on the neuroanatomy of healthy elderly. Neuroimage 26:900-911.

• Stewart B, Dufouil C, Godin O, Ritchie K, Maillard P, Delcroix N, Crivello F, Mazoyer B, Tzourio C (2008) Neuroimaging correlates of subjective memory deficits in a community population. Neurology 70:1601-1607.

• Crivello F, Lemaitre H, Dufouil C, Grassiot B, Delcroix N, Tzourio-Mazoyer N, Tzourio C, Mazoyer B (2010). Effects of ApoE-ε4 allele load and age on the rates of grey matter and hippocampal volumes loss in a longitudinal cohort of 1,186 healthy elderly persons. Neuroimage 53:1064-1069.

• Kurth T, Mohamed S, Maillard P, Zhu YC Chabriat H, Mazoyer B, Bousser MG, Dufouil C, Tzourio C (2011) Headache, Migraine, and Structural Brain Lesions and Function: population-based EVA MRI Study. British Medical Journal Jan 18;342:c7357.

• Stewart B, Godin O, Crivello F, Maillard P, Mazoyer B, Tzourio C, Dufouil C (2011) Longitudinal neuroimaging correlates of subjective memory impairment in a 4-year prospective community study. British Journal of Psychiatry 198:199-205.

• Tzourio-Mazoyer N, Marie D, Zago L, Perchey G, Leroux G, Mellet E, Jobard G, Joliot M, Crivello F, Petit L, Mazoyer B (2014) Heschl’s gyrification pattern is related to speech listening hemispheric lateralization fMRI investigation in 281 healthy volunteers. Brain Structure and Function (epub March 18)

d) INCF/IMAGEN: Jean-Baptiste Poline

• http://www.incf.org/documents/workshop-reports/towards-a-multi-modal-human-brain-atlas;

• http://www.incf.org/documents/incf-at-a-glance

• Poline JB, Breeze JL, Ghosh S, Gorgolewski K, Halchenko YO, Hanke M, Haselgrove C, Helmer KG, Keator DB, Marcus DS, Poldrack RA, Schwartz Y, Ashburner J, Kennedy DN. (2012) Data sharing in neuroimaging research. Frontiers in Neuroinformatics 2012 | doi: 10.3389/fninf.2012.00009 http://journal.frontiersin.org/Journal/10.3389/fninf.2012.00009/abstract

e) OASIS/HCP: Dan Marcus

• https://db.humanconnectome.org; https://www.oasisbrains.org

• http://www.xnat.org

f) BRAINS: Susan Shenkin

• Dickie, D.A., Job, D.E., Wardlaw, J.M., Laidlaw, D.H., Bastin, M.E:(2014) Evidence of non-normal distributions in brain imaging data from normal subjects: implications for diagnosis of disease. Proc. Intl. Soc. Mag. Reson. Med. 22.

• Dickie, D.A., Job, D.E., Rodríguez González, D., Shenkin, S.D., Ahearn, T.S., Murray, A.D., Wardlaw, J.M:(2013). Variance in brain volume with advancing age: implications for defining the limits of normality .PLOS ONE 8(12): e84093. DOI: 10.1371/journal.pone.0084093

• Dickie, D.A., Job, D.E., Poole, I., Ahearn, T.S., Staff, R.T., Murray, A.D., Wardlaw, J.M: (2012). Do brain image databanks support understanding of normal ageing brain structure? A systematic review Eur Radiol. 22 (7), 1385–1394. Received editorial: Barkhof, F. (2012). Making better use of our brain MRI research data.

• Farrell C, Chappell F, Armitage PA, Keston P, MacLullich A, Shenkin S, Wardlaw JM. European Radiology, 2009; 19(1):177-183 - Development and initial testing of normal reference MR images for the brain at ages 65-70 and 75-80 years

g) EPI2: Rotterdam/Leiden: Aad van der Lugt

• www.populationimaging.eu

• MA Ikram, A van der Lugt, WJ Neissen, GP Krestin, PJ Koudstaal, A Hofman, MMB Breteler, MW Vernnoij The Rotterdam Scan Study: design and update up to 2012 Eur J Epidemiology (2011) 26: 811-824

h) Rhineland: Monique Breteler

• http://www.dzne.de/en/research/research-areas/population-studies.html

i) Biobank: Steve Smith

• http://www.ukbiobank.ac.uk/

• http://imaging.ukbiobank.ac.uk/imaging.html

j) UK Dementia Platform: Clare Mackay (see resources in folder, UKDP and MIRIAD slide)

• http://www.mrc.ac.uk/research/facilities/dementias-research-platform/

k) Perinatal banks: James Boardman

• Serag A, Aljabar P, Ball G, Counsell SJ, Boardman JP, Rutherford MA, Edwards AD, Hajnal JV, Rueckert D. Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression. Neuroimage. 2012 Feb 1;59(3):2255-65

• Bassi L, Chew A, Merchant N, Ball G, Ramenghi L, Boardman J, Allsop JM, Doria V, Arichi T, Mosca F, Edwards AD, Cowan FM, Rutherford MA, Counsell SJ. Diffusion tensor imaging in preterm infants with punctate white matter lesions. Pediatr Res. 2011 Jun;69(6):561-6.

• Kuklisova-Murgasova M, Aljabar P, Srinivasan L, Counsell SJ, Doria V, Serag A, Gousias IS, Boardman JP, Rutherford MA, Edwards AD, Hajnal JV, Rueckert D. A dynamic 4D probabilistic atlas of the developing brain. Neuroimage. 2011 Feb 14;54(4):2750-63

Resources from Serena Counsell’s group:

• http://www.kcl.ac.uk/medicine/research/divisions/imaging/centres/cdb/index.aspx

Resources from Petra Hüppi’s group (Lana Vasung):

• Dubois J, Benders M, Cachia A, Lazeyras F, Ha-Vinh Leuchter R, Sizonenko SV, Borradori-Tolsa C, Mangin JF, Hüppi PS. Mapping the early cortical folding process in the preterm newborn brain. Cereb Cortex. 2008 Jun;18(6):1444-54. http://cercor.oxfordjournals.org/content/18/6/1444.long

• Fischi-Gómez E¹, Vasung L, Meskaldji DE, Lazeyras F, Borradori-Tolsa C, Hagmann P, Barisnikov K, Thiran JP, Hüppi PSStructural Brain Connectivity in School-Age Preterm Infants Provides Evidence for Impaired Networks Relevant for Higher Order Cognitive Skills and Social Cognition. Cereb Cortex. 2014 May 2. [Epub ahead of print] http://cercor.oxfordjournals.org/content/early/2014/05/02/cercor.bhu073.long

• Gui L, Lisowski R, Faundez T, Hüppi PS, Lazeyras F, Kocher M. Morphology-driven automatic segmentation of MR images of the neonatal brain. Med Image Anal. 2012 Dec;16(8):1565-79. doi: 10.1016/j.media.2012.07.006. Epub 2012 Jul 31. http://www.sciencedirect.com/science/article/pii/S1361841512000989

• Kunz N, Zhang H, Vasung L, O'Brien KR, Assaf Y, Lazeyras F, Alexander DC, Hüppi PS.Assessing white matter microstructure of the newborn with multi-shell diffusion MRI and biophysical compartment models.Neuroimage. 2014 Aug 1;96:288-99. doi: 10.1016/j.neuroimage.2014.03.057. Epub 2014 Mar 28. http://www.sciencedirect.com/science/article/pii/S1053811914002183

• Kwon SH, Vasung L, Ment LR, Huppi PS.The role of neuroimaging in predicting neurodevelopmental outcomes of preterm neonates. Clin Perinatol. 2014 Mar;41(1):257-83. doi: 10.1016/j.clp.2013.10.003. Epub 2013 Dec 12. http://www.sciencedirect.com/science/article/pii/S0095510813001292

• van de Looij Y, Vasung L, Sizonenko SV, Hüppi PS. MRI of animal models of developmental disorders and translation to human imaging. Curr Opin Neurol. 2014 Apr;27(2):157-67. doi: 10.1097/WCO.0000000000000066

Session 2 "What is normal?": Alan Evans

• Wachbroit R. Normality as a biological concept. Philosophy of Science 1994;61:579-591 http://www.jstor.org/stable/188336

Discussion groups:

1. Minimum image and metadata to define normality (John Ashburner)

2. How to use existing data, likely gaps (Monique Breteler)

3. Combining all stages of life in one image bank (James Boardman/Dominic Job)

Session 3 "Legal and ethical issues" Grahame Laurie

Discussion groups:

1. Consent, industry, international issues (Burkhard Schaefer)

2. Privacy, anonymisation, levels of access (Hester Ward)

3. Research tourism, incidental findings (Alison Murray)

• Schmidt CO, Hegenscheid K, Erdmann P, Kohlmann T, Langanke M, Völzke H, Puls R, Assel H, Biffar R, Grabe HJ. Psychosocial consequences and severity of disclosed incidental findings from whole-body MRI in a general population study. European Radiology, May 2013, Volume 23, Issue 5, pp 1343-1351

Session 4 Multisource 'big' data: "What do we need to use big data" JB Poline

• JB Poline, JL. Breeze, St Ghosh, KGorgolewski, YO Halchenko, M Hanke, C Haselgrove, K G. Helmer, DB. Keator, DS Marcus, RA Poldrack, Y Schwartz, J Ashburner DN Kennedy - Data sharing in neuroimaging research Front. Neuroinform., 2012 | doi: 10.3389/fninf.2012.00009

http://journal.frontiersin.org/Journal/10.3389/fninf.2012.00009/abstract

• Poline, JB, and RA Poldrack. Introduction to the Special Issue: Toward a New Era of Databasing and Data Sharing for Neuroimaging. NeuroImage 82, (2013): 645–46. http://www.sciencedirect.com/science/article/pii/S1053811913009075

• Open access: Practical costs of data sharing Geoffrey J. Goodhill Nature 509, 33 (30 April 2014) | doi:10.1038/509033b http://www.nature.com/nature/journal/v509/n7498/full/509033b.html and reply Steve Eglan http://www.nature.com/nature/journal/v510/n7505/pdf/510340c.pdf

Discussion groups:

1) Harmonising data (Aziz Sheikh)

• Lynch, C. (2008) Big data: How do your data grow? Nature 455, 28-29

• K Amunts, MJ Hawrylycz, DC Van Essen, JD Van Horn, N Harel, J-B Poline, F De Martino, JG Bjaalie, G Dehaene-Lambertz ,S Dehaene, P Valdes-Sosa, B Thirion, K Zilles, SL Hill, MB Abrams, PA Tass, W Vanduffel, AC Evans, SB Eickhoff, Interoperable atlases of the human brain NeuroImage.2014, 99: 525–532; DOI: 10.1016/j.neuroimage.2014.06.010

2) Database Infrastructure (Dan Marcus)

3) Data provenance, quality assurance (Albert Burger)

• W3C PROV: Provenance Current Status: http://www.w3.org/standards/techs/provenance#w3c_all

• EDBT/ICDT 2013 (http://www.edbt.org/Proceedings/2013-Genova/edbt_toc.html) Missier P, Belhajjame K, Cheney J. The W3C PROV family of specifications for modelling provenance metadata, EDBT '13 Proceedings of the 16th International Conference on Extending Database Technology p773-776, http://www.edbt.org/Proceedings/2013-Genova/papers/edbt/a80-missier.pdf

• ACM Practice: A Primer on Provenance http://cacm.acm.org/magazines/2014/5/174341-a-primer-on-provenance/fulltext

• AJ MacKenzie-Graham, JD Van Horn, R P Woods, KL Crawford, AW Toga Provenance in NeuroimagingNeuroimage. Aug 1, 2008; 42(1): 178–195. doi: 10.1016/j.neuroimage.2008.04.186

• AW Toga Neuroimage databases: The good, the bad and the ugly Nature Reviews Neuroscience 3, 302-309 (April 2002) | doi:10.1038/nrn782

• JB Poline, JL. Breeze, St Ghosh, KGorgolewski, YO Halchenko, M Hanke, C Haselgrove, K G. Helmer, DB. Keator, DS Marcus, RA Poldrack, Y Schwartz, J Ashburner DN Kennedy - Data sharing in neuroimaging research Front. Neuroinform., 2012 | doi: 10.3389/fninf.2012.00009 http://journal.frontiersin.org/Journal/10.3389/fninf.2012.00009/abstract

Session 5 Making image databanks work: Steve Smith

1) Atlas creation tools and registration issues (variability) (Bernard Mazoyer)

2) Data sharing/citation/storage (Steve Pavis and David Wyper)

• EE Wilhelm, E Oster, I Shoulson. Approaches and Costs for Sharing Clinical Research Data JAMA. Published online February 20, 2014. doi:10.1001

• S Schneeweiss Learning from Big Health Care Data N Engl J Med 2014;370:2161-2163/jama.2014.850

• R Kush, M Goldman Fostering Responsible Data Sharing through Standards N Engl J Med 2014;370:2163-2165

• BM Psaty and AM Breckenridge Mini-Sentinel and Regulatory Science - Big Data Rendered Fit and Functional N Engl J Med 2014;370:2165-2167

Other general useful resources:

• G Ziegler, GR Ridgway, R Dahnke, C Gaser, for The Alzheimer's Disease Neuroimaging Initiative Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects NeuroImage, Vol 97, 15 August 2014, P 333–348, ^a Wellcome Trust Center for Neuroimaging, Institute of Neurology, London, UK. DOI: 10.1016/j.neuroimage.2014.04.018

• MIRIAD: Minimal Interval Resonance Imaging in Alzheimer's Disease (Nick Fox)

46 clinical AD, 23 age‐matched elderly controls, Longitudinal (up to 12 scans) volumetric MRI scanning on single 1.5T scanner http://www.ucl.ac.uk/drc/research/miriad/Database

• G Neil Roberts: Guo et al Towards an elastographic atlas of brain anatomy PLOSOne 2013 DOI: 10.1371/journal.pone.0071807 (in file)

• Cresswell, KM; Bates, DW; Sheikh, A, Ten key considerations for the successful implementation and adoption of large-scale health information technology. J Am Med Inform Assoc, 2013 vol. 20(e1) pp. e9-e13. PMID: 23599226. PMCID: PMC3715363

• J. B. Poline, R. A. Poldrack, Introduction to the special issue: Towards a new era of databasing and datasharing for neuroimaging. NeuroImage, Vol 82, 15 November 2013, pp645-646.

 

Many thanks to our funders whose contributions have made this meeting possible: