Hostname: page-component-f554764f5-sl7kg Total loading time: 0 Render date: 2025-04-19T00:32:13.182Z Has data issue: false hasContentIssue false
  • English
  • Français

A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps

Published online by Cambridge University Press:  11 June 2011

J. Radua ,
D. Mataix-Cols ,
M.L. Phillips ,
W. El-Hage ,
D.M. Kronhaus ,
N. Cardoner  and
S. Surguladze
J. Radua*
Affiliation:
Department of psychosis Studies, institute of psychiatry, King's College London, PO 69, London, SE5 8AF, UK FIDMAG, CIBERSAM, Sant Boi de Llobregat, Spain
D. Mataix-Cols
Affiliation:
Department of psychosis Studies, institute of psychiatry, King's College London, PO 69, London, SE5 8AF, UK
M.L. Phillips
Affiliation:
Department of psychiatry, western psychiatric institute and clinic, university of Pittsburgh school of medicine, Pittsburgh, USA Department of psychological medicine, Cardiff university school of medicine, Cardiff, UK
W. El-Hage
Affiliation:
Inserm U930 ERL CNRS 3106, université François-Rabelais, Tours, France
D.M. Kronhaus
Affiliation:
Cygnet Health Care, UK
N. Cardoner
Affiliation:
Despartment of psychiatry, Bellvitge university hospital-IDIBELL, CIBERSAM, Barcelona, Spain
S. Surguladze
Affiliation:
Department of psychosis Studies, institute of psychiatry, King's College London, PO 69, London, SE5 8AF, UK Cygnet Health Care, UK
*
*Corresponding author. Tel.: +44 20 78 48 03 63; fax: +44 78 48 03 79. E-mail address:[email protected] (J. Radua).
Get access

Abstract

Meta-analyses are essential to summarize the results of the growing number of neuroimaging studies in psychiatry, neurology and allied disciplines. Image-based meta-analyses use full image information (i.e. the statistical parametric maps) and well-established statistics, but images are rarely available making them highly unfeasible. Peak-probability meta-analyses such as activation likelihood estimation (ALE) or multilevel kernel density analysis (MKDA) are more feasible as they only need reported peak coordinates. Signed-differences methods, such as signed differential mapping (SDM) build upon the positive features of existing peak-probability methods and enable meta-analyses of studies comparing patients with controls. In this paper we present a new version of SDM, named Effect Size SDM (ES-SDM), which enables the combination of statistical parametric maps and peak coordinates and uses well-established statistics. We validated the new method by comparing the results of an ES-SDM meta-analysis of studies on the brain response to fearful faces with the results of a pooled analysis of the original individual data. The results showed that ES-SDM is a valid and reliable coordinate-based method, whose performance might be additionally increased by including statistical parametric maps. We anticipate that ES-SDM will be a helpful tool for researchers in the fields of psychiatry, neurology and allied disciplines.

Keywords

Meta-analysisNeuroimagingPeak coordinateSigned differential mappingStatistical parametric map
Type
Original articles
Information
European Psychiatry , Volume 27 , Issue 8 , November 2012 , pp. 605 - 611
Copyright
Copyright © European Psychiatric Association 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Bonilha, L., Rorden, C., Castellano, G., Pereira, F., Rio, P.A., Cendes, F.et al.Voxel-based morphometry reveals gray matter network atrophy in refractory medial temporal lobe epilepsy. Arch Neurol. 2004; 61 9: 1379–1384.CrossRefGoogle ScholarPubMed
Bora, E., Fornito, A., Radua, J., Walterfang, M., Seal, M., Wood, S.et al.Neuroanatomical abnormalities in schizophrenia: a multimodal voxel-wise meta-analysis and meta-regression analysis. Schizophr Res. 127 1–3: 2011 46–57.CrossRefGoogle Scholar
Bora, E., Fornito, A., Yucel, M., Pantelis, C.Voxel-wise meta-analysis of gray matter abnormalities in bipolar disorder. Biol Psychiatry. 2010; 67 11: 1097–1105.CrossRefGoogle Scholar
Chen, Z., Ma, L.Grey matter volume changes over the whole brain in amyotrophic lateral sclerosis: a voxel-wise meta-analysis of voxel-based morphometry studies. Amyotroph Lateral Scler. 2010.CrossRefGoogle ScholarPubMed
Cooper, H., Hedges, L.V.Handbook of research synthesis. New York: Russell Sage Foundation; 1994.Google Scholar
DerSimonian, R., Laird, N.Meta-analysis in clinical trials. Control Clin Trials. 1986; 7 3: 177–188.CrossRefGoogle ScholarPubMed
Dice, L.R.Measures of the amount of ecologic association between species. Ecology. 1945; 26 3: 297–302.CrossRefGoogle Scholar
Eickhoff, S.B., Laird, A.R., Grefkes, C., Wang, L.E., Zilles, K., Fox, P.T.Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: a random-effects approach based on empirical estimates of spatial uncertainty. Hum Brain Mapp. 2009; 30 9: 2907–2926.CrossRefGoogle ScholarPubMed
Fusar-Poli, P., Placentino, A., Carletti, F., Landi, P., Allen, P., Surguladze, S.et al.Functional atlas of emotional faces processing: a voxel-based meta-analysis of 105 functional magnetic resonance imaging studies. J Psychiatry Neurosci. 2009; 34 6: 418–432.Google ScholarPubMed
Gartus, A., Geissler, A., Foki, T., Tahamtan, A.R., Pahs, G., Barth, M.et al.Comparison of fMRI coregistration results between human experts and software solutions in patients and healthy subjects. Eur Radiol. 2007; 17 6: 1634–1643.CrossRefGoogle ScholarPubMed
Hedges, L.V.Distribution theory for Glass's estimator of effect size and related estimators. J Educ Stat. 1981; 6 2: 107–128.CrossRefGoogle Scholar
Hedges, L.V., Olkin, I.Statistical methods for meta-analysis. Orlando: Academic Press; 1985.Google Scholar
Higgins, J.P. T. and Green, S. Cochrane Handbook for Systematic Reviews of Interventions. Version 5.0.2. http://www.cochrane-handbook.org/. 2009. (GENERIC) Ref Type: Electronic CitationGoogle Scholar
Lambert, P.C., Sutton, A.J., Abrams, K.R., Jones, D.R.A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis. J Clin Epidemiol. 2002; 55 1: 86–94.CrossRefGoogle ScholarPubMed
Lazar, N.A., Luna, B., Sweeney, J.A., Eddy, W.F., Combining Brains:, A survey of methods for statistical pooling of information. NeuroImage. 2002; 16: 538–550.CrossRefGoogle ScholarPubMed
Radua, J., Mataix-Cols, D.Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. Br J Psychiatry. 2009; 195: 391–400.CrossRefGoogle ScholarPubMed
Radua, J., Mataix-Cols, D.Heterogeneity of coordinate-based meta-analyses of neuroimaging data: an example from studies in OCD – authors’ reply. Br J Psychiatry. 2010; 197 1: 77.CrossRefGoogle Scholar
Radua, J., Phillips, M.L., Russell, T., Lawrence, N., Marshall, N., Kalidindi, S.et al.Neural response to specific components of fearful faces in healthy and schizophrenic adults. NeuroImage. 2010; 49 1: 939–946.CrossRefGoogle ScholarPubMed
Radua, J., van den Heuvel, O.A., Surguladze, S., Mataix-Cols, D.Meta-analytical comparison of voxel-based morphometry studies in obsessive-compulsive disorder vs. other anxiety disorders. Arch Gen Psychiatry. 2010; 67 7: 701–711.CrossRefGoogle ScholarPubMed
Radua, J., Via, E., Catani, M., Mataix-Cols, D.Voxel-based meta-analysis of regional white matter volume differences in Autism Spectrum Disorder vs. healthy controls. Psychol Med. 2010 [In Press].Google Scholar
Salimi-Khorshidi, G., Smith, S.M., Keltner, J.R., Wager, T.D., Nichols, T.E.Meta-analysis of neuroimaging data: a comparison of image-based and coordinate-based pooling of studies. NeuroImage. 2009; 45 3: 810–823.CrossRefGoogle ScholarPubMed
Stewart, L.A., Parmar, M.K.Meta-analysis of the literature or of individual patient data: is there a difference?. Lancet. 1993; 341 8842: 418–422.CrossRefGoogle ScholarPubMed
Turkeltaub, P.E., Eden, G.F., Jones, K.M., Zeffiro, T.A.Meta-analysis of the functional neuroanatomy of single-word reading: method and validation. NeuroImage. 16 3 Pt 1 2002 765–780.CrossRefGoogle Scholar
Via, E., Radua, J., Cardoner, N., Happe, F., Mataix-Cols, D.Meta-analysis of gray matter abnormalities in autism spectrum disorder: should Asperger disorder be subsumed under a broader umbrella of autistic pectrum disorder?. Arch Gen Psychiatry. 2011; 68 4: 409–418.CrossRefGoogle Scholar
Viechtbauer, W.Bias and effciency of meta-analytic variance estimators in the random-effects model. Journal of Educational and Behavioral Statistics. 2005; 30: 261–293.CrossRefGoogle Scholar
Wager, T.D., Barrett, L., Bliss-Moreau, E., Lindquist, K., Duncan, S., Kober, H.et al.The neuroimaging of emotion. Anonymous handbook of emotions. New York: Guilford; 2007.Google Scholar
Wager, T.D., Lindquist, M., Kaplan, L.Meta-analysis of functional neuroimaging data: current and future directions. Soc Cogn Affect Neurosci. 2007; 2: 150–158.CrossRefGoogle ScholarPubMed
Submit a response

Comments

No Comments have been published for this article.