RT Journal Article
SR Electronic
T1 Harmonization of cortical thickness measurements across scanners and sites
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 148502
DO 10.1101/148502
A1 Jean-Philippe Fortin
A1 Nicholas Cullen
A1 Yvette I. Sheline
A1 Warren D. Taylor
A1 Irem Aselcioglu
A1 Phil Adams
A1 Crystal Cooper
A1 Maurizio Fava
A1 Patrick J. McGrath
A1 Melvin McInnis
A1 Ramin V. Parsey
A1 Mary L. Phillips
A1 Madhukar H. Trivedi
A1 Myrna M. Weissman
A1 Russell T. Shinohara
YR 2017
UL http://biorxiv.org/content/early/2017/06/10/148502.abstract
AB With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as “scanner effects”, can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements, across a total of 11 scanners. We propose a set of general tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.AbbreviationsANTsAdvanced normalization toolsADAlzheimer’s diseaseADNIAlzheimer’s Disease Neuroimaging InitiativeANOVAAnalysis of varianceDTIDiffusion tensor imagingEBEmpirical BayesEMBARCEstablishing Moderators and Biosignatures of Antidepressant Response in Clinical careFAFractional anisotropyFWERFamily-wise error rateGPRGaussian process regressionHAMDHamilton Depression Rating ScaleIPWInverse probability weightingLDALinear discriminant analysisLLDLate-life depressionMASQMood and Anxiety Symptom QuestionnaireMCIMild cognitive impairmentMDMean diffusivityMVPAMultivariate pattern analysisOASISOpen Access Series of Imaging StudiesPCPrincipal componentPCAPrincipal component analysisQIDSQuick Inventory for Depression SymptomatologyRMSERoot-mean-square errorROIRegion of interestSTAISpielberger State-Trait Anxiety InventorySVMSupport vector machineSVRSupport vector regressionVDLCVascular disease: Longitudinal changes