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Inter-site and inter-scanner diffusion MRI data harmonization.

dc.contributor.author Andaluz, N
dc.contributor.author Bouix, S
dc.contributor.author Coimbra, R
dc.contributor.author Coleman, MJ
dc.contributor.author Flashman, LA
dc.contributor.author George, MS
dc.contributor.author Grant, Gerald Arthur
dc.contributor.author Kubicki, M
dc.contributor.author Marx, Christine Elizabeth
dc.contributor.author McAllister, TW
dc.contributor.author Michailovich, O
dc.contributor.author Mirzaalian, H
dc.contributor.author Morey, Rajendra A
dc.contributor.author Ning, L
dc.contributor.author Pasternak, O
dc.contributor.author Rathi, Y
dc.contributor.author Savadjiev, P
dc.contributor.author Shenton, ME
dc.contributor.author Shutter, L
dc.contributor.author Stein, MB
dc.contributor.author Westin, CF
dc.contributor.author Zafonte, RD
dc.coverage.spatial United States
dc.date.accessioned 2016-08-01T14:33:11Z
dc.date.issued 2016-07-15
dc.identifier http://www.ncbi.nlm.nih.gov/pubmed/27138209
dc.identifier S1053-8119(16)30081-7
dc.identifier.uri http://hdl.handle.net/10161/12540
dc.description.abstract We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.
dc.language eng
dc.relation.ispartof Neuroimage
dc.relation.isversionof 10.1016/j.neuroimage.2016.04.041
dc.subject Diffusion MRI
dc.subject Harmonization
dc.subject Inter-scanner
dc.subject Intra-site
dc.subject Multi-site
dc.title Inter-site and inter-scanner diffusion MRI data harmonization.
dc.type Journal article
pubs.author-url http://www.ncbi.nlm.nih.gov/pubmed/27138209
pubs.begin-page 311
pubs.end-page 323
pubs.organisational-group Clinical Science Departments
pubs.organisational-group Duke
pubs.organisational-group Duke Institute for Brain Sciences
pubs.organisational-group Duke-UNC Center for Brain Imaging and Analysis
pubs.organisational-group Institutes and Centers
pubs.organisational-group Institutes and Provost's Academic Units
pubs.organisational-group Psychiatry & Behavioral Sciences
pubs.organisational-group Psychiatry & Behavioral Sciences, Translational Neuroscience
pubs.organisational-group School of Medicine
pubs.organisational-group University Institutes and Centers
pubs.publication-status Published
pubs.volume 135
dc.identifier.eissn 1095-9572


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