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

Publication ,  Journal Article
Mirzaalian, H; Ning, L; Savadjiev, P; Pasternak, O; Bouix, S; Michailovich, O; Grant, G; Marx, CE; Morey, RA; Flashman, LA; George, MS ...
Published in: Neuroimage
July 15, 2016

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.

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Published In

Neuroimage

DOI

EISSN

1095-9572

Publication Date

July 15, 2016

Volume

135

Start / End Page

311 / 323

Location

United States

Related Subject Headings

  • Subtraction Technique
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Neurology & Neurosurgery
  • Male
  • Information Storage and Retrieval
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Humans
  • Female
 

Citation

APA
Chicago
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Mirzaalian, H., Ning, L., Savadjiev, P., Pasternak, O., Bouix, S., Michailovich, O., … Rathi, Y. (2016). Inter-site and inter-scanner diffusion MRI data harmonization. Neuroimage, 135, 311–323. https://doi.org/10.1016/j.neuroimage.2016.04.041
Mirzaalian, H., L. Ning, P. Savadjiev, O. Pasternak, S. Bouix, O. Michailovich, G. Grant, et al. “Inter-site and inter-scanner diffusion MRI data harmonization.Neuroimage 135 (July 15, 2016): 311–23. https://doi.org/10.1016/j.neuroimage.2016.04.041.
Mirzaalian H, Ning L, Savadjiev P, Pasternak O, Bouix S, Michailovich O, et al. Inter-site and inter-scanner diffusion MRI data harmonization. Neuroimage. 2016 Jul 15;135:311–23.
Mirzaalian, H., et al. “Inter-site and inter-scanner diffusion MRI data harmonization.Neuroimage, vol. 135, July 2016, pp. 311–23. Pubmed, doi:10.1016/j.neuroimage.2016.04.041.
Mirzaalian H, Ning L, Savadjiev P, Pasternak O, Bouix S, Michailovich O, Grant G, Marx CE, Morey RA, Flashman LA, George MS, McAllister TW, Andaluz N, Shutter L, Coimbra R, Zafonte RD, Coleman MJ, Kubicki M, Westin CF, Stein MB, Shenton ME, Rathi Y. Inter-site and inter-scanner diffusion MRI data harmonization. Neuroimage. 2016 Jul 15;135:311–323.
Journal cover image

Published In

Neuroimage

DOI

EISSN

1095-9572

Publication Date

July 15, 2016

Volume

135

Start / End Page

311 / 323

Location

United States

Related Subject Headings

  • Subtraction Technique
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Neurology & Neurosurgery
  • Male
  • Information Storage and Retrieval
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Humans
  • Female