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Gray Matter Surface Based Spatial Statistics (GS-BSS) in Diffusion Microstructure

  • Prasanna ParvathaneniEmail author
  • Baxter P. Rogers
  • Yuankai Huo
  • Kurt G. Schilling
  • Allison E. Hainline
  • Adam W. Anderson
  • Neil D. Woodward
  • Bennett A. Landman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10433)

Abstract

Tract-based spatial statistics (TBSS) has proven to be a popular technique for performing voxel-wise statistical analysis that aims to improve sensitivity and interpretability of analysis of multi-subject diffusion imaging studies in white matter. With the advent of advanced diffusion MRI models – e.g., the neurite orientation dispersion density imaging (NODDI), it is of interest to analyze microstructural changes within gray matter (GM). A recent study has proposed using NODDI in gray matter based spatial statistics (N-GBSS) to perform voxel-wise statistical analysis on GM microstructure. N-GBSS adapts TBSS by skeletonizing the GM and projecting diffusion metrics to a cortical ribbon. In this study, we propose an alternate approach, known as gray matter surface based spatial statistics (GS-BSS), to perform statistical analysis using gray matter surfaces by incorporating established methods of registration techniques of GM surface segmentation on structural images. Diffusion microstructure features from NODDI and GM surfaces are transferred to standard space. All the surfaces are then projected onto a common GM surface non-linearly using diffeomorphic spectral matching on cortical surfaces. Prior post-mortem studies have shown reduced dendritic length in prefrontal cortex region in schizophrenia and bipolar disorder population. To validate the results, statistical tests are compared between GS-BSS and N-GBSS to study the differences between healthy and psychosis population. Significant results confirming the microstructural changes are presented. GS-BSS results show higher sensitivity to group differences between healthy and psychosis population in previously known regions.

Keywords

NODDI Brain microstructure Gray matter surface based analysis 

Notes

Acknowledgements

This work was supported by NIH R01EB017230 & R01MH102266 & Grant UL1 RR024975-01 & Grant 2 UL1 TR000445-06

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Prasanna Parvathaneni
    • 1
    Email author
  • Baxter P. Rogers
    • 2
  • Yuankai Huo
    • 1
  • Kurt G. Schilling
    • 2
  • Allison E. Hainline
    • 3
  • Adam W. Anderson
    • 2
  • Neil D. Woodward
    • 4
  • Bennett A. Landman
    • 1
    • 2
    • 4
  1. 1.Electrical EngineeringVanderbilt UniversityNashvilleUSA
  2. 2.Vanderbilt University Institute of Imaging ScienceVanderbilt UniversityNashvilleUSA
  3. 3.BiostatisticsVanderbilt UniversityNashvilleUSA
  4. 4.Department of Psychiatry and Behavioral SciencesVanderbilt University School of MedicineNashvilleUSA

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