Tract-Specific Group Analysis in Fetal Cohorts Using in utero Diffusion Tensor Imaging

  • Shadab KhanEmail author
  • Caitlin K. Rollins
  • Cynthia M. Ortinau
  • Onur Afacan
  • Simon K. Warfield
  • Ali Gholipour
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11072)


Diffusion tensor imaging (DTI) based group analysis has helped uncover the impact of white matter injuries in a wide range of studies involving subjects from preterm neonates to adults. The application of these methods to fetal cohorts, however, has been hampered by the challenging nature of in utero fetal DTI caused by unconstrained fetal motion, limited scan times, and limited signal-to-noise ratio. We present a framework that addresses these issues to systematically evaluate group differences in fetal cohorts. A motion-robust DTI computation approach with a new unbiased DTI template construction method is unified with kernel-regression in age and tensor-specific registration to normalize DTI volumes in an unbiased space. A robust statistical approach is used to map region-specific group differences to the medial representation of the tracts of interest. The proposed approach was applied and showed, for the first time, differences in local white matter fractional anisotropy based on in utero DTI of fetuses with congenital heart disease and age-matched healthy controls. This paper suggests the need for fetal-specific pipelines to be used for DTI-based group analysis involving fetal cohorts.


  1. 1.
    Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C.: Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 12(1), 26–41 (2008)CrossRefGoogle Scholar
  2. 2.
    Ball, G., et al.: An optimised tract-based spatial statistics protocol for neonates: applications to prematurity and chronic lung disease. NeuroImage 53(1), 94–102 (2010)CrossRefGoogle Scholar
  3. 3.
    Braga, R.M., et al.: Development of the corticospinal and callosal tracts from extremely premature birth up to 2 years of age. PLoS ONE 10(5), 1–15 (2015)CrossRefGoogle Scholar
  4. 4.
    Davis, B.C., Fletcher, P.T., Bullitt, E., Joshi, S.: Population shape regression from random design data. Int. J. Comput. Vis. 90, 255–266 (2010)CrossRefGoogle Scholar
  5. 5.
    Fogtmann, M., et al.: A unified approach to diffusion direction sensitive slice registration and 3-D DTI reconstruction from moving fetal brain anatomy. IEEE Trans. Med. Imaging 33(2), 272–289 (2014)CrossRefGoogle Scholar
  6. 6.
    Jiang, S., et al.: Diffusion tensor imaging (DTI) of the brain in moving subjects: application to in-utero fetal and ex-utero studies. Mag. Reson. Med. 62(3), 645–655 (2009)CrossRefGoogle Scholar
  7. 7.
    Kainz, B., et al.: Fast volume reconstruction from motion corrupted stacks of 2D slices. IEEE Trans. Med. Imaging 34(9), 1901–1913 (2015)CrossRefGoogle Scholar
  8. 8.
    Kelly, C.J., et al.: Impaired development of the cerebral cortex in infants with congenital heart disease is correlated to reduced cerebral oxygen delivery. Sci. Rep. 7(1), 15088 (2017)CrossRefGoogle Scholar
  9. 9.
    Marami, B., et al.: Temporal slice registration and robust diffusion-tensor reconstruction for improved fetal brain structural connectivity analysis. NeuroImage 156, 475–488 (2017)CrossRefGoogle Scholar
  10. 10.
    Miller, S.P., et al.: Abnormal brain development in newborns with congenital heart disease. New Engl. J. Med. 357(19), 1928–1938 (2007)CrossRefGoogle Scholar
  11. 11.
    Pecheva, D., et al.: A tract-specific approach to assessing white matter in preterm infants. NeuroImage 157, 675–694 (2017)CrossRefGoogle Scholar
  12. 12.
    Rollins, C.K., et al.: White matter microstructure and cognition in adolescents with congenital heart disease. J. Pediatr. 165(5), 936–944 (2014)CrossRefGoogle Scholar
  13. 13.
    Smith, S.M., et al.: Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31(4), 1487–1505 (2006)CrossRefGoogle Scholar
  14. 14.
    Yushkevich, P.A.: Continuous medial representation of brain structures using the biharmonic PDE. NeuroImage 45(1), S99–S110 (2009)CrossRefGoogle Scholar
  15. 15.
    Yushkevich, P.A., Zhang, H., Simon, T.J., Gee, J.C.: Structure-specific statistical mapping of white matter tracts. NeuroImage 41(2), 448–461 (2008)CrossRefGoogle Scholar
  16. 16.
    Zhang, H., et al.: A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features. Med. Image Anal. 14(5), 666–673 (2010)CrossRefGoogle Scholar
  17. 17.
    Zhang, H., Yushkevich, P.A., Alexander, D.C., Gee, J.C.: Deformable registration of diffusion tensor MR images with explicit orientation optimization. Med. Image Anal. 10(5), 764–785 (2006)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Shadab Khan
    • 1
    Email author
  • Caitlin K. Rollins
    • 1
  • Cynthia M. Ortinau
    • 2
  • Onur Afacan
    • 1
  • Simon K. Warfield
    • 1
  • Ali Gholipour
    • 1
  1. 1.Boston Children’s Hospital and Harvard Medical SchoolBostonUSA
  2. 2.Washington University School of MedicineSt. LouisUSA

Personalised recommendations