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Brain Structure and Function

, Volume 223, Issue 2, pp 635–651 | Cite as

A probabilistic atlas of fiber crossings for variability reduction of anisotropy measures

  • Lukas J. VolzEmail author
  • M. Cieslak
  • S. T. Grafton
Original Article

Abstract

Diffusion imaging enables assessment of human brain white matter (WM) in vivo. WM microstructural integrity is routinely quantified via fractional anisotropy (FA). However, FA is also influenced by the number of differentially oriented fiber populations per voxel. To date, the precise statistical relationship between FA and fiber populations has not been characterized, complicating microstructural integrity assessment. Here, we used 630 state-of-the-art diffusion datasets from the Human Connectome Project, which allowed us to infer the number of fiber populations per voxel in a model-free fashion. Beyond the known impact on mean FA, variance of anisotropy distributions was drastically impacted, not only for FA, but also the more recent anisotropy indices generalized FA and multidimensional anisotropy. To ameliorate this bias, we introduce a probabilistic WM atlas delineating the number of distinctly oriented fiber populations per voxel. Our atlas shows that the majority of WM voxels features two differentially directed fiber populations (44.7%) rather than unidirectional fibers (32.9%) and identified WM regions with high numbers of crossing fibers, referred to as crossing pockets. Compartmentalizing anisotropy drastically reduced variance in group comparisons ranging from the whole brain to a few voxels in a single slice. In summary, we demonstrate a systematic effect of intra-voxel diffusion inhomogeneity on anisotropy. Moreover, we introduce a potential solution: The provided probabilistic WM atlas can easily be used with any given diffusion dataset to enhance the statistical robustness of anisotropy measures and increase their neurobiological utility.

Keywords

Diffusion MRI Human Connectome Project Voxel-wise comparison White matter Human anatomy 

Notes

Acknowledgements

The study was supported by a Grant from the General Electric-National Football League Head Health Challenge and the Institute for Collaborative Biotechnologies through Grant W911NF-09-0001 from the U.S. Army Research Office.

Supplementary material

429_2017_1508_MOESM1_ESM.eps (36 mb)
Supplementary Figure 1: Constructing the dTDM for different sub-samples of subjects resulted in highly similar segmentations WM. High similarity between WM segmentations was reflected by the proportion of assigned labels for the whole brain (A) and the CST (B). Furthermore, spatial distribution of dTDMs constructed for different sub-cohorts was highly similar (C-F), corroborating the reliability of the dTDM construction (EPS 36897 kb)
429_2017_1508_MOESM2_ESM.eps (2.5 mb)
Supplementary Figure 2: A symmetrical CST mask was constructed by flipping the left hemispheric CST mask from the SPM anatomy toolbox (Eickhoff et al. 2005) along the midsagittal plane. Of note, both the spatial extend of the symmetrical CST mask (yellow) and the original asymmetrical CST mask (blue), as well as resulting compartment specific anisotropy estimates were highly similar, demonstrating that it is highly unlikely that a bias was introduced by the symmetrical CST (EPS 2536 kb)
429_2017_1508_MOESM3_ESM.eps (4.8 mb)
Supplementary material 3 (EPS 4885 kb)

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Psychological and Brain SciencesUniversity of California at Santa BarbaraSanta BarbaraUSA
  2. 2.SAGE Center for the Study of the MindUniversity of CaliforniaSanta BarbaraUSA

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