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Isotropic non-white matter partial volume effects in constrained spherical deconvolution

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Abstract
Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a non-invasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. Significant partial volume effects (PVEs) are present in the DVV signal due to relatively large voxel sizes. These PVEs can be caused by both non-WM tissue, such as gray matter (GM) and cerebrospinal fluid (CSF), and by multiple non-parallel WM fiber populations. High angular resolution diffusion imaging (HARDI) methods have been developed to correctly characterize complex WM fiber configurations, but to date, many of the HARDI methods do not account for non-WM PVEs. In this work, we investigated the isotropic PVEs caused by non-WM tissue in WM voxels on fiber orientations extracted with constrained spherical deconvolution (CSD). Experiments were performed on simulated and real DW-MRI data. In particular, simulations were performed to demonstrate the effects of varying the diffusion weightings, signal-to-noise ratios (SNRs), fiber configurations, and tissue fractions. Our results show that the presence of non-WM tissue signal causes a decrease in the precision of the detected fiber orientations and an increase in the detection of false peaks in CSD. We estimated 35-50% of WM voxels to be affected by non-WM PVEs. For HARDI sequences, which typically have a relatively high degree of diffusion weighting, these adverse effects are most pronounced in voxels with GM PVEs. The non-WM PVEs become severe with 50% GM volume for maximum spherical harmonics orders of 8 and below, and already with 25% GM volume for higher orders. In addition, a low diffusion weighting or SNR increases the effects. The non-WM PVEs may cause problems in connectomics, where reliable fiber tracking at the WM G M interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm(2), reasonable SNR (similar to 30) and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs in CSD.
Keywords
LIVING HUMAN BRAIN, FIBER ORIENTATION, WHITE-MATTER, DIFFUSION-TENSOR MRI, WEIGHTED MRI, CROSSING FIBERS, SPIN-ECHO, B-MATRIX, TRACTOGRAPHY, GRADIENT, diffusion MRI, fiber orientation, partial volume effect, constrained spherical deconvolution, gray matter

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Chicago
Roine, Timo, Ben Jeurissen, Daniele Perrone, Jan Aelterman, Alexander Leemans, Wilfried Philips, and Jan Sijbers. 2014. “Isotropic Non-white Matter Partial Volume Effects in Constrained Spherical Deconvolution.” Frontiers in Neuroscience 8 (28): 1–9.
APA
Roine, T., Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., & Sijbers, J. (2014). Isotropic non-white matter partial volume effects in constrained spherical deconvolution. FRONTIERS IN NEUROSCIENCE, 8(28), 1–9.
Vancouver
1.
Roine T, Jeurissen B, Perrone D, Aelterman J, Leemans A, Philips W, et al. Isotropic non-white matter partial volume effects in constrained spherical deconvolution. FRONTIERS IN NEUROSCIENCE. 2014;8(28):1–9.
MLA
Roine, Timo, Ben Jeurissen, Daniele Perrone, et al. “Isotropic Non-white Matter Partial Volume Effects in Constrained Spherical Deconvolution.” FRONTIERS IN NEUROSCIENCE 8.28 (2014): 1–9. Print.
@article{4327780,
  abstract     = {Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a non-invasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. Significant partial volume effects (PVEs) are present in the DVV signal due to relatively large voxel sizes. These PVEs can be caused by both non-WM tissue, such as gray matter (GM) and cerebrospinal fluid (CSF), and by multiple non-parallel WM fiber populations. High angular resolution diffusion imaging (HARDI) methods have been developed to correctly characterize complex WM fiber configurations, but to date, many of the HARDI methods do not account for non-WM PVEs. In this work, we investigated the isotropic PVEs caused by non-WM tissue in WM voxels on fiber orientations extracted with constrained spherical deconvolution (CSD). Experiments were performed on simulated and real DW-MRI data. In particular, simulations were performed to demonstrate the effects of varying the diffusion weightings, signal-to-noise ratios (SNRs), fiber configurations, and tissue fractions. Our results show that the presence of non-WM tissue signal causes a decrease in the precision of the detected fiber orientations and an increase in the detection of false peaks in CSD. We estimated 35-50\% of WM voxels to be affected by non-WM PVEs. For HARDI sequences, which typically have a relatively high degree of diffusion weighting, these adverse effects are most pronounced in voxels with GM PVEs. The non-WM PVEs become severe with 50\% GM volume for maximum spherical harmonics orders of 8 and below, and already with 25\% GM volume for higher orders. In addition, a low diffusion weighting or SNR increases the effects. The non-WM PVEs may cause problems in connectomics, where reliable fiber tracking at the WM G M interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm(2), reasonable SNR (similar to 30) and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs in CSD.},
  articleno    = {8},
  author       = {Roine, Timo and Jeurissen, Ben and Perrone, Daniele and Aelterman, Jan and Leemans, Alexander and Philips, Wilfried and Sijbers, Jan},
  issn         = {1662-5196},
  journal      = {FRONTIERS IN NEUROSCIENCE},
  keyword      = {LIVING HUMAN BRAIN,FIBER ORIENTATION,WHITE-MATTER,DIFFUSION-TENSOR MRI,WEIGHTED MRI,CROSSING FIBERS,SPIN-ECHO,B-MATRIX,TRACTOGRAPHY,GRADIENT,diffusion MRI,fiber orientation,partial volume effect,constrained spherical deconvolution,gray matter},
  language     = {eng},
  number       = {28},
  pages        = {8:1--8:9},
  title        = {Isotropic non-white matter partial volume effects in constrained spherical deconvolution},
  url          = {http://dx.doi.org/10.3389/fninf.2014.00028},
  volume       = {8},
  year         = {2014},
}

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