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

Roine T, Jeurissen B, Perrone D, Aelterman J, Leemans A, Philips W, Sijbers J - Front Neuroinform (2014)

Bottom Line: 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.In addition, a low diffusion weighting or SNR increases the effects.

View Article: PubMed Central - PubMed

Affiliation: iMinds-Vision Lab, Department of Physics, University of Antwerp Antwerp, Belgium.

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 DW 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-GM interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm(2), reasonable SNR (~30) and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs in CSD.

No MeSH data available.


The effect of varying angle between the two crossing fiber configurations with 50% non-WM partial volume (CSF, GM and air) to bias (A), 95% confidence interval (CI) (B), and the number of correct (C) and false peaks (D) estimated with CSD (with up to eighth-order SH, diffusion weighting 3000 s/mm2, and SNR 30). For comparison, 100% WM measures are provided.
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Figure 6: The effect of varying angle between the two crossing fiber configurations with 50% non-WM partial volume (CSF, GM and air) to bias (A), 95% confidence interval (CI) (B), and the number of correct (C) and false peaks (D) estimated with CSD (with up to eighth-order SH, diffusion weighting 3000 s/mm2, and SNR 30). For comparison, 100% WM measures are provided.

Mentions: Figure 6 shows the effects of varying angle between the two crossing fiber configurations. With an angle of 40° between the two fiber configurations, the correct peaks could not be properly identified. However, with an angle of 50°, they could still be reliably detected without isotropic PVEs, but any type of non-WM volume caused a decrease in the fraction of the correct peaks identified (Figure 6C). With higher angles, the correct peaks were identified correctly and without more bias than in pure WM (Figure 6A). The precision of the identified fiber orientations and the number of false peaks identified improved when the angle between the fiber configurations increased (Figures 6B,D).


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

Roine T, Jeurissen B, Perrone D, Aelterman J, Leemans A, Philips W, Sijbers J - Front Neuroinform (2014)

The effect of varying angle between the two crossing fiber configurations with 50% non-WM partial volume (CSF, GM and air) to bias (A), 95% confidence interval (CI) (B), and the number of correct (C) and false peaks (D) estimated with CSD (with up to eighth-order SH, diffusion weighting 3000 s/mm2, and SNR 30). For comparison, 100% WM measures are provided.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3975100&req=5

Figure 6: The effect of varying angle between the two crossing fiber configurations with 50% non-WM partial volume (CSF, GM and air) to bias (A), 95% confidence interval (CI) (B), and the number of correct (C) and false peaks (D) estimated with CSD (with up to eighth-order SH, diffusion weighting 3000 s/mm2, and SNR 30). For comparison, 100% WM measures are provided.
Mentions: Figure 6 shows the effects of varying angle between the two crossing fiber configurations. With an angle of 40° between the two fiber configurations, the correct peaks could not be properly identified. However, with an angle of 50°, they could still be reliably detected without isotropic PVEs, but any type of non-WM volume caused a decrease in the fraction of the correct peaks identified (Figure 6C). With higher angles, the correct peaks were identified correctly and without more bias than in pure WM (Figure 6A). The precision of the identified fiber orientations and the number of false peaks identified improved when the angle between the fiber configurations increased (Figures 6B,D).

Bottom Line: 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.In addition, a low diffusion weighting or SNR increases the effects.

View Article: PubMed Central - PubMed

Affiliation: iMinds-Vision Lab, Department of Physics, University of Antwerp Antwerp, Belgium.

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 DW 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-GM interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm(2), reasonable SNR (~30) and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs in CSD.

No MeSH data available.