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Extrapolation-Based References Improve Motion and Eddy-Current Correction of High B-Value DWI Data: Application in Parkinson's Disease Dementia.

Nilsson M, Szczepankiewicz F, van Westen D, Hansson O - PLoS ONE (2015)

Bottom Line: Conventional correction resulted in systematic registration errors for high b-value data.The extrapolation-based methods did not exhibit such errors, yielding more accurate tractography and up to 50% lower standard deviation in DKI metrics.Statistically significant differences were found between patients and controls when using the extrapolation-based motion correction that were not detected when using the conventional method.

View Article: PubMed Central - PubMed

Affiliation: Lund University Bioimaging Center, Lund University, Lund, Sweden.

ABSTRACT

Purpose: Conventional motion and eddy-current correction, where each diffusion-weighted volume is registered to a non diffusion-weighted reference, suffers from poor accuracy for high b-value data. An alternative approach is to extrapolate reference volumes from low b-value data. We aim to compare the performance of conventional and extrapolation-based correction of diffusional kurtosis imaging (DKI) data, and to demonstrate the impact of the correction approach on group comparison studies.

Methods: DKI was performed in patients with Parkinson's disease dementia (PDD), and healthy age-matched controls, using b-values of up to 2750 s/mm2. The accuracy of conventional and extrapolation-based correction methods was investigated. Parameters from DTI and DKI were compared between patients and controls in the cingulum and the anterior thalamic projection tract.

Results: Conventional correction resulted in systematic registration errors for high b-value data. The extrapolation-based methods did not exhibit such errors, yielding more accurate tractography and up to 50% lower standard deviation in DKI metrics. Statistically significant differences were found between patients and controls when using the extrapolation-based motion correction that were not detected when using the conventional method.

Conclusion: We recommend that conventional motion and eddy-current correction should be abandoned for high b-value data in favour of more accurate methods using extrapolation-based references.

No MeSH data available.


Related in: MedlinePlus

The challenge: Motion and eddy-current correction of diffusion MRI data in the elderly brain.Top row: Non diffusion-weighted MR-image (left), and diffusion-weighted images, encoded using a b-value of 1000 s/mm2 (middle) and 2750 s/mm2 (right) and averaged across multiple directions. Note that the rim of CSF surrounding the anterior part of the brain visualized in the non-diffusion weighted image to the left is absent in the diffusion weighted images. Bottom: Normalized plot of the logarithm of the MR signal as a function of position along the lines indicated in the images at the top. The anterior position where the MR signal turns into background is shifted posteriorly when comparing the zero b-value profile (blue) to the high b-value profile (orange). If the correction employs a non diffusion-encoded reference, the difference in contrast may cause the high b-value data to be erroneously scaled in the antero-posterior direction to fit the low b-value signal outline.
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pone.0141825.g001: The challenge: Motion and eddy-current correction of diffusion MRI data in the elderly brain.Top row: Non diffusion-weighted MR-image (left), and diffusion-weighted images, encoded using a b-value of 1000 s/mm2 (middle) and 2750 s/mm2 (right) and averaged across multiple directions. Note that the rim of CSF surrounding the anterior part of the brain visualized in the non-diffusion weighted image to the left is absent in the diffusion weighted images. Bottom: Normalized plot of the logarithm of the MR signal as a function of position along the lines indicated in the images at the top. The anterior position where the MR signal turns into background is shifted posteriorly when comparing the zero b-value profile (blue) to the high b-value profile (orange). If the correction employs a non diffusion-encoded reference, the difference in contrast may cause the high b-value data to be erroneously scaled in the antero-posterior direction to fit the low b-value signal outline.

Mentions: We will refer to the method where a full affine transform is used to register diffusion-weighted volumes to a non diffusion-weighted reference by optimizing the mutual information as the ‘conventional method’. Although mutual information metrics are designed to allow registration of images with different contrasts, the conventional method suffers from poor accuracy [16], mainly due to the large difference in contrast between low and high b-value images. This difference is most pronounced where a rim of CSF surrounds the brain, which is common in elderly subjects and patients with cerebral atrophy. This rim of CSF is clearly visible in non diffusion-weighted images, but is completely attenuated in high b-value images, which results in an inward shift of the apparent brain outline (Fig 1). This shift may induce errors in conventional motion and eddy-current correction of high b-value data, since image registration algorithms tend to match borders. Extrapolation-based correction, where reference volumes with appropriate high b-value contrast are extrapolated from low b-value data, was suggested by Ben-Amitay et al as a potential solution [16]. The benefit of such a method is that low b-value data can be corrected using the conventional method with a precision sufficient for accurate extrapolation of undistorted reference volumes. Ben-Amitay et al used standard DTI analysis on the low b-value data, and adapted the results for the CHARMED model in order to extrapolate to high b-value shells. However, standard DTI performs poorly in regions where tissue is mixed with free water such as CSF [17], which may have a negative impact on the extrapolation.


Extrapolation-Based References Improve Motion and Eddy-Current Correction of High B-Value DWI Data: Application in Parkinson's Disease Dementia.

Nilsson M, Szczepankiewicz F, van Westen D, Hansson O - PLoS ONE (2015)

The challenge: Motion and eddy-current correction of diffusion MRI data in the elderly brain.Top row: Non diffusion-weighted MR-image (left), and diffusion-weighted images, encoded using a b-value of 1000 s/mm2 (middle) and 2750 s/mm2 (right) and averaged across multiple directions. Note that the rim of CSF surrounding the anterior part of the brain visualized in the non-diffusion weighted image to the left is absent in the diffusion weighted images. Bottom: Normalized plot of the logarithm of the MR signal as a function of position along the lines indicated in the images at the top. The anterior position where the MR signal turns into background is shifted posteriorly when comparing the zero b-value profile (blue) to the high b-value profile (orange). If the correction employs a non diffusion-encoded reference, the difference in contrast may cause the high b-value data to be erroneously scaled in the antero-posterior direction to fit the low b-value signal outline.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4631453&req=5

pone.0141825.g001: The challenge: Motion and eddy-current correction of diffusion MRI data in the elderly brain.Top row: Non diffusion-weighted MR-image (left), and diffusion-weighted images, encoded using a b-value of 1000 s/mm2 (middle) and 2750 s/mm2 (right) and averaged across multiple directions. Note that the rim of CSF surrounding the anterior part of the brain visualized in the non-diffusion weighted image to the left is absent in the diffusion weighted images. Bottom: Normalized plot of the logarithm of the MR signal as a function of position along the lines indicated in the images at the top. The anterior position where the MR signal turns into background is shifted posteriorly when comparing the zero b-value profile (blue) to the high b-value profile (orange). If the correction employs a non diffusion-encoded reference, the difference in contrast may cause the high b-value data to be erroneously scaled in the antero-posterior direction to fit the low b-value signal outline.
Mentions: We will refer to the method where a full affine transform is used to register diffusion-weighted volumes to a non diffusion-weighted reference by optimizing the mutual information as the ‘conventional method’. Although mutual information metrics are designed to allow registration of images with different contrasts, the conventional method suffers from poor accuracy [16], mainly due to the large difference in contrast between low and high b-value images. This difference is most pronounced where a rim of CSF surrounds the brain, which is common in elderly subjects and patients with cerebral atrophy. This rim of CSF is clearly visible in non diffusion-weighted images, but is completely attenuated in high b-value images, which results in an inward shift of the apparent brain outline (Fig 1). This shift may induce errors in conventional motion and eddy-current correction of high b-value data, since image registration algorithms tend to match borders. Extrapolation-based correction, where reference volumes with appropriate high b-value contrast are extrapolated from low b-value data, was suggested by Ben-Amitay et al as a potential solution [16]. The benefit of such a method is that low b-value data can be corrected using the conventional method with a precision sufficient for accurate extrapolation of undistorted reference volumes. Ben-Amitay et al used standard DTI analysis on the low b-value data, and adapted the results for the CHARMED model in order to extrapolate to high b-value shells. However, standard DTI performs poorly in regions where tissue is mixed with free water such as CSF [17], which may have a negative impact on the extrapolation.

Bottom Line: Conventional correction resulted in systematic registration errors for high b-value data.The extrapolation-based methods did not exhibit such errors, yielding more accurate tractography and up to 50% lower standard deviation in DKI metrics.Statistically significant differences were found between patients and controls when using the extrapolation-based motion correction that were not detected when using the conventional method.

View Article: PubMed Central - PubMed

Affiliation: Lund University Bioimaging Center, Lund University, Lund, Sweden.

ABSTRACT

Purpose: Conventional motion and eddy-current correction, where each diffusion-weighted volume is registered to a non diffusion-weighted reference, suffers from poor accuracy for high b-value data. An alternative approach is to extrapolate reference volumes from low b-value data. We aim to compare the performance of conventional and extrapolation-based correction of diffusional kurtosis imaging (DKI) data, and to demonstrate the impact of the correction approach on group comparison studies.

Methods: DKI was performed in patients with Parkinson's disease dementia (PDD), and healthy age-matched controls, using b-values of up to 2750 s/mm2. The accuracy of conventional and extrapolation-based correction methods was investigated. Parameters from DTI and DKI were compared between patients and controls in the cingulum and the anterior thalamic projection tract.

Results: Conventional correction resulted in systematic registration errors for high b-value data. The extrapolation-based methods did not exhibit such errors, yielding more accurate tractography and up to 50% lower standard deviation in DKI metrics. Statistically significant differences were found between patients and controls when using the extrapolation-based motion correction that were not detected when using the conventional method.

Conclusion: We recommend that conventional motion and eddy-current correction should be abandoned for high b-value data in favour of more accurate methods using extrapolation-based references.

No MeSH data available.


Related in: MedlinePlus