Literature DB >> 21924365

How and how not to correct for CSF-contamination in diffusion MRI.

Claudia Metzler-Baddeley1, Michael J O'Sullivan, Sonya Bells, Ofer Pasternak, Derek K Jones.   

Abstract

Diffusion MRI is used extensively to investigate changes in white matter microstructure related to brain development and pathology. Ageing, however, is also associated with significant white and grey matter loss which in turn can lead to cerebrospinal fluid (CSF) based partial volume artefacts in diffusion MRI metrics. This is especially problematic in regions prone to CSF contamination, such as the fornix and the genu of corpus callosum, structures that pass through or close to the ventricles respectively. The aim of this study was to model the effects of CSF contamination on diffusion MRI metrics, and to evaluate different post-acquisition strategies to correct for CSF-contamination: Controlling for whole brain volume and correcting on a voxel-wise basis using the Free Water Elimination (FWE) approach. Using the fornix as an exemplar of a structure prone to CSF-contamination, corrections were applied to tract-specific and voxel-based [tract based spatial statistics (TBSS)] analyses of empirical DT-MRI data from 39 older adults (53-93 years of age). In addition to significant age-related decreases in whole brain volume and fornix tissue volume fraction, age was also associated with a reduction in mean fractional anisotropy and increase in diffusivity metrics in the fornix. The experimental data agreed with the simulations in that diffusivity metrics (mean diffusivity, axial and radial diffusivity) were more prone to partial volume CSF-contamination errors than fractional anisotropy. After FWE-based voxel-by-voxel partial volume corrections, the significant positive correlations between age and diffusivity metrics, in particular with axial diffusivity, disappeared whereas the correlation with anisotropy remained. In contrast, correcting for whole brain volume had little effect in removing these spurious correlations. Our study highlights the importance of correcting for CSF-contamination partial volume effects in the structures of interest on a voxel-by-voxel basis prior to drawing inferences about underlying changes in white matter structures and have implications for the interpretation of many recent diffusion MRI results in ageing and disease.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21924365     DOI: 10.1016/j.neuroimage.2011.08.043

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  135 in total

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3.  Gray matter alterations in early aging: a diffusion magnetic resonance imaging study.

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Journal:  Hum Brain Mapp       Date:  2013-12-31       Impact factor: 5.038

4.  A new approach to corpus callosum anomalies in idiopathic scoliosis using diffusion tensor magnetic resonance imaging.

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5.  Amyloid burden accelerates white matter degradation in cognitively normal elderly individuals.

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6.  Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging.

Authors:  Alicia W Yang; Jens H Jensen; Caixia C Hu; Ali Tabesh; Maria F Falangola; Joseph A Helpern
Journal:  J Magn Reson Imaging       Date:  2012-10-03       Impact factor: 4.813

7.  Perivascular space fluid contributes to diffusion tensor imaging changes in white matter.

Authors:  Farshid Sepehrband; Ryan P Cabeen; Jeiran Choupan; Giuseppe Barisano; Meng Law; Arthur W Toga
Journal:  Neuroimage       Date:  2019-04-30       Impact factor: 6.556

8.  Cingulum microstructure predicts cognitive control in older age and mild cognitive impairment.

Authors:  Claudia Metzler-Baddeley; Derek K Jones; Jessica Steventon; Laura Westacott; John P Aggleton; Michael J O'Sullivan
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9.  Re-examining age-related differences in white matter microstructure with free-water corrected diffusion tensor imaging.

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Journal:  Neurobiol Aging       Date:  2018-08-01       Impact factor: 4.673

Review 10.  Longitudinal Progression Markers of Parkinson's Disease: Current View on Structural Imaging.

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Journal:  Curr Neurol Neurosci Rep       Date:  2018-10-02       Impact factor: 5.081

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