The effect of template selection on diffusion tensor voxel-based analysis results

Hecke, Wim Van; Leemans, Alexander; Sage, Caroline; Emsell, Louise; Veraart, Jelle; Sijbers, Jan; Sunaert, Stefan; Parizel, Paul M.

doi:10.1016/j.neuroimage.2010.12.005

Cited by 60 publications

(56 citation statements)

References 40 publications

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“…To minimize registration errors, we used a population atlasebased approach and sophisticated well-validated nonlinear registration methods (Avants et al, 2008) and assessed registration accuracy at each stage of the processing and analysis pipeline. However, as with all studies of this type, we cannot rule out the contribution of subtle registration, interpolation, and partial volume effects to our findings (Van Hecke et al, 2011;Vos et al, 2011). In this context, although we did not detect voxelwise correlations between age and WM volume, it is still possible that the associations we have detected reflect age-related macrostructural changes rather than changes in specific microstructural elements such as myelin content.…”

Section: Methodological Considerationscontrasting

confidence: 53%

Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI

Billiet

Vandenbulcke

Mädler

et al. 2015

Neurobiology of Aging

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Age-related microstructural differences have been detected using diffusion tensor imaging (DTI). Although DTI is sensitive to the effects of aging, it is not specific to any underlying biological mechanism, including demyelination. Combining multiexponential T2 relaxation (MET2) and multishell diffusion MRI (dMRI) techniques may elucidate such processes. Multishell dMRI and MET2 data were acquired from 59 healthy participants aged 17-70 years. Whole-brain and regional age-associated correlations of measures related to multiple dMRI models (DTI, diffusion kurtosis imaging [DKI], neurite orientation dispersion and density imaging [NODDI]) and myelin-sensitive MET2 metrics were assessed. DTI and NODDI revealed widespread increases in isotropic diffusivity with increasing age. In frontal white matter, fractional anisotropy linearly decreased with age, paralleled by increased "neurite" dispersion and no difference in myelin water fraction. DKI measures and neurite density correlated well with myelin water fraction and intracellular and extracellular water fraction. DTI estimates remain among the most sensitive markers for age-related alterations in white matter. NODDI, DKI, and MET2 indicate that the initial decrease in frontal fractional anisotropy may be due to increased axonal dispersion rather than demyelination.

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Section: Methodological Considerationscontrasting

confidence: 53%

Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI

Billiet

Vandenbulcke

Mädler

et al. 2015

Neurobiology of Aging

Self Cite

186

189

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“…In relation to template type, the observed differences are of interest, as previous findings have shown that study-specific templates provide greater sensitivity and accuracy than standard templates [39]. The results in this study show a slight improvement in reliability when using a study-specific template; however, in three methods and two regions, age modeling slightly improved with the standard template.…”

Section: Discussionmentioning

confidence: 48%

“…There has also been extensive testing of skeleton-based analysis to understand its strengths and limitations [28] [26] [37] as well as comparing to voxel-based analysis and region-based analysis [20] [21]. Previous work has also evaluated the choice of template type, showing the advantages of study-specific and high-quality templates [38] [39] [40] [41]. This paper builds on these prior findings by expanding the range of methods simultaneously compared in evaluation.…”

Section: Introductionmentioning

confidence: 99%

A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging

2017

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This paper presents a comparative evaluation of methods for automated voxel-based spatial mapping in diffusion tensor imaging studies. Such methods are an essential step in computational pipelines and provide anatomically comparable measurements across a population in atlas-based studies. To better understand their strengths and weaknesses, we tested a total of eight methods for voxel-based spatial mapping in two types of diffusion tensor templates. The methods were evaluated with respect to scan-rescan reliability and an application to normal aging. The methods included voxel-based analysis with and without smoothing, two types of region-based analysis, and combinations thereof with skeletonization. The templates included a study-specific template created with DTI-TK and the IIT template serving as a standard template. To control for other factors in the pipeline, the experiments used a common dataset, acquired at 1.5T with a single shell high angular resolution diffusion MR imaging protocol, and tensor-based spatial normalization with DTI-TK. Scan-rescan reliability was assessed using the coefficient of variation (CV) and intraclass correlation (ICC) in eight subjects with three scans each. Sensitivity to normal aging was assessed in a population of 80 subjects aged 25 to 65 years old, and methods were compared with respect to the anatomical agreement of significant findings and the R2 of the associated models of fractional anisotropy. The results show that reliability depended greatly on the method used for spatial mapping. The largest differences in reliability were found when adding smoothing and comparing voxel-based and region-based analyses. Skeletonization and template type were found to have either a small or negligible effect on reliability. The aging results showed agreement among the methods in nine brain areas, with some methods showing more sensitivity than others. Skeletonization and smoothing were not major factors affecting sensitivity to aging, but the standard template showed higher R2 in several conditions. A structural comparison of the templates showed that large deformations between them may be related to observed differences in patterns of significant voxels. Most areas showed significantly higher R2 with voxel-based analysis, particularly when clusters were smaller than the available regions-of-interest. Looking forward, these results can potentially help to interpret results from existing white matter imaging studies, as well as provide a resource to help in planning future studies to maximize reliability and sensitivity with regard to the scientific goals at hand.

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“…A key step of both voxel- and fixel-based analysis is the spatial normalisation of all subject images, ideally to a representative average study-specific template (Mohammadi et al, 2012, Van Hecke et al, 2011). This involves deriving a non-linear warp for each subject that maps each point in the template image to a corresponding point in the subject image.…”

Section: Methodsmentioning

confidence: 99%

Investigating white matter fibre density and morphology using fixel-based analysis

et al. 2017

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Voxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel (‘fixels’), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e.g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable.

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The effect of template selection on diffusion tensor voxel-based analysis results

Cited by 60 publications

References 40 publications

Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI

Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI

A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging

Investigating white matter fibre density and morphology using fixel-based analysis

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