Derek K Jones

Cardiff University, Cardiff, Wales, United Kingdom

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Publications (65)307.32 Total impact

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    ABSTRACT: Diffusion MRI is used widely to probe microstructural alterations in neurological and psychiatric disease. However, ageing and neurodegeneration are also associated with atrophy, which leads to artefacts through partial volume effects due to cerebrospinal-fluid contamination (CSFC). The aim of this study was to explore the influence of CSFC on apparent microstructural changes in mild cognitive impairment (MCI) at several spatial levels: individually reconstructed tracts; at the level of a whole white matter skeleton (tract-based spatial statistics); and histograms derived from all white matter. 25 individuals with MCI and 20 matched controls underwent diffusion MRI. We corrected for CSFC using a post-acquisition voxel-by-voxel approach of free-water elimination. Tracts varied in their susceptibility to CSFC. The apparent pattern of tract involvement in disease shifted when correction was applied. Both spurious group differences, driven by CSFC, and masking of true differences were observed. Tract-based spatial statistics were found to be robust across much of the skeleton but with some localised CSFC effects. Diffusivity measures were affected disproportionately in MCI, and group differences in fornix microstructure were exaggerated. Group differences in white matter histogram measures were also partly driven by CSFC. For diffusivity measures, up to two thirds of observed group differences were due to CSFC. Our results demonstrate that CSFC has an impact on quantitative differences between MCI and controls. Furthermore, it affects the apparent spatial pattern of white matter involvement. Free-water elimination provides a step towards disentangling intrinsic and volumetric alterations in individuals prone to atrophy.
    NeuroImage 02/2014; · 6.25 Impact Factor
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    ABSTRACT: Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter(e.g., local fibre architecture, axon morphology, myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametricdata for a comprehensive assessment of white matter properties. The present work exploits that framework to characterize the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, blackwith the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterizing the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, blackshowing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts.
    NeuroImage 12/2013; · 6.25 Impact Factor
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    ABSTRACT: The prevalence of obesity and associated health conditions is increasing in the developed world. Obesity is related to atrophy and dysfunction of the hippocampus and hippocampal lesions may lead to increased appetite and weight gain. The hippocampus is connected via the fornix tract to the hypothalamus, orbitofrontal cortex, and the nucleus accumbens, all key structures for homeostatic and reward related control of food intake. The present study employed diffusion MRI tractography to investigate the relationship between microstructural properties of the fornix and variation in Body Mass Index (BMI), within normal and overweight ranges, in a group of community-dwelling older adults (53-93 years old). Larger BMI was associated with larger axial and mean diffusivity in the fornix (r = 0.64 and r = 0.55 respectively), relationships that were most pronounced in overweight individuals. Moreover, controlling for age, education, cognitive performance, blood pressure and global brain volume increased these correlations. Similar associations were not found in the parahippocampal cingulum, a comparison temporal association pathway. Thus, microstructural changes in fornix white matter were observed in older adults with increasing BMI levels from within normal to overweight ranges, so are not exclusively related to obesity. We propose that hippocampal-hypothalamic-prefrontal interactions, mediated by the fornix, contribute to the healthy functioning of networks involved in food intake control. The fornix, in turn, may display alterations in microstructure that reflect weight gain.
    PLoS ONE 01/2013; 8(3):e59849. · 3.73 Impact Factor
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    ABSTRACT: Cognitive control, an important facet of human cognition, provides flexibility in response to varying behavioral demands. Previous work has focused on the role of prefrontal cortex, notably the anterior cingulate cortex. However, it is now clear that this is one node of a distributed cognitive network. In this emerging network view, structural connections are inherent elements, but their role has not been emphasized. Furthermore, lesion and functional imaging studies have contributed little knowledge about anatomical segregation, functional specialization, and behavioral importance of white matter connections. The relationship between cognitive control and microstructure of connections within the cingulum, a major white matter tract and conduit of projections to prefrontal sites, was probed in vivo in humans with diffusion MRI. Twenty healthy controls and 25 individuals with amnestic mild cognitive impairment (MCI), an early stage of age-associated cognitive deterioration, underwent cognitive testing, including several measures of cognitive control. For each individual, the anterior, middle, posterior, and parahippocampal portions of the cingulum bundle were reconstructed separately using deterministic tractography and anatomical landmarks. Microstructural variation in the left anterior cingulum was closely related to interindividual control based on verbal or symbolic rules. Errors in a task that involved maintenance of spatial rules were largely restricted to patients with MCI and were related, additionally, to right anterior cingulum microstructure. Cognitive control in MCI was also independently related to posterior parahippocampal connections. These results show how specific subpopulations of connections are critical in cognitive control and illustrate fine-grained anatomical specializations in the white matter infrastructure of this network.
    Journal of Neuroscience 12/2012; 32(49):17612-17619. · 6.91 Impact Factor
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    ABSTRACT: OBJECTIVE: To examine the pattern of association between microstructure of temporal lobe connections and the breakdown of episodic memory that is a core feature of mild cognitive impairment (MCI). METHODS: Twenty-five individuals with MCI and 20 matched controls underwent diffusion MRI and cognitive assessment. Three temporal pathways were reconstructed by tractography: fornix, parahippocampal cingulum (PHC), and uncinate fasciculus. Tissue volume fraction-a tract-specific measure of atrophy-and microstructural measures were derived for each tract. To test specificity of associations, a comparison tract (corticospinal tract) and control cognitive domains were also examined. RESULTS: In MCI, tissue volume fraction was reduced in the fornix. Axial and radial diffusivity were increased in uncinate and PHC implying more subtle microstructural change. In controls, tissue volume fraction in the fornix was the predominant correlate of free recall. In contrast, in MCI, the strongest relationship was with left PHC. Microstructure of uncinate and PHC also correlated with recognition memory, and recognition confidence, in MCI. CONCLUSIONS: Episodic memory in MCI is related to the structure of multiple temporal association pathways. These associations are not confined to the fornix, as they are in healthy young and older adults. In MCI, because of a compromised fornix, alternative pathways may contribute disproportionally to episodic memory performance.
    Neurology 11/2012; · 8.25 Impact Factor
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    ABSTRACT: The development of therapeutic strategies that promote functional recovery is a major goal of multiple sclerosis (MS) research. Neuroscientific and methodological advances have improved our understanding of the brain's recovery from damage, generating novel hypotheses about potential targets and modes of intervention, and laying the foundation for development of scientifically informed recovery-promoting strategies in interventional studies. This Review aims to encourage the transition from characterization of recovery mechanisms to development of strategies that promote recovery in MS. We discuss current evidence for functional reorganization that underlies recovery and its implications for development of new recovery-oriented strategies in MS. Promotion of functional recovery requires an improved understanding of recovery mechanisms that can be modulated by interventions and the development of robust measurements of therapeutic effects. As imaging methods can be used to measure functional and structural alterations associated with recovery, this Review discusses their use to obtain reliable markers of the effects of interventions.
    Nature Reviews Neurology 09/2012; · 15.52 Impact Factor
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    ABSTRACT: Diffusion-weighted MRI (DW-MRI) has been increasingly used in imaging neuroscience over the last decade. An early form of this technique, diffusion tensor imaging (DTI) was rapidly implemented by major MRI scanner companies as a scanner selling point. Due to the ease of use of such implementations, and the plausibility of some of their results, DTI was leapt on by imaging neuroscientists who saw it as a powerful and unique new tool for exploring the structural connectivity of human brain. However, DTI is a rather approximate technique, and its results have frequently been given implausible interpretations that have escaped proper critique and have appeared misleadingly in journals of high reputation. In order to encourage the use of improved DW-MRI methods, which have a better chance of characterizing the actual fiber structure of white matter, and to warn against the misuse and misinterpretation of DTI, we review the physics of DW-MRI, indicate currently preferred methodology, and explain the limits of interpretation of its results. We conclude with a list of 'Do's and Don'ts' which define good practice in this expanding area of imaging neuroscience.
    NeuroImage 07/2012; · 6.25 Impact Factor
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    ABSTRACT: It has long been recognized that the diffusion tensor model is inappropriate to characterize complex fiber architecture, causing tensor-derived measures such as the primary eigenvector and fractional anisotropy to be unreliable or misleading in these regions. There is however still debate about the impact of this problem in practice. A recent study using a Bayesian automatic relevance detection (ARD) multicompartment model suggested that a third of white matter (WM) voxels contain crossing fibers, a value that, whilst already significant, is likely to be an underestimate. The aim of this study is to provide more robust estimates of the proportion of affected voxels, the number of fiber orientations within each WM voxel, and the impact on tensor-derived analyses, using large, high-quality diffusion-weighted data sets, with reconstruction parameters optimized specifically for this task. Two reconstruction algorithms were used: constrained spherical deconvolution (CSD), and the ARD method used in the previous study. We estimate the proportion of WM voxels containing crossing fibers to be ∼90% (using CSD) and 63% (using ARD). Both these values are much higher than previously reported, strongly suggesting that the diffusion tensor model is inadequate in the vast majority of WM regions. This has serious implications for downstream processing applications that depend on this model, particularly tractography, and the interpretation of anisotropy and radial/axial diffusivity measures. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.
    Human Brain Mapping 05/2012; · 6.88 Impact Factor
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    ABSTRACT: Altered white matter microstructure in tracts integral to mood regulation networks could underlie vulnerability to major depressive disorder (MDD). Guided by functional magnetic resonance studies, we explored whether a positive family history of MDD (FH+) and anhedonia (reduced capacity for pleasure) were associated with altered white matter microstructure in the cingulum bundles and uncinate fasciculi. Diffusion tensor magnetic resonance imaging data were acquired on 34 healthy female student volunteers (mean age 22 years). Exclusion criteria included other current or previous psychiatric disorder, current depression, and current psychotropic medication. Family history was determined using established criteria. Fiber tractography was performed for each individual for a priori tracts of interest and a comparison tract. Mean fractional anisotropy (FA), an index of microstructure, was calculated for each tract. Tracts were reconstructed in 18 FH+ individuals and 15 FH- individuals, who did not differ by age or subclinical depressive symptoms. FH+ subjects had 3% to 5% lower FA in the right and left cingulum bundles than FH- individuals (p = .012, p = .059, respectively). Post hoc analysis demonstrated 8% lower FA in the left subgenual cingulate (p = .007). Hedonic tone correlated positively with FA in the right and left cingulum bundles (r = .342, p = .052; r = .477, p = .005, respectively), and the left subgenual cingulum (r = .500, p = .003). Both family history of MDD and subclinical anhedonia are associated with reduced FA in the bilateral cingulum bundles, particularly in the left subgenual cingulum. Altered cingulum white matter architecture is implicated in the etiology of MDD.
    Biological psychiatry 02/2012; 72(4):296-302. · 8.93 Impact Factor
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    ABSTRACT: In diffusion tensor magnetic resonance imaging (DT-MRI), limitations concerning complex fiber architecture (when an image voxel contains fiber populations with more than one dominant orientation) are well-known. Fractional anisotropy (FA) values are lower in such areas because of a lower directionality of diffusion on the voxel-scale, which makes the interpretation of FA less straightforward. Moreover, the interpretation of the axial and radial diffusivities is far from trivial when there is more than one dominant fiber orientation within a voxel. In this work, using (i) theoretical considerations, (ii) simulations, and (iii) experimental data, it is demonstrated that the mean diffusivity (or the trace of the diffusion tensor) is lower in complex white matter configurations, compared with tissue where there is a single dominant fiber orientation within the voxel. We show that the magnitude of this reduction depends on various factors, including configurational and microstructural properties (e.g., the relative contributions of different fiber populations) and acquisition settings (e.g., the b-value). These results increase our understanding of the quantitative metrics obtained from DT-MRI and, in particular, the effect of the microstructural architecture on the mean diffusivity. More importantly, they reinforce the growing awareness that differences in DT-MRI metrics need to be interpreted cautiously.
    NeuroImage 02/2012; 59(3):2208-16. · 6.25 Impact Factor
  • Shani Ben-Amitay, Derek K Jones, Yaniv Assaf
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    ABSTRACT: It has been suggested that, high b-value diffusion weighted MRI improves the sensitivity and specificity of these images to tissue microstructure when compared with "clinical" b-value diffusion weighted MRI (b ≈ 1000 s/mm(2)). However, it suffers from poor signal to noise ratio - leading to longer acquisition times and therefore more motion artifacts. Together with the orientational sensitivity of the diffusion weighted MRI signal, the contrast at different b-values and different gradient directions is significantly different. These features of high b-value diffusion images preclude the ability to perform conventional image-registration-based motion/distortion correction. Here, we suggest a framework based on both experimental data (diffusion tensor MRI) and simulations (using the composite hindered and restricted model of diffusion framework) to correct the motion induced misalignments and artifacts of high b-value diffusion weighted MRI. This approach was evaluated using visual assessment of the registered diffusion weighted MRI and the composite hindered and restricted model of diffusion analysis results, as well as residual analysis to assess the quality of the composite hindered and restricted model of diffusion fitting. Both qualitative and quantitative results demonstrate an improvement in fitting the data to the composite hindered and restricted model of diffusion model following the suggested registration framework, thereby, addressing a long-standing problem and making the correction of motion/distortions in data collected at high b-values feasible for the first time.
    Magnetic Resonance in Medicine 12/2011; 67(6):1694-702. · 3.27 Impact Factor
  • Silvia De Santis, Yaniv Assaf, Derek K Jones
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    ABSTRACT: The aim of this work was to understand biophysical substrate underpinning contrast in diffusional kurtosis imaging (DKI) in white matter, using the composite hindered and restricted model of diffusion (CHARMED). A theoretical relationship between the kurtosis function K and the CHARMED parameters, i.e., the restricted volume fraction RF and the axonal longitudinal diffusivity D was derived for the propagator used in the CHARMED model. Evidence for a similar correlation between these measures was then investigated in vivo across different WM regions in five healthy young subjects that underwent a CHARMED protocol at 3T. Our theoretical treatment shows that K has an increasing trend for both increasing RF values and increasing D. In vivo, a significant positive correlation (P < 0.001) was found between the kurtosis orthogonal to the fibre orientation K (⊥) and RF. A multilinear regression showed that K (⊥) values are better explained by a mixed contribution of both RF and D. The CHARMED model was used to understand whether and where DKI contrast can be explained in terms of the underlying axonal geometry. This work demonstrates that the information contained in DKI overlaps with the information extracted by CHARMED in areas of higher intra-voxel directional coherence.
    MAGMA Magnetic Resonance Materials in Physics Biology and Medicine 11/2011; 25(4):267-76. · 1.86 Impact Factor
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    ABSTRACT: Human episodic memory is supported by networks of white matter tracts that connect frontal, temporal, and parietal regions. Degradation of white matter microstructure is increasingly recognized as a general mechanism of cognitive deterioration with aging. However, atrophy of gray matter regions also occurs and, to date, the potential role of specific white matter connections has been largely ignored. Changes to frontotemporal tracts may be important for the decline of episodic memory; while frontotemporal cooperation is known to be critical, the precise pathways of interaction are unknown. Diffusion-weighted MRI tractography was used to reconstruct three candidate fasciculi known to link components of memory networks: the fornix, the parahippocampal cingulum, and the uncinate fasciculus. Age-related changes in the microstructure of these tracts were investigated in 40 healthy older adults between the ages of 53 and 93 years. The relationships between aging, microstructure, and episodic memory were assessed for each individual tract. Age-related reductions of mean fractional anisotropy and/or increased mean diffusivity were found in all three tracts. However, age-related decline in recall was specifically associated with degradation of fornix microstructure, consistent with the view that this tract is important for episodic memory. In contrast, a decline in uncinate fasciculus microstructure was linked to impaired error monitoring in a visual object-location association task, echoing the effects of uncinate transection in monkeys. These results suggest that degradation of microstructure in the fornix and the uncinate fasciculus make critical but differential contributions to the mechanisms underlying age-related cognitive decline and subserve distinct components of memory.
    Journal of Neuroscience 09/2011; 31(37):13236-45. · 6.91 Impact Factor
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    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.
    NeuroImage 09/2011; 59(2):1394-403. · 6.25 Impact Factor
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    Richard A Edden, Derek K Jones
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    ABSTRACT: Group comparisons of indices derived from diffusion tensor imaging are common in the literature. An increasingly popular approach to performing such comparisons is the skeleton-projection based approach where, for example, fractional anisotropy (FA) values are projected onto a skeletonized version of the data to minimize differences due to spatial misalignment. In this work, we examine the spatial heterogeneity of the statistical power to detect group differences, and show that there is an intrinsic spatial heterogeneity, with more 'central' structures having less variance within a population. Importantly, we also demonstrate a previously unreported feature of skeleton-based analysis methods, that is that the width of the skeleton depends on the relative orientation to the imaging matrix. Due to the way in which the inferential statistics are performed, this means that structures that are obliquely oriented to the imaging matrix are more likely to show significant differences than when aligned with the imaging matrix. This has profound implications for the interpretation of results obtained from such analysis, especially when there are no a priori hypotheses concerning the spatial location of any group differences. For a uniform (DC) offset between two groups, the skeleton projection-based approaches will be most likely to reveal a difference in centrally located white matter structures oriented obliquely to the imaging matrix.
    Journal of neuroscience methods 07/2011; 201(1):213-9. · 2.30 Impact Factor
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    ABSTRACT: Functional magnetic resonance imaging (fMRI) techniques allow definition of cortical nodes that are presumed to be components of large-scale distributed brain networks involved in cognitive processes. However, very few investigations examine whether such functionally defined areas are in fact structurally connected. Here, we used combined fMRI and diffusion MRI-based tractography to define the cortical network involved in saccadic eye movement control in humans. The results of this multimodal imaging approach demonstrate white matter pathways connecting the frontal eye fields and supplementary eye fields, consistent with the known connectivity of these regions in macaque monkeys. Importantly, however, these connections appeared to be more prominent in the right hemisphere of humans. In addition, there was evidence of a dorsal frontoparietal pathway connecting the frontal eye field and the inferior parietal lobe, also right hemisphere dominant, consistent with specialization of the right hemisphere for directed attention in humans. These findings demonstrate the utility and potential of using multimodal imaging techniques to define large-scale distributed brain networks, including those that demonstrate known hemispheric asymmetries in humans.
    Cerebral Cortex 06/2011; 22(4):765-75. · 6.83 Impact Factor
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    ABSTRACT: Constrained spherical deconvolution (CSD) is a new technique that, based on high-angular resolution diffusion imaging (HARDI) MR data, estimates the orientation of multiple intravoxel fiber populations within regions of complex white matter architecture, thereby overcoming the limitations of the widely used diffusion tensor imaging (DTI) technique. One of its main applications is fiber tractography. The noisy nature of diffusion-weighted (DW) images, however, affects the estimated orientations and the resulting fiber trajectories will be subject to uncertainty. The impact of noise can be large, especially for HARDI measurements, which employ relatively high b-values. To quantify the effects of noise on fiber trajectories, probabilistic tractography was introduced, which considers multiple possible pathways emanating from one seed point, taking into account the uncertainty of local fiber orientations. In this work, a probabilistic tractography algorithm is presented based on CSD and the residual bootstrap. CSD, which provides accurate and precise estimates of multiple fiber orientations, is used to extract the local fiber orientations. The residual bootstrap is used to estimate fiber tract probability within a clinical time frame, without prior assumptions about the form of uncertainty in the data. By means of Monte Carlo simulations, the performance of the CSD fiber pathway uncertainty estimator is measured in terms of accuracy and precision. In addition, the performance of the proposed method is compared to state-of-the-art DTI residual bootstrap tractography and to an existing probabilistic CSD tractography algorithm using clinical DW data.
    Human Brain Mapping 03/2011; 32(3):461-79. · 6.88 Impact Factor
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    ABSTRACT: During the last decade, diffusion tensor imaging (DTI) has been used extensively to investigate microstructural properties of white matter fiber pathways. In many of these DTI-based studies, fiber tractography has been used to infer relationships between bundle-specific mean DTI metrics and measures-of-interest (e.g., when studying diffusion changes related to age, cognitive performance, etc.) or to assess potential differences between populations (e.g., comparing males vs. females, healthy vs. diseased subjects, etc.). As partial volume effects (PVEs) are known to affect tractography and, subsequently, the estimated DTI measures sampled along these reconstructed tracts in an adverse way, it is important to gain insight into potential confounding factors that may modulate this PVE. For instance, for thicker fiber bundles, the contribution of PVE-contaminated voxels to the mean metric for the entire fiber bundle will be smaller, and vice-versa - which means that the extent of PVE-contamination will vary from bundle to bundle. With the growing popularity of tractography-based methods in both fundamental research and clinical applications, it is of paramount importance to examine the presence of PVE-related covariates, such as thickness, orientation, curvature, and shape of a fiber bundle, and to investigate the extent to which these hidden confounds affect diffusion measures. To test the hypothesis that these PVE-related covariates modulate DTI metrics depending on the shape of a bundle, we performed simulations with synthetic diffusion phantoms and analyzed bundle-specific DTI measures of the cingulum and the corpus callosum in 55 healthy subjects. Our results indicate that the estimated bundle-specific mean values of diffusion metrics, including the frequently used fractional anisotropy and mean diffusivity, were indeed modulated by fiber bundle thickness, orientation, and curvature. Correlation analyses between gender and diffusion measures yield different results when volume is included as a covariate. This indicates that incorporating these PVE-related factors in DTI analyses is imperative to disentangle changes in "true microstructural" tissue properties from these hidden covariates.
    NeuroImage 01/2011; 55(4):1566-76. · 6.25 Impact Factor
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    Derek K Jones, Alexander Leemans
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    ABSTRACT: Diffusion tensor MRI (DT-MRI) is the only non-invasive method for characterising the microstructural organization of tissue in vivo. Generating parametric maps that help to visualise different aspects of the tissue microstructure (mean diffusivity, tissue anisotropy and dominant fibre orientation) involves a number of steps from deciding on the optimal acquisition parameters on the scanner, collecting the data, pre-processing the data and fitting the model to generating final parametric maps for entry into statistical data analysis. Here, we describe an entire protocol that we have used on over 400 subjects with great success in our laboratory. In the 'Notes' section, we justify our choice of the various parameters/choices along the way so that the reader may adapt/modify the protocol to their own time/hardware constraints.
    Methods in molecular biology (Clifton, N.J.) 01/2011; 711:127-44.

Publication Stats

5k Citations
954 Downloads
4k Views
307.32 Total Impact Points

Institutions

  • 2007–2013
    • Cardiff University
      • • Institute of Psychological Medicine and Clinical Neurosciences
      • • School of Psychology
      Cardiff, Wales, United Kingdom
  • 2011–2012
    • University Medical Center Utrecht
      • • Image Sciences Institute
      • • Department of Radiology
      Utrecht, Provincie Utrecht, Netherlands
    • Johns Hopkins University
      Baltimore, Maryland, United States
  • 2005–2010
    • King's College London
      • • Department of Psychological Medicine
      • • Institute of Psychiatry
      • • Department of Neuroimaging
      London, ENG, United Kingdom
  • 2006
    • National Institute of Child Health and Human Development
      Maryland, United States
  • 2002–2006
    • National Institutes of Health
      • Section on Tissue Biophysics and Biomimetics
      Bethesda, MD, United States
  • 1999–2002
    • University of Leicester
      Leiscester, England, United Kingdom