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Derek K Jones

Publications and source records attributed to Derek K Jones.

18 recordsLinked to original sources
PubMed2006

Age effects on diffusion tensor magnetic resonance imaging tractography measures of frontal cortex connections in schizophrenia.

Diffusion tensor magnetic resonance imaging (DT-MRI) has previously been used to investigate white matter tracts in schizophrenia, with inconsistent results. The aim of the study was to use a novel method for tract-specific measurements of fronto-temporal fasciculi in early-onset schizophrenia. We hypothesized that by making tract-specific measurements, clear diffusion abnormalities would be revealed in specific fasciculi in schizophrenia. Measurements of diffusion anisotropy and mean diffusivity were localized within fronto-temporal fasciculi by forming 3-D reconstructions of the cingulum, uncinate, superior longitudinal, and inferior fronto-occipital fasciculi using diffusion tensor tractography. We were limited in our ability to test our hypothesis by the important and surprising finding that age affected DT-MRI-based measures in schizophrenia patients in a different way from comparison subjects, most notably in the left superior longitudinal fasciculus. The youngest schizophrenia patients that we studied had lower diffusion anisotropy than age-matched comparison subjects, but this difference diminished with increasing age. The main conclusion of this study was that direct comparisons of absolute DT-MRI-based measures between individuals with schizophrenia and comparison subjects may be problematic and misleading because of underlying age-related differences in brain maturation between groups.

Adult↗
PubMed2006

Just how much data need to be collected for reliable bootstrap DT-MRI?

Diffusion tensor MRI (DT-MRI) can provide estimates of fiber orientation derived from the orientational dependence of the diffusivity of water molecules, enabling the reconstruction of white matter fiber pathways using tractography methods. However, noise arising from various sources can introduce uncertainty into the estimates of the elements of the diffusion tensor, resulting in errors in fiber orientation estimates such that tractography reconstructions of fiber pathways potentially can be imprecise and inaccurate. Recently, attempts have been made to characterize the uncertainty in DT-MRI-derived parameters using the bootstrap method; however, several questions remain open regarding the number of repeat measurements and bootstraps required to accurately and precisely reconstruct the probability distributions of the DT-MRI parameters. This study investigates the accuracy and precision of the bootstrap method for characterizing distributions of DT-MRI parameters. A number of experimental bootstrap designs and sampling schemes containing different numbers of isotropically distributed gradient vectors are considered, using an idealized system where the true variability in each parameter is known. This study demonstrates that for most DT-MRI experiments, robust results will be obtained if the minimum number of bootstraps is approximately 500, and that at least five repeat samples of each diffusion-weighted intensity should be used for bootstrapping.

Algorithms↗
PubMed2005

Tract-specific anisotropy measurements in diffusion tensor imaging.

Diffusion tensor magnetic resonance imaging (DT-MRI) has been used to examine the microstructure of individual white matter tracts, often in neuropsychiatric conditions without identifiable focal pathology. However, the voxel-based group-mapping and region-of-interest (ROI) approaches used to analyse the data have inherent conceptual and practical difficulties. Taking the example of the genu of the corpus callosum in a sample of schizophrenic patients, we discuss the difficulties in attempting to replicate a voxel-based finding of reduced anisotropy using two ROI methods. Firstly we consider conventional ROIs; secondly, we present a novel tractography-based approach. The problems of both methods are explored, particularly of high variance and ROI definition. The potential benefits of the tractographic method for neuropsychiatric conditions with subtle and diffuse pathology are outlined.

Adult↗
PubMed2005

The effect of filter size on VBM analyses of DT-MRI data.

Voxel-based morphometry (VBM) has been used to analyze diffusion tensor MRI (DT-MRI) data in a number of studies. In VBM, following spatial normalization, data are smoothed to improve the validity of statistical inferences and to reduce inter-individual variation. However, the size of the smoothing filter used for VBM of DT-MRI data is highly variable across studies. For example, a literature review revealed that Gaussian smoothing kernels ranging in size (full width at half maximum) from zero to 16 mm have been used in DT-MRI VBM type studies. To investigate the effect of varying filter size in such analyses, whole brain DT-MRI data from 14 schizophrenic patients were compared with those of 14 matched control subjects using VBM, when the filter size was varied from zero to 16 mm. Within this range of smoothing, four different conclusions regarding apparent patient control differences could be made: (i) no significant patient-control differences; (ii) reduced FA in right superior temporal gyrus (STG) in patients; (iii) reduced FA in both right STG and left cerebellum in patients; and (iv) reduced FA only in left cerebellum in patients. These findings stress the importance of recognizing the effect of the matched filter theorem on VBM analyses of DT-MRI data. Finally, we investigated whether one of the underlying assumptions of parametric VBM, i.e., the normality of the residuals, is met. Our results suggest that, even with moderate smoothing, a large number of voxels within central white matter regions may have non-normally distributed residuals thus making valid statistical inferences with a parametric approach problematic in these areas.

Adult↗
PubMed2005

Perisylvian language networks of the human brain.

Early anatomically based models of language consisted of an arcuate tract connecting Broca's speech and Wernicke's comprehension centers; a lesion of the tract resulted in conduction aphasia. However, the heterogeneous clinical presentations of conduction aphasia suggest a greater complexity of perisylvian anatomical connections than allowed for in the classical anatomical model. This article re-explores perisylvian language connectivity using in vivo diffusion tensor magnetic resonance imaging tractography. Diffusion tensor magnetic resonance imaging data from 11 right-handed healthy male subjects were averaged, and the arcuate fasciculus of the left hemisphere reconstructed from this data using an interactive dissection technique. Beyond the classical arcuate pathway connecting Broca's and Wernicke's areas directly, we show a previously undescribed, indirect pathway passing through inferior parietal cortex. The indirect pathway runs parallel and lateral to the classical arcuate fasciculus and is composed of an anterior segment connecting Broca's territory with the inferior parietal lobe and a posterior segment connecting the inferior parietal lobe to Wernicke's territory. This model of two parallel pathways helps explain the diverse clinical presentations of conduction aphasia. The anatomical findings are also relevant to the evolution of language, provide a framework for Lichtheim's symptom-based neurological model of aphasia, and constrain, anatomically, contemporary connectionist accounts of language.

Adult↗
PubMed2005

RESTORE: robust estimation of tensors by outlier rejection.

Signal variability in diffusion weighted imaging (DWI) is influenced by both thermal noise and spatially and temporally varying artifacts such as subject motion and cardiac pulsation. In this paper, the effects of DWI artifacts on estimated tensor values, such as trace and fractional anisotropy, are analyzed using Monte Carlo simulations. A novel approach for robust diffusion tensor estimation, called RESTORE (for robust estimation of tensors by outlier rejection), is proposed. This method uses iteratively reweighted least-squares regression to identify potential outliers and subsequently exclude them. Results from both simulated and clinical diffusion data sets indicate that the RESTORE method improves tensor estimation compared to the commonly used linear and nonlinear least-squares tensor fitting methods and a recently proposed method based on the Geman-McClure M-estimator. The RESTORE method could potentially remove the need for cardiac gating in DWI acquisitions and should be applicable to other MR imaging techniques that use univariate or multivariate regression to fit MRI data to a model.

Algorithms↗
PubMed2005

Confidence mapping in diffusion tensor magnetic resonance imaging tractography using a bootstrap approach.

The bootstrap technique is an extremely powerful nonparametric statistical procedure for determining the uncertainty in a given statistic. However, its use in diffusion tensor MRI tractography remains virtually unexplored. This work shows how the bootstrap can be used to assign confidence to results obtained with deterministic tracking algorithms. By invoking the concept of a "tract-propagator," it also underlines the important effect of local fiber architecture or architectural milieu on tracking reproducibility. Finally, the practical advantages and limitations of the technique are discussed. Not only does the bootstrap allow any deterministic tractography algorithm to be used in a probabilistic fashion, but also its model-free inclusion of all sources of variability (including those that cannot be modeled) means that it provides the most realistic approach to probabilistic tractography.

Algorithms↗
PubMed2005

PASTA: pointwise assessment of streamline tractography attributes.

Diffusion tensor MRI tractography aims to reconstruct noninvasively the 3D trajectories of white matter fasciculi within the brain, providing neuroscientists and clinicians with a potentially useful tool for mapping brain architecture. While this technique is widely used to visualize white matter pathways, the associated uncertainty in fiber orientation and artifacts have, to date, not been visualized in conjunction with the trajectory data. In this work, the bootstrap method was used to determine the distributions of diffusion indices such as trace and anisotropy, together with the uncertainty in fiber orientation. A novel visualization scheme was developed to encode this information at each point along reconstructed trajectories. By integrating these schemes into a graphical user interface, a new tool which we call PASTA (Pointwise Assessment of Streamline Tractography Attributes) was created to facilitate identification of artifacts in tractography that would otherwise go undetected.

Brain Mapping↗
PubMed2005

A diffusion tensor magnetic resonance imaging study of frontal cortex connections in very-late-onset schizophrenia-like psychosis.

OBJECTIVE: Onset of psychosis after the age of 60 may be associated with structural abnormalities within cerebral white matter. The authors looked within white-matter tracts, which mediate connectivity of the frontal lobes, in psychotic patients for evidence of loss of fiber integrity consistent with degenerative damage. METHODS: Fourteen patients with very-late-onset schizophrenia-like psychosis and an age-matched control group underwent diffusion tensor magnetic resonance imaging. Tract maps were constructed for each subject from the imaging data, and measurements of fractional anisotropy and mean diffusivity were made within the uncinate, superior longitudinal, and inferior occipito-frontal fasciculi, and the cingulum. RESULTS: There were no significant differences in fractional anisotropy, a measure of the ordering of axons within fiber tracts, nor in mean diffusivity, an orientationally-averaged measure of the bulk diffusivity within each voxel, between patients and control subjects. CONCLUSION: The lack of difference in fractional anisotropy and mean diffusivity measures between patients and controls argues against the presence of structural abnormalities within these tracts and the notion that a focal white-matter abnormality within the tracts investigated underpins the onset of psychosis.

Age of Onset↗
PubMed2004

The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study.

There are conflicting opinions in the literature as to whether it is more beneficial to use a large number of gradient sampling orientations in diffusion tensor MRI (DT-MRI) experiments than to use a smaller number of carefully chosen orientations. In this study, Monte Carlo simulations were used to study the effect of using different gradient sampling schemes on estimates of tensor-derived quantities assuming a b-value of 1000 smm(-2). The study focused in particular on the effect that the number of unique gradient orientations has on uncertainty in estimates of tensor-orientation, and on estimates of the trace and anisotropy of the diffusion tensor. The results challenge the recently proposed notion that a set of six icosahedrally-arranged orientations is optimal for DT-MRI. It is shown that at least 20 unique sampling orientations are necessary for a robust estimation of anisotropy, whereas at least 30 unique sampling orientations are required for a robust estimation of tensor-orientation and mean diffusivity. Finally, the performance of sampling schemes that use low numbers of sampling orientations, but make efficient use of available gradient power, are compared to less efficient schemes with larger numbers of sampling orientations, and the relevant scenarios in which each type of scheme should be used are discussed.

Algorithms↗
PubMed2004

"Squashing peanuts and smashing pumpkins": how noise distorts diffusion-weighted MR data.

New diffusion-weighted imaging (DWI) methods, including high-b, q-space, and high angular resolution MRI methods, attempt to extract information about non-Gaussian diffusion in tissue that is not provided by low-b-value (b approximately 1000 s mm(-2)) diffusion or diffusion tensor magnetic resonance imaging (DT-MRI). Additionally, DWI data with higher spatial resolution are being acquired to resolve fine anatomic structures, such as white matter fasciculi. Increasing diffusion-weighting or decreasing voxel size can reduce the signal-to-noise ratio so that some DWI signals are close to the background noise level. Here we report several new artifacts that can be explained by considering how background noise affects the peanut-shaped angular apparent diffusion coefficient (ADC) profile. These include an orientationally dependent deviation from Gaussian behavior of the ADC profile, an underestimation of indices of diffusion anisotropy, and a correlation between estimates of mean diffusivity and diffusion anisotropy. We also discuss how noise can cause increased gray/white matter DWI contrast at higher b values and an apparent elevation of diffusion anisotropy in acute ischemia. Importantly, all of these artifacts are negligible in the b-value range typically used in DT-MRI of brain (b approximately 1000 s mm(-2)). Finally, we demonstrate a strategy for ameliorating the rectified noise artifact in data collected at higher b values.

Anisotropy↗
PubMed2003

Occipito-temporal connections in the human brain.

Diffusion tensor MRI (DT-MRI) provides information about the structural organization and orientation of white matter fibres and, through the technique of 'tractography', reveals the trajectories of cerebral white matter tracts. We used tractography in the living human brain to address the disputed issue of the nature of occipital and temporal connections. Classical anatomical studies described direct fibre connections between occipital and anterior temporal cortex in a bundle labelled the inferior longitudinal fasciculus (ILF). However, their presence has been challenged by more recent evidence suggesting that connections between the two regions are entirely indirect, conveyed by the occipito-temporal projection system--a chain of U-shaped association fibres. DT-MRI data were collected from 11 right-handed healthy subjects (mean age 33.3 +/- 4.7 years). Each data set was co-registered with a standard MRI brain template, and a group-averaged DT-MRI data set was created. 'Virtual' in vivo dissection of occipito-temporal connections was performed in the group-averaged data. Further detailed virtual dissection was performed on the single brain data sets. Our results suggest that in addition to the indirect connections of the occipito-temporal projection system: (i) a major associative connection between the occipital and anterior temporal lobe is provided by a fibre bundle whose origin, course and termination are consistent with classical descriptions of the ILF in man and with monkey visual anatomy; (ii) the tractography-defined ILF is structurally distinct from fibres of the optic radiation and from U-shaped fibres connecting adjacent gyri; (iii) it arises in extrastriate visual 'association' areas; and (iv) it projects to lateral and medial anterior temporal regions. While the function of the direct ILF pathway is unclear, it appears to mediate the fast transfer of visual signals to anterior temporal regions and neuromodulatory back-projections from the amygdala to early visual areas. Future tractography studies of patients with occipito-temporal disconnection syndromes may help define the functional roles of the direct and indirect occipito-temporal pathways.

Adult↗
PubMed2003

Determining and visualizing uncertainty in estimates of fiber orientation from diffusion tensor MRI.

Diffusion tensor MRI (DT-MRI) permits determination of the dominant orientation of structured tissue within an image voxel. This has led to the development of 2D graphical methods for representing fiber orientation and DT-MRI "tractography," which aims to reconstruct the 3D trajectories of white matter fasciculi. Most contemporary fiber orientation mapping schemes and tractography algorithms employ the directional information contained in the eigenvectors of the diffusion tensor to approximate white matter fiber orientation. However, while the uncertainty associated with every estimate of an eigenvector has long been recognized, no attempts to quantify this uncertainty in vivo have been reported. Here, a method is proposed for determining confidence intervals in fiber orientation from real DT-MRI data using the bootstrap method. This is used to construct maps of the "cone of uncertainty," allowing simultaneous viewing of fiber orientation and its uncertainty, and to examine the relationship between orientation uncertainty and tissue anisotropy.

Anisotropy↗
PubMed2002

Virtual in vivo interactive dissection of white matter fasciculi in the human brain.

This work reports the use of diffusion tensor magnetic resonance tractography to visualize the three-dimensional (3D) structure of the major white matter fasciculi within living human brain. Specifically, we applied this technique to visualize in vivo (i) the superior longitudinal (arcuate) fasciculus, (ii) the inferior longitudinal fasciculus, (iii) the superior fronto-occipital (subcallosal) fasciculus, (iv) the inferior frontooccipital fasciculus, (v) the uncinate fasciculus, (vi) the cingulum, (vii) the anterior commissure, (viii) the corpus callosum, (ix) the internal capsule, and (x) the fornix. These fasciculi were first isolated and were then interactively displayed as a 3D-rendered object. The virtual tract maps obtained in vivo using this approach were faithful to the classical descriptions of white matter anatomy that have previously been documented in postmortem studies. Since we have been able to interactively delineate and visualize white matter fasciculi over their entire length in vivo, in a manner that has only previously been possible by histological means, "virtual in vivo interactive dissection" (VIVID) adds a new dimension to anatomical descriptions of the living human brain.

Adult↗
PubMed2002

Spatial normalization and averaging of diffusion tensor MRI data sets.

Diffusion tensor magnetic resonance imaging (DT-MRI) is unique in providing information about both the structural integrity and the orientation of white matter fibers in vivo and, through "tractography", revealing the trajectories of white matter tracts. DT-MRI is therefore a promising technique for detecting differences in white matter architecture between different subject populations. However, while studies involving analyses of group averages of scalar quantities derived from DT-MRI data have been performed, as yet there have been no similar studies involving the whole tensor. Here we present the first step towards realizing such a study, i.e., the spatial normalization of whole tensor data sets. The approach is illustrated by spatial normalization of 10 DT-MRI data sets to a standard anatomical template. Both qualitative and quantitative approaches are described for assessing the results of spatial normalization. Techniques are then described for combining the spatially normalized data sets according to three definitions of average, i.e., the mean, median, and mode of a distribution of tensors. The current absence of, and hence need for, appropriate statistical tests for comparison of results derived from group-averaged DT-MRI data sets is then discussed. Finally, the feasibility of performing tractography on the group-averaged DT-MRI data set is investigated and the possibility and implications of generating a generic map of brain connectivity from a group of subjects is considered.

Adult↗
PubMedDate not supplied

Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review.

This article treats the theoretical underpinnings of diffusion-tensor magnetic resonance imaging (DT-MRI), as well as experimental design and data analysis issues. We review the mathematical model underlying DT-MRI, discuss the quantitative parameters that are derived from the measured effective diffusion tensor, and describe artifacts that arise in typical DT-MRI acquisitions. We also discuss difficulties in identifying appropriate models to describe water diffusion in heterogeneous tissues, as well as in interpreting experimental data obtained in such issues. Finally, we describe new statistical methods that have been developed to analyse DT-MRI data, and their potential uses in clinical and multi-site studies.

Anisotropy↗
PubMedDate not supplied

Applications of diffusion-weighted and diffusion tensor MRI to white matter diseases - a review.

This paper reviews the current applications of diffusion-weighted and diffusion tensor MRI in diseases of the brain white matter. The contribution that diffusion-weighted imaging has made to our understanding of white matter diseases is critically appraised. The quantitative nature of diffusion MRI is one of its major attractions; however, this is offset by the more advanced hardware required to collect diffusion-weighted images reliably, and the more complex processing to produce quantitative parametric diffusion images. With the now common availability of scanners equipped to perform echo-planar imaging, the acquisition of diffusion tensor images is sure to become more widespread and routine.

Alzheimer Disease↗