Biomedical subjects

Daniel C Alexander

Publications and source records attributed to Daniel C Alexander.

11 recordsLinked to original sources

PubMed2006

Deformable registration of diffusion tensor MR images with explicit orientation optimization.

In this paper, we present a novel deformable registration algorithm for diffusion tensor MR images that enables explicit optimization of tensor reorientation. The optimization seeks a piecewise affine transformation that divides the image domain into uniform regions and transform each region affinely. The objective function captures both the image similarity and the smoothness of the transformation across region boundaries. The image similarity enables explicit orientation optimization by incorporating tensor reorientation, which is necessary for warping diffusion tensor images. The objective function is formulated in a way that allows explicit implementation of analytic derivatives to drive fast and accurate optimization using the conjugate gradient method. By explicitly optimizing tensor reorientation, the algorithm is designed to take advantage of similarity measures comparing tensors as a whole. The optimal transformation is hierarchically refined in a subdivision framework. A comparison with affine registration for inter-subject normalization of 8 subjects shows that the proposed algorithm improves the alignment of several major white matter structures examined: the anterior thalamic radiations, the inferior fronto-occipital fasciculi, the corticospinal/corticobulbar tracts and the genu and the splenium of the corpus callosum. The alignment of white matter structures is assessed using a novel scheme of computing distances between the corresponding fiber bundles derived from tractography.

Adult↗

PubMed2006

Non-invasive mapping of corticofugal fibres from multiple motor areas--relevance to stroke recovery.

Recovery of motor function after subcortical stroke appears to be related to the integrity of descending connections from the ipsilesional cortical motor system, a view supported by the observation of greater than normal movement-related activation in ipsilesional motor regions in chronic subcortical stroke patients. This suggests that damage to the descending output fibres from one region of the cortical motor system may be compensated by activity in areas that retain corticofugal outputs. Though the trajectories of corticofugal fibres from each major component of the motor system through the corona radiata and internal capsule are well described in non-human primates, they have not been described fully in humans. Our study set out to map the trajectories of these connections in a group of healthy volunteers (8 male, 4 female; age range = 31-68 years, median = 48.5 years) and establish whether this knowledge can be used to assess stroke-induced disconnection of the cortical motor system and better interpret functional reorganization of the cortical motor system. We describe the trajectories of the connections from each major component of the motor system to the cerebral peduncle using diffusion-weighted imaging and probabilistic tractography in normal subjects. We observed good reproducibility of these connections over subjects. The comparative topography of these connections revealed many similarities between humans and other primates. We then inferred damage to corticofugal pathways in stroke patients (n = 3) by comparing the overlap between regions of subcortical white matter damage with the trajectories of the connections to each motor area. In a small series of case studies, we found that inferred disconnections could explain enhanced hand-grip-related responses, as assessed with functional MRI, in the ipsilesional motor system. These results confirm that selective disruption of motor corticofugal fibres influences functional reorganization and outcome in individual patients.

Adult↗

PubMed2006

Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study.

Functional lateralization is a feature of human brain function, most apparent in the typical left-hemisphere specialization for language. A number of anatomical and imaging studies have examined whether structural asymmetries underlie this functional lateralization. We combined functional MRI (fMRI) and diffusion-weighted imaging (DWI) with tractography to study 10 healthy right-handed subjects. Three language fMRI paradigms were used to define language-related regions in inferior frontal and superior temporal regions. A probabilistic tractography technique was then employed to delineate the connections of these functionally defined regions. We demonstrated consistent connections between Broca's and Wernicke's areas along the superior longitudinal fasciculus bilaterally but more extensive fronto-temporal connectivity on the left than the right. Both tract volumes and mean fractional anisotropy (FA) were significantly greater on the left than the right. We also demonstrated a correlation between measures of structure and function, with subjects with more lateralized fMRI activation having a more highly lateralized mean FA of their connections. These structural asymmetries are in keeping with the lateralization of language function and indicate the major structural connections underlying this function.

Adult↗

PubMed2006

Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI.

This paper uses the theory of Cramer-Rao lower bounds (CRLB) to obtain optimal acquisition schemes for in vivo quantitative magnetization transfer (MT) imaging, although the method is generally applicable to any multiparametric MRI technique. Quantitative MT fits a two-pool model to data collected at different sampling points or settings of amplitude and offset frequency in the MT saturation pulses. Here we use simple objective functions based on the CRLB to optimize sampling strategies for multiple parameters simultaneously, and use simulated annealing to minimize these objective functions with respect to the sampling configuration. Experiments compare optimal schemes derived for quantitative MT in the human white matter (WM) at 1.5T with previously published schemes using both synthetic and human-brain data. Results show large reductions in error of the fitted parameters with the new schemes, which greatly increases the clinical potential of in vivo quantitative MT. Since the sampling-scheme optimization requires specific settings of the MT parameters, we also show that the optimum schemes are robust to these settings within the range of MT parameters observed in the brain.

Adult↗

PubMed2005

Optimal imaging parameters for fiber-orientation estimation in diffusion MRI.

This study uses Monte Carlo simulations to investigate the optimal value of the diffusion weighting factor b for estimating white-matter fiber orientations using diffusion MRI with a standard spherical sampling scheme. We devise an algorithm for determining the optimal echo time, pulse width, and pulse separation in the pulsed-gradient spin-echo sequence for a specific value of b. The Monte Carlo simulations provide an estimate of the optimal value of b for recovering one and two fiber orientations. We show that the optimum is largely independent of the noise level in the measurements and the number of gradient directions and that the optimum depends only weakly on the diffusion anisotropy, the maximum gradient strength, and the spin-spin relaxation time. The optimum depends strongly on the mean diffusivity. In brain tissue, the optima we estimate are in the ranges [0.7, 1.0] x 10(9) s m(-2) and [2.2, 2.8] x 10(9) s m(-2) for the one- and two-fiber cases, respectively. The best b for estimating the fractional anisotropy is slightly higher than for estimating fiber directions in the one-fiber case and slightly lower in the two-fiber case. To estimate Tr(D) in the one-fiber case, the optimal setting is higher still. Simulations suggest that a ratio of high to low b measurements of 5 to 1 is a good compromise for measuring fiber directions and size and shape indices.

Algorithms↗

PubMed2005

Probabilistic anatomical connectivity derived from the microscopic persistent angular structure of cerebral tissue.

Recently developed methods to extract the persistent angular structure (PAS) of axonal fibre bundles from diffusion-weighted magnetic resonance imaging (MRI) data are applied to drive probabilistic fibre tracking, designed to provide estimates of anatomical cerebral connectivity. The behaviour of the PAS function in the presence of realistic data noise is modelled for a range of single and multiple fibre configurations. This allows probability density functions (PDFs) to be generated that are parametrized according to the anisotropy of individual fibre populations. The PDFs are incorporated in a probabilistic fibre-tracking method to allow the estimation of whole-brain maps of anatomical connection probability. These methods are applied in two exemplar experiments in the corticospinal tract to show that it is possible to connect the entire primary motor cortex (M1) when tracing from the cerebral peduncles, and that the reverse experiment of tracking from M1 successfully identifies high probability connection via the pyramidal tracts. Using the extracted PAS in probabilistic fibre tracking allows higher specificity and sensitivity than previously reported fibre tracking using diffusion-weighted MRI in the corticospinal tract.

Anisotropy↗

PubMed2005

Multiple-fiber reconstruction algorithms for diffusion MRI.

This chapter reviews multiple-fiber reconstruction algorithms for diffusion magnetic resonance imaging (MRI) and provides some initial comparative results for two such algorithms, q-ball imaging and PASMRI, on data from a typical clinical diffusion MRI acquisition. The chapter highlights the problems with standard approaches, such as diffusion-tensor MRI, to motivate a recent set of alternative approaches. The review concentrates on the software implementation of the new techniques. Results of the preliminary comparison show that PASMRI recovers the principal directions of simple test functions more consistently than q-ball imaging and produces qualitatively better results on the test data set. Further simulations suggest that a moderate increase in data quality allows q-ball, which is much faster to run, to recover directions with consistency comparable to that of PASMRI on the test data.

Algorithms↗

PubMed2004

Lateralization of ventral and dorsal auditory-language pathways in the human brain.

Recent electrophysiological investigations of the auditory system in primates along with functional neuroimaging studies of auditory perception in humans have suggested there are two pathways arising from the primary auditory cortex. In the primate brain, a 'ventral' pathway is thought to project anteriorly from the primary auditory cortex to prefrontal areas along the superior temporal gyrus while a separate 'dorsal' route connects these areas posteriorly via the inferior parietal lobe. We use diffusion MRI tractography, a noninvasive technique based on diffusion-weighted MRI, to investigate the possibility of a similar pattern of connectivity in the human brain for the first time. The dorsal pathway from Wernicke's area to Broca's area is shown to include the arcuate fasciculus and connectivity to Brodmann area 40, lateral superior temporal gyrus (LSTG), and lateral middle temporal gyrus. A ventral route between Wernicke's area and Broca's area is demonstrated that connects via the external capsule/uncinate fasciculus and the medial superior temporal gyrus. Ventral connections are also observed in the lateral superior and middle temporal gyri. The connections are stronger in the dominant hemisphere, in agreement with previous studies of functional lateralization of auditory-language processing.

Adult↗

PubMed2003

Persistent Angular Structure: new insights from diffusion MRI data. Dummy version.

We determine a statistic called the radially Persistent Angular Structure (PAS) from samples of the Fourier transform of a three-dimensional function. The method has applications in diffusion magnetic resonance imaging (MRI), which samples the Fourier transform of the probability density function of particle displacements. The persistent angular structure is then a representation of the relative mobility of particles in each direction. In combination, PAS-MRI computes the persistent angular structure at each voxel of an image. This technique has biomedical applications, where it reveals the orientations of microstructural fibres, such as white-matter fibres in the brain. We test PAS-MRI on synthetic and human brain data. The data come from a standard acquisition scheme for diffusion-tensor MRI in which the samples in each voxel lie on a sphere in Fourier space.

Algorithms↗

PubMed2003

Probabilistic Monte Carlo based mapping of cerebral connections utilising whole-brain crossing fibre information.

A methodology is presented for estimation of a probability density function of cerebral fibre orientations when one or two fibres are present in a voxel. All data are acquired on a clinical MR scanner, using widely available acquisition techniques. The method models measurements of water diffusion in a single fibre by a Gaussian density function and in multiple fibres by a mixture of Gaussian densities. The effects of noise on complex MR diffusion weighted data are explicitly simluated and parameterised. This information is used for standard and Monte Carlo streamline methods. Deterministic and probabilistic maps of anatomical voxel scale connectivity between brain regions are generated.

Algorithms↗

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↗