Alan Connelly

Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution

Diffusion-weighted magnetic resonance imaging can provide information related to the arrangement of white matter fibers. The diffusion tensor is the model most commonly used to derive the orientation of the fibers within a voxel. However, this model has been shown to fail in regions containing several fiber populations with distinct orientations. A number of alternative models have been suggested, such as multiple tensor fitting, q-space, and Q-ball imaging. However, each of these has inherent limitations. In this study, we propose a novel method for estimating the fiber orientation distribution directly from high angular resolution diffusion-weighted MR data without the need for prior assumptions regarding the number of fiber populations present. We assume that all white matter fiber bundles in the brain share identical diffusion characteristics, thus implicitly assigning any differences in diffusion anisotropy to partial volume effects. The diffusion-weighted signal attenuation measured over the surface of a sphere can then be expressed as the convolution over the sphere of a response function (the diffusion-weighted attenuation profile for a typical fiber bundle) with the fiber orientation density function (ODF). The fiber ODF (the distribution of fiber orientations within the voxel) can therefore be obtained using spherical deconvolution. The properties of the technique are demonstrated using simulations and on data acquired from a volunteer using a standard 1.5-T clinical scanner. The technique can recover the fiber ODF in regions of multiple fiber crossing and holds promise for applications such as tractography.

Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution

Diffusion-weighted (DW) MR images contain information about the orientation of brain white matter fibres that potentially can be used to study human brain connectivity in vivo using tractography techniques. Currently, the diffusion tensor model is widely used to extract fibre directions from DW-MRI data, but fails in regions containing multiple fibre orientations. The spherical deconvolution technique has recently been proposed to address this limitation. It provides an estimate of the fibre orientation distribution (FOD) by assuming the DW signal measured from any fibre bundle is adequately described by a single response function. However, the deconvolution is ill-conditioned and susceptible to noise contamination. This tends to introduce artefactual negative regions in the FOD, which are clearly physically impossible. In this study, the introduction of a constraint on such negative regions is proposed to improve the conditioning of the spherical deconvolution. This approach is shown to provide FOD estimates that are robust to noise whilst preserving angular resolution. The approach also permits the use of super-resolution, whereby more FOD parameters are estimated than were actually measured, improving the angular resolution of the results. The method provides much better defined fibre orientation estimates, and allows orientations to be resolved that are separated by smaller angles than previously possible. This should allow tractography algorithms to be designed that are able to track reliably through crossing fibre regions.

Image-selected in Vivo spectroscopy (ISIS). A new technique for spatially selective nmr spectroscopy

Abstract A method of spatial localization is described which is particularly suitable for the in vivo spectroscopic investigation of biological and medical samples. The technique overcomes most of the technical problems associated with localized NMR spectroscopy and allows the spectrum to be investigated from a cube which can be positioned by reference to an NMR image. The cube can be reduced or enlarged, and can be rapidly moved in space to investigate further volumes of interest within the sample. The first experimental results from a phantom and the human leg are presented.

MRtrix: Diffusion tractography in crossing fiber regions

In recent years, diffusion‐weighted magnetic resonance imaging has attracted considerable attention due to its unique potential to delineate the white matter pathways of the brain. However, methodologies currently available and in common use among neuroscientists and clinicians are typically based on the diffusion tensor model, which has comprehensively been shown to be inadequate to characterize diffusion in brain white matter. This is due to the fact that it is only capable of resolving a single fiber orientation per voxel, causing incorrect fiber orientations, and hence pathways, to be estimated through these voxels. Given that the proportion of affected voxels has been recently estimated at 90%, this is a serious limitation. Furthermore, most implementations use simple “deterministic” streamlines tracking algorithms, which have now been superseded by “probabilistic” approaches. In this study, we present a robust set of tools to perform tractography, using fiber orientations estimated using the validated constrained spherical deconvolution method, coupled with a probabilistic streamlines tracking algorithm. This methodology is shown to provide superior delineations of a number of known white matter tracts, in a manner robust to crossing fiber effects. These tools have been compiled into a software package, called MRtrix, which has been made freely available for use by the scientific community.

Delay and dispersion effects in dynamic susceptibility contrast MRI: Simulations using singular value decomposition

Dynamic susceptibility contrast (DSC) MRI is now increasingly used for measuring perfusion in many different applications. The quantification of DSC data requires the measurement of the arterial input function (AIF) and the deconvolution of the tissue concentration time curve. One of the most accepted deconvolution methods is the use of singular value decomposition (SVD). Simulations were performed to evaluate the effects on DSC quantification of the presence of delay and dispersion in the estimated AIF. Both delay and dispersion were found to introduce significant underestimation of cerebral blood flow (CBF) and overestimation of mean transit time (MTT). While the error introduced by the delay can be corrected by using the information of the arrival time of the bolus, the correction for the dispersion is less straightforward and requires a model for the vasculature. Magn Reson Med 44:466–473, 2000.

Magnetic resonance spectroscopy in temporal lobe epilepsy

We used proton magnetic resonance spectroscopy (1H MRS) to investigate the temporal lobes of 25 patients with temporal lobe epilepsy. Spectra were obtained from 2 × 2 × 2 cm cubes in the medial region of the temporal lobe, and were analyzed on the basis of signals from N-acetylaspartate (NAA), creatine + phosphocreatine (Cr), and choline-containing compounds (Cho). In comparison with control subjects, the temporal lobes ipsilateral to the seizure focus showed a mean reduction of 22% in the NAA signal, with a 15% increase in the Cr signal and a 25% increase in the Cho signal. There were smaller effects in the contralateral temporal lobes. These spectral abnormalities may reflect neuronal loss or damage, together with reactive astrocytosis. The NAA/Cho+Cr ratio was abnormally low in 88% of the patients, 40% showing bilateral effects. On the basis of the NAA/Cho+Cr ratio, we correctly achieved lateralization in 15 cases, with three incorrect. Two of the incorrect lateralizations also had imaging abnormalities on the contralateral side, and the other had severe bilateral abnormalities on MRS. We conclude that 1H MRS provides useful information in the preoperative investigation of patients with temporal lobe epilepsy, contributing to lateralization and detecting bilateral abnormalities.

Resolving crossing fibres using constrained spherical deconvolution: validation using diffusion-weighted imaging phantom data.

Diffusion-weighted imaging can potentially be used to infer the connectivity of the human brain in vivo using fibre-tracking techniques, and is therefore of great interest to neuroscientists and clinicians. A key requirement for fibre tracking is the accurate estimation of white matter fibre orientations within each imaging voxel. The diffusion tensor model, which is widely used for this purpose, has been shown to be inadequate in crossing fibre regions. A number of approaches have recently been proposed to address this issue, based on high angular resolution diffusion-weighted imaging (HARDI) data. In this study, an experimental model of crossing fibres, consisting of water-filled plastic capillaries, is used to thoroughly assess three such techniques: constrained spherical deconvolution (CSD), super-resolved CSD (super-CSD) and Q-ball imaging (QBI). HARDI data were acquired over a range of crossing angles and b-values, from which fibre orientations were computed using each technique. All techniques were capable of resolving the two fibre populations down to a crossing angle of 45 degrees , and down to 30 degrees for super-CSD. A bias was observed in the fibre orientations estimated by QBI for crossing angles other than 90 degrees, consistent with previous simulation results. Finally, for a 45 degrees crossing, the minimum b-value required to resolve the fibre orientations was 4000 s/mm(2) for QBI, 2000 s/mm(2) for CSD, and 1000 s/mm(2) for super-CSD. The quality of estimation of fibre orientations may profoundly affect fibre tracking attempts, and the results presented provide important additional information regarding performance characteristics of well-known methods.

Detection of hippocampal pathology in intractable partial epilepsy Increased sensitivity with quantitative magnetic resonance T2 relaxometry

Abnormal T2-weighted signal intensity in the hippocampus may be difficult to detect visually, and T2 mapping provides an objective means of assessing signal abnormality. We investigated 50 adult outpatients suffering from intractable partial epilepsy with MRI optimized to detect hippocampal and cortical gray matter abnormalities, and with MR T2 relaxation mapping. The range of normal hippocampal T2 relaxation times is small (99 to 106 msec), and the measurements are reproducible between observers. There were abnormal hippocampal T2 relaxation times in the hippocampus ipsilateral to the site of seizure origin in 70% of patients studied, with the more severe abnormality in the ipsilateral hippocampus in all cases. All hippocampal T2 measurements greater than 116 msec were associated with temporal lobe epilepsy and pathologic or MRI evidence of hippocampal sclerosis, or both. Bilateral abnormalities were present in 29% of cases with hippocampal sclerosis.

Quantification of Perfusion Using Bolus Tracking Magnetic Resonance Imaging in Stroke Assumptions, Limitations, and Potential Implications for Clinical Use

Background— MR techniques have been very powerful in providing indicators of tissue perfusion, particularly in studies of cerebral ischemia. There is considerable interest in performing absolute perfusion measurements, with the aim of improving the characterization of tissue “at risk” of stroke. However, some important caveats relating to absolute measurements need to be taken into account. The purpose of this article is to discuss some of the issues involved and the potential implications for absolute cerebral blood flow measurements in clinical use. Summary of Comment— In bolus tracking MRI, deconvolution of the concentration-time course can in theory provide accurate quantification. However, there are several important assumptions in the tracer kinetic model used, some of which may be invalid in cerebral ischemia. These can introduce significant errors in perfusion quantification. Conclusions— Although we believe that bolus tracking MRI is a powerful technique for the evaluation of perfusion in cerebral ischemia, interpretation of perfusion maps requires caution; this is particularly true when absolute quantification is attempted. Work is currently under way in a number of centers to address these problems, and with appropriate modeling they may be overcome in the future. In the interim, we believe that it is necessary for users of bolus tracking perfusion data to be aware of the current technical limitations if they are to avoid misinterpretation or overinterpretation of their findings.

Language fMRI abnormalities associated with FOXP2 gene mutation.

Half the members of the KE family suffer from a speech and language disorder caused by a mutation in the FOXP2 gene. We examined functional brain abnormalities associated with this mutation using two fMRI language experiments, one involving covert (silent) verb generation and the other overt (spoken) verb generation and word repetition. The unaffected family members showed a typical left-dominant distribution of activation involving Brocas area in the generation tasks and a more bilateral distribution in the repetition task, whereas the affected members showed a more posterior and more extensively bilateral pattern of activation in all tasks. Consistent with previously reported bilateral morphological abnormalities, the affected members showed significant underactivation relative to the unaffected members in Brocas area and its right homolog, as well as in other cortical language-related regions and in the putamen. Our findings suggest that the FOXP2 gene is critically involved in the development of the neural systems that mediate speech and language.