Faculty Bibliography

PURPOSE/OBJECTIVE:Linear least squares estimators are widely used in diffusion MRI for the estimation of diffusion parameters. Although adding proper weights is necessary to increase the precision of these linear estimators, there is no consensus on how to practically define them. In this study, the impact of the commonly used weighting strategies on the accuracy and precision of linear diffusion parameter estimators is evaluated and compared with the nonlinear least squares estimation approach. METHODS:Simulation and real data experiments were done to study the performance of the weighted linear least squares estimators with weights defined by (a) the squares of the respective noisy diffusion-weighted signals; and (b) the squares of the predicted signals, which are reconstructed from a previous estimate of the diffusion model parameters. RESULTS:The negative effect of weighting strategy (a) on the accuracy of the estimator was surprisingly high. Multi-step weighting strategies yield better performance and, in some cases, even outperformed the nonlinear least squares estimator. CONCLUSION/CONCLUSIONS:If proper weighting strategies are applied, the weighted linear least squares approach shows high performance characteristics in terms of accuracy/precision and may even be preferred over nonlinear estimation methods.

During the last decade, many approaches have been proposed for improving the estimation of diffusion measures. These techniques have already shown an increase in accuracy based on theoretical considerations, such as incorporating prior knowledge of the data distribution. The increased accuracy of diffusion metric estimators is typically observed in well-defined simulations, where the assumptions regarding properties of the data distribution are known to be valid. In practice, however, correcting for subject motion and geometric eddy current deformations alters the data distribution tremendously such that it can no longer be expressed in a closed form. The image processing steps that precede the model fitting will render several assumptions on the data distribution invalid, potentially nullifying the benefit of applying more advanced diffusion estimators. In this work, we present a generic diffusion model fitting framework that considers some statistics of diffusion MRI data. A central role in the framework is played by the conditional least squares estimator. We demonstrate that the accuracy of that particular estimator can generally be preserved, regardless the applied preprocessing steps, if the noise parameter is known a priori. To fulfill that condition, we also propose an approach for the estimation of spatially varying noise levels.

BACKGROUND:An effective NMDA antagonist imaging model may find key utility in advancing schizophrenia drug discovery research. We investigated effects of subchronic treatment with the NMDA antagonist memantine by using behavioural observation and multimodal MRI. METHODS:Pharmacological MRI (phMRI) was used to map the neuroanatomical binding sites of memantine after acute and subchronic treatment. Resting state fMRI (rs-fMRI) and diffusion MRI were used to study the changes in functional connectivity (FC) and ultra-structural tissue integrity before and after subchronic memantine treatment. Further corroborating behavioural evidences were documented. RESULTS:Dose-dependent phMRI activation was observed in the prelimbic cortex following acute doses of memantine. Subchronic treatment revealed significant effects in the hippocampus, cingulate, prelimbic and retrosplenial cortices. Decreases in FC amongst the hippocampal and frontal cortical structures (prelimbic, cingulate) were apparent through rs-fMRI investigation, indicating a loss of connectivity. Diffusion kurtosis MRI showed decreases in fractional anisotropy and mean diffusivity changes, suggesting ultra-structural changes in the hippocampus and cingulate cortex. Limited behavioural assessment suggested that memantine induced behavioural effects comparable to other NMDA antagonists as measured by locomotor hyperactivity and that the effects could be reversed by antipsychotic drugs. CONCLUSION/CONCLUSIONS:Our findings substantiate the hypothesis that repeated NMDA receptor blockade with nonspecific, noncompetitive NMDA antagonists may lead to functional and ultra-structural alterations, particularly in the hippocampus and cingulate cortex. These changes may underlie the behavioural effects. Furthermore, the present findings underscore the utility and the translational potential of multimodal MR imaging and acute/subchronic memantine model in the search for novel disease-modifying treatments for schizophrenia.

Rodent models of Huntington disease (HD) are valuable tools for investigating HD pathophysiology and evaluating new therapeutic approaches. Non-invasive characterization of HD-related phenotype changes is important for monitoring progression of pathological processes and possible effects of interventions. The first transgenic rat model for HD exhibits progressive late-onset affective, cognitive, and motor impairments, as well as neuropathological features reflecting observations from HD patients. In this report, we contribute to the anatomical phenotyping of this model by comparing high-resolution ex vivo DTI measurements obtained in aged transgenic HD rats and wild-type controls. By region of interest analysis supplemented by voxel-based statistics, we find little evidence of atrophy in basal ganglia regions, but demonstrate altered DTI measurements in the dorsal and ventral striatum, globus pallidus, entopeduncular nucleus, substantia nigra, and hippocampus. These changes are largely compatible with DTI findings in preclinical and clinical HD patients. We confirm earlier reports that HD rats express a moderate neuropathological phenotype, and provide evidence of altered DTI measures in specific HD-related brain regions, in the absence of pronounced morphometric changes.

PURPOSE/OBJECTIVE:Amyloid deposition in the brain is considered an initial event in the progression of Alzheimer's disease. We hypothesized that the presence of amyloid plaques in the brain of APP/presenilin 1 mice leads to higher diffusion kurtosis measures due to increased microstructural complexity. As such, our purpose was to provide an in vivo proof of principle for detection of amyloidosis by diffusion kurtosis imaging (DKI). METHODS:APPKM670/671NL /presenilin 1 L166P mice (n = 5) and wild-type littermates (n = 5) underwent DKI at the age of 16 months. Averaged diffusion and diffusion kurtosis parameters were obtained for multiple regions (hippocampus-cortex-thalamus-cerebellum). After DKI, mice were sacrificed for amyloid staining. RESULTS:Histograms of the frequency distribution of the DKI parameters tended to shift to higher values. After normalization of absolute values to the cerebellum, a nearly plaque-free region, mean, radial, and axial diffusion kurtosis were significantly higher in APP/presenilin 1 mice as compared to wild-type in the cortex and thalamus, regions demonstrating substantial amyloid staining. CONCLUSION/CONCLUSIONS:The current study, although small-scale, suggests increased DKI metrics, in the absence of alterations in diffusion tensor imaging metrics in the cortex and thalamus of APP/presenilin 1 mice with established amyloidosis. These results warrant further investigations on the potential of DKI as a sensitive marker for Alzheimer's disease.

OBJECTIVE:To evaluate the effect of monophasic combined oral contraceptive pill (COCP) and menstrual cycle phase in healthy young women on white matter (WM) organization using diffusion tensor imaging (DTI). METHODS:Thirty young women were included in the study; 15 women used COCP and 15 women had a natural cycle. All subjects underwent DTI magnetic resonance imaging during the follicular and luteal phase of their cycle, or in different COCP cycle phases. DTI parameters were obtained in different WM structures by performing diffusion tensor fibre tractography. Fractional anisotropy and mean diffusivity were calculated for different WM structures. Hormonal plasma concentrations were measured in peripheral venous blood samples and correlated with the DTI findings. RESULTS:We found a significant difference in mean diffusivity in the fornix between the COCP and the natural cycle group. Mean diffusivity values in the fornix were negatively correlated with luteinizing hormone and estradiol blood concentrations. CONCLUSION/CONCLUSIONS:An important part in the limbic system, the fornix, regulates emotional processes. Differences in diffusion parameters in the fornix may contribute to behavioural alternations related to COCP use. This finding also suggests that the use of oral contraceptives needs to be taken into account when designing DTI group studies.

Diffusion weighted magnetic resonance images are often acquired with single shot multislice imaging sequences, because of their short scanning times and robustness to motion. To minimize noise and acquisition time, images are generally acquired with either anisotropic or isotropic low resolution voxels, which impedes subsequent posterior image processing and visualization. In this article, we propose a super-resolution method for diffusion weighted imaging that combines anisotropic multislice images to enhance the spatial resolution of diffusion tensor data. Each diffusion weighted image is reconstructed from a set of arbitrarily oriented images with a low through-plane resolution. The quality of the reconstructed diffusion weighted images was evaluated by diffusion tensor metrics and tractography. Experiments with simulated data, a hardware DTI phantom, as well as in vivo human brain data were conducted. Our results show a significant increase in spatial resolution of the diffusion tensor data while preserving high signal to noise ratio.

Effective denoising is vital for proper analysis and accurate quantitative measurements from magnetic resonance (MR) images. Even though many methods were proposed to denoise MR images, only few deal with the estimation of true signal from MR images acquired with phased-array coils. If the magnitude data from phased array coils are reconstructed as the root sum of squares, in the absence of noise correlations and subsampling, the data is assumed to follow a non central-χ distribution. However, when the k-space is subsampled to increase the acquisition speed (as in GRAPPA like methods), noise becomes spatially varying. In this note, we propose a method to denoise multiple-coil acquired MR images. Both the non central-χ distribution and the spatially varying nature of the noise is taken into account in the proposed method. Experiments were conducted on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method.

An important focus of Huntington Disease (HD) research is the identification of symptom-independent biomarkers of HD neuropathology. There is an urgent need for reproducible, sensitive and specific outcome measures, which can be used to track disease onset as well as progression. Neuroimaging studies, in particular diffusion-based MRI methods, are powerful probes for characterizing the effects of disease and aging on tissue microstructure. We report novel diffusional kurtosis imaging (DKI) findings in aged transgenic HD rats. We demonstrate altered diffusion metrics in the (pre)frontal cerebral cortex, external capsule and striatum. Presence of increased diffusion complexity and restriction in the striatum is confirmed by an increased fiber dispersion in this region. Immunostaining of the same specimens reveals decreased number of microglia in the (pre)frontal cortex, and increased numbers of oligodendrocytes in the striatum. We conclude that DKI allows sensitive and specific characterization of altered tissue integrity in this HD rat model, indicating a promising potential for diagnostic imaging of gray and white matter pathology.

The authors give an algorithm for recovering the centre and view direction of a one-dimensional camera with known principal point but unknown focal distance, by means of one view with four recognised landmarks. The involved algebra is reduced to solving a quadratic equation. This 4-point-method appears to be more robust than the existing 5-point-algorithm for locating a totally uncalibrated camera by means of chasles conics. On the other hand, the authors' method can offer an alternative for the triangulation method if the value of the focal length is unknown or unreliable (e.g. because of autozoom). © 2012 The Institution of Engineering and Technology.