Publications by Year: 2016

BACKGROUND: Dystonia, a debilitating movement disorder characterized by abnormal fixed positions and/or twisting postures, is associated with dysfunction of motor control networks. While gross brain lesions can produce secondary dystonias, advanced neuroimaging techniques have been required to identify network abnormalities in primary dystonias. Prior neuroimaging studies have provided valuable insights into the pathophysiology of dystonia, but few directly assessed the gross volume of motor control regions, and to our knowledge, none identified abnormalities common to multiple types of idiopathic focal dystonia.

Background and Purpose. Low-grade gliomas show infiltrative growth in white matter tracts. Diffusion tensor tractography can noninvasively assess white matter tracts. The aim was to preoperatively assess tumor growth in white matter tracts using quantitative MR tractography (3T). The hypothesis was that suspected infiltrated tracts would have altered diffusional properties in infiltrated tract segments compared to noninfiltrated tracts. Materials and Methods. Forty-eight patients with suspected low-grade glioma were included after written informed consent and underwent preoperative diffusion tensor imaging in this prospective review-board approved study. Major white matter tracts in both hemispheres were tracked, segmented, and visually assessed for tumor involvement in thirty-four patients with gliomas grade II or III (astrocytomas or oligodendrogliomas) on postoperative neuropathological evaluation. Relative fractional anisotropy (rFA) and mean diffusivity (rMD) in tract segments were calculated and compared with visual evaluation and neuropathological diagnosis. Results. Tract segment infiltration on visual evaluation was associated with a lower rFA and high rMD in a majority of evaluated tract segments (89% and 78%, resp.). Grade II and grade III gliomas had similar infiltrating behavior. Conclusion. Quantitative MR tractography corresponds to visual evaluation of suspected tract infiltration. It may be useful for an objective preoperative evaluation of tract segment involvement.

Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts.

OBJECTIVE: We aimed to test whether in vivo levels of magnetic resonance spectroscopy (MRS) metabolites myo-inositol (mI), N-acetylaspartate (NAA), and choline are abnormal already during preclinical Alzheimer disease (AD), relating these changes to amyloid or tau pathology, and functional connectivity.

Rasagiline is a monoamine oxidase type B inhibitor that possesses no amphetamine-like properties, and provides symptomatic relief in early and late stages of Parkinson’s disease (PD). Data in animal models of PD suggest that chronic administration of rasagiline is associated with structural changes in the substantia nigra, and raise the question whether the structure and function of the basal ganglia could be different in PD patients treated chronically with rasagiline as compared with PD patients not treated with rasagiline. Here, we performed a retrospective cross-sectional magnetic resonance imaging (MRI) study at 3 T that investigated nigrostriatal function and structure in PD patients who had taken rasagiline before testing (\~8 months), PD who had not taken rasagiline before testing, and age-matched controls. The two PD groups were selected a priori to not differ significantly in age, sex, disease duration, severity of symptoms, cognitive status, and total levodopa equivalent daily dose of medication. We evaluated percent signal change in the posterior putamen during force production using functional MRI, free-water in the posterior substantia nigra using diffusion MRI, and performance on a bimanual coordination task using a pegboard test. All patients were tested after overnight withdrawal from antiparkinsonian medication. The rasagiline group had greater percent signal change in the posterior putamen, less free-water in the posterior substantia nigra, and better performance on the coordination task than the group not taking rasagiline. These findings point to a possible chronic effect of rasagiline on the structure and function of the basal ganglia in PD. Hum Brain Mapp 37:2894-2903, 2016. © 2016 Wiley Periodicals, Inc.

We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.

Skin is attractive for drug therapy because it offers an easily accessible route without first-pass metabolism. Transdermal drug delivery is also associated with high patient compliance and through the site of application, the drug delivery can be locally directed. However, to succeed with transdermal drug delivery it is often required to overcome the low permeability of the upper layer of the skin, the stratum corneum (SC). One common strategy is to employ so-called penetration enhancers that supposedly act to increase the drug passage across SC. Still, there is a lack of understanding of the molecular effects of so-called penetration enhancers on the skin barrier membrane, the SC. In this study, we provide a molecular characterization of how different classes of compounds, suggested as penetration enhancers, influence lipid and protein components in SC. The compounds investigated include monoterpenes, fatty acids, osmolytes, surfactant, and Azone. We employ natural abundance (13)C polarization transfer solid-state nuclear magnetic resonance (NMR) on intact porcine SC. With this method it is possible to detect small changes in the mobility of the minor fluid lipid and protein SC components, and simultaneously obtain information on the major fraction of solid SC components. The balance between fluid and solid components in the SC is essential to determine macroscopic material properties of the SC, including barrier and mechanical properties. We study SC at different hydration levels corresponding to SC in ambient air and under occlusion. The NMR studies are complemented with diffusion cell experiments that provide quantitative data on skin permeability when treated with different compounds. By correlating the effects on SC molecular components and SC barrier function, we aim at deepened understanding of diffusional transport in SC, and how this can be controlled, which can be utilized for optimal design of transdermal drug delivery formulations.

Disentangling the tissue microstructural information from the diffusion magnetic resonance imaging (dMRI) measurements is quite important for extracting brain tissue specific measures. The autocorrelation function of diffusing spins is key for understanding the relation between dMRI signals and the acquisition gradient sequences. In this paper, we demonstrate that the autocorrelation of diffusion in restricted or bounded spaces can be well approximated by exponential functions. To this end, we propose to use the multivariate Ornstein-Uhlenbeck (OU) process to model the matrix-valued exponential autocorrelation function of three-dimensional diffusion processes with bounded trajectories. We present detailed analysis on the relation between the model parameters and the time-dependent apparent axon radius and provide a general model for dMRI signals from the frequency domain perspective. For our experimental setup, we model the diffusion signal as a mixture of two compartments that correspond to diffusing spins with bounded and unbounded trajectories, and analyze the corpus-callosum in an ex-vivo data set of a monkey brain.

PURPOSE: Tractography is the most anatomically accurate method for delineating white matter tracts in the brain, yet few studies have examined multiple tracts using tractography in patients with schizophrenia (SCZ). We analyze 5 white matter connections important in the pathophysiology of SCZ: uncinate fasciculus, cingulum bundle (CB), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus, and arcuate fasciculus (AF). Additionally, we investigate the relationship between diffusion tensor imaging (DTI) markers and neuropsychological measures. METHODS: High-resolution DTI data were acquired on a 3 Tesla scanner in 30 patients with early-course SCZ and 30 healthy controls (HC) from the Boston Center for Intervention Development and Applied Research study. After manually guided tracts delineation, fractional anisotropy (FA), trace, radial diffusivity (RD), and axial diffusivity (AD) were calculated and averaged along each tract. The association of DTI measures with the Scales for the Assessment of Negative and Positive Symptoms and neuropsychological measures was evaluated. RESULTS: Compared to HC, patients exhibited reduced FA and increased trace and RD in the right AF, CB, and ILF. A discriminant analysis showed the possible use of FA of these tracts for better future group membership classifications. FA and RD of the right ILF and AF were associated with positive symptoms while FA and RD of the right CB were associated with memory performance and processing speed. CONCLUSION: We observed white matter alterations in the right CB, ILF, and AF, possibly caused by myelin disruptions. The structural abnormalities interact with cognitive performance, and are linked to clinical symptoms.

BACKGROUND: Alcoholism has been linked to deficits in cognitive, behavioral, and emotional functions, and the cerebellum is important for optimal functioning of these abilities. However, little is known about how individual differences such as gender and drinking history might influence regional cerebellar abnormalities. METHODS: Volumetric analyses of the cerebellum and its subregions were performed in relation to the interaction of gender and measures of drinking history. Structural magnetic resonance imaging scans of 44 alcoholic individuals (23 men) and 39 nonalcoholic controls (18 men) were obtained. In addition to measuring total cerebellar gray and white matter volumes, we measured 64 individual cerebellar parcellation units, as well as functionally defined a priori regions of interest that have been shown to correspond to functions impaired in alcoholism. RESULTS: Total cerebellar white matter volume was smaller in alcoholic relative to nonalcoholic participants. Moreover, volumes of parcellation units varied with drinking history, showing negative associations between years of heavy drinking and the anterior lobe, the vestibulocerebellar lobe, and the spinocerebellar subdivision. The negative association between anterior volume and years of heavy drinking was driven primarily by alcoholic men. Additionally, we observed larger white and gray matter volumes for alcoholic women than for alcoholic men. CONCLUSIONS: The identification of drinking-related abnormalities in cerebellar subregions lays a foundation that can be utilized to inform how cerebro-cerebellar networks are perturbed in this pathological condition. These results also provide estimates of how gender and individual differences in drinking history can predict cerebellar volumes.