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Background: Magnetic Resonance Imaging (MRI) has become part of clinical routine for diagnosis of neurodegenerative brain disorders. Acquisitions are performed at multiple centers, using multiple imaging systems and is therefore subjected to intra‐ and inter‐scanner variability. Detailed analysis of brain volumetry differences between MRI systems and scan‐rescan acquisitions can provide useful information to correct for different MRI scanner effects in future multi‐center longitudinal studies. Method: The study population (n=10) consisted of five cognitively healthy controls and five patients belonging to different stages of the AD continuum. Subjects underwent brain MRI acquisitions on three different MRI systems with harmonized scan parameters: Philips Achieva dStream 1.5T, Philips Ingenia 3T and GE Discovery MR750w 3T. Sequences were harmonized by keeping acquisition parameters similar (Table 1). To test intra‐scanner variability, each participant underwent two subsequent MRI scans (between‐scan repositioning time 3‐5 minutes) per imaging system, repeated on three different MRI systems within two hours to test inter‐scanner variability. A total of 60 MRI scans were acquired for downstream comparative analysis. Brain volumes, including whole brain, (cortical) gray matter, hippocampal volumes, lateral ventricles, frontal, temporal and parietal cortices were computed with icobrain dm (v5.0). Coefficients of variation (CV), absolute volume differences (AVD), Dice similarity coefficients (DSC) and intraclass correlation coefficients (ICC) were computed to assess within‐ and between‐scanner agreement. Result: The intra‐scanner CVs over all volumes were 0.948% for Discovery MR750w, 1.050% for Achieva and 1.152% for Ingenia. The inter‐scanner CVs were 3.016% for all‐scanner comparisons, 2.044% for Ingenia vs. Achieva, 3.191% for Achieva vs. GE and 3.326% for Ingenia vs. GE. The AVDs and ICCs were in line with the CV values. The intra‐scanner DSCs (mean±SD) over all volumes were 0.917±0.011 for Discovery MR750w, 0.917±0.010 for Achieva and 0.917±0.015 for Ingenia. The inter‐scanner DSCs were 0.898±0.017 for all‐scanner comparisons, 0.912±0.012 for Ingenia vs. Achieva, 0.888±0.013 for Achieva vs. Discovery MR750w and 0.893±0.015 for Ingenia vs. Discovery MR750w (Table 2, 3, Figure 1). Conclusion: The variability results show an excellent agreement (CV<2%) for within‐scanner and a good agreement (CV<5%) for between‐scanner comparisons in terms of clinical relevance, indicating that MRI acquisition harmonization is beneficial for automated MRI volumetry software. [ABSTRACT FROM AUTHOR]

Aims: Tuberous sclerosis complex (TSC) is a genetic disorder associated with dysregulation of the mechanistic target of rapamycin complex 1 (mTORC1) signalling pathway. Neurodevelopmental disorders, frequently present in TSC, are linked to cortical tubers in the brain. We previously reported microRNA‐34a (miR‐34a) among the most upregulated miRs in tubers. Here, we characterised miR‐34a expression in tubers with the focus on the early brain development and assessed the regulation of mTORC1 pathway and corticogenesis by miR‐34a. Methods: We analysed the expression of miR‐34a in resected cortical tubers (n = 37) compared with autopsy‐derived control tissue (n = 27). The effect of miR‐34a overexpression on corticogenesis was assessed in mice at E18. The regulation of the mTORC1 pathway and the expression of the bioinformatically predicted target genes were assessed in primary astrocyte cultures from three patients with TSC and in SH‐SY5Y cells following miR‐34a transfection. Results: The peak of miR‐34a overexpression in tubers was observed during infancy, concomitant with the presence of pathological markers, particularly in giant cells and dysmorphic neurons. miR‐34a was also strongly expressed in foetal TSC cortex. Overexpression of miR‐34a in mouse embryos decreased the percentage of cells migrated to the cortical plate. The transfection of miR‐34a mimic in TSC astrocytes negatively regulated mTORC1 and decreased the expression of the target genes RAS related (RRAS) and NOTCH1. Conclusions: MicroRNA‐34a is most highly overexpressed in tubers during foetal and early postnatal brain development. miR‐34a can negatively regulate mTORC1; however, it may also contribute to abnormal corticogenesis in TSC. [ABSTRACT FROM AUTHOR]

Background: MRI allows detecting functional and structural connectivity changes in Alzheimer's disease (AD). However, the relative importance of the corresponding MRI‐biomarkers is not fully understood. Moreover, several of these connectivity changes are not only driven by AD but also by healthy aging, which can limit the use of these biomarkers. Therefore, we looked at how 31‐different MRI biomarkers change due to aging and the presence of AD. Furthermore, we trained a set of machine‐learning‐models to distinguish AD from control subjects. The models were used to rank the features in terms of classification‐performance and analyze the impact of including age. Method: 20 AD patients and 20 age and gender‐matched healthy controls underwent MRI scanning (3T GE), including T1‐weighted, diffusion‐MRI, and resting‐state‐fMRI (rsfMRI). Whole‐brain (WB), white matter (WM), gray matter (GM), cortical GM and left and right hippocampi volumes were measured using T1‐images and icobrain. rsfMRI between regions of the default mode network was assessed using group independent component analysis. Median diffusivity and kurtosis values in GM and WM were determined. T‐tests between groups and ANOVA analysis using a Generalized‐Linear‐Model that included age and AD‐status as covariates were conducted for each feature. For assessing the ability of each feature to separate AD subjects from controls, a Support‐Vector‐Machine (SVM) model was trained using each feature separately and each feature with age. Performance was measured using 10‐fold cross‐validation. Result: Figure 1 shows the table with the ANOVA results. Generally, rsfMRI features showed only a significant association with disease‐status, whereas structural and diffusion‐derived features showed both an association with age and disease‐status. Figure 2 shows the classification performance for the different SVM models. Regarding classification performance, the models trained with the total volume of the hippocampus achieved the highest performance (accuracy:77%, sensitivity:64%, specificity:89%). Despite several of the features changing with both age and AD‐status, the inclusion of age in the SVM‐models didn't provide an advantage in classification performance. Conclusion: Multiple MRI‐biomarkers are able to detect structural and functional connectivity changes associated with AD. From those, the hippocampi volumes are the ones that better distinguish AD patients from cognitively‐healthy subjects. [ABSTRACT FROM AUTHOR]

Objective. To investigate possible neurobehavioral changes secondary to a mindfulness based intervention (MBI) training for individuals living with Parkinson’s disease (PD). Background. In the context of complementary medicine, MBIs are increasingly being used for stress reduction and in patient populations coping with chronic illness. The use of alternative and complementary medicine may be higher in patients with chronic conditions such as PD. However, behavioral effects of mindfulness training in PD have not yet been reported in the literature and this points to an unmet need and warrants further examination. Methods. A total of 27 out of 30 PD patients completed a randomized controlled longitudinal trial. Questionnaires and the UPDRS I–IV were obtained at baseline and 8-week follow-up. Results. Significant changes after the MBI were found including a 5.5 point decrease on the UPDRS motor score, an increase of 0.79 points on Parkinson’s disease questionnaire (PDQ-39) pain item, and a 3.15 point increase in the Five Facet Mindfulness Questionnaire observe facet. Conclusions. To the best of our knowledge, this is the first quantitative analysis of neurobehavioral effects of MBI in PD. [ABSTRACT FROM AUTHOR]

Objectives A broad range of subtle and markedly heterogenous neuroanatomical abnormalities of grey matter and white matter have been reported in bipolar disorder. Euthymic bipolar disorder patients represent a clinically homogenous group in which to identify trait-based biomarkers of bipolar disorder. In this study, we sought to clarify the nature and extent of neuroanatomical differences in a large, clinically homogeneous group of euthymic bipolar disorder patients. Methods Structural magnetic resonance imaging ( sMRI) was obtained for 60 patients with prospectively confirmed euthymic bipolar I disorder and 60 individually age- and gender-matched healthy volunteers. High angular resolution diffusion tensor imaging (DTI) scans were obtained for a subset of this sample comprising 35 patients and 43 controls. Voxel-based analysis of both sMRI and DTI data sets was performed. Results Bipolar disorder patients displayed global reductions in white matter volume and fractional anisotropy reductions in the corpus callosum, posterior cingulum, and prefrontal white matter compared with controls. There were corresponding increases in radial diffusivity in the callosal splenium in patients compared with controls. No significant group differences were detected in grey matter. In patients, lithium was associated with a bilateral increase in grey matter volume in the temporal lobes, but not with any DTI parameter. Conclusions Euthymic bipolar I disorder is characterized by both diffuse global white matter deficits and potential regional disorganization in interhemispheric and longitudinal tracts, while grey matter appears to be preserved. [ABSTRACT FROM AUTHOR]

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. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Our sense of body position and movement independent of vision (i.e., proprioception) relies on muscle spindle feedback and is vital for performing motor acts. In this study, we first sought to elucidate age-related differences in the central processing of proprioceptive information by stimulating foot muscle spindles and by measuring neural activation with functional magnetic resonance imaging. We found that healthy older adults activated a similar, distributed network of primary somatosensory and secondary-associative cortical brain regions as young individuals during the vibration-induced muscle spindle stimulation. A significant decrease in neural activity was also found in a cluster of right putamen voxels for the older age group when compared with the younger age group. Given these differences, we performed two additional analyses within each group that quantified the degree to which age-dependent activity was related to (1) brain structure and (2) a behavioral measure of proprioceptive ability. Using diffusion tensor imaging, older (but not younger) adults with higher mean fractional anisotropy were found to have increased right putamen neural activity. Age-dependent right putamen activity seen during tendon vibration was also correlated with a behavioral test of proprioceptive ability measuring ankle joint position sense in both young and old age groups. Partial correlation tests determined that the relationship between elderly joint position sense and neural activity in right putamen was mediated by brain structure, but not vice versa. These results suggest that structural differences within the right putamen are related to reduced activation in the elderly and potentially serve as biomarker of proprioceptive sensibility in older adults. Hum Brain Mapp, 2012. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

A computational framework to obtain an accurate quantification of the Gaussian and non-Gaussian component of water molecules' diffusion through brain tissues with diffusion kurtosis imaging, is presented. The diffusion kurtosis imaging model quantifies the kurtosis, the degree of non-Gaussianity, on a direction dependent basis, constituting a higher order diffusion kurtosis tensor, which is estimated in addition to the well-known diffusion tensor. To reconcile with the physical phenomenon of molecular diffusion, both tensor estimates should lie within a physically acceptable range. Otherwise, clinically and artificially significant changes in diffusion (kurtosis) parameters might be confounded. To guarantee physical relevance, we here suggest to estimate both diffusional tensors by maximizing the joint likelihood function of all Rician distributed diffusion weighted images given the diffusion kurtosis imaging model while imposing a set of nonlinear constraints. As shown in this study, correctly accounting for the Rician noise structure is necessary to avoid significant overestimation of the kurtosis values. The performance of the constrained estimator was evaluated and compared to more commonly used strategies during simulations. Human brain data were used to emphasize the need for constrained estimators as not imposing the constraints give rise to constraint violations in about 70% of the brain voxels. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

The article presents a study which examined how the cognitive defects experienced by some breast cancer survivors are related to chemotherapy-induced structural changes in cerebral white matter (WM). It also provides neuropsychological, fractional anisotropy (FA) and magnetic resonance (MR) image assessment of the subjects. It suggests that WM integrity is lower in chemotherapy-treated breast cancer patients when compared with healthy controls or with nonchemotherapy-treated patients.

With diffusion tensor imaging, the diffusion of water molecules through brain structures is quantified by parameters, which are estimated assuming monoexponential diffusion-weighted signal attenuation. The estimated diffusion parameters, however, depend on the diffusion weighting strength, the b-value, which hampers the interpretation and comparison of various diffusion tensor imaging studies. In this study, a likelihood ratio test is used to show that the diffusion kurtosis imaging model provides a more accurate parameterization of both the Gaussian and non-Gaussian diffusion component compared with diffusion tensor imaging. As a result, the diffusion kurtosis imaging model provides a b-value-independent estimation of the widely used diffusion tensor parameters as demonstrated with diffusion-weighted rat data, which was acquired with eight different b-values, uniformly distributed in a range of [0,2800 sec/mm2]. In addition, the diffusion parameter values are significantly increased in comparison to the values estimated with the diffusion tensor imaging model in all major rat brain structures. As incorrectly assuming additive Gaussian noise on the diffusion-weighted data will result in an overestimated degree of non-Gaussian diffusion and a b-value-dependent underestimation of diffusivity measures, a Rician noise model was used in this study. Magn Reson Med, 2010. © 2010 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Reconstruction of white matter (WM) fiber tracts based on diffusion tensor imaging (DTI) is increasingly being used in clinical and research settings to study normal and pathological WM tissue as well as the maturation of this WM tissue. Such fiber tracking (FT) methodology, however, is highly dependent on the manual delineation of anatomical landmarks and the algorithm settings, often rendering the reproducibility and reliability questionable. Predefining these regions of interest on a fractional anisotropy (FA) atlas in standard space has already been shown to improve the reliability of FT results. In this paper, we constructed a new DTI atlas, which contains the complete diffusion tensor information in ICBM152 coordinates. From this high-dimensional DTI atlas, and using robust FT protocols, we reconstructed a large number of WM tracts. Subsequently, we created tract masks from these fiber tract bundles and evaluated the atlas framework by comparing the reproducibility of the results obtained from our standardized tract masks with regions-of-interest labels from the conventional FA-based WM atlas. Finally, we assessed laterality and age-related WM changes in 42 normal subjects aged 0 to 18 years using these tractography-derived tract segmentations. In agreement with previous literature, we observed an FA increase with age, which was mainly due to the decrease of perpendicular diffusivity. In addition, major functional pathways in the language, motor, and limbic system, showed a significant asymmetry in terms of the observed diffusion metrics. Hum Brain Mapp, 2010. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Voxel-based analysis (VBA) methods are increasingly being used to compare diffusion tensor image (DTI) properties across different populations of subjects. Although VBA has many advantages, its results are highly dependent on several parameter settings, such as those from the coregistration technique applied to align the data, the smoothing kernel, the statistics, and the post-hoc analyses. In particular, to increase the signal-to-noise ratio and to mitigate the adverse effect of residual image misalignments, DTI data are often smoothed before VBA with an isotropic Gaussian kernel with a full width half maximum up to 16 × 16 × 16 mm3. However, using isotropic smoothing kernels can significantly partial volume or voxel averaging artifacts, adversely affecting the true diffusion properties of the underlying fiber tissue. In this work, we compared VBA results between the isotropic and an anisotropic Gaussian filtering method using a simulated framework. Our results clearly demonstrate an increased sensitivity and specificity of detecting a predefined simulated pathology when the anisotropic smoothing kernel was used. Hum Brain Mapp, 2010. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Voxel-based analyses (VBA) are increasingly being used to detect white matter abnormalities with diffusion tensor imaging (DTI) in different types of pathologies. However, the validity, specificity, and sensitivity of statistical inferences of group differences to a large extent depend on the quality of the spatial normalization of the DTI images. Using high-dimensional nonrigid coregistration techniques that are able to align both the spatial and orientational diffusion information and incorporate appropriate templates that contain this complete DT information may improve this quality. Alternatively, a hybrid technique such as tract-based spatial statistics (TBSS) may improve the reliability of the statistical results by generating voxel-wise statistics without the need for perfect image alignment and spatial smoothing. In this study, we have used (1) a coregistration algorithm that was optimized for coregistration of DTI data and (2) a population-based DTI atlas to reanalyze our previously published VBA, which compared the fractional anisotropy and mean diffusivity maps of patients with amyotrophic lateral sclerosis (ALS) with those of healthy controls. Additionally, we performed a complementary TBSS analysis to improve our understanding and interpretation of the VBA results. We demonstrate that, as the overall variance of the diffusion properties is lowered after normalizing the DTI data with such recently developed techniques (VBA using our own optimized high-dimensional nonrigid coregistration and TBSS), more reliable voxel-wise statistical results can be obtained than had previously been possible, with our VBA and TBSS yielding very similar results. This study provides support for the view of ALS as a multisystem disease, in which the entire frontotemporal lobe is implicated. Hum Brain Mapp, 2009. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Purpose To examine the T2-normal appearing spinal cord of patients with multiple sclerosis (MS) using diffusion tensor imaging. Materials and Methods Diffusion tensor images of the spinal cord were acquired from 21 healthy subjects, 11 MS patients with spinal cord lesions, and 10 MS patients without spinal cord lesions on the T2-weighted MR images. Different diffusion measures were evaluated using both a region of interest (ROI) -based and a diffusion tensor tractography-based segmentation approach. Results It was observed that the FA, the transverse diffusivity λ⟂, and the ratio of the longitudinal and transverse diffusivities (λ∥/λ ⟂) were significantly lower in the spinal cord of MS patients with spinal cord lesions compared with the control subjects using both the ROI method ( P = 0.014, P = 0.028, and P = 0.039, respectively) and the tractography-based approach ( P = 0.006, P = 0.037, and P = 0.012, respectively). For both image analysis methods, the FA and the λ ∥/λ ⟂ values were significantly different between the control group and the MS patient group without T2 spinal cord lesions ( P = 0.013). Conclusion Our results suggest that the spinal cord may still be affected by MS, even when lesions are not detected on a conventional MR scan. In addition, we demonstrated that diffusion tensor tractography is a robust tool to analyze the spinal cord of MS patients. J. Magn. Reson. Imaging 2009;30:25-34. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Purpose To compare region of interest (ROI)-based and diffusion tensor tractography (DTT)-based methods for evaluating diffusion properties of the spinal cord as a function of age. Materials and Methods Commonly, an ROI segmentation is used to delineate the spinal cord. In this work, new segmentation methods are developed based on DTT. In a first, DTT-based, segmentation approach, the diffusion properties are calculated on the tracts. In a second method, the diffusion properties are analyzed in the spinal cord voxels that contain a certain number of tracts. We studied the changes in diffusion properties of the human spinal cord in subjects of different ages. Diffusion tensor imaging (DTI) measurements of the cervical spinal cord were acquired on 42 healthy volunteers (age range = 19-87 years). The fractional anisotropy (FA), the mean diffusivity (MD), and eigenvalues (λ1, λ2, and λ3) were compared for the ROI- and DTT-based segmentation methods. Results Our automatic techniques are shown to be highly reproducible and sensitive for detecting DTI changes. FA decreased (r = -0.38; P < 0.05), whereas MD and eigenvalues increased (r = ± 0.45; P < 0.05) with age. These trends were not statistically significant for the ROI-based segmentation ( P > 0.05). Conclusion DTT is a robust and reproducible technique to segment the voxels of interest in the spinal cord. J. Magn. Reson. Imaging 2008;27:978-991. © 2008 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]