Barmpoutis, Angelos
2010-01-01
Registration of Diffusion-Weighted MR Images (DW-MRI) can be achieved by registering the corresponding 2nd-order Diffusion Tensor Images (DTI). However, it has been shown that higher-order diffusion tensors (e.g. order-4) outperform the traditional DTI in approximating complex fiber structures such as fiber crossings. In this paper we present a novel method for unbiased group-wise non-rigid registration and atlas construction of 4th-order diffusion tensor fields. To the best of our knowledge there is no other existing method to achieve this task. First we define a metric on the space of positive-valued functions based on the Riemannian metric of real positive numbers (denoted by ℝ+). Then, we use this metric in a novel functional minimization method for non-rigid 4th-order tensor field registration. We define a cost function that accounts for the 4th-order tensor re-orientation during the registration process and has analytic derivatives with respect to the transformation parameters. Finally, the tensor field atlas is computed as the minimizer of the variance defined using the Riemannian metric. We quantitatively compare the proposed method with other techniques that register scalar-valued or diffusion tensor (rank-2) representations of the DWMRI. PMID:20436782
Li, Jonathan Y; Middleton, Dana M; Chen, Steven; White, Leonard; Ellinwood, N Matthew; Dickson, Patricia; Vite, Charles; Bradbury, Allison; Provenzale, James M
2017-08-01
Purpose We describe a novel technique for measuring diffusion tensor imaging metrics in the canine brain. We hypothesized that a standard method for region of interest placement could be developed that is highly reproducible, with less than 10% difference in measurements between raters. Methods Two sets of canine brains (three seven-week-old full-brains and two 17-week-old single hemispheres) were scanned ex-vivo on a 7T small-animal magnetic resonance imaging system. Strict region of interest placement criteria were developed and then used by two raters to independently measure diffusion tensor imaging metrics within four different white-matter regions within each specimen. Average values of fractional anisotropy, radial diffusivity, and the three eigenvalues (λ1, λ2, and λ3) within each region in each specimen overall and within each individual image slice were compared between raters by calculating the percentage difference between raters for each metric. Results The mean percentage difference between raters for all diffusion tensor imaging metrics when pooled by each region and specimen was 1.44% (range: 0.01-5.17%). The mean percentage difference between raters for all diffusion tensor imaging metrics when compared by individual image slice was 2.23% (range: 0.75-4.58%) per hemisphere. Conclusion Our results indicate that the technique described is highly reproducible, even when applied to canine specimens of differing age, morphology, and image resolution. We propose this technique for future studies of diffusion tensor imaging analysis in canine brains and for cross-sectional and longitudinal studies of canine brain models of human central nervous system disease.
Adaptive distance metric learning for diffusion tensor image segmentation.
Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W
2014-01-01
High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.
Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation
Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.
2014-01-01
High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858
Hiremath, S B; Muraleedharan, A; Kumar, S; Nagesh, C; Kesavadas, C; Abraham, M; Kapilamoorthy, T R; Thomas, B
2017-04-01
Tumefactive demyelinating lesions with atypical features can mimic high-grade gliomas on conventional imaging sequences. The aim of this study was to assess the role of conventional imaging, DTI metrics ( p:q tensor decomposition), and DSC perfusion in differentiating tumefactive demyelinating lesions and high-grade gliomas. Fourteen patients with tumefactive demyelinating lesions and 21 patients with high-grade gliomas underwent brain MR imaging with conventional, DTI, and DSC perfusion imaging. Imaging sequences were assessed for differentiation of the lesions. DTI metrics in the enhancing areas and perilesional hyperintensity were obtained by ROI analysis, and the relative CBV values in enhancing areas were calculated on DSC perfusion imaging. Conventional imaging sequences had a sensitivity of 80.9% and specificity of 57.1% in differentiating high-grade gliomas ( P = .049) from tumefactive demyelinating lesions. DTI metrics ( p : q tensor decomposition) and DSC perfusion demonstrated a statistically significant difference in the mean values of ADC, the isotropic component of the diffusion tensor, the anisotropic component of the diffusion tensor, the total magnitude of the diffusion tensor, and rCBV among enhancing portions in tumefactive demyelinating lesions and high-grade gliomas ( P ≤ .02), with the highest specificity for ADC, the anisotropic component of the diffusion tensor, and relative CBV (92.9%). Mean fractional anisotropy values showed no significant statistical difference between tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI and DSC parameters improved the diagnostic accuracy (area under the curve = 0.901). Addition of a heterogeneous enhancement pattern to DTI and DSC parameters improved it further (area under the curve = 0.966). The sensitivity increased from 71.4% to 85.7% after the addition of the enhancement pattern. DTI and DSC perfusion add profoundly to conventional imaging in differentiating tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI metrics and DSC perfusion markedly improved diagnostic accuracy. © 2017 by American Journal of Neuroradiology.
Huang, Qi; Lv, Xin; He, Yushuang; Wei, Xing; Ma, Meigang; Liao, Yuhan; Qin, Chao; Wu, Yuan
2017-12-01
Patients with epilepsy (PWE) are more likely to suffer from migraine attack, and aberrant white matter (WM) organization may be the mechanism underlying this phenomenon. This study aimed to use diffusion tensor imaging (DTI) technique to quantify WM structural differences in PWE with interictal migraine. Diffusion tensor imaging data were acquired in 13 PWE with migraine and 12 PWE without migraine. Diffusion metrics were analyzed using tract-atlas-based spatial statistics analysis. Atlas-based and tract-based spatial statistical analyses were conducted for robustness analysis. Correlation was explored between altered DTI metrics and clinical parameters. The main results are as follows: (i) Axonal damage plays a key role in PWE with interictal migraine. (ii) Significant diffusing alterations included higher fractional anisotropy (FA) in the fornix, higher mean diffusivity (MD) in the middle cerebellar peduncle (CP), left superior CP, and right uncinate fasciculus, and higher axial diffusivity (AD) in the middle CP and right medial lemniscus. (iii) Diffusion tensor imaging metrics has the tendency of correlation with seizure/migraine type and duration. Results indicate that characteristic structural impairments exist in PWE with interictal migraine. Epilepsy may contribute to migraine by altering WMs in the brain stem. White matter tracts in the fornix and right uncinate fasciculus also mediate migraine after epilepsy. This finding may improve our understanding of the pathological mechanisms underlying migraine attack after epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.
DR-TAMAS: Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures
Irfanoglu, M. Okan; Nayak, Amritha; Jenkins, Jeffrey; Hutchinson, Elizabeth B.; Sadeghi, Neda; Thomas, Cibu P.; Pierpaoli, Carlo
2016-01-01
In this work, we propose DR-TAMAS (Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures), a novel framework for intersubject registration of Diffusion Tensor Imaging (DTI) data sets. This framework is optimized for brain data and its main goal is to achieve an accurate alignment of all brain structures, including white matter (WM), gray matter (GM), and spaces containing cerebrospinal fluid (CSF). Currently most DTI-based spatial normalization algorithms emphasize alignment of anisotropic structures. While some diffusion-derived metrics, such as diffusion anisotropy and tensor eigenvector orientation, are highly informative for proper alignment of WM, other tensor metrics such as the trace or mean diffusivity (MD) are fundamental for a proper alignment of GM and CSF boundaries. Moreover, it is desirable to include information from structural MRI data, e.g., T1-weighted or T2-weighted images, which are usually available together with the diffusion data. The fundamental property of DR-TAMAS is to achieve global anatomical accuracy by incorporating in its cost function the most informative metrics locally. Another important feature of DR-TAMAS is a symmetric time-varying velocity-based transformation model, which enables it to account for potentially large anatomical variability in healthy subjects and patients. The performance of DR-TAMAS is evaluated with several data sets and compared with other widely-used diffeomorphic image registration techniques employing both full tensor information and/or DTI-derived scalar maps. Our results show that the proposed method has excellent overall performance in the entire brain, while being equivalent to the best existing methods in WM. PMID:26931817
DR-TAMAS: Diffeomorphic Registration for Tensor Accurate Alignment of Anatomical Structures.
Irfanoglu, M Okan; Nayak, Amritha; Jenkins, Jeffrey; Hutchinson, Elizabeth B; Sadeghi, Neda; Thomas, Cibu P; Pierpaoli, Carlo
2016-05-15
In this work, we propose DR-TAMAS (Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures), a novel framework for intersubject registration of Diffusion Tensor Imaging (DTI) data sets. This framework is optimized for brain data and its main goal is to achieve an accurate alignment of all brain structures, including white matter (WM), gray matter (GM), and spaces containing cerebrospinal fluid (CSF). Currently most DTI-based spatial normalization algorithms emphasize alignment of anisotropic structures. While some diffusion-derived metrics, such as diffusion anisotropy and tensor eigenvector orientation, are highly informative for proper alignment of WM, other tensor metrics such as the trace or mean diffusivity (MD) are fundamental for a proper alignment of GM and CSF boundaries. Moreover, it is desirable to include information from structural MRI data, e.g., T1-weighted or T2-weighted images, which are usually available together with the diffusion data. The fundamental property of DR-TAMAS is to achieve global anatomical accuracy by incorporating in its cost function the most informative metrics locally. Another important feature of DR-TAMAS is a symmetric time-varying velocity-based transformation model, which enables it to account for potentially large anatomical variability in healthy subjects and patients. The performance of DR-TAMAS is evaluated with several data sets and compared with other widely-used diffeomorphic image registration techniques employing both full tensor information and/or DTI-derived scalar maps. Our results show that the proposed method has excellent overall performance in the entire brain, while being equivalent to the best existing methods in WM. Copyright © 2016 Elsevier Inc. All rights reserved.
Vorburger, Robert S; Habeck, Christian G; Narkhede, Atul; Guzman, Vanessa A; Manly, Jennifer J; Brickman, Adam M
2016-01-01
Diffusion tensor imaging suffers from an intrinsic low signal-to-noise ratio. Bootstrap algorithms have been introduced to provide a non-parametric method to estimate the uncertainty of the measured diffusion parameters. To quantify the variability of the principal diffusion direction, bootstrap-derived metrics such as the cone of uncertainty have been proposed. However, bootstrap-derived metrics are not independent of the underlying diffusion profile. A higher mean diffusivity causes a smaller signal-to-noise ratio and, thus, increases the measurement uncertainty. Moreover, the goodness of the tensor model, which relies strongly on the complexity of the underlying diffusion profile, influences bootstrap-derived metrics as well. The presented simulations clearly depict the cone of uncertainty as a function of the underlying diffusion profile. Since the relationship of the cone of uncertainty and common diffusion parameters, such as the mean diffusivity and the fractional anisotropy, is not linear, the cone of uncertainty has a different sensitivity. In vivo analysis of the fornix reveals the cone of uncertainty to be a predictor of memory function among older adults. No significant correlation occurs with the common diffusion parameters. The present work not only demonstrates the cone of uncertainty as a function of the actual diffusion profile, but also discloses the cone of uncertainty as a sensitive predictor of memory function. Future studies should incorporate bootstrap-derived metrics to provide more comprehensive analysis.
Automatic deformable diffusion tensor registration for fiber population analysis.
Irfanoglu, M O; Machiraju, R; Sammet, S; Pierpaoli, C; Knopp, M V
2008-01-01
In this work, we propose a novel method for deformable tensor-to-tensor registration of Diffusion Tensor Images. Our registration method models the distances in between the tensors with Geode-sic-Loxodromes and employs a version of Multi-Dimensional Scaling (MDS) algorithm to unfold the manifold described with this metric. Defining the same shape properties as tensors, the vector images obtained through MDS are fed into a multi-step vector-image registration scheme and the resulting deformation fields are used to reorient the tensor fields. Results on brain DTI indicate that the proposed method is very suitable for deformable fiber-to-fiber correspondence and DTI-atlas construction.
Lancaster, Melissa A; Olson, Daniel V; McCrea, Michael A; Nelson, Lindsay D; LaRoche, Ashley A; Muftuler, L Tugan
2016-11-01
Recent neuroimaging studies have suggested that following sport-related concussion (SRC) physiological brain alterations may persist after an athlete has shown full symptom recovery. Diffusion MRI is a versatile technique to study white matter injury following SRC, yet serial follow-up studies in the very acute stages following SRC utilizing a comprehensive set of diffusion metrics are lacking. The aim of the current study was to characterize white matter changes within 24 hours of concussion in a group of high school and collegiate athletes, using Diffusion Tensor and Diffusion Kurtosis Tensor metrics. Participants were reassessed a week later. At 24 hours post-injury, the concussed group reported significantly more concussion symptoms than a well-matched control group and demonstrated poorer performance on a cognitive screening measure, yet these differences were nonsignificant at the 8-day follow-up. Similarly, within 24-hours after injury, the concussed group exhibited a widespread decrease in mean diffusivity, increased axial kurtosis and, to a lesser extent, decreased axial and radial diffusivities compared with control subjects. At 8 days post injury, the differences in these diffusion metrics were even more widespread in the injured athletes, despite improvement of symptoms and cognitive performance. These MRI findings suggest that the athletes might not have reached full physiological recovery a week after the injury. These findings have significant implications for the management of SRC because allowing an athlete to return to play before the brain has fully recovered from injury may have negative consequences. Hum Brain Mapp 37:3821-3834, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
White matter damage in primary progressive aphasias: a diffusion tensor tractography study.
Galantucci, Sebastiano; Tartaglia, Maria Carmela; Wilson, Stephen M; Henry, Maya L; Filippi, Massimo; Agosta, Federica; Dronkers, Nina F; Henry, Roland G; Ogar, Jennifer M; Miller, Bruce L; Gorno-Tempini, Maria Luisa
2011-10-01
Primary progressive aphasia is a clinical syndrome that encompasses three major phenotypes: non-fluent/agrammatic, semantic and logopenic. These clinical entities have been associated with characteristic patterns of focal grey matter atrophy in left posterior frontoinsular, anterior temporal and left temporoparietal regions, respectively. Recently, network-level dysfunction has been hypothesized but research to date has focused largely on studying grey matter damage. The aim of this study was to assess the integrity of white matter tracts in the different primary progressive aphasia subtypes. We used diffusion tensor imaging in 48 individuals: nine non-fluent, nine semantic, nine logopenic and 21 age-matched controls. Probabilistic tractography was used to identify bilateral inferior longitudinal (anterior, middle, posterior) and uncinate fasciculi (referred to as the ventral pathway); and the superior longitudinal fasciculus segmented into its frontosupramarginal, frontoangular, frontotemporal and temporoparietal components, (referred to as the dorsal pathway). We compared the tracts' mean fractional anisotropy, axial, radial and mean diffusivities for each tract in the different diagnostic categories. The most prominent white matter changes were found in the dorsal pathways in non-fluent patients, in the two ventral pathways and the temporal components of the dorsal pathways in semantic variant, and in the temporoparietal component of the dorsal bundles in logopenic patients. Each of the primary progressive aphasia variants showed different patterns of diffusion tensor metrics alterations: non-fluent patients showed the greatest changes in fractional anisotropy and radial and mean diffusivities; semantic variant patients had severe changes in all metrics; and logopenic patients had the least white matter damage, mainly involving diffusivity, with fractional anisotropy altered only in the temporoparietal component of the dorsal pathway. This study demonstrates that both careful dissection of the main language tracts and consideration of all diffusion tensor metrics are necessary to characterize the white matter changes that occur in the variants of primary progressive aphasia. These results highlight the potential value of diffusion tensor imaging as a new tool in the multimodal diagnostic evaluation of primary progressive aphasia.
Baust, Maximilian; Weinmann, Andreas; Wieczorek, Matthias; Lasser, Tobias; Storath, Martin; Navab, Nassir
2016-08-01
In this paper, we consider combined TV denoising and diffusion tensor fitting in DTI using the affine-invariant Riemannian metric on the space of diffusion tensors. Instead of first fitting the diffusion tensors, and then denoising them, we define a suitable TV type energy functional which incorporates the measured DWIs (using an inverse problem setup) and which measures the nearness of neighboring tensors in the manifold. To approach this functional, we propose generalized forward- backward splitting algorithms which combine an explicit and several implicit steps performed on a decomposition of the functional. We validate the performance of the derived algorithms on synthetic and real DTI data. In particular, we work on real 3D data. To our knowledge, the present paper describes the first approach to TV regularization in a combined manifold and inverse problem setup.
Spin echo versus stimulated echo diffusion tensor imaging of the in vivo human heart
von Deuster, Constantin; Stoeck, Christian T.; Genet, Martin; Atkinson, David
2015-01-01
Purpose To compare signal‐to‐noise ratio (SNR) efficiency and diffusion tensor metrics of cardiac diffusion tensor mapping using acceleration‐compensated spin‐echo (SE) and stimulated echo acquisition mode (STEAM) imaging. Methods Diffusion weighted SE and STEAM sequences were implemented on a clinical 1.5 Tesla MR system. The SNR efficiency of SE and STEAM was measured (b = 50–450 s/mm2) in isotropic agar, anisotropic diffusion phantoms and the in vivo human heart. Diffusion tensor analysis was performed on mean diffusivity, fractional anisotropy, helix and transverse angles. Results In the isotropic phantom, the ratio of SNR efficiency for SE versus STEAM, SNRt(SE/STEAM), was 2.84 ± 0.08 for all tested b‐values. In the anisotropic diffusion phantom the ratio decreased from 2.75 ± 0.05 to 2.20 ± 0.13 with increasing b‐value, similar to the in vivo decrease from 2.91 ± 0.43 to 2.30 ± 0.30. Diffusion tensor analysis revealed reduced deviation of helix angles from a linear transmural model and reduced transverse angle standard deviation for SE compared with STEAM. Mean diffusivity and fractional anisotropy were measured to be statistically different (P < 0.001) between SE and STEAM. Conclusion Cardiac DTI using motion‐compensated SE yields a 2.3–2.9× increase in SNR efficiency relative to STEAM and improved accuracy of tensor metrics. The SE method hence presents an attractive alternative to STEAM based approaches. Magn Reson Med 76:862–872, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:26445426
Fluid Registration of Diffusion Tensor Images Using Information Theory
Chiang, Ming-Chang; Leow, Alex D.; Klunder, Andrea D.; Dutton, Rebecca A.; Barysheva, Marina; Rose, Stephen E.; McMahon, Katie L.; de Zubicaray, Greig I.; Toga, Arthur W.; Thompson, Paul M.
2008-01-01
We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data. PMID:18390342
White matter damage in primary progressive aphasias: a diffusion tensor tractography study
Galantucci, Sebastiano; Tartaglia, Maria Carmela; Wilson, Stephen M.; Henry, Maya L.; Filippi, Massimo; Agosta, Federica; Dronkers, Nina F.; Henry, Roland G.; Ogar, Jennifer M.; Miller, Bruce L.
2011-01-01
Primary progressive aphasia is a clinical syndrome that encompasses three major phenotypes: non-fluent/agrammatic, semantic and logopenic. These clinical entities have been associated with characteristic patterns of focal grey matter atrophy in left posterior frontoinsular, anterior temporal and left temporoparietal regions, respectively. Recently, network-level dysfunction has been hypothesized but research to date has focused largely on studying grey matter damage. The aim of this study was to assess the integrity of white matter tracts in the different primary progressive aphasia subtypes. We used diffusion tensor imaging in 48 individuals: nine non-fluent, nine semantic, nine logopenic and 21 age-matched controls. Probabilistic tractography was used to identify bilateral inferior longitudinal (anterior, middle, posterior) and uncinate fasciculi (referred to as the ventral pathway); and the superior longitudinal fasciculus segmented into its frontosupramarginal, frontoangular, frontotemporal and temporoparietal components, (referred to as the dorsal pathway). We compared the tracts’ mean fractional anisotropy, axial, radial and mean diffusivities for each tract in the different diagnostic categories. The most prominent white matter changes were found in the dorsal pathways in non-fluent patients, in the two ventral pathways and the temporal components of the dorsal pathways in semantic variant, and in the temporoparietal component of the dorsal bundles in logopenic patients. Each of the primary progressive aphasia variants showed different patterns of diffusion tensor metrics alterations: non-fluent patients showed the greatest changes in fractional anisotropy and radial and mean diffusivities; semantic variant patients had severe changes in all metrics; and logopenic patients had the least white matter damage, mainly involving diffusivity, with fractional anisotropy altered only in the temporoparietal component of the dorsal pathway. This study demonstrates that both careful dissection of the main language tracts and consideration of all diffusion tensor metrics are necessary to characterize the white matter changes that occur in the variants of primary progressive aphasia. These results highlight the potential value of diffusion tensor imaging as a new tool in the multimodal diagnostic evaluation of primary progressive aphasia. PMID:21666264
Guglielmetti, C.; Veraart, J.; Roelant, E.; Mai, Z.; Daans, J.; Van Audekerke, J.; Naeyaert, M.; Vanhoutte, G.; Delgado y Palacios, R.; Praet, J.; Fieremans, E.; Ponsaerts, P.; Sijbers, J.; Van der Linden, A.; Verhoye, M.
2016-01-01
Although MRI is the gold standard for the diagnosis and monitoring of multiple sclerosis (MS), current conventional MRI techniques often fail to detect cortical alterations and provide little information about gliosis, axonal damage and myelin status of lesioned areas. Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) provide sensitive and complementary measures of the neural tissue microstructure. Additionally, specific white matter tract integrity (WMTI) metrics modelling the diffusion in white matter were recently derived. In the current study we used the well-characterized cuprizone mouse model of central nervous system demyelination to assess the temporal evolution of diffusion tensor (DT), diffusion kurtosis tensor (DK) and WMTI-derived metrics following acute inflammatory demyelination and spontaneous remyelination. While DT-derived metrics were unable to detect cuprizone induced cortical alterations, the mean kurtosis (MK) and radial kurtosis (RK) were found decreased under cuprizone administration, as compared to age-matched controls, in both the motor and somatosensory cortices. The MK remained decreased in the motor cortices at the end of the recovery period, reflecting long lasting impairment of myelination. In white matter, DT, DK and WMTI-derived metrics enabled the detection of cuprizone induced changes differentially according to the stage and the severity of the lesion. More specifically, MK, RK and the axonal water fraction (AWF) were the most sensitive for the detection of cuprizone induced changes in the genu of the corpus callosum, a region less affected by cuprizone administration. Additionally, microgliosis was associated with an increase of MK and RK during the acute inflammatory demyelination phase. In regions undergoing severe demyelination, namely the body and splenium of the corpus callosum, DT-derived metrics, notably the mean diffusion (MD) and radial diffusion (RD), were among the best discriminators between cuprizone and control groups, hence highlighting their ability to detect both acute and long lasting changes. Interestingly, WMTI-derived metrics showed the aptitude to distinguish between the different stage of the disease. Both the intra-axonal diffusivity (Da) and the AWF were found to be decreased in the cuprizone treated group, Da specifically decreased during the acute inflammatory demyelinating phase whereas the AWF decrease was associated to the spontaneous remyelination and the recovery period. Altogether our results demonstrate that DKI is sensitive to alterations of cortical areas and provides, along with WMTI metrics, information that is complementary to DT-derived metrics for the characterization of demyelination in both white and grey matter and subsequent inflammatory processes associated with a demyelinating event. PMID:26525654
Tudela, Raúl; Muñoz-Moreno, Emma; López-Gil, Xavier; Soria, Guadalupe
2017-01-01
Diffusion-weighted imaging (DWI) quantifies water molecule diffusion within tissues and is becoming an increasingly used technique. However, it is very challenging as correct quantification depends on many different factors, ranging from acquisition parameters to a long pipeline of image processing. In this work, we investigated the influence of voxel geometry on diffusion analysis, comparing different acquisition orientations as well as isometric and anisometric voxels. Diffusion-weighted images of one rat brain were acquired with four different voxel geometries (one isometric and three anisometric in different directions) and three different encoding orientations (coronal, axial and sagittal). Diffusion tensor scalar measurements, tractography and the brain structural connectome were analyzed for each of the 12 acquisitions. The acquisition direction with respect to the main magnetic field orientation affected the diffusion results. When the acquisition slice-encoding direction was not aligned with the main magnetic field, there were more artifacts and a lower signal-to-noise ratio that led to less anisotropic tensors (lower fractional anisotropic values), producing poorer quality results. The use of anisometric voxels generated statistically significant differences in the values of diffusion metrics in specific regions. It also elicited differences in tract reconstruction and in different graph metric values describing the brain networks. Our results highlight the importance of taking into account the geometric aspects of acquisitions, especially when comparing diffusion data acquired using different geometries.
Ex Vivo Diffusion Tensor Imaging of Spinal Cord Injury in Rats of Varying Degrees of Severity
Jirjis, Michael B.; Kurpad, Shekar N.
2013-01-01
Abstract The aim of this study was to characterize magnetic resonance diffusion tensor imaging (DTI) in proximal regions of the spinal cord following a thoracic spinal cord injury (SCI). Sprague–Dawley rats (n=40) were administered a control, mild, moderate, or severe contusion injury at the T8 vertebral level. Six direction diffusion weighted images (DWIs) were collected ex vivo along the length of the spinal cord, with an echo/repetition time of 31.6 ms/14 sec and b=500 sec/mm2. Diffusion metrics were correlated to hindlimb motor function. Significant differences were found for whole cord region of interest (ROI) drawings for fractional anisotropy (FA), mean diffusivity (MD), longitudinal diffusion coefficient (LD), and radial diffusion coefficient (RD) at each of the cervical levels (p<0.01). Motor function correlated with MD in the cervical segments of the spinal cord (r2=0.80). The diffusivity of water significantly decreased throughout “uninjured” portions of the spinal cord following a contusion injury (p<0.05). Diffusivity metrics were found to be altered following SCI in both white and gray matter regions. Injury severity was associated with diffusion changes over the entire length of the cord. This study demonstrates that DTI is sensitive to SCI in regions remote from injury, suggesting that the diffusion metrics may be used as a biomarker for severity of injury. PMID:23782233
Axial diffusivity of the corona radiata correlated with ventricular size in adult hydrocephalus.
Cauley, Keith A; Cataltepe, Oguz
2014-07-01
Hydrocephalus causes changes in the diffusion-tensor properties of periventricular white matter. Understanding the nature of these changes may aid in the diagnosis and treatment planning of this relatively common neurologic condition. Because ventricular size is a common measure of the severity of hydrocephalus, we hypothesized that a quantitative correlation could be made between the ventricular size and diffusion-tensor changes in the periventricular corona radiata. In this article, we investigated this relationship in adult patients with hydrocephalus and in healthy adult subjects. Diffusion-tensor imaging metrics of the corona radiata were correlated with ventricular size in 14 adult patients with acute hydrocephalus, 16 patients with long-standing hydrocephalus, and 48 consecutive healthy adult subjects. Regression analysis was performed to investigate the relationship between ventricular size and the diffusion-tensor metrics of the corona radiata. Subject age was analyzed as a covariable. There is a linear correlation between fractional anisotropy of the corona radiata and ventricular size in acute hydrocephalus (r = 0.784, p < 0.001), with positive correlation with axial diffusivity (r = 0.636, p = 0.014) and negative correlation with radial diffusivity (r = 0.668, p = 0.009). In healthy subjects, axial diffusion in the periventricular corona radiata is more strongly correlated with ventricular size than with patient age (r = 0.466, p < 0.001, compared with r = 0.058, p = 0.269). Axial diffusivity of the corona radiata is linearly correlated with ventricular size in healthy adults and in patients with hydrocephalus. Radial diffusivity of the corona radiata decreases linearly with ventricular size in acute hydrocephalus but is not significantly correlated with ventricular size in healthy subjects or in patients with long-standing hydrocephalus.
Motion immune diffusion imaging using augmented MUSE (AMUSE) for high-resolution multi-shot EPI
Guhaniyogi, Shayan; Chu, Mei-Lan; Chang, Hing-Chiu; Song, Allen W.; Chen, Nan-kuei
2015-01-01
Purpose To develop new techniques for reducing the effects of microscopic and macroscopic patient motion in diffusion imaging acquired with high-resolution multi-shot EPI. Theory The previously reported Multiplexed Sensitivity Encoding (MUSE) algorithm is extended to account for macroscopic pixel misregistrations as well as motion-induced phase errors in a technique called Augmented MUSE (AMUSE). Furthermore, to obtain more accurate quantitative DTI measures in the presence of subject motion, we also account for the altered diffusion encoding among shots arising from macroscopic motion. Methods MUSE and AMUSE were evaluated on simulated and in vivo motion-corrupted multi-shot diffusion data. Evaluations were made both on the resulting imaging quality and estimated diffusion tensor metrics. Results AMUSE was found to reduce image blurring resulting from macroscopic subject motion compared to MUSE, but yielded inaccurate tensor estimations when neglecting the altered diffusion encoding. Including the altered diffusion encoding in AMUSE produced better estimations of diffusion tensors. Conclusion The use of AMUSE allows for improved image quality and diffusion tensor accuracy in the presence of macroscopic subject motion during multi-shot diffusion imaging. These techniques should facilitate future high-resolution diffusion imaging. PMID:25762216
Symmetric Positive 4th Order Tensors & Their Estimation from Diffusion Weighted MRI⋆
Barmpoutis, Angelos; Jian, Bing; Vemuri, Baba C.; Shepherd, Timothy M.
2009-01-01
In Diffusion Weighted Magnetic Resonance Image (DW-MRI) processing a 2nd order tensor has been commonly used to approximate the diffusivity function at each lattice point of the DW-MRI data. It is now well known that this 2nd-order approximation fails to approximate complex local tissue structures, such as fibers crossings. In this paper we employ a 4th order symmetric positive semi-definite (PSD) tensor approximation to represent the diffusivity function and present a novel technique to estimate these tensors from the DW-MRI data guaranteeing the PSD property. There have been several published articles in literature on higher order tensor approximations of the diffusivity function but none of them guarantee the positive semi-definite constraint, which is a fundamental constraint since negative values of the diffusivity coefficients are not meaningful. In our methods, we parameterize the 4th order tensors as a sum of squares of quadratic forms by using the so called Gram matrix method from linear algebra and its relation to the Hilbert’s theorem on ternary quartics. This parametric representation is then used in a nonlinear-least squares formulation to estimate the PSD tensors of order 4 from the data. We define a metric for the higher-order tensors and employ it for regularization across the lattice. Finally, performance of this model is depicted on synthetic data as well as real DW-MRI from an isolated rat hippocampus. PMID:17633709
Correlation between diffusion kurtosis and NODDI metrics in neonates and young children
NASA Astrophysics Data System (ADS)
Ahmed, Shaheen; Wang, Zhiyue J.; Chia, Jonathan M.; Rollins, Nancy K.
2016-03-01
Diffusion Tensor Imaging (DTI) uses single shell gradient encoding scheme for studying brain tissue diffusion. NODDI (Neurite Orientation Dispersion and Density Imaging) incorporates a gradient scheme with multiple b-values which is used to characterize neurite density and coherence of neuron fiber orientations. Similarly, the diffusion kurtosis imaging also uses a multiple shell scheme to quantify non-Gaussian diffusion but does not assume a tissue model like NODDI. In this study we investigate the connection between metrics derived by NODDI and DKI in children with ages from 46 weeks to 6 years. We correlate the NODDI metrics and Kurtosis measures from the same ROIs in multiple brain regions. We compare the range of these metrics between neonates (46 - 47 weeks), infants (2 -10 months) and young children (2 - 6 years). We find that there exists strong correlation between neurite density vs. mean kurtosis, orientation dispersion vs. kurtosis fractional anisotropy (FA) in pediatric brain imaging.
Generalized minimal principle for rotor filaments.
Dierckx, Hans; Wellner, Marcel; Bernus, Olivier; Verschelde, Henri
2015-05-01
To a reaction-diffusion medium with an inhomogeneous anisotropic diffusion tensor D, we add a fourth spatial dimension such that the determinant of the diffusion tensor is constant in four dimensions. We propose a generalized minimal principle for rotor filaments, stating that the scroll wave filament strives to minimize its surface area in the higher-dimensional space. As a consequence, stationary scroll wave filaments in the original 3D medium are geodesic curves with respect to the metric tensor G=det(D)D(-1). The theory is confirmed by numerical simulations for positive and negative filament tension and a model with a non-stationary spiral core. We conclude that filaments in cardiac tissue with positive tension preferentially reside or anchor in regions where cardiac cells are less interconnected, such as portions of the cardiac wall with a large number of cleavage planes.
Sigmund, E E; Baete, S H; Luo, T; Patel, K; Wang, D; Rossi, I; Duarte, A; Bruno, M; Mossa, D; Femia, A; Ramachandran, S; Stoffel, D; Babb, J S; Franks, A; Bencardino, J
2018-06-04
Dermatomyositis (DM) is an idiopathic inflammatory myopathy involving severe debilitation in need of diagnostics. We evaluated the proximal lower extremity musculature with diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM) and dynamic DTI in DM patients and controls and compared with standard clinical workup. METHODS: In this IRB-approved, HIPAA-compliant study with written informed consent, anatomical, Dixon fat/water and diffusion imaging were collected in bilateral thigh MRI of 22 controls and 27 DM patients in a 3T scanner. Compartments were scored on T1/T2 scales. Single voxel dynamic DTI metrics in quadriceps before and after 3-min leg exercise were measured. Spearman rank correlation and mixed model analysis of variance/covariance (ANOVA/ANCOVA) were used to correlate with T1 and T2 scores and to compare patients with controls. DM patients showed significantly lower pseudo-diffusion and volume in quadriceps than controls. All subjects showed significant correlation between T1 score and signal-weighted fat fraction; tissue diffusion and pseudo-diffusion varied significantly with T1 and T2 score in patients. Radial and mean diffusion exercise response in patients was significantly higher than controls. Static and dynamic diffusion imaging metrics show correlation with conventional imaging scores, reveal spatial heterogeneity, and provide means to differentiate dermatomyositis patients from controls. • Diffusion imaging shows regional differences between thigh muscles of dermatomyositis patients and controls. • Signal-weighted fat fraction and diffusion metrics correlate with T1/T2 scores of disease severity. • Dermatomyositis patients show significantly higher radial diffusion exercise response than controls.
DTI segmentation by statistical surface evolution.
Lenglet, Christophe; Rousson, Mikaël; Deriche, Rachid
2006-06-01
We address the problem of the segmentation of cerebral white matter structures from diffusion tensor images (DTI). A DTI produces, from a set of diffusion-weighted MR images, tensor-valued images where each voxel is assigned with a 3 x 3 symmetric, positive-definite matrix. This second order tensor is simply the covariance matrix of a local Gaussian process, with zero-mean, modeling the average motion of water molecules. As we will show in this paper, the definition of a dissimilarity measure and statistics between such quantities is a nontrivial task which must be tackled carefully. We claim and demonstrate that, by using the theoretically well-founded differential geometrical properties of the manifold of multivariate normal distributions, it is possible to improve the quality of the segmentation results obtained with other dissimilarity measures such as the Euclidean distance or the Kullback-Leibler divergence. The main goal of this paper is to prove that the choice of the probability metric, i.e., the dissimilarity measure, has a deep impact on the tensor statistics and, hence, on the achieved results. We introduce a variational formulation, in the level-set framework, to estimate the optimal segmentation of a DTI according to the following hypothesis: Diffusion tensors exhibit a Gaussian distribution in the different partitions. We must also respect the geometric constraints imposed by the interfaces existing among the cerebral structures and detected by the gradient of the DTI. We show how to express all the statistical quantities for the different probability metrics. We validate and compare the results obtained on various synthetic data-sets, a biological rat spinal cord phantom and human brain DTIs.
Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging
Lauzon, Carolyn B.; Asman, Andrew J.; Esparza, Michael L.; Burns, Scott S.; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W.; Davis, Nicole; Cutting, Laurie E.; Landman, Bennett A.
2013-01-01
Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible. PMID:23637895
Simultaneous analysis and quality assurance for diffusion tensor imaging.
Lauzon, Carolyn B; Asman, Andrew J; Esparza, Michael L; Burns, Scott S; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W; Davis, Nicole; Cutting, Laurie E; Landman, Bennett A
2013-01-01
Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible.
Hung, Peter S-P; Chen, David Q; Davis, Karen D; Zhong, Jidan; Hodaie, Mojgan
2017-01-01
Trigeminal neuralgia (TN) is a chronic neuropathic facial pain disorder that commonly responds to surgery. A proportion of patients, however, do not benefit and suffer ongoing pain. There are currently no imaging tools that permit the prediction of treatment response. To address this paucity, we used diffusion tensor imaging (DTI) to determine whether pre-surgical trigeminal nerve microstructural diffusivities can prognosticate response to TN treatment. In 31 TN patients and 16 healthy controls, multi-tensor tractography was used to extract DTI-derived metrics-axial (AD), radial (RD), mean diffusivity (MD), and fractional anisotropy (FA)-from the cisternal segment, root entry zone and pontine segment of trigeminal nerves for false discovery rate-corrected Student's t -tests. Ipsilateral diffusivities were bootstrap resampled to visualize group-level diffusivity thresholds of long-term response. To obtain an individual-level statistical classifier of surgical response, we conducted discriminant function analysis (DFA) with the type of surgery chosen alongside ipsilateral measurements and ipsilateral/contralateral ratios of AD and RD from all regions of interest as prediction variables. Abnormal diffusivity in the trigeminal pontine fibers, demonstrated by increased AD, highlighted non-responders (n = 14) compared to controls. Bootstrap resampling revealed three ipsilateral diffusivity thresholds of response-pontine AD, MD, cisternal FA-separating 85% of non-responders from responders. DFA produced an 83.9% (71.0% using leave-one-out-cross-validation) accurate prognosticator of response that successfully identified 12/14 non-responders. Our study demonstrates that pre-surgical DTI metrics can serve as a highly predictive, individualized tool to prognosticate surgical response. We further highlight abnormal pontine segment diffusivities as key features of treatment non-response and confirm the axiom that central pain does not commonly benefit from peripheral treatments.
Advances in magnetic resonance neuroimaging techniques in the evaluation of neonatal encephalopathy.
Panigrahy, Ashok; Blüml, Stefan
2007-02-01
Magnetic resonance (MR) imaging has become an essential tool in the evaluation of neonatal encephalopathy. Magnetic resonance-compatible neonatal incubators allow sick neonates to be transported to the MR scanner, and neonatal head coils can improve signal-to-noise ratio, critical for advanced MR imaging techniques. Refinement of conventional imaging techniques include the use of PROPELLER techniques for motion correction. Magnetic resonance spectroscopic imaging and diffusion tensor imaging provide quantitative assessment of both brain development and brain injury in the newborn with respect to metabolite abnormalities and hypoxic-ischemic injury. Knowledge of normal developmental changes in MR spectroscopy metabolite concentration and diffusion tensor metrics is essential to interpret pathological cases. Perfusion MR and functional MR can provide additional physiological information. Both MR spectroscopy and diffusion tensor imaging can provide additional information in the differential of neonatal encephalopathy, including perinatal white matter injury, hypoxic-ischemic brain injury, metabolic disease, infection, and birth injury.
Dimensions of Attention Associated With the Microstructure of Corona Radiata White Matter.
Stave, Elise A; De Bellis, Michael D; Hooper, Steven R; Woolley, Donald P; Chang, Suk Ki; Chen, Steven D
2017-04-01
Mirsky proposed a model of attention that included these dimensions: focus/execute, sustain, stabilize, encode, and shift. The neural correlates of these dimensions were investigated within corona radiata subregions in healthy youth. Diffusion tensor imaging and neuropsychological assessments were conducted in 79 healthy, right-handed youth aged 4-17 years. Diffusion tensor imaging maps were analyzed using standardized parcellation methods. Partial Pearson correlations between neuropsychological standardized scores, representing these attention dimensions, and diffusion tensor imaging measures of corona radiata subregions were calculated after adjusting for gender and IQ. Significant correlations were found between the focus/execute, sustain, stabilize, and shift dimensions and imaging metrics in hypothesized corona radiata subregions. Results suggest that greater microstructural white matter integrity of the corona radiata is partly associated with attention across 4 attention dimensions. Findings suggest that white matter microstructure of the corona radiata is a neural correlate of several, but not all, attention dimensions.
Dimensions of Attention Associated with the Microstructure of Corona Radiata White Matter
Stave, Elise A.; Hooper, Stephen R.; Woolley, Donald P.; Chang, Suk Ki; Chen, Steven D.
2016-01-01
Mirsky proposed a model of attention that included these dimensions: focus/execute, sustain, stabilize, encode, and shift. The neural correlates of these dimensions were investigated within corona radiate subregions in healthy youth. Diffusion tensor imaging and neuropsychological assessments were conducted in 79 healthy, right-handed youth aged 4–17 years. Diffusion tensor imaging maps were analyzed using standardized parcellation methods. Partial Pearson correlations between neuropsychological standardized scores, representing these attention dimensions, and diffusion tensor imaging measures of corona radiate subregions were calculated after adjusting for gender and IQ. Significant correlations were found between the focus/execute, sustain, stabilize and shift dimensions and imaging metrics in hypothesized corona radiate subregions. Results suggest that greater microstructural white matter integrity of the corona radiata is partly associated with attention across four attention dimensions. Findings suggest that white matter microstructure of the corona radiata is a neural correlate of several, but not all, attention dimensions. PMID:28090797
Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging.
Yang, Alicia W; Jensen, Jens H; Hu, Caixia C; Tabesh, Ali; Falangola, Maria F; Helpern, Joseph A
2013-02-01
To evaluate the cerebral spinal fluid (CSF) partial volume effect on diffusional kurtosis imaging (DKI) metrics in white matter and cortical gray matter. Four healthy volunteers participated in this study. Standard DKI and fluid-attenuated inversion recovery (FLAIR) DKI experiments were performed using a twice-refocused-spin-echo diffusion sequence. The conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, D[symbol in text], D[symbol in text] together with DKI metrics of mean, axial, and radial kurtosis (MK, K[symbol in text], K[symbol in text], were measured and compared. Single image slices located above the lateral ventricles, with similar anatomical features for each subject, were selected to minimize the effect of CSF from the ventricles. In white matter, differences of less than 10% were observed between diffusion metrics measured with standard DKI and FLAIR-DKI sequences, suggesting minimal CSF contamination. For gray matter, conventional DTI metrics differed by 19% to 52%, reflecting significant CSF partial volume effects. Kurtosis metrics, however, changed by 11% or less, indicating greater robustness with respect to CSF contamination. Kurtosis metrics are less sensitive to CSF partial voluming in cortical gray matter than conventional diffusion metrics. The kurtosis metrics may then be more specific indicators of changes in tissue microstructure, provided the effect sizes for the changes are comparable. Copyright © 2012 Wiley Periodicals, Inc.
Evaluation of diffusion kurtosis imaging in ex vivo hypomyelinated mouse brains.
Kelm, Nathaniel D; West, Kathryn L; Carson, Robert P; Gochberg, Daniel F; Ess, Kevin C; Does, Mark D
2016-01-01
Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and DKI-derived white matter tract integrity metrics (WMTI) were experimentally evaluated ex vivo through comparisons to histological measurements and established magnetic resonance imaging (MRI) measures of myelin in two knockout mouse models with varying degrees of hypomyelination. DKI metrics of mean and radial kurtosis were found to be better indicators of myelin content than conventional DTI metrics. The biophysical WMTI model based on the DKI framework reported on axon water fraction with good accuracy in cases with near normal axon density, but did not provide additional specificity to myelination. Overall, DKI provided additional information regarding white matter microstructure compared with DTI, making it an attractive method for future assessments of white matter development and pathology. Copyright © 2015 Elsevier Inc. All rights reserved.
Liu, W; Yan, B; An, D; Niu, R; Tang, Y; Tong, X; Gong, Q; Zhou, D
2017-12-01
This study aimed to assess the evolution of perinodular and contralateral white matter abnormalities in patients with periventricular nodular heterotopia (PNH) and epilepsy. Diffusion tensor imaging (DTI) (64 directions) and 3 T structural magnetic resonance imaging were performed in 29 PNH patients (mean age 27.3 years), and 16 patients underwent a second scan (average time between the two scans 1.1 years). Fractional anisotropy and mean diffusivity were measured within the perilesional and contralateral white matter. Longitudinal analysis showed that white matter located 10 mm from the focal nodule displayed characteristics intermediate to tissue 5 mm away, and normal-appearing white matter (NAWM) also established evolution profiles of perinodular white matter in different cortical lobes. Compared to 29 age- and sex-matched healthy controls, significant decreased fractional anisotropy and elevated mean diffusivity values were observed in regions 5 and 10 mm from nodules (P < 0.01), whilst DTI metrics of the remaining NAWM did not differ significantly from controls. Additionally, normal DTI metrics were shown in the contralateral region in patients with unilateral PNH. Periventricular nodular heterotopia is associated with microstructural abnormalities within the perilesional white matter and the extent decreases with increasing distance from the nodule. In the homologous contralateral region, white matter diffusion metrics were unchanged in unilateral PNH. These findings have clinical implications with respect to the medical and surgical interventions of PNH-related epilepsy. © 2017 EAN.
Whittaker, Heather T; Zhu, Shenghua; Di Curzio, Domenico L; Buist, Richard; Li, Xin-Min; Noy, Suzanna; Wiseman, Frances K; Thiessen, Jonathan D; Martin, Melanie
2018-07-01
Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T 1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T 1 -weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD. Copyright © 2018. Published by Elsevier Inc.
Improvement of Reliability of Diffusion Tensor Metrics in Thigh Skeletal Muscles.
Keller, Sarah; Chhabra, Avneesh; Ahmed, Shaheen; Kim, Anne C; Chia, Jonathan M; Yamamura, Jin; Wang, Zhiyue J
2018-05-01
Quantitative diffusion tensor imaging (DTI) of skeletal muscles is challenging due to the bias in DTI metrics, such as fractional anisotropy (FA) and mean diffusivity (MD), related to insufficient signal-to-noise ratio (SNR). This study compares the bias of DTI metrics in skeletal muscles via pixel-based and region-of-interest (ROI)-based analysis. DTI of the thigh muscles was conducted on a 3.0-T system in N = 11 volunteers using a fat-suppressed single-shot spin-echo echo planar imaging (SS SE-EPI) sequence with eight repetitions (number of signal averages (NSA) = 4 or 8 for each repeat). The SNR was calculated for different NSAs and estimated for the composite images combining all data (effective NSA = 48) as standard reference. The bias of MD and FA derived by pixel-based and ROI-based quantification were compared at different NSAs. An "intra-ROI diffusion direction dispersion angle (IRDDDA)" was calculated to assess the uniformity of diffusion within the ROI. Using our standard reference image with NSA = 48, the ROI-based and pixel-based measurements agreed for FA and MD. Larger disagreements were observed for the pixel-based quantification at NSA = 4. MD was less sensitive than FA to the noise level. The IRDDDA decreased with higher NSA. At NSA = 4, ROI-based FA showed a lower average bias (0.9% vs. 37.4%) and narrower 95% limits of agreement compared to the pixel-based method. The ROI-based estimation of FA is less prone to bias than the pixel-based estimations when SNR is low. The IRDDDA can be applied as a quantitative quality measure to assess reliability of ROI-based DTI metrics. Copyright © 2018 Elsevier B.V. All rights reserved.
Palacios, E M; Martin, A J; Boss, M A; Ezekiel, F; Chang, Y S; Yuh, E L; Vassar, M J; Schnyer, D M; MacDonald, C L; Crawford, K L; Irimia, A; Toga, A W; Mukherjee, P
2017-03-01
Precision medicine is an approach to disease diagnosis, treatment, and prevention that relies on quantitative biomarkers that minimize the variability of individual patient measurements. The aim of this study was to assess the intersite variability after harmonization of a high-angular-resolution 3T diffusion tensor imaging protocol across 13 scanners at the 11 academic medical centers participating in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury multisite study. Diffusion MR imaging was acquired from a novel isotropic diffusion phantom developed at the National Institute of Standards and Technology and from the brain of a traveling volunteer on thirteen 3T MR imaging scanners representing 3 major vendors (GE Healthcare, Philips Healthcare, and Siemens). Means of the DTI parameters and their coefficients of variation across scanners were calculated for each DTI metric and white matter tract. For the National Institute of Standards and Technology diffusion phantom, the coefficients of variation of the apparent diffusion coefficient across the 13 scanners was <3.8% for a range of diffusivities from 0.4 to 1.1 × 10 -6 mm 2 /s. For the volunteer, the coefficients of variations across scanners of the 4 primary DTI metrics, each averaged over the entire white matter skeleton, were all <5%. In individual white matter tracts, large central pathways showed good reproducibility with the coefficients of variation consistently below 5%. However, smaller tracts showed more variability, with the coefficients of variation of some DTI metrics reaching 10%. The results suggest the feasibility of standardizing DTI across 3T scanners from different MR imaging vendors in a large-scale neuroimaging research study. © 2017 by American Journal of Neuroradiology.
Giraudo, Chiara; Motyka, Stanislav; Weber, Michael; Resinger, Christoph; Thorsten, Feiweier; Traxler, Hannes; Trattnig, Siegfried; Bogner, Wolfgang
2017-08-01
The aim of this study was to investigate the origin of random image artifacts in stimulated echo acquisition mode diffusion tensor imaging (STEAM-DTI), assess the role of averaging, develop an automated artifact postprocessing correction method using weighted mean of signal intensities (WMSIs), and compare it with other correction techniques. Institutional review board approval and written informed consent were obtained. The right calf and thigh of 10 volunteers were scanned on a 3 T magnetic resonance imaging scanner using a STEAM-DTI sequence.Artifacts (ie, signal loss) in STEAM-based DTI, presumably caused by involuntary muscle contractions, were investigated in volunteers and ex vivo (ie, human cadaver calf and turkey leg using the same DTI parameters as for the volunteers). An automated postprocessing artifact correction method based on the WMSI was developed and compared with previous approaches (ie, iteratively reweighted linear least squares and informed robust estimation of tensors by outlier rejection [iRESTORE]). Diffusion tensor imaging and fiber tracking metrics, using different averages and artifact corrections, were compared for region of interest- and mask-based analyses. One-way repeated measures analysis of variance with Greenhouse-Geisser correction and Bonferroni post hoc tests were used to evaluate differences among all tested conditions. Qualitative assessment (ie, images quality) for native and corrected images was performed using the paired t test. Randomly localized and shaped artifacts affected all volunteer data sets. Artifact burden during voluntary muscle contractions increased on average from 23.1% to 77.5% but were absent ex vivo. Diffusion tensor imaging metrics (mean diffusivity, fractional anisotropy, radial diffusivity, and axial diffusivity) had a heterogeneous behavior, but in the range reported by literature. Fiber track metrics (number, length, and volume) significantly improved in both calves and thighs after artifact correction in region of interest- and mask-based analyses (P < 0.05 each). Iteratively reweighted linear least squares and iRESTORE showed equivalent results, but WMSI was faster than iRESTORE. Muscle delineation and artifact load significantly improved after correction (P < 0.05 each). Weighted mean of signal intensity correction significantly improved STEAM-based quantitative DTI analyses and fiber tracking of lower-limb muscles, providing a robust tool for musculoskeletal applications.
Helmer, K G; Chou, M-C; Preciado, R I; Gimi, B; Rollins, N K; Song, A; Turner, J; Mori, S
2016-02-27
MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables.
A Review of Tensors and Tensor Signal Processing
NASA Astrophysics Data System (ADS)
Cammoun, L.; Castaño-Moraga, C. A.; Muñoz-Moreno, E.; Sosa-Cabrera, D.; Acar, B.; Rodriguez-Florido, M. A.; Brun, A.; Knutsson, H.; Thiran, J. P.
Tensors have been broadly used in mathematics and physics, since they are a generalization of scalars or vectors and allow to represent more complex properties. In this chapter we present an overview of some tensor applications, especially those focused on the image processing field. From a mathematical point of view, a lot of work has been developed about tensor calculus, which obviously is more complex than scalar or vectorial calculus. Moreover, tensors can represent the metric of a vector space, which is very useful in the field of differential geometry. In physics, tensors have been used to describe several magnitudes, such as the strain or stress of materials. In solid mechanics, tensors are used to define the generalized Hooke’s law, where a fourth order tensor relates the strain and stress tensors. In fluid dynamics, the velocity gradient tensor provides information about the vorticity and the strain of the fluids. Also an electromagnetic tensor is defined, that simplifies the notation of the Maxwell equations. But tensors are not constrained to physics and mathematics. They have been used, for instance, in medical imaging, where we can highlight two applications: the diffusion tensor image, which represents how molecules diffuse inside the tissues and is broadly used for brain imaging; and the tensorial elastography, which computes the strain and vorticity tensor to analyze the tissues properties. Tensors have also been used in computer vision to provide information about the local structure or to define anisotropic image filters.
Woo, John H; Wang, Sumei; Melhem, Elias R; Gee, James C; Cucchiara, Andrew; McCluskey, Leo; Elman, Lauren
2014-01-01
To assess the relationship between clinically assessed Upper Motor Neuron (UMN) disease in Amyotrophic Lateral Sclerosis (ALS) and local diffusion alterations measured in the brain corticospinal tract (CST) by a tractography-driven template-space region-of-interest (ROI) analysis of Diffusion Tensor Imaging (DTI). This cross-sectional study included 34 patients with ALS, on whom DTI was performed. Clinical measures were separately obtained including the Penn UMN Score, a summary metric based upon standard clinical methods. After normalizing all DTI data to a population-specific template, tractography was performed to determine a region-of-interest (ROI) outlining the CST, in which average Mean Diffusivity (MD) and Fractional Anisotropy (FA) were estimated. Linear regression analyses were used to investigate associations of DTI metrics (MD, FA) with clinical measures (Penn UMN Score, ALSFRS-R, duration-of-disease), along with age, sex, handedness, and El Escorial category as covariates. For MD, the regression model was significant (p = 0.02), and the only significant predictors were the Penn UMN Score (p = 0.005) and age (p = 0.03). The FA regression model was also significant (p = 0.02); the only significant predictor was the Penn UMN Score (p = 0.003). Measured by the template-space ROI method, both MD and FA were linearly associated with the Penn UMN Score, supporting the hypothesis that DTI alterations reflect UMN pathology as assessed by the clinical examination.
Helmer, K. G.; Chou, M-C.; Preciado, R. I.; Gimi, B.; Rollins, N. K.; Song, A.; Turner, J.; Mori, S.
2016-01-01
MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables. PMID:27350723
Neji, Radhouène; Besbes, Ahmed; Komodakis, Nikos; Deux, Jean-François; Maatouk, Mezri; Rahmouni, Alain; Bassez, Guillaume; Fleury, Gilles; Paragios, Nikos
2009-01-01
In this paper, we present a manifold clustering method fo the classification of fibers obtained from diffusion tensor images (DTI) of the human skeletal muscle. Using a linear programming formulation of prototype-based clustering, we propose a novel fiber classification algorithm over manifolds that circumvents the necessity to embed the data in low dimensional spaces and determines automatically the number of clusters. Furthermore, we propose the use of angular Hilbertian metrics between multivariate normal distributions to define a family of distances between tensors that we generalize to fibers. These metrics are used to approximate the geodesic distances over the fiber manifold. We also discuss the case where only geodesic distances to a reduced set of landmark fibers are available. The experimental validation of the method is done using a manually annotated significant dataset of DTI of the calf muscle for healthy and diseased subjects.
Association between sociability and diffusion tensor imaging in BALB/cJ mice.
Kim, Sungheon; Pickup, Stephen; Fairless, Andrew H; Ittyerah, Ranjit; Dow, Holly C; Abel, Ted; Brodkin, Edward S; Poptani, Harish
2012-01-01
The purpose of this study was to use high-resolution diffusion tensor imaging (DTI) to investigate the association between DTI metrics and sociability in BALB/c inbred mice. The sociability of prepubescent (30-day-old) BALB/cJ mice was operationally defined as the time that the mice spent sniffing a stimulus mouse in a social choice test. High-resolution ex vivo DTI data on 12 BALB/cJ mouse brains were acquired using a 9.4-T vertical-bore magnet. Regression analysis was conducted to investigate the association between DTI metrics and sociability. Significant positive regression (p < 0.001) between social sniffing time and fractional anisotropy was found in 10 regions located in the thalamic nuclei, zona incerta/substantia nigra, visual/orbital/somatosensory cortices and entorhinal cortex. In addition, significant negative regression (p < 0.001) between social sniffing time and mean diffusivity was found in five areas located in the sensory cortex, motor cortex, external capsule and amygdaloid region. In all regions showing significant regression with either the mean diffusivity or fractional anisotropy, the tertiary eigenvalue correlated negatively with the social sniffing time. This study demonstrates the feasibility of using DTI to detect brain regions associated with sociability in a mouse model system. Copyright © 2011 John Wiley & Sons, Ltd.
An optimization-based framework for anisotropic simplex mesh adaptation
NASA Astrophysics Data System (ADS)
Yano, Masayuki; Darmofal, David L.
2012-09-01
We present a general framework for anisotropic h-adaptation of simplex meshes. Given a discretization and any element-wise, localizable error estimate, our adaptive method iterates toward a mesh that minimizes error for a given degrees of freedom. Utilizing mesh-metric duality, we consider a continuous optimization problem of the Riemannian metric tensor field that provides an anisotropic description of element sizes. First, our method performs a series of local solves to survey the behavior of the local error function. This information is then synthesized using an affine-invariant tensor manipulation framework to reconstruct an approximate gradient of the error function with respect to the metric tensor field. Finally, we perform gradient descent in the metric space to drive the mesh toward optimality. The method is first demonstrated to produce optimal anisotropic meshes minimizing the L2 projection error for a pair of canonical problems containing a singularity and a singular perturbation. The effectiveness of the framework is then demonstrated in the context of output-based adaptation for the advection-diffusion equation using a high-order discontinuous Galerkin discretization and the dual-weighted residual (DWR) error estimate. The method presented provides a unified framework for optimizing both the element size and anisotropy distribution using an a posteriori error estimate and enables efficient adaptation of anisotropic simplex meshes for high-order discretizations.
Irie, Ryusuke; Kamagata, Koji; Kerever, Aurelien; Ueda, Ryo; Yokosawa, Suguru; Otake, Yosuke; Ochi, Hisaaki; Yoshizawa, Hidekazu; Hayashi, Ayato; Tagawa, Kazuhiko; Okazawa, Hitoshi; Takahashi, Kohske; Sato, Kanako; Hori, Masaaki; Arikawa-Hirasawa, Eri; Aoki, Shigeki
2018-01-01
Purpose: Diffusional kurtosis imaging (DKI) enables sensitive measurement of tissue microstructure by quantifying the non-Gaussian diffusion of water. Although DKI is widely applied in many situations, histological correlation with DKI analysis is lacking. The purpose of this study was to determine the relationship between DKI metrics and neurite density measured using confocal microscopy of a cleared mouse brain. Methods: One thy-1 yellow fluorescent protein 16 mouse was deeply anesthetized and perfusion fixation was performed. The brain was carefully dissected out and whole-brain MRI was performed using a 7T animal MRI system. DKI and diffusion tensor imaging (DTI) data were obtained. After the MRI scan, brain sections were prepared and then cleared using aminoalcohols (CUBIC). Confocal microscopy was performed using a two-photon confocal microscope with a laser. Forty-eight ROIs were set on the caudate putamen, seven ROIs on the anterior commissure, and seven ROIs on the ventral hippocampal commissure on the confocal microscopic image and a corresponding MR image. In each ROI, histological neurite density and the metrics of DKI and DTI were calculated. The correlations between diffusion metrics and neurite density were analyzed using Pearson correlation coefficient analysis. Results: Mean kurtosis (MK) (P = 5.2 × 10−9, r = 0.73) and radial kurtosis (P = 2.3 × 10−9, r = 0.74) strongly correlated with neurite density in the caudate putamen. The correlation between fractional anisotropy (FA) and neurite density was moderate (P = 0.0030, r = 0.42). In the anterior commissure and the ventral hippocampal commissure, neurite density and FA are very strongly correlated (P = 1.3 × 10−5, r = 0.90). MK in these areas were very high value and showed no significant correlation (P = 0.48). Conclusion: DKI accurately reflected neurite density in the area with crossing fibers, potentially allowing evaluation of complex microstructures. PMID:29213008
Irie, Ryusuke; Kamagata, Koji; Kerever, Aurelien; Ueda, Ryo; Yokosawa, Suguru; Otake, Yosuke; Ochi, Hisaaki; Yoshizawa, Hidekazu; Hayashi, Ayato; Tagawa, Kazuhiko; Okazawa, Hitoshi; Takahashi, Kohske; Sato, Kanako; Hori, Masaaki; Arikawa-Hirasawa, Eri; Aoki, Shigeki
2018-04-10
Diffusional kurtosis imaging (DKI) enables sensitive measurement of tissue microstructure by quantifying the non-Gaussian diffusion of water. Although DKI is widely applied in many situations, histological correlation with DKI analysis is lacking. The purpose of this study was to determine the relationship between DKI metrics and neurite density measured using confocal microscopy of a cleared mouse brain. One thy-1 yellow fluorescent protein 16 mouse was deeply anesthetized and perfusion fixation was performed. The brain was carefully dissected out and whole-brain MRI was performed using a 7T animal MRI system. DKI and diffusion tensor imaging (DTI) data were obtained. After the MRI scan, brain sections were prepared and then cleared using aminoalcohols (CUBIC). Confocal microscopy was performed using a two-photon confocal microscope with a laser. Forty-eight ROIs were set on the caudate putamen, seven ROIs on the anterior commissure, and seven ROIs on the ventral hippocampal commissure on the confocal microscopic image and a corresponding MR image. In each ROI, histological neurite density and the metrics of DKI and DTI were calculated. The correlations between diffusion metrics and neurite density were analyzed using Pearson correlation coefficient analysis. Mean kurtosis (MK) (P = 5.2 × 10 -9 , r = 0.73) and radial kurtosis (P = 2.3 × 10 -9 , r = 0.74) strongly correlated with neurite density in the caudate putamen. The correlation between fractional anisotropy (FA) and neurite density was moderate (P = 0.0030, r = 0.42). In the anterior commissure and the ventral hippocampal commissure, neurite density and FA are very strongly correlated (P = 1.3 × 10 -5 , r = 0.90). MK in these areas were very high value and showed no significant correlation (P = 0.48). DKI accurately reflected neurite density in the area with crossing fibers, potentially allowing evaluation of complex microstructures.
Helmer, K G; Chou, M-C; Preciado, R I; Gimi, B; Rollins, N K; Song, A; Turner, J; Mori, S
2016-02-27
It is now common for magnetic-resonance-imaging (MRI) based multi-site trials to include diffusion-weighted imaging (DWI) as part of the protocol. It is also common for these sites to possess MR scanners of different manufacturers, different software and hardware, and different software licenses. These differences mean that scanners may not be able to acquire data with the same number of gradient amplitude values and number of available gradient directions. Variability can also occur in achievable b-values and minimum echo times. The challenge of a multi-site study then, is to create a common protocol by understanding and then minimizing the effects of scanner variability and identifying reliable and accurate diffusion metrics. This study describes the effect of site, scanner vendor, field strength, and TE on two diffusion metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA) using two common analyses (region-of-interest and mean-bin value of whole brain histograms). The goal of the study was to identify sources of variability in diffusion-sensitized imaging and their influence on commonly reported metrics. The results demonstrate that the site, vendor, field strength, and echo time all contribute to variability in FA and MD, though to different extent. We conclude that characterization of the variability of DTI metrics due to site, vendor, field strength, and echo time is a worthwhile step in the construction of multi-center trials.
A diffusion tensor imaging tractography algorithm based on Navier-Stokes fluid mechanics.
Hageman, Nathan S; Toga, Arthur W; Narr, Katherine L; Shattuck, David W
2009-03-01
We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color images of the DTI dataset.
A Diffusion Tensor Imaging Tractography Algorithm Based on Navier-Stokes Fluid Mechanics
Hageman, Nathan S.; Toga, Arthur W.; Narr, Katherine; Shattuck, David W.
2009-01-01
We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color (DEC) images of the DTI dataset. PMID:19244007
Elzibak, Alyaa H; Noseworthy, Michael D
2014-10-01
To investigate whether postural change from erect to recumbent position affects calf muscle water diffusivity. Ten healthy adults (27.2 ± 4.9 years, 3 females) were imaged at baseline (following assumption of recumbent position), and after 34 min (session 2) and 64 min (session 3) of laying supine within a 3T MRI scanner. Diffusion tensor imaging (DTI) eigenvalues, fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were evaluated in five calf muscles (anterior and posterior tibialis and triceps surae) during each of the three imaging sessions. Significant decreases were observed in all of the eigenvalues and ADC in each of the muscles with postural change. These reductions ranged from 3.2 to 6.7% and 3.4 to 7.5% for the various DTI metrics, following 34 and 64 min of supine rest, respectively (P < 0.05). No significant differences were noted in ADC or eigenvalues between the second and third imaging sessions for any muscle. FA did not change significantly with postural manipulation in any muscle compartment. Diffusion tensor imaging indices were altered with postural change. As differences were not apparent between the latter two imaging sessions, we suggest that a short supine resting period (~34 min) is sufficient for muscle diffusivity to stabilize prior to quantitative MR imaging in healthy young adults.
Ardekani, Siamak; Selva, Luis; Sayre, James; Sinha, Usha
2006-11-01
Single-shot echo-planar based diffusion tensor imaging is prone to geometric and intensity distortions. Parallel imaging is a means of reducing these distortions while preserving spatial resolution. A quantitative comparison at 3 T of parallel imaging for diffusion tensor images (DTI) using k-space (generalized auto-calibrating partially parallel acquisitions; GRAPPA) and image domain (sensitivity encoding; SENSE) reconstructions at different acceleration factors, R, is reported here. Images were evaluated using 8 human subjects with repeated scans for 2 subjects to estimate reproducibility. Mutual information (MI) was used to assess the global changes in geometric distortions. The effects of parallel imaging techniques on random noise and reconstruction artifacts were evaluated by placing 26 regions of interest and computing the standard deviation of apparent diffusion coefficient and fractional anisotropy along with the error of fitting the data to the diffusion model (residual error). The larger positive values in mutual information index with increasing R values confirmed the anticipated decrease in distortions. Further, the MI index of GRAPPA sequences for a given R factor was larger than the corresponding mSENSE images. The residual error was lowest in the images acquired without parallel imaging and among the parallel reconstruction methods, the R = 2 acquisitions had the least error. The standard deviation, accuracy, and reproducibility of the apparent diffusion coefficient and fractional anisotropy in homogenous tissue regions showed that GRAPPA acquired with R = 2 had the least amount of systematic and random noise and of these, significant differences with mSENSE, R = 2 were found only for the fractional anisotropy index. Evaluation of the current implementation of parallel reconstruction algorithms identified GRAPPA acquired with R = 2 as optimal for diffusion tensor imaging.
Faber, J; Wilde, E A; Hanten, G; Ewing-Cobbs, L; Aitken, M E; Yallampalli, R; MacLeod, M C; Mullins, S H; Chu, Z D; Li, X; Hunter, J V; Noble-Haeusslein, L; Levin, H S
2016-01-01
The long-term effects of TBI on verbal fluency and related structures, as well as the relation between cognition and structural integrity, were evaluated. It was hypothesized that the group with TBI would evidence poorer performance on cognitive measures and a decrease in structural integrity. Between a paediatric group with TBI and a group of typically-developing children, the long-term effects of traumatic brain injury were investigated in relation to both structural integrity and cognition. Common metrics for diffusion tensor imaging (DTI) were used as indicators of white matter integrity. Using DTI, this study examined ventral striatum (VS) integrity in 21 patients aged 10-18 years sustaining moderate-to-severe traumatic brain injury (TBI) 5-15 years earlier and 16 demographically comparable subjects. All participants completed Delis-Kaplan Executive Functioning System (D-KEFS) sub-tests. The group with TBI exhibited lower fractional anisotropy (FA) and executive functioning performance and higher apparent diffusion coefficient (ADC). DTI metrics correlated with D-KEFS performance (right VS FA with Inhibition errors, right VS ADC with Letter Fluency, left VS FA and ADC with Category Switching). TBI affects VS integrity, even in a chronic phase, and may contribute to executive functioning deficits.
Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors.
Wagner, Matthias W; Narayan, Anand K; Bosemani, Thangamadhan; Huisman, Thierry A G M; Poretti, Andrea
2016-05-01
Apparent diffusion coefficient (ADC) values have been shown to assist in differentiating cerebellar pilocytic astrocytomas and medulloblastomas. Previous studies have applied only ADC measurements and calculated the mean/median values. Here we investigated the value of diffusion tensor imaging (DTI) histogram characteristics of the entire tumor for differentiation of cerebellar pilocytic astrocytomas and medulloblastomas. Presurgical DTI data were analyzed with a region of interest (ROI) approach to include the entire tumor. For each tumor, histogram-derived metrics including the 25th percentile, 75th percentile, and skewness were calculated for fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity. The histogram metrics were used as primary predictors of interest in a logistic regression model. Statistical significance levels were set at p < .01. The study population included 17 children with pilocytic astrocytoma and 16 with medulloblastoma (mean age, 9.21 ± 5.18 years and 7.66 ± 4.97 years, respectively). Compared to children with medulloblastoma, children with pilocytic astrocytoma showed higher MD (P = .003 and P = .008), AD (P = .004 and P = .007), and RD (P = .003 and P = .009) values for the 25th and 75th percentile. In addition, histogram skewness showed statistically significant differences for MD between low- and high-grade tumors (P = .008). The 25th percentile for MD yields the best results for the presurgical differentiation between pediatric cerebellar pilocytic astrocytomas and medulloblastomas. The analysis of other DTI metrics does not provide additional diagnostic value. Our study confirms the diagnostic value of the quantitative histogram analysis of DTI data in pediatric neuro-oncology. Copyright © 2015 by the American Society of Neuroimaging.
Sadeghi, N.; Namjoshi, D.; Irfanoglu, M. O.; Wellington, C.; Diaz-Arrastia, R.
2017-01-01
Diffuse axonal injury (DAI) is a hallmark of traumatic brain injury (TBI) pathology. Recently, the Closed Head Injury Model of Engineered Rotational Acceleration (CHIMERA) was developed to generate an experimental model of DAI in a mouse. The characterization of DAI using diffusion tensor magnetic resonance imaging (MRI; diffusion tensor imaging, DTI) may provide a useful set of outcome measures for preclinical and clinical studies. The objective of this study was to identify the complex neurobiological underpinnings of DTI features following DAI using a comprehensive and quantitative evaluation of DTI and histopathology in the CHIMERA mouse model. A consistent neuroanatomical pattern of pathology in specific white matter tracts was identified across ex vivo DTI maps and photomicrographs of histology. These observations were confirmed by voxelwise and regional analysis of DTI maps, demonstrating reduced fractional anisotropy (FA) in distinct regions such as the optic tract. Similar regions were identified by quantitative histology and exhibited axonal damage as well as robust gliosis. Additional analysis using a machine-learning algorithm was performed to identify regions and metrics important for injury classification in a manner free from potential user bias. This analysis found that diffusion metrics were able to identify injured brains almost with the same degree of accuracy as the histology metrics. Good agreement between regions detected as abnormal by histology and MRI was also found. The findings of this work elucidate the complexity of cellular changes that give rise to imaging abnormalities and provide a comprehensive and quantitative evaluation of the relative importance of DTI and histological measures to detect brain injury. PMID:28966972
Brain structural changes in spasmodic dysphonia: A multimodal magnetic resonance imaging study.
Kostic, Vladimir S; Agosta, Federica; Sarro, Lidia; Tomić, Aleksandra; Kresojević, Nikola; Galantucci, Sebastiano; Svetel, Marina; Valsasina, Paola; Filippi, Massimo
2016-04-01
The pathophysiology of spasmodic dysphonia is poorly understood. This study evaluated patterns of cortical morphology, basal ganglia, and white matter microstructural alterations in patients with spasmodic dysphonia relative to healthy controls. T1-weighted and diffusion tensor magnetic resonance imaging (MRI) scans were obtained from 13 spasmodic dysphonia patients and 30 controls. Tract-based spatial statistics was applied to compare diffusion tensor MRI indices (i.e., mean, radial and axial diffusivities, and fractional anisotropy) between groups on a voxel-by-voxel basis. Cortical measures were analyzed using surface-based morphometry. Basal ganglia were segmented on T1-weighted images, and volumes and diffusion tensor MRI metrics of nuclei were measured. Relative to controls, patients with spasmodic dysphonia showed increased cortical surface area of the primary somatosensory cortex bilaterally in a region consistent with the buccal sensory representation, as well as right primary motor cortex, left superior temporal, supramarginal and superior frontal gyri. A decreased cortical area was found in the rolandic operculum bilaterally, left superior/inferior parietal and lingual gyri, as well as in the right angular gyrus. Compared to controls, spasmodic dysphonia patients showed increased diffusivities and decreased fractional anisotropy of the corpus callosum and major white matter tracts, in the right hemisphere. Altered diffusion tensor MRI measures were found in the right caudate and putamen nuclei with no volumetric changes. Multi-level alterations in voice-controlling networks, that included regions devoted not only to sensorimotor integration, motor preparation and motor execution, but also processing of auditory and visual information during speech, might have a role in the pathophysiology of spasmodic dysphonia. Copyright © 2016 Elsevier Ltd. All rights reserved.
Dayan, Michael; Munoz, Monica; Jentschke, Sebastian; Chadwick, Martin J; Cooper, Janine M; Riney, Kate; Vargha-Khadem, Faraneh; Clark, Chris A
2015-01-01
The optic radiation (OR) is a component of the visual system known to be myelin mature very early in life. Diffusion tensor imaging (DTI) and its unique ability to reconstruct the OR in vivo were used to study structural maturation through analysis of DTI metrics in a cohort of 90 children aged 5-18 years. As the OR is at risk of damage during epilepsy surgery, we measured its position relative to characteristic anatomical landmarks. Anatomical distances, DTI metrics and volume of the OR were investigated for age, gender and hemisphere effects. We observed changes in DTI metrics with age comparable to known trajectories in other white matter tracts. Left lateralization of DTI metrics was observed that showed a gender effect in lateralization. Sexual dimorphism of DTI metrics in the right hemisphere was also found. With respect to OR dimensions, volume was shown to be right lateralised and sexual dimorphism demonstrated for the extent of the left OR. The anatomical results presented for the OR have potentially important applications for neurosurgical planning.
White matter microstructural alterations in clinically isolated syndrome and multiple sclerosis.
Huang, Jing; Liu, Yaou; Zhao, Tengda; Shu, Ni; Duan, Yunyun; Ren, Zhuoqiong; Sun, Zheng; Liu, Zheng; Chen, Hai; Dong, Huiqing; Li, Kuncheng
2018-07-01
This study aims to determine whether and how diffusion alteration occurs in the earliest stage of multiple sclerosis (MS) and the differences in diffusion metrics between CIS and MS by using the tract-based spatial statistics (TBSS) method based on diffusion tensor imaging (DTI). Thirty-six CIS patients (mean age ± SD: 34.0 years ± 12.6), 36 relapsing-remitting multiple sclerosis (RRMS) patients (mean age ± SD: 35.0 years ± 9.4) and 36 age- and gender-matched normal controls (NCs) were included in this study. Voxel-wise analyses were performed with TBSS using multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ 1 ) and radial diffusivity (λ 23 ). In the CIS patients, TBSS analyses revealed diffusion alterations in a few white matter (WM) regions including the anterior thalamic radiation, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, body and splenium of the corpus callosum, internal capsule, external capsule, and cerebral peduncle. MS patients showed more widespread diffusion changes (decreased FA, increased λ 1 , λ 23 and MD) than CIS. Exploratory analyses also revealed the possible associations between WM diffusion metrics and clinical variables (Expanded Disability Status Scale and disease duration) in the patients. This study provided imaging evidence for DTI abnormalities in CIS and MS and suggested that DTI can improve our knowledge of the path physiology of CIS and MS and clinical progression. Copyright © 2018 Elsevier Ltd. All rights reserved.
Asken, Breton Michael; DeKosky, Steven T; Clugston, James R; Jaffee, Michael S; Bauer, Russell M
2018-04-01
This review seeks to summarize diffusion tensor imaging (DTI) studies that have evaluated structural changes attributed to the mechanisms of mild traumatic brain injury (mTBI) in adult civilian, military, and athlete populations. Articles from 2002 to 2016 were retrieved from PubMed/MEDLINE, EBSCOhost, and Google Scholar, using a Boolean search string containing the following terms: "diffusion tensor imaging", "diffusion imaging", "DTI", "white matter", "concussion", "mild traumatic brain injury", "mTBI", "traumatic brain injury", and "TBI". We added studies not identified by this method that were found via manually-searched reference lists. We identified 86 eligible studies from English-language journals using, adult, human samples. Studies were evaluated based on duration between injury and DTI assessment, categorized as acute, subacute/chronic, remote mTBI, and repetitive brain trauma considerations. Since changes in brain structure after mTBI can also be affected by other co-occurring medical and demographic factors, we also briefly review DTI studies that have addressed socioeconomic status factors (SES), major depressive disorder (MDD), and attention-deficit hyperactivity disorder (ADHD). The review describes population-specific risks and the complications of clinical versus pathophysiological outcomes of mTBI. We had anticipated that the distinct population groups (civilian, military, and athlete) would require separate consideration, and various aspects of the study characteristics supported this. In general, study results suggested widespread but inconsistent differences in white matter diffusion metrics (primarily fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD], and axial diffusivity [AD]) following mTBI/concussion. Inspection of study designs and results revealed potential explanations for discrepant DTI findings, such as control group variability, analytic techniques, the manner in which regional differences were reported, and the presence or absence of persistent functional disturbances. DTI research in adult mTBI would benefit from more standardized imaging and analytic approaches. We also found significant overlap in white matter abnormalities reported in mTBI with those commonly affected by SES or the presence of MDD and ADHD. We conclude that DTI is sensitive to a wide range of group differences in diffusion metrics, but that it currently lacks the specificity necessary for meaningful clinical application. Properly controlled longitudinal studies with consistent and standardized functional outcomes are needed before establishing the utility of DTI in the clinical management of mTBI and concussion.
Castellano, Antonella; Papinutto, Nico; Cadioli, Marcello; Brugnara, Gianluca; Iadanza, Antonella; Scigliuolo, Graziana; Pareyson, Davide; Uziel, Graziella; Köhler, Wolfgang; Aubourg, Patrick; Falini, Andrea; Henry, Roland G; Politi, Letterio S; Salsano, Ettore
2016-06-01
Adrenomyeloneuropathy is the late-onset form of X-linked adrenoleukodystrophy, and is considered the most frequent metabolic hereditary spastic paraplegia. In adrenomyeloneuropathy the spinal cord is the main site of pathology. Differently from quantitative magnetic resonance imaging of the brain, little is known about the feasibility and utility of advanced neuroimaging in quantifying the spinal cord abnormalities in hereditary diseases. Moreover, little is known about the subtle pathological changes that can characterize the brain of adrenomyeloneuropathy subjects in the early stages of the disease. We performed a cross-sectional study on 13 patients with adrenomyeloneuropathy and 12 age-matched healthy control subjects who underwent quantitative magnetic resonance imaging to assess the structural changes of the upper spinal cord and brain. Total cord areas from C2-3 to T2-3 level were measured, and diffusion tensor imaging metrics, i.e. fractional anisotropy, mean, axial and radial diffusivity values were calculated in both grey and white matter of spinal cord. In the brain, grey matter regions were parcellated with Freesurfer and average volume and thickness, and mean diffusivity and fractional anisotropy from co-registered diffusion maps were calculated in each region. Brain white matter diffusion tensor imaging metrics were assessed using whole-brain tract-based spatial statistics, and tractography-based analysis on corticospinal tracts. Correlations among clinical, structural and diffusion tensor imaging measures were calculated. In patients total cord area was reduced by 26.3% to 40.2% at all tested levels (P < 0.0001). A mean 16% reduction of spinal cord white matter fractional anisotropy (P ≤ 0.0003) with a concomitant 9.7% axial diffusivity reduction (P < 0.009) and 34.5% radial diffusivity increase (P < 0.009) was observed, suggesting co-presence of axonal degeneration and demyelination. Brain tract-based spatial statistics showed a marked reduction of fractional anisotropy, increase of radial diffusivity (P < 0.001) and no axial diffusivity changes in several white matter tracts, including corticospinal tracts and optic radiations, indicating predominant demyelination. Tractography-based analysis confirmed the results within corticospinal tracts. No significant cortical volume and thickness reduction or grey matter diffusion tensor imaging values alterations were observed in patients. A correlation between radial diffusivity and disease duration along the corticospinal tracts (r = 0.806, P < 0.01) was found. In conclusion, in adrenomyeloneuropathy patients quantitative magnetic resonance imaging-derived measures identify and quantify structural changes in the upper spinal cord and brain which agree with the expected histopathology, and suggest that the disease could be primarily caused by a demyelination rather than a primitive axonal damage. The results of this study may also encourage the employment of quantitative magnetic resonance imaging in other hereditary diseases with spinal cord involvement. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Paniagua, Beatriz; Ehlers, Cindy; Crews, Fulton; Budin, Francois; Larson, Garrett; Styner, Martin; Oguz, Ipek
2011-03-01
Understanding the effects of adolescent binge drinking that persist into adulthood is a crucial public health issue. Adolescent intermittent ethanol exposure (AIE) is an animal model that can be used to investigate these effects in rodents. In this work, we investigate the application of a particular image analysis technique, tensor-based morphometry, for detecting anatomical differences between AIE and control rats using Diffusion Tensor Imaging (DTI). Deformation field analysis is a popular method for detecting volumetric changes analyzing Jacobian determinants calculated on deformation fields. Recent studies showed that computing deformation field metrics on the full deformation tensor, often referred to as tensor-based morphometry (TBM), increases the sensitivity to anatomical differences. In this paper we conduct a comprehensive TBM study for precisely locating differences between control and AIE rats. Using a DTI RARE sequence designed for minimal geometric distortion, 12-directional images were acquired postmortem for control and AIE rats (n=9). After preprocessing, average images for the two groups were constructed using an unbiased atlas building approach. We non-rigidly register the two atlases using Large Deformation Diffeomorphic Metric Mapping, and analyze the resulting deformation field using TBM. In particular, we evaluate the tensor determinant, geodesic anisotropy, and deformation direction vector (DDV) on the deformation field to detect structural differences. This yields data on the local amount of growth, shrinkage and the directionality of deformation between the groups. We show that TBM can thus be used to measure group morphological differences between rat populations, demonstrating the potential of the proposed framework.
Recent developments in fast kurtosis imaging
NASA Astrophysics Data System (ADS)
Hansen, Brian; Jespersen, Sune N.
2017-09-01
Diffusion kurtosis imaging (DKI) is an extension of the popular diffusion tensor imaging (DTI) technique. DKI takes into account leading deviations from Gaussian diffusion stemming from a number of effects related to the microarchitecture and compartmentalization in biological tissues. DKI therefore offers increased sensitivity to subtle microstructural alterations over conventional diffusion imaging such as DTI, as has been demonstrated in numerous reports. For this reason, interest in routine clinical application of DKI is growing rapidly. In an effort to facilitate more widespread use of DKI, recent work by our group has focused on developing experimentally fast and robust estimates of DKI metrics. A significant increase in speed is made possible by a reduction in data demand achieved through rigorous analysis of the relation between the DKI signal and the kurtosis tensor based metrics. The fast DKI methods therefore need only 13 or 19 images for DKI parameter estimation compared to more than 60 for the most modest DKI protocols applied today. Closed form solutions also ensure rapid calculation of most DKI metrics. Some parameters can even be reconstructed in real time, which may be valuable in the clinic. The fast techniques are based on conventional diffusion sequences and are therefore easily implemented on almost any clinical system, in contrast to a range of other recently proposed advanced diffusion techniques. In addition to its general applicability, this also ensures that any acceleration achieved in conventional DKI through sequence or hardware optimization will also translate directly to fast DKI acquisitions. In this review, we recapitulate the theoretical basis for the fast kurtosis techniques and their relation to conventional DKI. We then discuss the currently available variants of the fast DKI methods, their strengths and weaknesses, as well as their respective realms of application. These range from whole body applications to methods mostly suited for spinal cord or peripheral nerve, and analysis specific to brain white matter. Having covered these technical aspects, we proceed to review the fast kurtosis literature including validation studies, organ specific optimization studies and results from clinical applications.
NASA Astrophysics Data System (ADS)
Abdullah, Osama Mahmoud
Myocardial microstructure plays an important role in sustaining the orchestrated beating motion of the heart. Several microstructural components, including myocytes and auxiliary cells, extracellular space, and blood vessels provide the infrastructure for normal heart function, including excitation propagation, myocyte contraction, delivery of oxygen and nutrients, and removing byproduct wastes. Cardiac diseases cause deleterious changes to some or all of these microstructural components in the detrimental process of cardiac remodeling. Since heart failure is among the leading causes of death in the world, new and novel tools to noninvasively characterize heart microstructure are needed for monitoring and staging of cardiac disease. In this regards, diffusion magnetic resonance imaging (MRI) provides a promising framework to probe and quantify tissue microstructure without the need for exogenous contrast agent. As diffusion in 3-dimensional space is characterized by the diffusion tensor, MR diffusion tensor imaging (DTI) is being used to noninvasively measure anisotropic diffusion, and thus the magnitude and spatial orientation of microstructural organization of tissues, including the heart. However, even though in vivo cardiac DTI has become more clinically available, to date the origin and behavior of different microstructural components on the measured DTI signal remain to be explicitly specified. The presented studies in this work demonstrate that DTI can be used as a noninvasive and contrast-free imaging modality to characterize myocyte size and density, extracellular collagen content, and the directional magnitude of blood flow. The identified applications are expected to provide metrics to enable physicians to detect, quantify, and stage different microstructural components during progression of cardiac disease.
Diffusion Tensor Tractography Reveals Disrupted Structural Connectivity during Brain Aging
NASA Astrophysics Data System (ADS)
Lin, Lan; Tian, Miao; Wang, Qi; Wu, Shuicai
2017-10-01
Brain aging is one of the most crucial biological processes that entail many physical, biological, chemical, and psychological changes, and also a major risk factor for most common neurodegenerative diseases. To improve the quality of life for the elderly, it is important to understand how the brain is changed during the normal aging process. We compared diffusion tensor imaging (DTI)-based brain networks in a cohort of 75 healthy old subjects by using graph theory metrics to describe the anatomical networks and connectivity patterns, and network-based statistic (NBS) analysis was used to identify pairs of regions with altered structural connectivity. The NBS analysis revealed a significant network comprising nine distinct fiber bundles linking 10 different brain regions showed altered white matter structures in young-old group compare with middle-aged group (p < .05, family-wise error-corrected). Our results might guide future studies and help to gain a better understanding of brain aging.
Duchêne, Gaëtan; Peeters, Frank; Peeters, André; Duprez, Thierry
2017-08-01
To compare the sensitivity and early temporal changes of diffusion parameters obtained from diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), q-space analysis (QSA) and bi-exponential modelling in hyperacute stroke patients. A single investigational acquisition allowing the four diffusion analyses was performed on seven hyperacute stroke patients with a 3T system. The percentage change between ipsi- and contralateral regions were compared at admission and 24 h later. Two out of the seven patients were imaged every 6 h during this period. Kurtoses from both DKI and QSA were the most sensitive of the tested diffusion parameters in the few hours following ischemia. An early increase-maximum-decrease pattern of evolution was highlighted during the 24-h period for all parameters proportional to diffusion coefficients. A similar pattern was observed for both kurtoses in only one of two patients. Our comparison was performed using identical diffusion encoding timings and on patients in the same stage of their condition. Although preliminary, our findings confirm those of previous studies that showed enhanced sensitivity of kurtosis. A fine time mapping of diffusion metrics in hyperacute stroke patients was presented which advocates for further investigations on larger animal or human cohorts.
Fetal diffusion tensor quantification of brainstem pathology in Chiari II malformation.
Woitek, Ramona; Prayer, Daniela; Weber, Michael; Amann, Gabriele; Seidl, Rainer; Bettelheim, Dieter; Schöpf, Veronika; Brugger, Peter C; Furtner, Julia; Asenbaum, Ulrika; Kasprian, Gregor
2016-05-01
This prenatal MRI study evaluated the potential of diffusion tensor imaging (DTI) metrics to identify changes in the midbrain of fetuses with Chiari II malformations compared to fetuses with mild ventriculomegaly, hydrocephalus and normal CNS development. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were calculated from a region of interest (ROI) in the midbrain of 46 fetuses with normal CNS, 15 with Chiari II malformations, eight with hydrocephalus and 12 with mild ventriculomegaly. Fetuses with different diagnoses were compared group-wise after age-matching. Axial T2W-FSE sequences and single-shot echo planar DTI sequences (16 non-collinear diffusion gradient-encoding directions, b-values of 0 and 700 s/mm(2), 1.5 Tesla) were evaluated retrospectively. In Chiari II malformations, FA was significantly higher than in age-matched fetuses with a normal CNS (p = .003), while ADC was not significantly different. No differences in DTI metrics between normal controls and fetuses with hydrocephalus or vetriculomegaly were detected. DTI can detect and quantify parenchymal alterations of the fetal midbrain in Chiari II malformations. Therefore, in cases of enlarged fetal ventricles, FA of the fetal midbrain may contribute to the differentiation between Chiari II malformation and other entities. • FA in the fetal midbrain is elevated in Chiari II malformations. • FA is not elevated in hydrocephalus and mild ventriculomegaly without Chiari II. • Measuring FA may help distinguish different causes for enlarged ventricles prenatally. • Elevated FA may aid in the diagnosis of open neural tube defects. • Elevated FA might contribute to stratification for prenatal surgery in Chiari II.
Prescribed curvature tensor in locally conformally flat manifolds
NASA Astrophysics Data System (ADS)
Pina, Romildo; Pieterzack, Mauricio
2018-01-01
A global existence theorem for the prescribed curvature tensor problem in locally conformally flat manifolds is proved for a special class of tensors R. Necessary and sufficient conditions for the existence of a metric g ¯ , conformal to Euclidean g, are determined such that R ¯ = R, where R ¯ is the Riemannian curvature tensor of the metric g ¯ . The solution to this problem is given explicitly for special cases of the tensor R, including the case where the metric g ¯ is complete on Rn. Similar problems are considered for locally conformally flat manifolds.
An exploration of diffusion tensor eigenvector variability within human calf muscles.
Rockel, Conrad; Noseworthy, Michael D
2016-01-01
To explore the effect of diffusion tensor imaging (DTI) acquisition parameters on principal and minor eigenvector stability within human lower leg skeletal muscles. Lower leg muscles were evaluated in seven healthy subjects at 3T using an 8-channel transmit/receive coil. Diffusion-encoding was performed with nine signal averages (NSA) using 6, 15, and 25 directions (NDD). Individual DTI volumes were combined into aggregate volumes of 3, 2, and 1 NSA according to number of directions. Tensor eigenvalues (λ1 , λ2 , λ3 ), eigenvectors (ε1 , ε2 , ε3 ), and DTI metrics (fractional anisotropy [FA] and mean diffusivity [MD]) were calculated for each combination of NSA and NDD. Spatial maps of signal-to-noise ratio (SNR), λ3 :λ2 ratio, and zenith angle were also calculated for region of interest (ROI) analysis of vector orientation consistency. ε1 variability was only moderately related to ε2 variability (r = 0.4045). Variation of ε1 was affected by NDD, not NSA (P < 0.0002), while variation of ε2 was affected by NSA, not NDD (P < 0.0003). In terms of tensor shape, vector variability was weakly related to FA (ε1 :r = -0.1854, ε2 : ns), but had a stronger relation to the λ3 :λ2 ratio (ε1 :r = -0.5221, ε2 :r = -0.1771). Vector variability was also weakly related to SNR (ε1 :r = -0.2873, ε2 :r = -0.3483). Zenith angle was found to be strongly associated with variability of ε1 (r = 0.8048) but only weakly with that of ε2 (r = 0.2135). The second eigenvector (ε2 ) displayed higher directional variability relative to ε1 , and was only marginally affected by experimental conditions that impacted ε1 variability. © 2015 Wiley Periodicals, Inc.
Jelescu, Ileana O; Zurek, Magdalena; Winters, Kerryanne V; Veraart, Jelle; Rajaratnam, Anjali; Kim, Nathanael S; Babb, James S; Shepherd, Timothy M; Novikov, Dmitry S; Kim, Sungheon G; Fieremans, Els
2016-05-15
There is a need for accurate quantitative non-invasive biomarkers to monitor myelin pathology in vivo and distinguish myelin changes from other pathological features including inflammation and axonal loss. Conventional MRI metrics such as T2, magnetization transfer ratio and radial diffusivity have proven sensitivity but not specificity. In highly coherent white matter bundles, compartment-specific white matter tract integrity (WMTI) metrics can be directly derived from the diffusion and kurtosis tensors: axonal water fraction, intra-axonal diffusivity, and extra-axonal radial and axial diffusivities. We evaluate the potential of WMTI to quantify demyelination by monitoring the effects of both acute (6weeks) and chronic (12weeks) cuprizone intoxication and subsequent recovery in the mouse corpus callosum, and compare its performance with that of conventional metrics (T2, magnetization transfer, and DTI parameters). The changes observed in vivo correlated with those obtained from quantitative electron microscopy image analysis. A 6-week intoxication produced a significant decrease in axonal water fraction (p<0.001), with only mild changes in extra-axonal radial diffusivity, consistent with patchy demyelination, while a 12-week intoxication caused a more marked decrease in extra-axonal radial diffusivity (p=0.0135), consistent with more severe demyelination and clearance of the extra-axonal space. Results thus revealed increased specificity of the axonal water fraction and extra-axonal radial diffusivity parameters to different degrees and patterns of demyelination. The specificities of these parameters were corroborated by their respective correlations with microstructural features: the axonal water fraction correlated significantly with the electron microscopy derived total axonal water fraction (ρ=0.66; p=0.0014) but not with the g-ratio, while the extra-axonal radial diffusivity correlated with the g-ratio (ρ=0.48; p=0.0342) but not with the electron microscopy derived axonal water fraction. These parameters represent promising candidates as clinically feasible biomarkers of demyelination and remyelination in the white matter. Copyright © 2016 Elsevier Inc. All rights reserved.
MRI diffusion tensor reconstruction with PROPELLER data acquisition.
Cheryauka, Arvidas B; Lee, James N; Samsonov, Alexei A; Defrise, Michel; Gullberg, Grant T
2004-02-01
MRI diffusion imaging is effective in measuring the diffusion tensor in brain, cardiac, liver, and spinal tissue. Diffusion tensor tomography MRI (DTT MRI) method is based on reconstructing the diffusion tensor field from measurements of projections of the tensor field. Projections are obtained by appropriate application of rotated diffusion gradients. In the present paper, the potential of a novel data acquisition scheme, PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction), is examined in combination with DTT MRI for its capability and sufficiency for diffusion imaging. An iterative reconstruction algorithm is used to reconstruct the diffusion tensor field from rotated diffusion weighted blades by appropriate rotated diffusion gradients. DTT MRI with PROPELLER data acquisition shows significant potential to reduce the number of weighted measurements, avoid ambiguity in reconstructing diffusion tensor parameters, increase signal-to-noise ratio, and decrease the influence of signal distortion.
Tu, Tsang-Wei; Lescher, Jacob D; Williams, Rashida A; Jikaria, Neekita; Turtzo, L Christine; Frank, Joseph A
2017-01-01
Spontaneous mild ventriculomegaly (MVM) was previously reported in ∼43% of Wistar rats in association with vascular anomalies without phenotypic manifestation. This mild traumatic brain injury (TBI) weight drop model study investigates whether MVM rats (n = 15) have different injury responses that could inadvertently complicate the interpretation of imaging studies compared with normal rats (n = 15). Quantitative MRI, including diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI), and immunohistochemistry (IHC) analysis were used to examine the injury pattern up to 8 days post-injury in MVM and normal rats. Prior to injury, the MVM brain showed significant higher mean diffusivity, axial diffusivity, and radial diffusivity, and lower fractional anisotropy (FA) and magnetization transfer ratio (MTR) in the corpus callosum than normal brain (p < 0.05). Following TBI, normal brains exhibited significant decreases of FA in the corpus callosum, whereas MVM brains demonstrated insignificant changes in FA, suggesting less axonal injury. At day 8 after mild TBI, MTR of the normal brains significantly decreased whereas the MTR of the MVM brains significantly increased. IHC staining substantiated the MRI findings, demonstrating limited axonal injury with significant increase of microgliosis and astrogliosis in MVM brain compared with normal animals. The radiological-pathological correlation data showed that both DTI and MTI were sensitive in detecting mild diffuse brain injury, although DTI metrics were more specific in correlating with histologically identified pathologies. Compared with the higher correlation levels reflecting axonal injury pathology in the normal rat mild TBI, the DTI and MTR metrics were more affected by the increased inflammation in the MVM rat mild TBI. Because MVM Wistar rats appear normal, there was a need to screen rats prior to TBI research to rule out the presence of ventriculomegaly, which may complicate the interpretation of imaging and IHC observations.
Lescher, Jacob D.; Williams, Rashida A.; Jikaria, Neekita; Turtzo, L. Christine; Frank, Joseph A.
2017-01-01
Abstract Spontaneous mild ventriculomegaly (MVM) was previously reported in ∼43% of Wistar rats in association with vascular anomalies without phenotypic manifestation. This mild traumatic brain injury (TBI) weight drop model study investigates whether MVM rats (n = 15) have different injury responses that could inadvertently complicate the interpretation of imaging studies compared with normal rats (n = 15). Quantitative MRI, including diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI), and immunohistochemistry (IHC) analysis were used to examine the injury pattern up to 8 days post-injury in MVM and normal rats. Prior to injury, the MVM brain showed significant higher mean diffusivity, axial diffusivity, and radial diffusivity, and lower fractional anisotropy (FA) and magnetization transfer ratio (MTR) in the corpus callosum than normal brain (p < 0.05). Following TBI, normal brains exhibited significant decreases of FA in the corpus callosum, whereas MVM brains demonstrated insignificant changes in FA, suggesting less axonal injury. At day 8 after mild TBI, MTR of the normal brains significantly decreased whereas the MTR of the MVM brains significantly increased. IHC staining substantiated the MRI findings, demonstrating limited axonal injury with significant increase of microgliosis and astrogliosis in MVM brain compared with normal animals. The radiological-pathological correlation data showed that both DTI and MTI were sensitive in detecting mild diffuse brain injury, although DTI metrics were more specific in correlating with histologically identified pathologies. Compared with the higher correlation levels reflecting axonal injury pathology in the normal rat mild TBI, the DTI and MTR metrics were more affected by the increased inflammation in the MVM rat mild TBI. Because MVM Wistar rats appear normal, there was a need to screen rats prior to TBI research to rule out the presence of ventriculomegaly, which may complicate the interpretation of imaging and IHC observations. PMID:26905805
Jespersen, Sune Nørhøj; Lundell, Henrik; Sønderby, Casper Kaae; Dyrby, Tim B
2013-12-01
Pulsed field gradient diffusion sequences (PFG) with multiple diffusion encoding blocks have been indicated to offer new microstructural tissue information, such as the ability to detect nonspherical compartment shapes in macroscopically isotropic samples, i.e. samples with negligible directional signal dependence on diffusion gradients in standard diffusion experiments. However, current acquisition schemes are not rotationally invariant in the sense that the derived metrics depend on the orientation of the sample, and are affected by the interplay of sampling directions and compartment orientation dispersion when applied to macroscopically anisotropic systems. Here we propose a new framework, the d-PFG 5-design, to enable rotationally invariant estimation of double wave vector diffusion metrics (d-PFG). The method is based on the idea that an appropriate orientational average of the signal emulates the signal from a powder preparation of the same sample, where macroscopic anisotropy is absent by construction. Our approach exploits the theory of exact numerical integration (quadrature) of polynomials on the rotation group, and we exemplify the general procedure with a set consisting of 60 pairs of diffusion wave vectors (the d-PFG 5-design) facilitating a theoretically exact determination of the fourth order Taylor or cumulant expansion of the orientationally averaged signal. The d-PFG 5-design is evaluated with numerical simulations and ex vivo high field diffusion MRI experiments in a nonhuman primate brain. Specifically, we demonstrate rotational invariance when estimating compartment eccentricity, which we show offers new microstructural information, complementary to that of fractional anisotropy (FA) from diffusion tensor imaging (DTI). The imaging observations are supported by a new theoretical result, directly relating compartment eccentricity to FA of individual pores. Copyright © 2013 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Hehl, Friedrich W.; Kiefer, Claus
2018-01-01
We perform a short comparison between the local and linear constitutive tensor χ ^{λ ν σ κ } in four-dimensional electrodynamics, the elasticity tensor c^{ijkl} in three-dimensional elasticity theory, and the DeWitt metric G^{abcd} in general relativity, with {a,b,\\ldots =1,2,3}. We find that the DeWitt metric has only six independent components.
Mustafi, Sourajit Mitra; Harezlak, Jaroslaw; Koch, Kevin M; Nencka, Andrew S; Meier, Timothy; West, John D; Giza, Christopher C; DiFiori, John; Guskiewicz, Kevin K; Mihalik, Jason; LaConte, Stephen M; Duma, Stefan M; Broglio, Steven P; Saykin, Andrew J; McCrea, Michael; McAllister, Thomas; Wu, Yu-Chien
2017-10-25
Sport-related concussion (SRC) is an important public health issue. While standardized assessment tools are useful in the clinical management of acute concussion, the underlying pathophysiology of SRC and the time course of physiological recovery after injury remain unclear. In this study, we used diffusion tensor imaging (DTI) to detect white-matter alterations in football players within 48 hours after SRC. As part of the NCAA-DoD CARE Consortium study of SRC, 30 American football players diagnosed with acute concussion, and 28 matched controls received clinical assessments and underwent advanced MRI scans. To avoid selection bias and partial voluming effects, whole-brain skeletonized white matter was examined via tract-based spatial statistics (TBSS) to investigate between group differences in DTI metrics and their associations with clinical outcome measures. Mean diffusivity was significantly higher in the brain white matter of the concussed athletes, particularly in frontal and sub-frontal long white-matter tracts. While no DTI metric was associated to any clinical measure in the contact-sport controls, in the concussed group, DTI exhibited correlations with clinical measures. Axial diffusivity demonstrated a significant positive correlation with the Brief Symptom Inventory (BSI) and a trend for a positive correlation with the symptom severity score of the Sports Concussion Assessment Tool (SCAT). In addition, concussed athletes with higher fractional anisotropy performed worse on the cognitive component of the Standardized Assessment of Concussion (SAC). Overall, the results of this study are consistent with the hypothesis that SRC is associated with changes in white-matter tracts shortly after injury, and these differences are correlated clinically with acute symptoms and functional impairments.
NASA Astrophysics Data System (ADS)
Cremaschini, Claudio; Stuchlík, Zdeněk
2018-05-01
A test fluid composed of relativistic collisionless neutral particles in the background of Kerr metric is expected to generate non-isotropic equilibrium configurations in which the corresponding stress-energy tensor exhibits pressure and temperature anisotropies. This arises as a consequence of the constraints placed on single-particle dynamics by Killing tensor symmetries, leading to a peculiar non-Maxwellian functional form of the kinetic distribution function describing the continuum system. Based on this outcome, in this paper the generation of Kerr-like metric by collisionless N -body systems of neutral matter orbiting in the field of a rotating black hole is reported. The result is obtained in the framework of covariant kinetic theory by solving the Einstein equations in terms of an analytical perturbative treatment whereby the gravitational field is decomposed as a prescribed background metric tensor described by the Kerr solution plus a self-field correction. The latter one is generated by the uncharged fluid at equilibrium and satisfies the linearized Einstein equations having the non-isotropic stress-energy tensor as source term. It is shown that the resulting self-metric is again of Kerr type, providing a mechanism of magnification of the background metric tensor and its qualitative features.
Kuhn, T; Gullett, J M; Nguyen, P; Boutzoukas, A E; Ford, A; Colon-Perez, L M; Triplett, W; Carney, P R; Mareci, T H; Price, C C; Bauer, R M
2016-06-01
This study examined the reliability of high angular resolution diffusion tensor imaging (HARDI) data collected on a single individual across several sessions using the same scanner. HARDI data was acquired for one healthy adult male at the same time of day on ten separate days across a one-month period. Environmental factors (e.g. temperature) were controlled across scanning sessions. Tract Based Spatial Statistics (TBSS) was used to assess session-to-session variability in measures of diffusion, fractional anisotropy (FA) and mean diffusivity (MD). To address reliability within specific structures of the medial temporal lobe (MTL; the focus of an ongoing investigation), probabilistic tractography segmented the Entorhinal cortex (ERc) based on connections with Hippocampus (HC), Perirhinal (PRc) and Parahippocampal (PHc) cortices. Streamline tractography generated edge weight (EW) metrics for the aforementioned ERc connections and, as comparison regions, connections between left and right rostral and caudal anterior cingulate cortex (ACC). Coefficients of variation (CoV) were derived for the surface area and volumes of these ERc connectivity-defined regions (CDR) and for EW across all ten scans, expecting that scan-to-scan reliability would yield low CoVs. TBSS revealed no significant variation in FA or MD across scanning sessions. Probabilistic tractography successfully reproduced histologically-verified adjacent medial temporal lobe circuits. Tractography-derived metrics displayed larger ranges of scanner-to-scanner variability. Connections involving HC displayed greater variability than metrics of connection between other investigated regions. By confirming the test retest reliability of HARDI data acquisition, support for the validity of significant results derived from diffusion data can be obtained.
The Riemannian geometry is not sufficient for the geometrization of the Maxwell's equations
NASA Astrophysics Data System (ADS)
Kulyabov, Dmitry S.; Korolkova, Anna V.; Velieva, Tatyana R.
2018-04-01
The transformation optics uses geometrized Maxwell's constitutive equations to solve the inverse problem of optics, namely to solve the problem of finding the parameters of the medium along the paths of propagation of the electromagnetic field. For the geometrization of Maxwell's constitutive equations, the quadratic Riemannian geometry is usually used. This is due to the use of the approaches of the general relativity. However, there arises the question of the insufficiency of the Riemannian structure for describing the constitutive tensor of the Maxwell's equations. The authors analyze the structure of the constitutive tensor and correlate it with the structure of the metric tensor of Riemannian geometry. It is concluded that the use of the quadratic metric for the geometrization of Maxwell's equations is insufficient, since the number of components of the metric tensor is less than the number of components of the constitutive tensor. A possible solution to this problem may be a transition to Finslerian geometry, in particular, the use of the Berwald-Moor metric to establish the structural correspondence between the field tensors of the electromagnetic field.
SHETTY, ANIL N.; CHIANG, SHARON; MALETIC-SAVATIC, MIRJANA; KASPRIAN, GREGOR; VANNUCCI, MARINA; LEE, WESLEY
2016-01-01
In this article, we discuss the theoretical background for diffusion weighted imaging and diffusion tensor imaging. Molecular diffusion is a random process involving thermal Brownian motion. In biological tissues, the underlying microstructures restrict the diffusion of water molecules, making diffusion directionally dependent. Water diffusion in tissue is mathematically characterized by the diffusion tensor, the elements of which contain information about the magnitude and direction of diffusion and is a function of the coordinate system. Thus, it is possible to generate contrast in tissue based primarily on diffusion effects. Expressing diffusion in terms of the measured diffusion coefficient (eigenvalue) in any one direction can lead to errors. Nowhere is this more evident than in white matter, due to the preferential orientation of myelin fibers. The directional dependency is removed by diagonalization of the diffusion tensor, which then yields a set of three eigenvalues and eigenvectors, representing the magnitude and direction of the three orthogonal axes of the diffusion ellipsoid, respectively. For example, the eigenvalue corresponding to the eigenvector along the long axis of the fiber corresponds qualitatively to diffusion with least restriction. Determination of the principal values of the diffusion tensor and various anisotropic indices provides structural information. We review the use of diffusion measurements using the modified Stejskal–Tanner diffusion equation. The anisotropy is analyzed by decomposing the diffusion tensor based on symmetrical properties describing the geometry of diffusion tensor. We further describe diffusion tensor properties in visualizing fiber tract organization of the human brain. PMID:27441031
Vedantam, Aditya; Hou, Ping; Chi, T. Linda; Dougherty, Patrick M.; Hess, Kenneth R.; Viswanathan, Ashwin
2017-01-01
Background Up to 20% of patients experience only partial pain relief after percutaneous cordotomy for cancer pain. Objective To determine whether diffusion tensor imaging (DTI) can quantify neural ablation and help evaluate early postoperative outcomes after cordotomy. Methods Patients undergoing percutaneous CT-guided cordotomy for intractable cancer pain were prospectively studied. Pre- and postoperative assessment was made using the visual analog scale (VAS) on pain and the pain severity scores of the Brief Pain Inventory Short Form. On postoperative day 1, DTI images of the high cervical spinal cord were obtained. DTI metrics were correlated with the number of ablations as well as early postoperative pain outcomes. Results Seven patients (4 male, mean age 53.8 ± 4.6 years) were studied. Fractional anisotropy of the hemicord was significantly lower on the side of the lesion as compared to the contralateral side (0.54 ± 0.03 vs. 0.63 ± 0.03, p < 0.001). Mean diffusivity correlated with the improvement in the VAS score at 1 week (r = 0.88, 95% CI = 0.34–1.00, p = 0.008), as well as the change in pain severity scores at 1 week (r = 0.99, 95% CI = 0.82–1.00, p < 0.001). Conclusion DTI metrics are sensitive to the number of ablations as well as early improvement in pain scores after cordotomy. DTI of the cervical spinal cord is a potential biomarker of neural ablation after percutaneous cordotomy for intractable cancer pain. PMID:28088799
Tarabichi, Osama; Kozin, Elliott D; Kanumuri, Vivek V; Barber, Samuel; Ghosh, Satra; Sitek, Kevin R; Reinshagen, Katherine; Herrmann, Barbara; Remenschneider, Aaron K; Lee, Daniel J
2018-03-01
Objective The radiologic evaluation of patients with hearing loss includes computed tomography and magnetic resonance imaging (MRI) to highlight temporal bone and cochlear nerve anatomy. The central auditory pathways are often not studied for routine clinical evaluation. Diffusion tensor imaging (DTI) is an emerging MRI-based modality that can reveal microstructural changes in white matter. In this systematic review, we summarize the value of DTI in the detection of structural changes of the central auditory pathways in patients with sensorineural hearing loss. Data Sources PubMed, Embase, and Cochrane. Review Methods We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement checklist for study design. All studies that included at least 1 sensorineural hearing loss patient with DTI outcome data were included. Results After inclusion and exclusion criteria were met, 20 articles were analyzed. Patients with bilateral hearing loss comprised 60.8% of all subjects. Patients with unilateral or progressive hearing loss and tinnitus made up the remaining studies. The auditory cortex and inferior colliculus (IC) were the most commonly studied regions using DTI, and most cases were found to have changes in diffusion metrics, such as fractional anisotropy, compared to normal hearing controls. Detectable changes in other auditory regions were reported, but there was a higher degree of variability. Conclusion White matter changes based on DTI metrics can be seen in patients with sensorineural hearing loss, but studies are few in number with modest sample sizes. Further standardization of DTI using a prospective study design with larger sample sizes is needed.
Steventon, Jessica J.; Trueman, Rebecca C.; Rosser, Anne E.; Jones, Derek K.
2016-01-01
Background Huge advances have been made in understanding and addressing confounds in diffusion MRI data to quantify white matter microstructure. However, there has been a lag in applying these advances in clinical research. Some confounds are more pronounced in HD which impedes data quality and interpretability of patient-control differences. This study presents an optimised analysis pipeline and addresses specific confounds in a HD patient cohort. Method 15 HD gene-positive and 13 matched control participants were scanned on a 3T MRI system with two diffusion MRI sequences. An optimised post processing pipeline included motion, eddy current and EPI correction, rotation of the B matrix, free water elimination (FWE) and tractography analysis using an algorithm capable of reconstructing crossing fibres. The corpus callosum was examined using both a region-of-interest and a deterministic tractography approach, using both conventional diffusion tensor imaging (DTI)-based and spherical deconvolution analyses. Results Correcting for CSF contamination significantly altered microstructural metrics and the detection of group differences. Reconstructing the corpus callosum using spherical deconvolution produced a more complete reconstruction with greater sensitivity to group differences, compared to DTI-based tractography. Tissue volume fraction (TVF) was reduced in HD participants and was more sensitive to disease burden compared to DTI metrics. Conclusion Addressing confounds in diffusion MR data results in more valid, anatomically faithful white matter tract reconstructions with reduced within-group variance. TVF is recommended as a complementary metric, providing insight into the relationship with clinical symptoms in HD not fully captured by conventional DTI metrics. PMID:26335798
Steventon, Jessica J; Trueman, Rebecca C; Rosser, Anne E; Jones, Derek K
2016-05-30
Huge advances have been made in understanding and addressing confounds in diffusion MRI data to quantify white matter microstructure. However, there has been a lag in applying these advances in clinical research. Some confounds are more pronounced in HD which impedes data quality and interpretability of patient-control differences. This study presents an optimised analysis pipeline and addresses specific confounds in a HD patient cohort. 15 HD gene-positive and 13 matched control participants were scanned on a 3T MRI system with two diffusion MRI sequences. An optimised post processing pipeline included motion, eddy current and EPI correction, rotation of the B matrix, free water elimination (FWE) and tractography analysis using an algorithm capable of reconstructing crossing fibres. The corpus callosum was examined using both a region-of-interest and a deterministic tractography approach, using both conventional diffusion tensor imaging (DTI)-based and spherical deconvolution analyses. Correcting for CSF contamination significantly altered microstructural metrics and the detection of group differences. Reconstructing the corpus callosum using spherical deconvolution produced a more complete reconstruction with greater sensitivity to group differences, compared to DTI-based tractography. Tissue volume fraction (TVF) was reduced in HD participants and was more sensitive to disease burden compared to DTI metrics. Addressing confounds in diffusion MR data results in more valid, anatomically faithful white matter tract reconstructions with reduced within-group variance. TVF is recommended as a complementary metric, providing insight into the relationship with clinical symptoms in HD not fully captured by conventional DTI metrics. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
Measurement tensors in diffusion MRI: generalizing the concept of diffusion encoding.
Westin, Carl-Fredrik; Szczepankiewicz, Filip; Pasternak, Ofer; Ozarslan, Evren; Topgaard, Daniel; Knutsson, Hans; Nilsson, Markus
2014-01-01
In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its covariance (a 4th order tensor).
Rosskopf, Johannes; Müller, Hans-Peter; Dreyhaupt, Jens; Gorges, Martin; Ludolph, Albert C; Kassubek, Jan
2015-03-01
Diffusion tensor imaging (DTI) for assessing ALS-associated white matter alterations has still not reached the level of a neuroimaging biomarker. Since large-scale multicentre DTI studies in ALS may be hampered by differences in scanning protocols, an approach for pooling of DTI data acquired with different protocols was investigated. Three hundred and nine datasets from 170 ALS patients and 139 controls were collected ex post facto from a monocentric database reflecting different scanning protocols. A 3D correction algorithm was introduced for a combined analysis of DTI metrics despite different acquisition protocols, with the focus on the CST as the tract correlate of ALS neuropathological stage 1. A homogenous set of data was obtained by application of 3D correction matrices. Results showed that a fractional anisotropy (FA) threshold of 0.41 could be defined to discriminate ALS patients from controls (sensitivity/specificity, 74%/72%). For the remaining test sample, sensitivity/specificity values of 68%/74% were obtained. In conclusion, the objective was to merge data recorded with different DTI protocols with 3D correction matrices for analyses at group level. These post processing tools might facilitate analysis of large study samples in a multicentre setting for DTI analysis at group level to aid in establishing DTI as a non-invasive biomarker for ALS.
Aging in deep gray matter and white matter revealed by diffusional kurtosis imaging.
Gong, Nan-Jie; Wong, Chun-Sing; Chan, Chun-Chung; Leung, Lam-Ming; Chu, Yiu-Ching
2014-10-01
Diffusion tensor imaging has already been extensively used to probe microstructural alterations in white matter tracts, and scarcely, in deep gray matter. However, results in literature regarding age-related degenerative mechanisms in white matter tracts and parametric changes in the putamen are inconsistent. Diffusional kurtosis imaging is a mathematical extension of diffusion tensor imaging, which could more comprehensively mirror microstructure, particularly in isotropic tissues such as gray matter. In this study, we used the diffusional kurtosis imaging method and a white-matter model that provided metrics of explicit neurobiological interpretations in healthy participants (58 in total, aged from 25 to 84 years). Tract-based whole-brain analyses and regions-of-interest (anterior and posterior limbs of the internal capsule, cerebral peduncle, fornix, genu and splenium of corpus callosum, globus pallidus, substantia nigra, red nucleus, putamen, caudate nucleus, and thalamus) analyses were performed to examine parametric differences across regions and correlations with age. In white matter tracts, evidence was found supportive for anterior-posterior gradient and not completely supportive for retrogenesis theory. Age-related degenerations appeared to be broadly driven by axonal loss. Demyelination may also be a major driving mechanism, although confined to the anterior brain. In terms of deep gray matter, higher mean kurtosis and fractional anisotropy in the globus pallidus, substantia nigra, and red nucleus reflected higher microstructural complexity and directionality compared with the putamen, caudate nucleus, and thalamus. In particular, the unique age-related positive correlations for fractional anisotropy, mean kurtosis, and radial kurtosis in the putamen opposite to those in other regions call for further investigation of exact underlying mechanisms. In summary, the results suggested that diffusional kurtosis can provide measurements in a new dimension that were complementary to diffusivity metrics. Kurtosis together with diffusivity can more comprehensively characterize microstructural compositions and age-related changes than diffusivity alone. Combined with proper model, it may also assist in providing neurobiological interpretations of the identified alterations. Copyright © 2014 Elsevier Inc. All rights reserved.
Mohammadi, Siawoosh; Hutton, Chloe; Nagy, Zoltan; Josephs, Oliver; Weiskopf, Nikolaus
2013-01-01
Diffusion tensor imaging is widely used in research and clinical applications, but this modality is highly sensitive to artefacts. We developed an easy-to-implement extension of the original diffusion tensor model to account for physiological noise in diffusion tensor imaging using measures of peripheral physiology (pulse and respiration), the so-called extended tensor model. Within the framework of the extended tensor model two types of regressors, which respectively modeled small (linear) and strong (nonlinear) variations in the diffusion signal, were derived from peripheral measures. We tested the performance of four extended tensor models with different physiological noise regressors on nongated and gated diffusion tensor imaging data, and compared it to an established data-driven robust fitting method. In the brainstem and cerebellum the extended tensor models reduced the noise in the tensor-fit by up to 23% in accordance with previous studies on physiological noise. The extended tensor model addresses both large-amplitude outliers and small-amplitude signal-changes. The framework of the extended tensor model also facilitates further investigation into physiological noise in diffusion tensor imaging. The proposed extended tensor model can be readily combined with other artefact correction methods such as robust fitting and eddy current correction. PMID:22936599
Roalf, David R.; Quarmley, Megan; Elliott, Mark A.; Satterthwaite, Theodore D.; Vandekar, Simon N.; Ruparel, Kosha; Gennatas, Efstathios D.; Calkins, Monica E.; Moore, Tyler M.; Hopson, Ryan; Prabhakaran, Karthik; Jackson, Chad T.; Verma, Ragini; Hakonarson, Hakon; Gur, Ruben C.; Gur, Raquel E.
2015-01-01
Background Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g. motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1,601 youths ages of 8–21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics. Methods All diffusion-weighted images were acquired on the same scanner. Visual QA was performed on all subjects completing DTI; images were manually categorized as Poor, Good, or Excellent. Four image quality metrics were automatically computed and used to predict manual QA status: Mean voxel intensity outlier count (MEANVOX), Maximum voxel intensity outlier count (MAXVOX), mean relative motion (MOTION) and temporal signal-to-noise ratio (TSNR). Classification accuracy for each metric was calculated as the area under the receiver-operating characteristic curve (AUC). A threshold was generated for each measure that best differentiated visual QA status and applied in a validation sample. The effects of data quality on sensitivity to expected age effects in this developmental sample were then investigated using the traditional MRI diffusion metrics: fractional anisotropy (FA) and mean diffusivity (MD). Finally, our method of QA is compared to DTIPrep. Results TSNR (AUC=0.94) best differentiated Poor data from Good and Excellent data. MAXVOX (AUC=0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n=374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of age, sex and race in a matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images. Conclusion Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development. PMID:26520775
Vellmer, Sebastian; Tonoyan, Aram S; Suter, Dieter; Pronin, Igor N; Maximov, Ivan I
2018-02-01
Diffusion magnetic resonance imaging (dMRI) is a powerful tool in clinical applications, in particular, in oncology screening. dMRI demonstrated its benefit and efficiency in the localisation and detection of different types of human brain tumours. Clinical dMRI data suffer from multiple artefacts such as motion and eddy-current distortions, contamination by noise, outliers etc. In order to increase the image quality of the derived diffusion scalar metrics and the accuracy of the subsequent data analysis, various pre-processing approaches are actively developed and used. In the present work we assess the effect of different pre-processing procedures such as a noise correction, different smoothing algorithms and spatial interpolation of raw diffusion data, with respect to the accuracy of brain glioma differentiation. As a set of sensitive biomarkers of the glioma malignancy grades we chose the derived scalar metrics from diffusion and kurtosis tensor imaging as well as the neurite orientation dispersion and density imaging (NODDI) biophysical model. Our results show that the application of noise correction, anisotropic diffusion filtering, and cubic-order spline interpolation resulted in the highest sensitivity and specificity for glioma malignancy grading. Thus, these pre-processing steps are recommended for the statistical analysis in brain tumour studies. Copyright © 2017. Published by Elsevier GmbH.
Hasan, Khader M; Iftikhar, Amal; Kamali, Arash; Kramer, Larry A; Ashtari, Manzar; Cirino, Paul T; Papanicolaou, Andrew C; Fletcher, Jack M; Ewing-Cobbs, Linda
2009-06-18
The human brain uncinate fasciculus (UF) is an important cortico-cortical white matter pathway that directly connects the frontal and temporal lobes, although there is a lack of conclusive support for its exact functional role. Using diffusion tensor tractography, we extracted the UF, calculated its volume and normalized it with respect to each subject's intracranial volume (ICV) and analyzed its corresponding DTI metrics bilaterally on a cohort of 108 right-handed children and adults aged 7-68 years. Results showed inverted U-shaped curves for fractional anisotropy (FA) with advancing age and U-shaped curves for radial and axial diffusivities reflecting white matter progressive and regressive myelination and coherence dynamics that continue into young adulthood. The mean FA values of the UF were significantly larger on the left side in children (p=0.05), adults (p=0.0012) and the entire sample (p=0.0002). The FA leftward asymmetry (Left>Right) is shown to be due to increased leftward asymmetry in the axial diffusivity (p<0.0001) and a lack of asymmetry (p>0.23) for the radial diffusivity. This is the first study to provide baseline normative macro and microstructural age trajectories of the human UF across the lifespan. Results of this study may lend themselves to better understanding of UF role in future behavioral and clinical studies.
A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis.
Müller, Hans-Peter; Turner, Martin R; Grosskreutz, Julian; Abrahams, Sharon; Bede, Peter; Govind, Varan; Prudlo, Johannes; Ludolph, Albert C; Filippi, Massimo; Kassubek, Jan
2016-06-01
Damage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size. 442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups. Analysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings. This large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Extended Applicability of the Spherical-Harmonic and Point-Mass Modeling of the Gravity Field,
1980-02-01
the metric in spherical coordinates {X,F, rl reads ds2 = r2cos 2j dX2 + r 2d 2 + dr2 yielding the metric tensor and the associated metric tensor: {grs...leading to (3.52) would have required considerably more space if the tensor approach to this problem had been avoided, whether for pedagogical or other...useful, especially from the pedagogical point of view, since it addresses itself to large audiences and exposes the treated subject in great depth. On
Diffusion tensor imaging using multiple coils for mouse brain connectomics.
Nouls, John C; Badea, Alexandra; Anderson, Robert B J; Cofer, Gary P; Allan Johnson, G
2018-06-01
The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal-to-noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil-dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two-coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade-offs between imaging throughput and connectivity matrix integrity, studies may seek to clarify how measurement variability, post-processing techniques and biological variability impact mouse brain connectomics. Copyright © 2018 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Kastor, David; Ray, Sourya; Traschen, Jennie
2017-10-01
We study the problem of finding brane-like solutions to Lovelock gravity, adopting a general approach to establish conditions that a lower dimensional base metric must satisfy in order that a solution to a given Lovelock theory can be constructed in one higher dimension. We find that for Lovelock theories with generic values of the coupling constants, the Lovelock tensors (higher curvature generalizations of the Einstein tensor) of the base metric must all be proportional to the metric. Hence, allowed base metrics form a subclass of Einstein metrics. This subclass includes so-called ‘universal metrics’, which have been previously investigated as solutions to quantum-corrected field equations. For specially tuned values of the Lovelock couplings, we find that the Lovelock tensors of the base metric need to satisfy fewer constraints. For example, for Lovelock theories with a unique vacuum there is only a single such constraint, a case previously identified in the literature, and brane solutions can be straightforwardly constructed.
[An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].
Xu, Yonghong; Gao, Shangce; Hao, Xiaofei
2016-04-01
Diffusion tensor imaging(DTI)is a rapid development technology in recent years of magnetic resonance imaging.The diffusion tensor interpolation is a very important procedure in DTI image processing.The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy,but the method does not revise the size of tensors.The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation.Firstly,we decomposed diffusion tensors with the direction of tensors being represented by quaternion.Then we revised the size and direction of the tensor respectively according to different situations.Finally,we acquired the tensor of interpolation point by calculating the weighted average.We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data.The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy(FA)and the determinant of tensors,but also preserve the tensor anisotropy at the same time.In conclusion,the improved method provides a kind of important interpolation method for diffusion tensor image processing.
Jovicich, Jorge; Marizzoni, Moira; Bosch, Beatriz; Bartrés-Faz, David; Arnold, Jennifer; Benninghoff, Jens; Wiltfang, Jens; Roccatagliata, Luca; Picco, Agnese; Nobili, Flavio; Blin, Oliver; Bombois, Stephanie; Lopes, Renaud; Bordet, Régis; Chanoine, Valérie; Ranjeva, Jean-Philippe; Didic, Mira; Gros-Dagnac, Hélène; Payoux, Pierre; Zoccatelli, Giada; Alessandrini, Franco; Beltramello, Alberto; Bargalló, Núria; Ferretti, Antonio; Caulo, Massimo; Aiello, Marco; Ragucci, Monica; Soricelli, Andrea; Salvadori, Nicola; Tarducci, Roberto; Floridi, Piero; Tsolaki, Magda; Constantinidis, Manos; Drevelegas, Antonios; Rossini, Paolo Maria; Marra, Camillo; Otto, Josephin; Reiss-Zimmermann, Martin; Hoffmann, Karl-Titus; Galluzzi, Samantha; Frisoni, Giovanni B
2014-11-01
Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios. Copyright © 2014 Elsevier Inc. All rights reserved.
Meoded, Avner; Kwan, Justin Y.; Peters, Tracy L.; Huey, Edward D.; Danielian, Laura E.; Wiggs, Edythe; Morrissette, Arthur; Wu, Tianxia; Russell, James W.; Bayat, Elham; Grafman, Jordan; Floeter, Mary Kay
2013-01-01
Introduction Executive dysfunction occurs in many patients with amyotrophic lateral sclerosis (ALS), but it has not been well studied in primary lateral sclerosis (PLS). The aims of this study were to (1) compare cognitive function in PLS to that in ALS patients, (2) explore the relationship between performance on specific cognitive tests and diffusion tensor imaging (DTI) metrics of white matter tracts and gray matter volumes, and (3) compare DTI metrics in patients with and without cognitive and behavioral changes. Methods The Delis-Kaplan Executive Function System (D-KEFS), the Mattis Dementia Rating Scale (DRS-2), and other behavior and mood scales were administered to 25 ALS patients and 25 PLS patients. Seventeen of the PLS patients, 13 of the ALS patients, and 17 healthy controls underwent structural magnetic resonance imaging (MRI) and DTI. Atlas-based analysis using MRI Studio software was used to measure fractional anisotropy, and axial and radial diffusivity of selected white matter tracts. Voxel-based morphometry was used to assess gray matter volumes. The relationship between diffusion properties of selected association and commissural white matter and performance on executive function and memory tests was explored using a linear regression model. Results More ALS than PLS patients had abnormal scores on the DRS-2. DRS-2 and D-KEFS scores were related to DTI metrics in several long association tracts and the callosum. Reduced gray matter volumes in motor and perirolandic areas were not associated with cognitive scores. Conclusion The changes in diffusion metrics of white matter long association tracts suggest that the loss of integrity of the networks connecting fronto-temporal areas to parietal and occipital areas contributes to cognitive impairment. PMID:24052798
Diffusion tensor imaging of the brainstem in children with achondroplasia
BOSEMANI, THANGAMADHAN; ORMAN, GUNES; CARSON, KATHRYN A; MEODED, AVNER; HUISMAN, THIERRY A G M; PORETTI, ANDREA
2014-01-01
Aim The aims of this study were to compare, using diffusion tensor imaging (DTI) of the brainstem, microstructural integrity of the white matter in children with achondroplasia and age-matched participants and to correlate the severity of craniocervical junction (CCJ) narrowing and neurological findings with DTI scalars in children with achondroplasia. This study also aimed to assess the potential role of fibroblast growth factor receptor type 3 on white matter microstructure. Method Diffusion tensor imaging was performed using a 1.5T magnetic resonance scanner and balanced pairs of diffusion gradients along 20 non-collinear directions. Measurements were obtained from regions of interest, sampled in each pontine corticospinal tract (CST), medial lemniscus, and middle cerebellar peduncle, as well as in the lower brainstem and centrum semiovale, for fractional anisotropy and for mean, axial and radial diffusivity. In addition, a severity score for achondroplasia was assessed by measuring CCJ narrowing. Result Eight patients with achondroplasia (seven males, one female; mean age 5y 6mo, range 1y 1mo–15y 1mo) and eight age- and sex-matched comparison participants (mean age 5y 2mo, range 1y 1mo–14y 11mo) were included in this study. Fractional anisotropy was lower and mean diffusivity and radial diffusivity were higher in the lower brainstem of patients with achondroplasia than in age-matched comparison participants. The CST and middle cerebellar peduncle of the participants showed increases in mean, axial, and radial diffusivity. Fractional anisotropy in the lower brainstem was negatively correlated with the degree of CCJ narrowing. No differences in the DTI metrics of the centrum semiovale were observed between the two groups. Interpretation The reduction in fractional anisotropy and increase in diffusivities in the lower brainstem of participants with achondroplasia may reflect secondary encephalomalacic degeneration and cavitation of the affected white matter tracts as shown by histology. In children with achondroplasia, DTI may serve as a potential biomarker for brainstem white matter injury and aid in the care and management of these patients. PMID:24825324
Diffusion tensor imaging of the brainstem in children with achondroplasia.
Bosemani, Thangamadhan; Orman, Gunes; Carson, Kathryn A; Meoded, Avner; Huisman, Thierry A G M; Poretti, Andrea
2014-11-01
The aims of this study were to compare, using diffusion tensor imaging (DTI) of the brainstem, microstructural integrity of the white matter in children with achondroplasia and age-matched participants and to correlate the severity of craniocervical junction (CCJ) narrowing and neurological findings with DTI scalars in children with achondroplasia. This study also aimed to assess the potential role of fibroblast growth factor receptor type 3 on white matter microstructure. Diffusion tensor imaging was performed using a 1.5T magnetic resonance scanner and balanced pairs of diffusion gradients along 20 non-collinear directions. Measurements were obtained from regions of interest, sampled in each pontine corticospinal tract (CST), medial lemniscus, and middle cerebellar peduncle, as well as in the lower brainstem and centrum semiovale, for fractional anisotropy and for mean, axial, and radial diffusivity. In addition, a severity score for achondroplasia was assessed by measuring CCJ narrowing. Eight patients with achondroplasia (seven males, one female; mean age 5y 6mo, range 1y 1mo-15y 1mo) and eight age- and sex-matched comparison participants (mean age 5y 2mo, range 1y 1mo-14y 11mo) were included in this study. Fractional anisotropy was lower and mean diffusivity and radial diffusivity were higher in the lower brainstem of patients with achondroplasia than in age-matched comparison participants. The CST and middle cerebellar peduncle of the participants showed increases in mean, axial, and radial diffusivity. Fractional anisotropy in the lower brainstem was negatively correlated with the degree of CCJ narrowing. No differences in the DTI metrics of the centrum semiovale were observed between the two groups. The reduction in fractional anisotropy and increase in diffusivities in the lower brainstem of participants with achondroplasia may reflect secondary encephalomalacic degeneration and cavitation of the affected white matter tracts as shown by histology. In children with achondroplasia, DTI may serve as a potential biomarker for brainstem white matter injury and aid in the care and management of these patients. © 2014 Mac Keith Press.
Sahara, Naruhiko; Perez, Pablo D.; Lin, Wen-Lang; Dickson, Dennis W.; Ren, Yan; Zeng, Huadong; Lewis, Jada; Febo, Marcelo
2016-01-01
Elevated expression of human hyperphosphorylated tau is associated with neuronal loss and white matter (WM) pathology in Alzheimer’s disease (AD) and related neurodegenerative disorders. Using in vivo diffusion tensor magnetic resonance imaging (DT-MRI) at 11.1 Tesla we measured age-related alterations in WM diffusion anisotropy indices in a mouse model of human tauopathy (rTg4510) and nontransgenic (nonTg) control mice at the age of 2.5, 4.5, and 8 months. Similar to previous DT-MRI studies in AD subjects, 8-month-old rTg4510 mice showed lower fractional anisotropy (FA) values in WM structures than nonTg. The low WM FA in rTg4510 mice was observed in the genu and splenium of the corpus callosum, anterior commissure, fimbria, and internal capsule and was associated with a higher radial diffusivity than nonTg. Interestingly, rTg4510 mice showed lower estimates for the mode of anisotropy than controls at 2.5 months suggesting that changes in this diffusivity metric are detectable at an early stage preceding severe tauopathy. Immunogold electron microscopy partly supports our diffusion tensor imaging findings. At the age of 4 months, rTg4510 mice show axonal tau inclusions and unmyelinated processes. At later ages (12 months and 14 months) we observed inclusions in myelin sheath, axons, and unmyelinated processes, and a “disorganized” pattern of myelinated fiber arrangement with enlarged inter-axonal spaces in rTg4510 but not in nonTg mice. Our data support a role for the progression of tau pathology in reduced WM integrity measured by DT-MRI. Further in vivo DT-MRI studies in the rTg4510 mouse should help better discern the detailed mechanisms of reduced FA and anisotropy mode, and the specific role of tau during neurodegeneration. PMID:24411290
Metric-affine f (R ,T ) theories of gravity and their applications
NASA Astrophysics Data System (ADS)
Barrientos, E.; Lobo, Francisco S. N.; Mendoza, S.; Olmo, Gonzalo J.; Rubiera-Garcia, D.
2018-05-01
We study f (R ,T ) theories of gravity, where T is the trace of the energy-momentum tensor Tμ ν, with independent metric and affine connection (metric-affine theories). We find that the resulting field equations share a close resemblance with their metric-affine f (R ) relatives once an effective energy-momentum tensor is introduced. As a result, the metric field equations are second-order and no new propagating degrees of freedom arise as compared to GR, which contrasts with the metric formulation of these theories, where a dynamical scalar degree of freedom is present. Analogously to its metric counterpart, the field equations impose the nonconservation of the energy-momentum tensor, which implies nongeodesic motion and consequently leads to the appearance of an extra force. The weak field limit leads to a modified Poisson equation formally identical to that found in Eddington-inspired Born-Infeld gravity. Furthermore, the coupling of these gravity theories to perfect fluids, electromagnetic, and scalar fields, and their potential applications are discussed.
Classification of Kantowski-Sachs metric via conformal Ricci collineations
NASA Astrophysics Data System (ADS)
Hussain, Tahir; Khan, Fawad; Bokhari, Ashfaque H.; Akhtar, Sumaira Saleem
In this paper, we present a classification of the Kantowski-Sachs spacetime metric according to its conformal Ricci collineations (CRCs). Solving the CRC equations, it is shown that the Kantowski-Sachs metric admits 15-dimensional Lie algebra of CRCs when its Ricci tensor is non-degenerate and an infinite dimensional group of CRCs when the Ricci tensor is degenerate. Some examples of Kantowski-Sachs metric admitting nontrivial CRCs are presented and their physical interpretation is provided.
Local metrics admitting a principal Killing-Yano tensor with torsion
NASA Astrophysics Data System (ADS)
Houri, Tsuyoshi; Kubizňák, David; Warnick, Claude M.; Yasui, Yukinori
2012-08-01
In this paper we initiate a classification of local metrics admitting the principal Killing-Yano tensor with a skew-symmetric torsion. It is demonstrated that in such spacetimes rank-2 Killing tensors occur naturally and mutually commute. We reduce the classification problem to that of solving a set of partial differential equations, and we present some solutions to these PDEs. In even dimensions, three types of local metrics are obtained: one of them naturally generalizes the torsion-less case while the others occur only when the torsion is present. In odd dimensions, we obtain more varieties of local metrics. The explicit metrics constructed in this paper are not the most general possible admitting the required symmetry; nevertheless, it is demonstrated that they cover a wide variety of solutions of various supergravities, such as the Kerr-Sen black holes of (un-)gauged Abelian heterotic supergravity, the Chong-Cvetic-Lü-Pope black hole solution of five-dimensional minimal supergravity or the Kähler with torsion manifolds. The relation between generalized Killing-Yano tensors and various torsion Killing spinors is also discussed.
Geodesic-loxodromes for diffusion tensor interpolation and difference measurement.
Kindlmann, Gordon; Estépar, Raúl San José; Niethammer, Marc; Haker, Steven; Westin, Carl-Fredrik
2007-01-01
In algorithms for processing diffusion tensor images, two common ingredients are interpolating tensors, and measuring the distance between them. We propose a new class of interpolation paths for tensors, termed geodesic-loxodromes, which explicitly preserve clinically important tensor attributes, such as mean diffusivity or fractional anisotropy, while using basic differential geometry to interpolate tensor orientation. This contrasts with previous Riemannian and Log-Euclidean methods that preserve the determinant. Path integrals of tangents of geodesic-loxodromes generate novel measures of over-all difference between two tensors, and of difference in shape and in orientation.
A Geometric Framework for the Kinematics of Crystals With Defects
2006-02-01
which parallel transport preserves dot products of vectors, i.e. r G G ¼ 0. It is called the Levi - Civita connection [57] or the Riemannian connection...yielding a null covariant derivative of the metric tensor is called a metric connection. The Levi – Civita connection of (8) is metric. Note that in...tensor formed by inserting the Levi – Civita con- nection (8) into (10). A geometric space B0 with metric G having R G ¼ 0 is called flat. One may show
Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images
ERIC Educational Resources Information Center
Barmpoutis, Angelos
2009-01-01
Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…
Gangolli, Mihika; Holleran, Laurena; Kim, Joong Hee; Stein, Thor D.; Alvarez, Victor; McKee, Ann C.; Brody, David L.
2017-01-01
Advanced diffusion MRI methods have recently been proposed for detection of pathologies such as traumatic axonal injury and chronic traumatic encephalopathy which commonly affect complex cortical brain regions. However, radiological-pathological correlations in human brain tissue that detail the relationship between the multi-component diffusion signal and underlying pathology are lacking. We present a nonlinear voxel based two dimensional coregistration method that is useful for matching diffusion signals to quantitative metrics of high resolution histological images. When validated in ex vivo human cortical tissue at a 250 × 250 × 500 micron spatial resolution, the method proved robust in correlations between generalized q-sampling imaging and histologically based white matter fiber orientations, with r = 0.94 for the primary fiber direction and r = 0.88 for secondary fiber direction in each voxel. Importantly, however, the correlation was substantially worse with reduced spatial resolution or with fiber orientations derived using a diffusion tensor model. Furthermore, we have detailed a quantitative histological metric of white matter fiber integrity termed power coherence capable of distinguishing between architecturally complex but intact white matter from disrupted white matter regions. These methods may allow for more sensitive and specific radiological-pathological correlations of neurodegenerative diseases affecting complex gray and white matter. PMID:28365421
Boespflug, Erin L; Storrs, Judd M; Allendorfer, Jane B; Lamy, Martine; Eliassen, James C; Page, Stephen
2014-09-01
Changes in diffusion tensor imaging (DTI) values co-occur with neurological and functional changes after stroke. However, quantitative DTI metrics have not been examined in response to participation in targeted rehabilitative interventions in chronic stroke. The primary purpose of this pilot study was to examine whether changes in DTI metrics co-occur with paretic arm movement changes among chronic stroke patients participating in a regimen of electrical stimulation targeting the paretic arm. Three subjects exhibiting stable arm hemiparesis were administered 30-minute (n = 1) or 120-minute (n = 2) therapy sessions emphasizing paretic arm use during valued, functional tasks and incorporating an electrical stimulation device. These sessions occurred every weekday for 8 weeks. A fourth subject served as a treatment control, participating in a 30-minute home exercise regimen without electrical stimulation every weekday for 8 weeks. DTI and behavioral outcome measures were acquired at baseline and after intervention. DTI data were analyzed using a region of interest (ROI) approach, with ROIs chosen based on tract involvement in sensorimotor function or as control regions. Behavioral outcome measures were the Fugl-Meyer Scale (FM) and the Action Research Arm Test (ARAT). The treatment control subject exhibited gains in pinch and grasp, as shown by a 5-point increase on the ARAT. The subject who participated in 30-minute therapy sessions exhibited no behavioral gains. Subjects participating in 120-minute therapy sessions displayed consistent impairment reductions and distal movement changes. DTI changes were largest in subjects two and three, with mean diffusivity (MD) decreases in the middle cerebellar peduncle and posterior limb of the internal capsule following treatment. No changes in fractional anisotropy (FA) were observed for sensorimotor tracts. Our preliminary results suggest that active rehabilitative therapies augmented by electrical stimulation may induce positive behavioral changes which are underscored by DTI changes indicative of increased white matter tract integrity in regions specific to sensory-motor function.
Diffusion tensor analysis with invariant gradients and rotation tangents.
Kindlmann, Gordon; Ennis, Daniel B; Whitaker, Ross T; Westin, Carl-Fredrik
2007-11-01
Guided by empirically established connections between clinically important tissue properties and diffusion tensor parameters, we introduce a framework for decomposing variations in diffusion tensors into changes in shape and orientation. Tensor shape and orientation both have three degrees-of-freedom, spanned by invariant gradients and rotation tangents, respectively. As an initial demonstration of the framework, we create a tunable measure of tensor difference that can selectively respond to shape and orientation. Second, to analyze the spatial gradient in a tensor volume (a third-order tensor), our framework generates edge strength measures that can discriminate between different neuroanatomical boundaries, as well as creating a novel detector of white matter tracts that are adjacent yet distinctly oriented. Finally, we apply the framework to decompose the fourth-order diffusion covariance tensor into individual and aggregate measures of shape and orientation covariance, including a direct approximation for the variance of tensor invariants such as fractional anisotropy.
Test-Retest Reliability of Diffusion Tensor Imaging in Huntington's Disease.
Cole, James H; Farmer, Ruth E; Rees, Elin M; Johnson, Hans J; Frost, Chris; Scahill, Rachael I; Hobbs, Nicola Z
2014-03-21
Diffusion tensor imaging (DTI) has shown microstructural abnormalities in patients with Huntington's Disease (HD) and work is underway to characterise how these abnormalities change with disease progression. Using methods that will be applied in longitudinal research, we sought to establish the reliability of DTI in early HD patients and controls. Test-retest reliability, quantified using the intraclass correlation coefficient (ICC), was assessed using region-of-interest (ROI)-based white matter atlas and voxelwise approaches on repeat scan data from 22 participants (10 early HD, 12 controls). T1 data was used to generate further ROIs for analysis in a reduced sample of 18 participants. The results suggest that fractional anisotropy (FA) and other diffusivity metrics are generally highly reliable, with ICCs indicating considerably lower within-subject compared to between-subject variability in both HD patients and controls. Where ICC was low, particularly for the diffusivity measures in the caudate and putamen, this was partly influenced by outliers. The analysis suggests that the specific DTI methods used here are appropriate for cross-sectional research in HD, and give confidence that they can also be applied longitudinally, although this requires further investigation. An important caveat for DTI studies is that test-retest reliability may not be evenly distributed throughout the brain whereby highly anisotropic white matter regions tended to show lower relative within-subject variability than other white or grey matter regions.
Classification of Hamilton-Jacobi separation in orthogonal coordinates with diagonal curvature
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rajaratnam, Krishan, E-mail: k2rajara@uwaterloo.ca; McLenaghan, Raymond G., E-mail: rgmclenaghan@uwaterloo.ca
2014-08-15
We find all orthogonal metrics where the geodesic Hamilton-Jacobi equation separates and the Riemann curvature tensor satisfies a certain equation (called the diagonal curvature condition). All orthogonal metrics of constant curvature satisfy the diagonal curvature condition. The metrics we find either correspond to a Benenti system or are warped product metrics where the induced metric on the base manifold corresponds to a Benenti system. Furthermore, we show that most metrics we find are characterized by concircular tensors; these metrics, called Kalnins-Eisenhart-Miller metrics, have an intrinsic characterization which can be used to obtain them on a given space. In conjunction withmore » other results, we show that the metrics we found constitute all separable metrics for Riemannian spaces of constant curvature and de Sitter space.« less
Meta-analysis of diffusion metrics for the prediction of tumor grade in gliomas.
Miloushev, V Z; Chow, D S; Filippi, C G
2015-02-01
Diffusion tensor metrics are potential in vivo quantitative neuroimaging biomarkers for the characterization of brain tumor subtype. This meta-analysis analyzes the ability of mean diffusivity and fractional anisotropy to distinguish low-grade from high-grade gliomas in the identifiable tumor core and the region of peripheral edema. A meta-analysis of articles with mean diffusivity and fractional anisotropy data for World Health Organization low-grade (I, II) and high-grade (III, IV) gliomas, between 2000 and 2013, was performed. Pooled data were analyzed by using the odds ratio and mean difference. Receiver operating characteristic analysis was performed for patient-level data. The minimum mean diffusivity of high-grade gliomas was decreased compared with low-grade gliomas. High-grade gliomas had decreased average mean diffusivity values compared with low-grade gliomas in the tumor core and increased average mean diffusivity values in the peripheral region. High-grade gliomas had increased FA values compared with low-grade gliomas in the tumor core, decreased values in the peripheral region, and a decreased fractional anisotropy difference between the tumor core and peripheral region. The minimum mean diffusivity differs significantly with respect to the World Health Organization grade of gliomas. Statistically significant effects of tumor grade on average mean diffusivity and fractional anisotropy were observed, supporting the concept that high-grade tumors are more destructive and infiltrative than low-grade tumors. Considerable heterogeneity within the literature may be due to systematic factors in addition to underlying lesion heterogeneity. © 2015 by American Journal of Neuroradiology.
Mayer, Andrew R.; Ling, Josef M.; Dodd, Andrew B.; Meier, Timothy B.; Hanlon, Faith M.; Klimaj, Stefan D.
2018-01-01
Although diffusion magnetic resonance imaging (dMRI) has been widely used to characterize the effects of repetitive mild traumatic brain injury (rmTBI), to date no studies have investigated how novel geometric models of microstructure relate to more typical diffusion tensor imaging (DTI) sequences. Moreover, few studies have evaluated the sensitivity of different registration pipelines (non-linear, linear and tract-based spatial statistics) for detecting dMRI abnormalities in clinical populations. Results from single-subject analyses in healthy controls (HC) indicated a strong negative relationship between fractional anisotropy (FA) and orientation dispersion index (ODI) in both white and gray matter. Equally important, only moderate relationships existed between all other estimates of free/intracellular water volume fractions and more traditional DTI metrics (FA, mean, axial and radial diffusivity). These findings suggest that geometric measures provide differential information about the cellular microstructure relative to traditional DTI measures. Results also suggest greater sensitivity for non-linear registration pipelines that maximize the anatomical information available in T1-weighted images. Clinically, rmTBI resulted in a pattern of decreased FA and increased ODI, largely overlapping in space, in conjunction with increased intracellular and free water fractions, highlighting the potential role of edema following repeated head trauma. In summary, current results suggest that geometric models of diffusion can provide relatively unique information regarding potential mechanisms of pathology that contribute to long-term neurological damage. PMID:27071950
Mayer, Andrew R; Ling, Josef M; Dodd, Andrew B; Meier, Timothy B; Hanlon, Faith M; Klimaj, Stefan D
2017-06-01
Although diffusion magnetic resonance imaging (dMRI) has been widely used to characterize the effects of repetitive mild traumatic brain injury (rmTBI), to date no studies have investigated how novel geometric models of microstructure relate to more typical diffusion tensor imaging (DTI) sequences. Moreover, few studies have evaluated the sensitivity of different registration pipelines (non-linear, linear and tract-based spatial statistics) for detecting dMRI abnormalities in clinical populations. Results from single-subject analyses in healthy controls (HC) indicated a strong negative relationship between fractional anisotropy (FA) and orientation dispersion index (ODI) in both white and gray matter. Equally important, only moderate relationships existed between all other estimates of free/intracellular water volume fractions and more traditional DTI metrics (FA, mean, axial and radial diffusivity). These findings suggest that geometric measures provide differential information about the cellular microstructure relative to traditional DTI measures. Results also suggest greater sensitivity for non-linear registration pipelines that maximize the anatomical information available in T 1 -weighted images. Clinically, rmTBI resulted in a pattern of decreased FA and increased ODI, largely overlapping in space, in conjunction with increased intracellular and free water fractions, highlighting the potential role of edema following repeated head trauma. In summary, current results suggest that geometric models of diffusion can provide relatively unique information regarding potential mechanisms of pathology that contribute to long-term neurological damage.
Neurocognitive Effects of Radiotherapy
2013-11-05
tensor imaging ( DTI ), perfusion and diffusion. The majority of patients have completed baseline and at least two additional time-points in regards...completed a 1 hour standard MRI as well as additional testing including diffuse tensor imaging ( DTI ), perfusion and diffusion. The majority of...including diffuse tensor imaging ( DTI ), perfusion and diffusion. The majority of patients have completed baseline and at least two additional time
NASA Astrophysics Data System (ADS)
Ammari, Habib; Qiu, Lingyun; Santosa, Fadil; Zhang, Wenlong
2017-12-01
In this paper we present a mathematical and numerical framework for a procedure of imaging anisotropic electrical conductivity tensor by integrating magneto-acoutic tomography with data acquired from diffusion tensor imaging. Magneto-acoustic tomography with magnetic induction (MAT-MI) is a hybrid, non-invasive medical imaging technique to produce conductivity images with improved spatial resolution and accuracy. Diffusion tensor imaging (DTI) is also a non-invasive technique for characterizing the diffusion properties of water molecules in tissues. We propose a model for anisotropic conductivity in which the conductivity is proportional to the diffusion tensor. Under this assumption, we propose an optimal control approach for reconstructing the anisotropic electrical conductivity tensor. We prove convergence and Lipschitz type stability of the algorithm and present numerical examples to illustrate its accuracy and feasibility.
Effective metrics and a fully covariant description of constitutive tensors in electrodynamics
NASA Astrophysics Data System (ADS)
Schuster, Sebastian; Visser, Matt
2017-12-01
Using electromagnetism to study analogue space-times is tantamount to considering consistency conditions for when a given (meta-) material would provide an analogue space-time model or—vice versa—characterizing which given metric could be modeled with a (meta-) material. While the consistency conditions themselves are by now well known and studied, the form the metric takes once they are satisfied is not. This question is mostly easily answered by keeping the formalisms of the two research fields here in contact as close to each other as possible. While fully covariant formulations of the electrodynamics of media have been around for a long while, they are usually abandoned for (3 +1 )- or six-dimensional formalisms. Here we use the fully unified and fully covariant approach. This enables us even to generalize the consistency conditions for the existence of an effective metric to arbitrary background metrics beyond flat space-time electrodynamics. We also show how the familiar matrices for permittivity ɛ , permeability μ-1, and magnetoelectric effects ζ can be seen as the three independent pieces of the Bel decomposition for the constitutive tensor Za b c d, i.e., the components of an orthogonal decomposition with respect to a given observer with four-velocity Va. Finally, we use the Moore-Penrose pseudoinverse and the closely related pseudodeterminant to then gain the desired reconstruction of the effective metric in terms of the permittivity tensor ɛa b, the permeability tensor [μ-1]a b, and the magnetoelectric tensor ζa b, as an explicit function geff(ɛ ,μ-1,ζ ).
White matter involvement in sporadic Creutzfeldt-Jakob disease
Mandelli, Maria Luisa; DeArmond, Stephen J.; Hess, Christopher P.; Vitali, Paolo; Papinutto, Nico; Oehler, Abby; Miller, Bruce L.; Lobach, Irina V.; Bastianello, Stefano; Geschwind, Michael D.; Henry, Roland G.
2014-01-01
Sporadic Creutzfeldt-Jakob disease is considered primarily a disease of grey matter, although the extent of white matter involvement has not been well described. We used diffusion tensor imaging to study the white matter in sporadic Creutzfeldt-Jakob disease compared to healthy control subjects and to correlated magnetic resonance imaging findings with histopathology. Twenty-six patients with sporadic Creutzfeldt-Jakob disease and nine age- and gender-matched healthy control subjects underwent volumetric T1-weighted and diffusion tensor imaging. Six patients had post-mortem brain analysis available for assessment of neuropathological findings associated with prion disease. Parcellation of the subcortical white matter was performed on 3D T1-weighted volumes using Freesurfer. Diffusion tensor imaging maps were calculated and transformed to the 3D-T1 space; the average value for each diffusion metric was calculated in the total white matter and in regional volumes of interest. Tract-based spatial statistics analysis was also performed to investigate the deeper white matter tracts. There was a significant reduction of mean (P = 0.002), axial (P = 0.0003) and radial (P = 0.0134) diffusivities in the total white matter in sporadic Creutzfeldt-Jakob disease. Mean diffusivity was significantly lower in most white matter volumes of interest (P < 0.05, corrected for multiple comparisons), with a generally symmetric pattern of involvement in sporadic Creutzfeldt-Jakob disease. Mean diffusivity reduction reflected concomitant decrease of both axial and radial diffusivity, without appreciable changes in white matter anisotropy. Tract-based spatial statistics analysis showed significant reductions of mean diffusivity within the white matter of patients with sporadic Creutzfeldt-Jakob disease, mainly in the left hemisphere, with a strong trend (P = 0.06) towards reduced mean diffusivity in most of the white matter bilaterally. In contrast, by visual assessment there was no white matter abnormality either on T2-weighted or diffusion-weighted images. Widespread reduction in white matter mean diffusivity, however, was apparent visibly on the quantitative attenuation coefficient maps compared to healthy control subjects. Neuropathological analysis showed diffuse astrocytic gliosis and activated microglia in the white matter, rare prion deposition and subtle subcortical microvacuolization, and patchy foci of demyelination with no evident white matter axonal degeneration. Decreased mean diffusivity on attenuation coefficient maps might be associated with astrocytic gliosis. We show for the first time significant global reduced mean diffusivity within the white matter in sporadic Creutzfeldt-Jakob disease, suggesting possible primary involvement of the white matter, rather than changes secondary to neuronal degeneration/loss. PMID:25367029
Boareto, Marcelo; Cesar, Jonatas; Leite, Vitor B P; Caticha, Nestor
2015-01-01
We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational method is applied to a cost function that penalizes large intraclass distances and favors small interclass distances. We find analytically the metric tensor that minimizes the cost function. Preprocessing the patterns by doing linear transformations using the metric tensor yields a dataset which can be more efficiently classified. We test our methods using publicly available datasets, for some standard classifiers. Among these datasets, two were tested by the MAQC-II project and, even without the use of further preprocessing, our results improve on their performance.
Caso, Francesca; Agosta, Federica; Volonté, Maria Antonietta; Ferraro, Pilar M; Tiraboschi, Pietro; Copetti, Massimiliano; Valsasina, Paola; Falautano, Monica; Comi, Giancarlo; Falini, Andrea; Filippi, Massimo
2016-10-01
Beside motor symptoms, patients with progressive supranuclear palsy syndrome (PSPs) commonly present cognitive and behavioral disorders. In this study we aimed to assess the structural brain correlates of cognitive impairment in PSPs. We enrolled 23 patients with probable PSP Richardson's syndrome and 15 matched healthy controls. Patients underwent an extensive clinical and neuropsychological evaluation. Cortical thickness measures and diffusion tensor metrics of white matter tracts were obtained. Random forest analysis was used to identify the strongest MRI predictors of cognitive impairment in PSPs at an individual patient level. PSPs patients were in a moderate stage of the disease showing mild cognitive deficits with prominent executive dysfunction. Relative to controls, PSPs patients had a focal, bilateral cortical thinning mainly located in the prefrontal/precentral cortex and temporal pole. PSPs patients also showed a distributed white matter damage involving the main tracts including the superior cerebellar peduncle, corpus callosum, corticospinal tract, and extramotor tracts, such as the inferior fronto-occipital, superior longitudinal and uncinate fasciculi, and cingulum, bilaterally. Regional cortical thinning measures did not relate with cognitive features, while white matter damage showed a significant impact on cognitive impairment (r values ranging from -0.80 to 0.74). PSPs patients show both focal cortical thinning in dorsolateral anterior regions and a distributed white matter damage involving the main motor and extramotor tracts. White matter measures are highly associated with cognitive deficits. Diffusion tensor MRI metrics are likely to be the most sensitive markers of extramotor deficits in PSPs. Copyright © 2016 Elsevier Ltd. All rights reserved.
Using Perturbation Theory to Reduce Noise in Diffusion Tensor Fields
Bansal, Ravi; Staib, Lawrence H.; Xu, Dongrong; Laine, Andrew F.; Liu, Jun; Peterson, Bradley S.
2009-01-01
We propose the use of Perturbation theory to reduce noise in Diffusion Tensor (DT) fields. Diffusion Tensor Imaging (DTI) encodes the diffusion of water molecules along different spatial directions in a positive-definite, 3 × 3 symmetric tensor. Eigenvectors and eigenvalues of DTs allow the in vivo visualization and quantitative analysis of white matter fiber bundles across the brain. The validity and reliability of these analyses are limited, however, by the low spatial resolution and low Signal-to-Noise Ratio (SNR) in DTI datasets. Our procedures can be applied to improve the validity and reliability of these quantitative analyses by reducing noise in the tensor fields. We model a tensor field as a three-dimensional Markov Random Field and then compute the likelihood and the prior terms of this model using Perturbation theory. The prior term constrains the tensor field to be smooth, whereas the likelihood term constrains the smoothed tensor field to be similar to the original field. Thus, the proposed method generates a smoothed field that is close in structure to the original tensor field. We evaluate the performance of our method both visually and quantitatively using synthetic and real-world datasets. We quantitatively assess the performance of our method by computing the SNR for eigenvalues and the coherence measures for eigenvectors of DTs across tensor fields. In addition, we quantitatively compare the performance of our procedures with the performance of one method that uses a Riemannian distance to compute the similarity between two tensors, and with another method that reduces noise in tensor fields by anisotropically filtering the diffusion weighted images that are used to estimate diffusion tensors. These experiments demonstrate that our method significantly increases the coherence of the eigenvectors and the SNR of the eigenvalues, while simultaneously preserving the fine structure and boundaries between homogeneous regions, in the smoothed tensor field. PMID:19540791
General Wahlquist metrics in all dimensions
NASA Astrophysics Data System (ADS)
Hinoue, Kazuki; Houri, Tsuyoshi; Rugina, Christina; Yasui, Yukinori
2014-07-01
It is shown that the Wahlquist metric, which is a stationary, axially symmetric perfect fluid solution with ρ +3p=const, admits a rank-2 generalized closed conformal Killing-Yano tensor with a skew-symmetric torsion. Taking advantage of the presence of such a tensor, we obtain a higher-dimensional generalization of the Wahlquist metric in arbitrary dimensions, including a family of vacuum black hole solutions with spherical horizon topology such as Schwarzschild-Tangherlini, Myers-Perry and higher-dimensional Kerr-NUT-(A)dS metrics and a family of static, spherically symmetric perfect fluid solutions in higher dimensions.
Quantum properties of affine-metric gravity with the cosmological term
NASA Astrophysics Data System (ADS)
Baurov, A. Yu; Pronin, P. I.; Stepanyantz, K. V.
2018-04-01
The paper contains analysis of the one-loop effective action for affine-metric gravity of the Hilbert–Einstein type with the cosmological term. We discuss different approaches to the calculation of the effective action, which depends on two independent variables, namely, the metric tensor and the affine connection. In the one-loop approximation we explain how the effective action can be obtained, if, at the first step of the calculation, the metric tensor is integrated out. It is demonstrated that the result is the same as in the case when one starts by integrating out the connection.
b matrix errors in echo planar diffusion tensor imaging
Boujraf, Saïd; Luypaert, Robert; Osteaux, Michel
2001-01-01
Diffusion‐weighted magnetic resonance imaging (DW‐MRI) is a recognized tool for early detection of infarction of the human brain. DW‐MRI uses the signal loss associated with the random thermal motion of water molecules in the presence of magnetic field gradients to derive parameters that reflect the translational mobility of the water molecules in tissues. If diffusion‐weighted images with different values of b matrix are acquired during one individual investigation, it is possible to calculate apparent diffusion coefficient maps that are the elements of the diffusion tensor. The diffusion tensor elements represent the apparent diffusion coefficient of protons of water molecules in each pixel in the corresponding sample. The relation between signal intensity in the diffusion‐weighted images, diffusion tensor, and b matrix is derived from the Bloch equations. Our goal is to establish the magnitude of the error made in the calculation of the elements of the diffusion tensor when the imaging gradients are ignored. PACS number(s): 87.57. –s, 87.61.–c PMID:11602015
Kamali, Tahereh; Stashuk, Daniel
2016-10-01
Robust and accurate segmentation of brain white matter (WM) fiber bundles assists in diagnosing and assessing progression or remission of neuropsychiatric diseases such as schizophrenia, autism and depression. Supervised segmentation methods are infeasible in most applications since generating gold standards is too costly. Hence, there is a growing interest in designing unsupervised methods. However, most conventional unsupervised methods require the number of clusters be known in advance which is not possible in most applications. The purpose of this study is to design an unsupervised segmentation algorithm for brain white matter fiber bundles which can automatically segment fiber bundles using intrinsic diffusion tensor imaging data information without considering any prior information or assumption about data distributions. Here, a new density based clustering algorithm called neighborhood distance entropy consistency (NDEC), is proposed which discovers natural clusters within data by simultaneously utilizing both local and global density information. The performance of NDEC is compared with other state of the art clustering algorithms including chameleon, spectral clustering, DBSCAN and k-means using Johns Hopkins University publicly available diffusion tensor imaging data. The performance of NDEC and other employed clustering algorithms were evaluated using dice ratio as an external evaluation criteria and density based clustering validation (DBCV) index as an internal evaluation metric. Across all employed clustering algorithms, NDEC obtained the highest average dice ratio (0.94) and DBCV value (0.71). NDEC can find clusters with arbitrary shapes and densities and consequently can be used for WM fiber bundle segmentation where there is no distinct boundary between various bundles. NDEC may also be used as an effective tool in other pattern recognition and medical diagnostic systems in which discovering natural clusters within data is a necessity. Copyright © 2016 Elsevier B.V. All rights reserved.
Tropine, Andrei; Dellani, Paulo D; Glaser, Martin; Bohl, Juergen; Plöner, Till; Vucurevic, Goran; Perneczky, Axel; Stoeter, Peter
2007-04-01
To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI). From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients. According to one-way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F=32.2; p<0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F=28.4; p<0.0001) and may be due to the fascicular arrangement of long spindle-shaped tumor cells and the high content of intra- and interfascicular fibers as shown in the histology. In addition, a capsule-like rim of the in-plane diffusion surrounded most meningiomas irrespective of their histological type. If these results correlate to the intraoperative findings of meningioma consistency, DTI-based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their "hard" or "soft" consistency prior to removal. Copyright (c) 2007 Wiley-Liss, Inc.
Q-space trajectory imaging for multidimensional diffusion MRI of the human brain
Westin, Carl-Fredrik; Knutsson, Hans; Pasternak, Ofer; Szczepankiewicz, Filip; Özarslan, Evren; van Westen, Danielle; Mattisson, Cecilia; Bogren, Mats; O’Donnell, Lauren; Kubicki, Marek; Topgaard, Daniel; Nilsson, Markus
2016-01-01
This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture. PMID:26923372
Aojula, Anuriti; Botfield, Hannah; McAllister, James Patterson; Gonzalez, Ana Maria; Abdullah, Osama; Logan, Ann; Sinclair, Alexandra
2016-05-31
In an effort to develop novel treatments for communicating hydrocephalus, we have shown previously that the transforming growth factor-β antagonist, decorin, inhibits subarachnoid fibrosis mediated ventriculomegaly; however decorin's ability to prevent cerebral cytopathology in communicating hydrocephalus has not been fully examined. Furthermore, the capacity for diffusion tensor imaging to act as a proxy measure of cerebral pathology in multiple sclerosis and spinal cord injury has recently been demonstrated. However, the use of diffusion tensor imaging to investigate cytopathological changes in communicating hydrocephalus is yet to occur. Hence, this study aimed to determine whether decorin treatment influences alterations in diffusion tensor imaging parameters and cytopathology in experimental communicating hydrocephalus. Moreover, the study also explored whether diffusion tensor imaging parameters correlate with cellular pathology in communicating hydrocephalus. Accordingly, communicating hydrocephalus was induced by injecting kaolin into the basal cisterns in 3-week old rats followed immediately by 14 days of continuous intraventricular delivery of either human recombinant decorin (n = 5) or vehicle (n = 6). Four rats remained as intact controls and a further four rats served as kaolin only controls. At 14-days post-kaolin, just prior to sacrifice, routine magnetic resonance imaging and magnetic resonance diffusion tensor imaging was conducted and the mean diffusivity, fractional anisotropy, radial and axial diffusivity of seven cerebral regions were assessed by voxel-based analysis in the corpus callosum, periventricular white matter, caudal internal capsule, CA1 hippocampus, and outer and inner parietal cortex. Myelin integrity, gliosis and aquaporin-4 levels were evaluated by post-mortem immunohistochemistry in the CA3 hippocampus and in the caudal brain of the same cerebral structures analysed by diffusion tensor imaging. Decorin significantly decreased myelin damage in the caudal internal capsule and prevented caudal periventricular white matter oedema and astrogliosis. Furthermore, decorin treatment prevented the increase in caudal periventricular white matter mean diffusivity (p = 0.032) as well as caudal corpus callosum axial diffusivity (p = 0.004) and radial diffusivity (p = 0.034). Furthermore, diffusion tensor imaging parameters correlated primarily with periventricular white matter astrocyte and aquaporin-4 levels. Overall, these findings suggest that decorin has the therapeutic potential to reduce white matter cytopathology in hydrocephalus. Moreover, diffusion tensor imaging is a useful tool to provide surrogate measures of periventricular white matter pathology in communicating hydrocephalus.
Avram, Alexandru V; Sarlls, Joelle E; Barnett, Alan S; Özarslan, Evren; Thomas, Cibu; Irfanoglu, M Okan; Hutchinson, Elizabeth; Pierpaoli, Carlo; Basser, Peter J
2016-02-15
Diffusion tensor imaging (DTI) is the most widely used method for characterizing noninvasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its ability to describe intricate tissue microanatomy. Consequently, the biological interpretation of microstructural parameters, such as fractional anisotropy or mean diffusivity, is often equivocal. We evaluate the clinical feasibility of assessing brain tissue microstructure with mean apparent propagator (MAP) MRI, a powerful analytical framework that efficiently measures the probability density function (PDF) of spin displacements and quantifies useful metrics of this PDF indicative of diffusion in complex microstructure (e.g., restrictions, multiple compartments). Rotation invariant and scalar parameters computed from the MAP show consistent variation across neuroanatomical brain regions and increased ability to differentiate tissues with distinct structural and architectural features compared with DTI-derived parameters. The return-to-origin probability (RTOP) appears to reflect cellularity and restrictions better than MD, while the non-Gaussianity (NG) measures diffusion heterogeneity by comprehensively quantifying the deviation between the spin displacement PDF and its Gaussian approximation. Both RTOP and NG can be decomposed in the local anatomical frame for reference determined by the orientation of the diffusion tensor and reveal additional information complementary to DTI. The propagator anisotropy (PA) shows high tissue contrast even in deep brain nuclei and cortical gray matter and is more uniform in white matter than the FA, which drops significantly in regions containing crossing fibers. Orientational profiles of the propagator computed analytically from the MAP MRI series coefficients allow separation of different fiber populations in regions of crossing white matter pathways, which in turn improves our ability to perform whole-brain fiber tractography. Reconstructions from subsampled data sets suggest that MAP MRI parameters can be computed from a relatively small number of DWIs acquired with high b-value and good signal-to-noise ratio in clinically achievable scan durations of less than 10min. The neuroanatomical consistency across healthy subjects and reproducibility in test-retest experiments of MAP MRI microstructural parameters further substantiate the robustness and clinical feasibility of this technique. The MAP MRI metrics could potentially provide more sensitive clinical biomarkers with increased pathophysiological specificity compared to microstructural measures derived using conventional diffusion MRI techniques. Published by Elsevier Inc.
Sánchez-Valle, Raquel; Monté, Gemma C; Sala-Llonch, Roser; Bosch, Beatriz; Fortea, Juan; Lladó, Albert; Antonell, Anna; Balasa, Mircea; Bargalló, Nuria; Molinuevo, José Luis
2016-01-01
PSEN1 mutations are the most frequent cause of autosomal dominant Alzheimer's disease (ADAD), and show nearly full penetrance. There is presently increasing interest in the study of biomarkers that track disease progression in order to test therapeutic interventions in ADAD. We used white mater (WM) volumetric characteristics and diffusion tensor imaging (DTI) metrics to investigate correlations with the normalized time to expected symptoms onset (relative age ratio) and group differences in a cohort of 36 subjects from PSEN1 ADAD families: 22 mutation carriers, 10 symptomatic (SMC) and 12 asymptomatic (AMC), and 14 non-carriers (NC). Subjects underwent a 3T MRI. WM morphometric data and DTI metrics were analyzed. We found that PSEN1 MC showed significant negative correlation between fractional anisotropy (FA) and the relative age ratio in the genus and body of corpus callosum and corona radiate (p < 0.05 Family-wise error correction (FWE) at cluster level) and positive correlation with mean diffusivity (MD), axial diffusivity (AxD), and radial diffusivity (RD) in the splenium of corpus callosum. SMC presented WM volume loss, reduced FA and increased MD, AxD, and RD in the anterior and posterior corona radiate, corpus callosum (p < 0.05 FWE) compared with NC. No significant differences were observed between AMC and NC in WM volume or DTI measures. These findings suggest that the integrity of the WM deteriorates linearly in PSEN1 ADAD from the early phases of the disease; thus DTI metrics might be useful to monitor the disease progression. However, the lack of significant alterations at the preclinical stages suggests that these indexes might not be good candidates for early markers of the disease.
Heaps-Woodruff, J M; Wright, P W; Ances, B M; Clifford, D; Paul, R H
2016-06-01
The purpose of the present study is to examine the integrity of white matter microstructure among individuals coinfected with HIV and HCV using diffusion tensor imaging (DTI). Twenty-five HIV+ patients, 21 HIV+/HCV+ patients, and 25 HIV- controls were included in this study. All HIV+ individuals were stable on combination antiretroviral therapy (cART; ≥3 months). All participants completed MRI and neuropsychological measures. Clinical variables including liver function, HIV-viral load, and CD4 count were collected from the patient groups. DTI metrics including mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and fractional anisotropy (FA) from five subregions of the corpus callosum were compared across groups. The HIV+/HCV+ group and HIV+ group were similar in terms of HIV clinical variables. None of the participants met criteria for cirrhosis or fibrosis. Within the anterior corpus callosum, significant differences were observed between both HIV+ groups compared to HIV- controls on DTI measures. HIV+ and HIV+/HCV+ groups had significantly lower FA values and higher MD and RD values compared to HIV- controls; however, no differences were present between the HIV+ and HIV+/HCV+ groups. Duration of HIV infection was significantly related to DTI metrics in total corpus callosum FA only, but not other markers of HIV disease burden or neurocognitive function. Both HIV+ and HIV+/HCV+ individuals had significant alterations in white matter integrity within the corpus callosum; however, there was no evidence for an additive effect of HCV coinfection. The association between DTI metrics and duration of HIV infection suggests that HIV may continue to negatively impact white matter integrity even in well-controlled disease.
Incekara, Fatih; Satoer, Djaina; Visch-Brink, Evy; Vincent, Arnaud; Smits, Marion
2018-06-08
OBJECTIVE The authors conducted a study to determine whether cognitive functioning of patients with presumed low-grade glioma is associated with white matter (WM) tract changes. METHODS The authors included 77 patients with presumed low-grade glioma who underwent awake surgery between 2005 and 2013. Diffusion tensor imaging with deterministic tractography was performed preoperatively to identify the arcuate, inferior frontooccipital, and uncinate fasciculi and to obtain the mean fractional anisotropy (FA) and mean diffusivity per tract. All patients were evaluated preoperatively using an extensive neuropsychological protocol that included assessments of the language, memory, and attention/executive function domains. Linear regression models were used to analyze each cognitive domain and each diffusion tensor imaging metric of the 3 WM tracts. RESULTS Significant correlations (corrected for multiple testing) were found between FA of the arcuate fasciculus and results of the repetition test for the language domain (β = 0.59, p < 0.0001) and between FA of the inferior frontooccipital fasciculus and results of the imprinting test for the memory domain (β = -0.55, p = 0.002) and the attention test for the attention and executive function domain (β = -0.62, p = 0.006). CONCLUSIONS In patients with glioma, language deficits in repetition of speech, imprinting, and attention deficits are associated with changes in the microarchitecture of the arcuate and inferior frontooccipital fasciculi.
Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study.
Tylee, Daniel S; Kikinis, Zora; Quinn, Thomas P; Antshel, Kevin M; Fremont, Wanda; Tahir, Muhammad A; Zhu, Anni; Gong, Xue; Glatt, Stephen J; Coman, Ioana L; Shenton, Martha E; Kates, Wendy R; Makris, Nikos
2017-01-01
Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a genetic neurodevelopmental syndrome that has been studied intensively in order to understand relationships between the genetic microdeletion, brain development, cognitive function, and the emergence of psychiatric symptoms. White matter microstructural abnormalities identified using diffusion tensor imaging methods have been reported to affect a variety of neuroanatomical tracts in 22q11.2DS. In the present study, we sought to combine two discovery-based approaches: (1) white matter query language was used to parcellate the brain's white matter into tracts connecting pairs of 34, bilateral cortical regions and (2) the diffusion imaging characteristics of the resulting tracts were analyzed using a machine-learning method called support vector machine in order to optimize the selection of a set of imaging features that maximally discriminated 22q11.2DS and comparison subjects. With this unique approach, we both confirmed previously-recognized 22q11.2DS-related abnormalities in the inferior longitudinal fasciculus (ILF), and identified, for the first time, 22q11.2DS-related anomalies in the middle longitudinal fascicle and the extreme capsule, which may have been overlooked in previous, hypothesis-guided studies. We further observed that, in participants with 22q11.2DS, ILF metrics were significantly associated with positive prodromal symptoms of psychosis.
Jing, Guojie; Yao, Xiaoteng; Li, Yiyi; Xie, Yituan; Li, Wang#x2019;an; Liu, Kejun; Jing, Yingchao; Li, Baisheng; Lv, Yifan; Ma, Baoxin
2014-01-01
Fractional anisotropy values in diffusion tensor imaging can quantitatively reflect the consistency of nerve fibers after brain damage, where higher values generally indicate less damage to nerve fibers. Therefore, we hypothesized that diffusion tensor imaging could be used to evaluate the effect of mild hypothermia on diffuse axonal injury. A total of 102 patients with diffuse axonal injury were randomly divided into two groups: normothermic and mild hypothermic treatment groups. Patient's modified Rankin scale scores 2 months after mild hypothermia were significantly lower than those for the normothermia group. The difference in average fractional anisotropy value for each region of interest before and after mild hypothermia was 1.32-1.36 times higher than the value in the normothermia group. Quantitative assessment of diffusion tensor imaging indicates that mild hypothermia therapy may be beneficial for patients with diffuse axonal injury. PMID:25206800
Pajevic, Sinisa; Aldroubi, Akram; Basser, Peter J
2002-01-01
The effective diffusion tensor of water, D, measured by diffusion tensor MRI (DT-MRI), is inherently a discrete, noisy, voxel-averaged sample of an underlying macroscopic effective diffusion tensor field, D(x). Within fibrous tissues this field is presumed to be continuous and smooth at a gross anatomical length scale. Here a new, general mathematical framework is proposed that uses measured DT-MRI data to produce a continuous approximation to D(x). One essential finding is that the continuous tensor field representation can be constructed by repeatedly performing one-dimensional B-spline transforms of the DT-MRI data. The fidelity and noise-immunity of this approximation are tested using a set of synthetically generated tensor fields to which background noise is added via Monte Carlo methods. Generally, these tensor field templates are reproduced faithfully except at boundaries where diffusion properties change discontinuously or where the tensor field is not microscopically homogeneous. Away from such regions, the tensor field approximation does not introduce bias in useful DT-MRI parameters, such as Trace(D(x)). It also facilitates the calculation of several new parameters, particularly differential quantities obtained from the tensor of spatial gradients of D(x). As an example, we show that they can identify tissue boundaries across which diffusion properties change rapidly using in vivo human brain data. One important application of this methodology is to improve the reliability and robustness of DT-MRI fiber tractography.
NASA Astrophysics Data System (ADS)
Skare, Stefan; Hedehus, Maj; Moseley, Michael E.; Li, Tie-Qiang
2000-12-01
Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.
Assessment of the overlap metric in the context of RI-MP2 and atomic batched tensor decomposed MP2
NASA Astrophysics Data System (ADS)
Schmitz, Gunnar; Christiansen, Ove
2018-06-01
The resolution-of-the-identity approximation (RI) is a standard tool to accelerate the evaluation of two electron repulsion integrals. However introducing further approximations on top of for example RI-MP2, makes it important to check again the made choices. Usually the so called Coulomb metric is used. An alternative is the less accurate overlap metric, which has the benefit of a faster decay with distance. We encountered both choices in our atomic batched tensor decomposed MP2 (AB-MP2) and went with the Coulomb metric for the safe choice. In this work we re-investigate the choice of Coulomb and overlap metric for RI-MP2 and AB-MP2.
Local White Matter Geometry from Diffusion Tensor Gradients
Savadjiev, Peter; Kindlmann, Gordon L.; Bouix, Sylvain; Shenton, Martha E.; Westin, Carl-Fredrik
2009-01-01
We introduce a mathematical framework for computing geometrical properties of white matter fibres directly from diffusion tensor fields. The key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a coordinate frame of tensor eigenvectors. The resulting eigenframe-centered representation then makes it possible to define scalar indices (or measures) that describe the local white matter geometry directly from the diffusion tensor field and its gradient, without requiring prior tractography. We derive new scalar indices of (1) fibre dispersion and (2) fibre curving, and we demonstrate them on synthetic and in vivo data. Finally, we illustrate their applicability to a group study on schizophrenia. PMID:19896542
Local White Matter Geometry from Diffusion Tensor Gradients
Savadjiev, Peter; Kindlmann, Gordon L.; Bouix, Sylvain; Shenton, Martha E.; Westin, Carl-Fredrik
2010-01-01
We introduce a mathematical framework for computing geometrical properties of white matter fibres directly from diffusion tensor fields. The key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a coordinate frame of tensor eigenvectors. The resulting eigenframe-centered representation then makes it possible to define scalar indices (or measures) that describe the local white matter geometry directly from the diffusion tensor field and its gradient, without requiring prior tractography. We derive new scalar indices of (1) fibre dispersion and (2) fibre curving, and we demonstrate them on synthetic and in vivo data. Finally, we illustrate their applicability to a group study on schizophrenia. PMID:20426006
Tractography from HARDI using an Intrinsic Unscented Kalman Filter
Cheng, Guang; Salehian, Hesamoddin; Forder, John R.; Vemuri, Baba C.
2014-01-01
A novel adaptation of the unscented Kalman filter (UKF) was recently introduced in literature for simultaneous multi-tensor estimation and fiber tractography from diffusion MRI. This technique has the advantage over other tractography methods in terms of computational efficiency, due to the fact that the UKF simultaneously estimates the diffusion tensors and propagates the most consistent direction to track along. This UKF and its variants reported later in literature however are not intrinsic to the space of diffusion tensors. Lack of this key property can possibly lead to inaccuracies in the multi-tensor estimation as well as in the tractography. In this paper, we propose a novel intrinsic unscented Kalman filter (IUKF) in the space of diffusion tensors which are symmetric positive definite matrices, that can be used for simultaneous recursive estimation of multi-tensors and propagation of directional information for use in fiber tractography from diffusion weighted MR data. In addition to being more accurate, IUKF retains all the advantages of UKF mentioned above. We demonstrate the accuracy and effectiveness of the proposed method via experiments publicly available phantom data from the fiber cup-challenge (MICCAI 2009) and diffusion weighted MR scans acquired from human brains and rat spinal cords. PMID:25203986
Lin, Wei-Che; Chou, Kun-Hsien; Chen, Chao-Long; Chen, Hsiu-Ling; Lu, Cheng-Hsien; Li, Shau-Hsuan; Huang, Chu-Chung; Lin, Ching-Po; Cheng, Yu-Fan
2014-01-01
Cerebral edema is the common pathogenic mechanism for cognitive impairment in minimal hepatic encephalopathy. Whether complete reversibility of brain edema, cognitive deficits, and their associated imaging can be achieved after liver transplantation remains an open question. To characterize white matter integrity before and after liver transplantation in patients with minimal hepatic encephalopathy, multiple diffusivity indices acquired via diffusion tensor imaging was applied. Twenty-eight patients and thirty age- and sex-matched healthy volunteers were included. Multiple diffusivity indices were obtained from diffusion tensor images, including mean diffusivity, fractional anisotropy, axial diffusivity and radial diffusivity. The assessment was repeated 6-12 month after transplantation. Differences in white matter integrity between groups, as well as longitudinal changes, were evaluated using tract-based spatial statistical analysis. Correlation analyses were performed to identify first scan before transplantation and interval changes among the neuropsychiatric tests, clinical laboratory tests, and diffusion tensor imaging indices. After transplantation, decreased water diffusivity without fractional anisotropy change indicating reversible cerebral edema was found in the left anterior cingulate, claustrum, postcentral gyrus, and right corpus callosum. However, a progressive decrease in fractional anisotropy and an increase in radial diffusivity suggesting demyelination were noted in temporal lobe. Improved pre-transplantation albumin levels and interval changes were associated with better recoveries of diffusion tensor imaging indices. Improvements in interval diffusion tensor imaging indices in the right postcentral gyrus were correlated with visuospatial function score correction. In conclusion, longitudinal voxel-wise analysis of multiple diffusion tensor imaging indices demonstrated different white matter changes in minimal hepatic encephalopathy patients. Transplantation improved extracellular cerebral edema and the results of associated cognition tests. However, white matter demyelination may advance in temporal lobe.
Recovery of White Matter following Pediatric Traumatic Brain Injury Depends on Injury Severity.
Genc, Sila; Anderson, Vicki; Ryan, Nicholas P; Malpas, Charles B; Catroppa, Cathy; Beauchamp, Miriam H; Silk, Timothy J
2017-02-15
Previous studies in pediatric traumatic brain injury (TBI) have been variable in describing the effects of injury severity on white-matter development. The present study used diffusion tensor imaging to investigate prospective sub-acute and longitudinal relationships between early clinical indicators of injury severity, diffusion metrics, and neuropsychological outcomes. Pediatric patients with TBI underwent magnetic resonance imaging (MRI) (n = 78, mean [M] = 10.56, standard deviation [SD] = 2.21 years) at the sub-acute stage after injury (M = 5.55, SD = 3.05 weeks), and typically developing children were also included and imaged (n = 30, M = 10.60, SD = 2.88 years). A sub-set of the patients with TBI (n = 15) was followed up with MRI 2 years post-injury. Diffusion MRI images were acquired at sub-acute and 2-year follow-up time points and analyzed using Tract-Based Spatial Statistics. At the sub-acute stage, mean diffusivity and axial diffusivity were significantly higher in the TBI group compared with matched controls (p < 0.05). TBI severity significantly predicted diffusion profiles at the sub-acute and 2-year post-injury MRI. Patients with more severe TBI also exhibited poorer information processing speed at 6-months post-injury, which in turn correlated with their diffusion metrics. These findings highlight that the severity of the injury not only has an impact on white-matter microstructure, it also impacts its recovery over time. Moreover, findings suggest that sub-acute microstructural changes may represent a useful prognostic marker to identify children at elevated risk for longer term deficits.
NASA Astrophysics Data System (ADS)
Gyrya, V.; Lipnikov, K.
2017-11-01
We present the arbitrary order mimetic finite difference (MFD) discretization for the diffusion equation with non-symmetric tensorial diffusion coefficient in a mixed formulation on general polygonal meshes. The diffusion tensor is assumed to be positive definite. The asymmetry of the diffusion tensor requires changes to the standard MFD construction. We present new approach for the construction that guarantees positive definiteness of the non-symmetric mass matrix in the space of discrete velocities. The numerically observed convergence rate for the scalar quantity matches the predicted one in the case of the lowest order mimetic scheme. For higher orders schemes, we observed super-convergence by one order for the scalar variable which is consistent with the previously published result for a symmetric diffusion tensor. The new scheme was also tested on a time-dependent problem modeling the Hall effect in the resistive magnetohydrodynamics.
Gyrya, V.; Lipnikov, K.
2017-07-18
Here, we present the arbitrary order mimetic finite difference (MFD) discretization for the diffusion equation with non-symmetric tensorial diffusion coefficient in a mixed formulation on general polygonal meshes. The diffusion tensor is assumed to be positive definite. The asymmetry of the diffusion tensor requires changes to the standard MFD construction. We also present new approach for the construction that guarantees positive definiteness of the non-symmetric mass matrix in the space of discrete velocities. The numerically observed convergence rate for the scalar quantity matches the predicted one in the case of the lowest order mimetic scheme. For higher orders schemes, wemore » observed super-convergence by one order for the scalar variable which is consistent with the previously published result for a symmetric diffusion tensor. The new scheme was also tested on a time-dependent problem modeling the Hall effect in the resistive magnetohydrodynamics.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gyrya, V.; Lipnikov, K.
Here, we present the arbitrary order mimetic finite difference (MFD) discretization for the diffusion equation with non-symmetric tensorial diffusion coefficient in a mixed formulation on general polygonal meshes. The diffusion tensor is assumed to be positive definite. The asymmetry of the diffusion tensor requires changes to the standard MFD construction. We also present new approach for the construction that guarantees positive definiteness of the non-symmetric mass matrix in the space of discrete velocities. The numerically observed convergence rate for the scalar quantity matches the predicted one in the case of the lowest order mimetic scheme. For higher orders schemes, wemore » observed super-convergence by one order for the scalar variable which is consistent with the previously published result for a symmetric diffusion tensor. The new scheme was also tested on a time-dependent problem modeling the Hall effect in the resistive magnetohydrodynamics.« less
Lorentzian three-metrics with degenerate Ricci tensors
NASA Astrophysics Data System (ADS)
McManus, Des J.
1995-03-01
A classification of Lorentzian three-metrics whose Ricci tensor satisfies Rij=λ1gij+λ2vivj with λ1 and λ2(≠0) constant where vivi=κ(=0 or ±1) is given. An explicit coordinate representation is given for all the metrics that admit a G4 group as their maximal isometry group. Those metrics that admit a G3 as their maximal isometry group belong to either Bianchi class VI0, or VII0, or VIII, or IX when κ ≠ 0, and to either Bianchi class III, or IV, or VI0, VIh, or VIII when κ=0. An explicit coordinate representation is given for all the inhomogeneous solutions in the case κ ≠ 0.
Microstructure of frontoparietal connections predicts individual resistance to sleep deprivation.
Cui, Jiaolong; Tkachenko, Olga; Gogel, Hannah; Kipman, Maia; Preer, Lily A; Weber, Mareen; Divatia, Shreya C; Demers, Lauren A; Olson, Elizabeth A; Buchholz, Jennifer L; Bark, John S; Rosso, Isabelle M; Rauch, Scott L; Killgore, William D S
2015-02-01
Sleep deprivation (SD) can degrade cognitive functioning, but growing evidence suggests that there are large individual differences in the vulnerability to this effect. Some evidence suggests that baseline differences in the responsiveness of a fronto-parietal attention system that is activated during working memory (WM) tasks may be associated with the ability to sustain vigilance during sleep deprivation. However, the neurocircuitry underlying this network remains virtually unexplored. In this study, we employed diffusion tensor imaging (DTI) to investigate the association between the microstructure of the axonal pathway connecting the frontal and parietal regions--i.e., the superior longitudinal fasciculus (SLF)--and individual resistance to SD. Thirty healthy participants (15 males) aged 20-43 years underwent functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) at rested wakefulness prior to a 28-hour period of SD. Task-related fronto-parietal fMRI activation clusters during a Sternberg WM Task were localized and used as seed regions for probabilistic fiber tractography. DTI metrics, including fractional anisotropy, mean diffusivity, axial and radial diffusivity were measured in the SLF. The psychomotor vigilance test (PVT) was used to evaluate resistance to SD. We found that activation in the left inferior parietal lobule (IPL) and dorsolateral prefrontal cortex (DLPFC) positively correlated with resistance. Higher fractional anisotropy of the left SLF comprising the primary axons connecting IPL and DLPFC was also associated with better resistance. These findings suggest that individual differences in resistance to SD are associated with the functional responsiveness of a fronto-parietal attention system and the microstructural properties of the axonal interconnections. Copyright © 2014 Elsevier Inc. All rights reserved.
Righini, Andrea; Doneda, Chiara; Parazzini, Cecilia; Arrigoni, Filippo; Matta, Ursula; Triulzi, Fabio
2010-11-01
The main purpose was to investigate any early diffusion tensor imaging (DTI) changes in corpus callosum (CC) associated with acute cerebral hemisphere lesions in term newborns. We retrospectively analysed 19 cases of term newborns acutely affected by focal or multi-focal lesions: hypoxic-ischemic encephalopathy, hypoglycaemic encephalopathy, focal ischemic stroke and deep medullary vein associated lesions. DTI was acquired at 1.5 Tesla with dedicated neonatal coil. DTI metrics (apparent diffusion coefficient (ADC), fractional anisotropy (FA), axial λ(∐) and radial λ(⟂) diffusivity) were measured in the hemisphere lesions and in the CC. The control group included seven normal newborns. The following significant differences were found between patients and normal controls in the CC: mean ADC was lower in patients (0.88 SD 0.23 versus 1.18 SD 0.07 μm(2)/s) and so was mean FA (0.50 SD 0.1 versus 0.67 SD 0.05) and mean λ(∐) value (1.61 SD 0.52 versus 2.36 SD 0.14 μm(2)/s). In CC the percentage of ADC always diminished independently of lesion age (with one exception), whereas in hemisphere lesions, it was negative in earlier lesions, but exceeded normal values in the older lesions. CC may undergo early DTI changes in newborns with acute focal or multi-focal hemisphere lesions of different aetiology. Although a direct insult to CC cannot be totally ruled out, DTI changes in CC (in particular λ(∐)) may also be compatible with very early Wallerian degeneration or pre-Wallerian degeneration.
Ghose, R; Fushman, D; Cowburn, D
2001-04-01
In this paper we present a method for determining the rotational diffusion tensor from NMR relaxation data using a combination of approximate and exact methods. The approximate method, which is computationally less intensive, computes values of the principal components of the diffusion tensor and estimates the Euler angles, which relate the principal axis frame of the diffusion tensor to the molecular frame. The approximate values of the principal components are then used as starting points for an exact calculation by a downhill simplex search for the principal components of the tensor over a grid of the space of Euler angles relating the diffusion tensor frame to the molecular frame. The search space of Euler angles is restricted using the tensor orientations calculated using the approximate method. The utility of this approach is demonstrated using both simulated and experimental relaxation data. A quality factor that determines the extent of the agreement between the measured and predicted relaxation data is provided. This approach is then used to estimate the relative orientation of SH3 and SH2 domains in the SH(32) dual-domain construct of Abelson kinase complexed with a consolidated ligand. Copyright 2001 Academic Press.
NASA Astrophysics Data System (ADS)
Ghose, Ranajeet; Fushman, David; Cowburn, David
2001-04-01
In this paper we present a method for determining the rotational diffusion tensor from NMR relaxation data using a combination of approximate and exact methods. The approximate method, which is computationally less intensive, computes values of the principal components of the diffusion tensor and estimates the Euler angles, which relate the principal axis frame of the diffusion tensor to the molecular frame. The approximate values of the principal components are then used as starting points for an exact calculation by a downhill simplex search for the principal components of the tensor over a grid of the space of Euler angles relating the diffusion tensor frame to the molecular frame. The search space of Euler angles is restricted using the tensor orientations calculated using the approximate method. The utility of this approach is demonstrated using both simulated and experimental relaxation data. A quality factor that determines the extent of the agreement between the measured and predicted relaxation data is provided. This approach is then used to estimate the relative orientation of SH3 and SH2 domains in the SH(32) dual-domain construct of Abelson kinase complexed with a consolidated ligand.
Fully Anisotropic Rotational Diffusion Tensor from Molecular Dynamics Simulations.
Linke, Max; Köfinger, Jürgen; Hummer, Gerhard
2018-05-31
We present a method to calculate the fully anisotropic rotational diffusion tensor from molecular dynamics simulations. Our approach is based on fitting the time-dependent covariance matrix of the quaternions that describe the rigid-body rotational dynamics. Explicit analytical expressions have been derived for the covariances by Favro, which are valid irrespective of the degree of anisotropy. We use these expressions to determine an optimal rotational diffusion tensor from trajectory data. The molecular structures are aligned against a reference by optimal rigid-body superposition. The quaternion covariances can then be obtained directly from the rotation matrices used in the alignment. The rotational diffusion tensor is determined by a fit to the time-dependent quaternion covariances, or directly by Laplace transformation and matrix diagonalization. To quantify uncertainties in the fit, we derive analytical expressions and compare them with the results of Brownian dynamics simulations of anisotropic rotational diffusion. We apply the method to microsecond long trajectories of the Dickerson-Drew B-DNA dodecamer and of horse heart myoglobin. The anisotropic rotational diffusion tensors calculated from simulations agree well with predictions from hydrodynamics.
Etherton, Mark R; Wu, Ona; Cougo, Pedro; Giese, Anne-Katrin; Cloonan, Lisa; Fitzpatrick, Kaitlin M; Kanakis, Allison S; Boulouis, Gregoire; Karadeli, Hasan H; Lauer, Arne; Rosand, Jonathan; Furie, Karen L; Rost, Natalia S
2017-12-01
Women have worse poststroke outcomes than men. We evaluated sex-specific clinical and neuroimaging characteristics of white matter in association with functional recovery after acute ischemic stroke. We performed a retrospective analysis of acute ischemic stroke patients with admission brain MRI and 3- to 6-month modified Rankin Scale score. White matter hyperintensity and acute infarct volume were quantified on fluid-attenuated inversion recovery and diffusion tensor imaging MRI, respectively. Diffusivity anisotropy metrics were calculated in normal appearing white matter contralateral to the acute ischemia. Among 319 patients with acute ischemic stroke, women were older (68.0 versus 62.7 years; P =0.004), had increased incidence of atrial fibrillation (21.4% versus 12.2%; P =0.04), and lower rate of tobacco use (21.1% versus 35.9%; P =0.03). There was no sex-specific difference in white matter hyperintensity volume, acute infarct volume, National Institutes of Health Stroke Scale, prestroke modified Rankin Scale score, or normal appearing white matter diffusivity anisotropy metrics. However, women were less likely to have an excellent outcome (modified Rankin Scale score <2: 49.6% versus 67.0%; P =0.005). In logistic regression analysis, female sex and the interaction of sex with fractional anisotropy, radial diffusivity, and axial diffusivity were independent predictors of functional outcome. Female sex is associated with decreased likelihood of excellent outcome after acute ischemic stroke. The correlation between markers of white matter integrity and functional outcomes in women, but not men, suggests a potential sex-specific mechanism. © 2017 American Heart Association, Inc.
Correlation of Diffusion and Metabolic Alterations in Different Clinical Forms of Multiple Sclerosis
Hannoun, Salem; Bagory, Matthieu; Durand-Dubief, Francoise; Ibarrola, Danielle; Comte, Jean-Christophe; Confavreux, Christian; Cotton, Francois; Sappey-Marinier, Dominique
2012-01-01
Diffusion tensor imaging (DTI) and MR spectroscopic imaging (MRSI) provide greater sensitivity than conventional MRI to detect diffuse alterations in normal appearing white matter (NAWM) of Multiple Sclerosis (MS) patients with different clinical forms. Therefore, the goal of this study is to combine DTI and MRSI measurements to analyze the relation between diffusion and metabolic markers, T2-weighted lesion load (T2-LL) and the patients clinical status. The sensitivity and specificity of both methods were then compared in terms of MS clinical forms differentiation. MR examination was performed on 71 MS patients (27 relapsing remitting (RR), 26 secondary progressive (SP) and 18 primary progressive (PP)) and 24 control subjects. DTI and MRSI measurements were obtained from two identical regions of interest selected in left and right centrum semioval (CSO) WM. DTI metrics and metabolic contents were significantly altered in MS patients with the exception of N-acetyl-aspartate (NAA) and NAA/Choline (Cho) ratio in RR patients. Significant correlations were observed between diffusion and metabolic measures to various degrees in every MS patients group. Most DTI metrics were significantly correlated with the T2-LL while only NAA/Cr ratio was correlated in RR patients. A comparison analysis of MR methods efficiency demonstrated a better sensitivity/specificity of DTI over MRSI. Nevertheless, NAA/Cr ratio could distinguish all MS and SP patients groups from controls, while NAA/Cho ratio differentiated PP patients from controls. This study demonstrated that diffusivity changes related to microstructural alterations were correlated with metabolic changes and provided a better sensitivity to detect early changes, particularly in RR patients who are more subject to inflammatory processes. In contrast, the better specificity of metabolic ratios to detect axonal damage and demyelination may provide a better index for identification of PP patients. PMID:22479330
Roniotis, Alexandros; Manikis, Georgios C; Sakkalis, Vangelis; Zervakis, Michalis E; Karatzanis, Ioannis; Marias, Kostas
2012-03-01
Glioma, especially glioblastoma, is a leading cause of brain cancer fatality involving highly invasive and neoplastic growth. Diffusive models of glioma growth use variations of the diffusion-reaction equation in order to simulate the invasive patterns of glioma cells by approximating the spatiotemporal change of glioma cell concentration. The most advanced diffusive models take into consideration the heterogeneous velocity of glioma in gray and white matter, by using two different discrete diffusion coefficients in these areas. Moreover, by using diffusion tensor imaging (DTI), they simulate the anisotropic migration of glioma cells, which is facilitated along white fibers, assuming diffusion tensors with different diffusion coefficients along each candidate direction of growth. Our study extends this concept by fully exploiting the proportions of white and gray matter extracted by normal brain atlases, rather than discretizing diffusion coefficients. Moreover, the proportions of white and gray matter, as well as the diffusion tensors, are extracted by the respective atlases; thus, no DTI processing is needed. Finally, we applied this novel glioma growth model on real data and the results indicate that prognostication rates can be improved. © 2012 IEEE
Intensity ratio to improve black hole assessment in multiple sclerosis.
Adusumilli, Gautam; Trinkaus, Kathryn; Sun, Peng; Lancia, Samantha; Viox, Jeffrey D; Wen, Jie; Naismith, Robert T; Cross, Anne H
2018-01-01
Improved imaging methods are critical to assess neurodegeneration and remyelination in multiple sclerosis. Chronic hypointensities observed on T1-weighted brain MRI, "persistent black holes," reflect severe focal tissue damage. Present measures consist of determining persistent black holes numbers and volumes, but do not quantitate severity of individual lesions. Develop a method to differentiate black and gray holes and estimate the severity of individual multiple sclerosis lesions using standard magnetic resonance imaging. 38 multiple sclerosis patients contributed images. Intensities of lesions on T1-weighted scans were assessed relative to cerebrospinal fluid intensity using commercial software. Magnetization transfer imaging, diffusion tensor imaging and clinical testing were performed to assess associations with T1w intensity-based measures. Intensity-based assessments of T1w hypointensities were reproducible and achieved > 90% concordance with expert rater determinations of "black" and "gray" holes. Intensity ratio values correlated with magnetization transfer ratios (R = 0.473) and diffusion tensor imaging metrics (R values ranging from 0.283 to -0.531) that have been associated with demyelination and axon loss. Intensity ratio values incorporated into T1w hypointensity volumes correlated with clinical measures of cognition. This method of determining the degree of hypointensity within multiple sclerosis lesions can add information to conventional imaging. Copyright © 2017 Elsevier B.V. All rights reserved.
Quantum-metric contribution to the pair mass in spin-orbit-coupled Fermi superfluids
NASA Astrophysics Data System (ADS)
Iskin, M.
2018-03-01
As a measure of the quantum distance between Bloch states in the Hilbert space, the quantum metric was introduced to solid-state physics through the real part of the so-called geometric Fubini-Study tensor, the imaginary part of which corresponds to the Berry curvature measuring the emergent gauge field in momentum space. Here, we first derive the Ginzburg-Landau theory near the critical superfluid transition temperature and then identify and analyze the geometric effects on the effective mass tensor of the Cooper pairs. By showing that the quantum-metric contribution accounts for a sizable fraction of the pair mass in a surprisingly large parameter regime throughout the BCS-Bose-Einstein condensate crossover, we not only reveal the physical origin of its governing role in the superfluid density tensor but also hint at its plausible roles in many other observables.
Quasi-topological Ricci polynomial gravities
NASA Astrophysics Data System (ADS)
Li, Yue-Zhou; Liu, Hai-Shan; Lü, H.
2018-02-01
Quasi-topological terms in gravity can be viewed as those that give no contribution to the equations of motion for a special subclass of metric ansätze. They therefore play no rôle in constructing these solutions, but can affect the general perturbations. We consider Einstein gravity extended with Ricci tensor polynomial invariants, which admits Einstein metrics with appropriate effective cosmological constants as its vacuum solutions. We construct three types of quasi-topological gravities. The first type is for the most general static metrics with spherical, toroidal or hyperbolic isometries. The second type is for the special static metrics where g tt g rr is constant. The third type is the linearized quasitopological gravities on the Einstein metrics. We construct and classify results that are either dependent on or independent of dimensions, up to the tenth order. We then consider a subset of these three types and obtain Lovelock-like quasi-topological gravities, that are independent of the dimensions. The linearized gravities on Einstein metrics on all dimensions are simply Einstein and hence ghost free. The theories become quasi-topological on static metrics in one specific dimension, but non-trivial in others. We also focus on the quasi-topological Ricci cubic invariant in four dimensions as a specific example to study its effect on holography, including shear viscosity, thermoelectric DC conductivities and butterfly velocity. In particular, we find that the holographic diffusivity bounds can be violated by the quasi-topological terms, which can induce an extra massive mode that yields a butterfly velocity unbound above.
Euclidean supersymmetric solutions with the self-dual Weyl tensor
NASA Astrophysics Data System (ADS)
Nozawa, Masato
2017-07-01
We explore the Euclidean supersymmetric solutions admitting the self-dual gauge field in the framework of N = 2 minimal gauged supergravity in four dimensions. According to the classification scheme utilizing the spinorial geometry or the bilinears of Killing spinors, the general solution preserves one quarter of supersymmetry and is described by the Przanowski-Tod class with the self-dual Weyl tensor. We demonstrate that there exists an additional Killing spinor, provided the Przanowski-Tod metric admits a Killing vector that commutes with the principal one. The proof proceeds by recasting the metric into another Przanowski-Tod form. This formalism enables us to show that the self-dual Reissner-Nordström-Taub-NUT-AdS metric possesses a second Killing spinor, which has been missed over many years. We also address the supersymmetry when the Przanowski-Tod space is conformal to each of the self-dual ambi-toric Kähler metrics. It turns out that three classes of solutions are all reduced to the self-dual Carter family, by virtue of the nondegenerate Killing-Yano tensor.
NASA Astrophysics Data System (ADS)
Popławski, Nikodem
2014-01-01
We propose a theory of gravitation, in which the affine connection is the only dynamical variable describing the gravitational field. We construct a simple dynamical Lagrangian density that is entirely composed from the connection, via its curvature and torsion, and is a polynomial function of its derivatives. It is given by the contraction of the Ricci tensor with a tensor which is inverse to the symmetric, contracted square of the torsion tensor, . We vary the total action for the gravitational field and matter with respect to the affine connection, assuming that the matter fields couple to the connection only through . We derive the resulting field equations and show that they are identical with the Einstein equations of general relativity with a nonzero cosmological constant if the tensor is regarded as proportional to the metric tensor. The cosmological constant is simply a constant of proportionality between the two tensors, which together with and provides a natural system of units in gravitational physics. This theory therefore provides a physical construction of the metric as a polynomial function of the connection, and explains dark energy as an intrinsic property of spacetime.
Gui, Minzhi; Tamhane, Ashish A; Arfanakis, Konstantinos
2008-05-01
To assess the effects of cardiac-induced brain pulsation on the noise of the diffusion tensor in Turboprop (a form of periodically rotated overlapping parallel lines with enhanced reconstruction [PROPELLER] imaging) diffusion tensor imaging (DTI). A total of six healthy human subjects were imaged with cardiac-gated as well as nongated Turboprop DTI. Gated and nongated Turboprop DTI datasets were also simulated using actual data acquired exclusively during the diastolic or systolic period of the cardiac cycle. The total variance of the diffusion tensor (TVDT) was measured and compared between acquisitions. The TVDT near the ventricles was significantly reduced in cardiac-gated compared to nongated Turboprop DTI acquisitions. Furthermore, the effects of brain pulsation were reduced, but not eliminated, when increasing the amount of data collected. Finally, data corrupted by cardiac-induced pulsation were not consistently detected by the step of the conventional Turboprop reconstruction algorithm that evaluates the quality of data in different blades. Thus, the inherent quality weighting of the conventional Turboprop reconstruction algorithm was unable to compensate for the increased noise in the diffusion tensor due to brain pulsation. Cardiac-induced brain pulsation increases the TVDT in Turboprop DTI. Use of cardiac gating to limit data acquisition to the diastolic period of the cardiac cycle reduces the TVDT at the expense of imaging time. (c) 2008 Wiley-Liss, Inc.
Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging
Reishofer, Gernot; Koschutnig, Karl; Langkammer, Christian; Porter, David; Jehna, Margit; Enzinger, Christian; Keeling, Stephen; Ebner, Franz
2013-01-01
Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min) generates results comparable to the un-regularized data with three averages (48 min). This significant reduction in scan time renders high resolution (1×1×2.5 mm3) diffusion tensor imaging of the entire brain applicable in a clinical context. PMID:24019951
A simple test for spacetime symmetry
NASA Astrophysics Data System (ADS)
Houri, Tsuyoshi; Yasui, Yukinori
2015-03-01
This paper presents a simple method for investigating spacetime symmetry for a given metric. The method makes use of the curvature conditions that are obtained from the Killing equations. We use the solutions of the curvature conditions to compute an upper bound on the number of Killing vector fields, as well as Killing-Yano (KY) tensors and closed conformal KY tensors. We also use them in the integration of the Killing equations. By means of the method, we thoroughly investigate KY symmetry of type D vacuum solutions such as the Kerr metric in four dimensions. The method is also applied to a large variety of physical metrics in four and five dimensions.
On the initial conditions of scalar and tensor fluctuations in f(R,φ ) gravity
NASA Astrophysics Data System (ADS)
Cheraghchi, S.; Shojai, F.
2018-05-01
We have considered the perturbation equations governing the growth of fluctuations during inflation in generalized scalar tensor theory f(R,φ ). We have found that the scalar metric perturbations at very early times are negligible compared to the scalar field perturbation, just like general relativity. At sufficiently early times, when the physical momentum of perturbation mode, q / a is much larger than the Hubble parameter H, i.e. q/a≫ H, we have obtained the metric and scalar field perturbation in the form of WKB solutions up to an undetermined coefficient. Then we have quantized the scalar fluctuations and expanded the metric and the scalar field perturbations with the help of annihilation and creation operators of the scalar field perturbation. The standard commutation relations of annihilation and creation operators fix the unknown coefficient. Going over to the gauge invariant quantities which are conserved beyond the horizon, we have obtained the initial condition of the generalized Mukhanov-Sasaki equation. Then a similar procedure is performed for the case of tensor metric perturbation. As an example of the generalized Mukhanov-Sasaki equation and its initial condition, we have proposed a power-law functional form as f(R,φ )=f_0 R^m φ ^n and obtained an exact inflationary solution. In this background, then we have discussed how the scalar and tensor fluctuations grow.
Comparison of scalar measures used in magnetic resonance diffusion tensor imaging.
Bahn, M M
1999-07-01
The tensors derived from diffusion tensor imaging describe complex diffusion in tissues. However, it is difficult to compare tensors directly or to produce images that contain all of the information of the tensor. Therefore, it is convenient to produce scalar measures that extract desired aspects of the tensor. These measures map the three-dimensional eigenvalues of the diffusion tensor into scalar values. The measures impose an order on eigenvalue space. Many invariant scalar measures have been introduced in the literature. In the present manuscript, a general approach for producing invariant scalar measures is introduced. Because it is often difficult to determine in clinical practice which of the many measures is best to apply to a given situation, two formalisms are introduced for the presentation, definition, and comparison of measures applied to eigenvalues: (1) normalized eigenvalue space, and (2) parametric eigenvalue transformation plots. All of the anisotropy information contained in the three eigenvalues can be retained and displayed in a two-dimensional plot, the normalized eigenvalue plot. An example is given of how to determine the best measure to use for a given situation by superimposing isometric contour lines from various anisotropy measures on plots of actual measured eigenvalue data points. Parametric eigenvalue transformation plots allow comparison of how different measures impose order on normalized eigenvalue space to determine whether the measures are equivalent and how the measures differ. These formalisms facilitate the comparison of scalar invariant measures for diffusion tensor imaging. Normalized eigenvalue space allows presentation of eigenvalue anisotropy information. Copyright 1999 Academic Press.
Basic concepts of MR imaging, diffusion MR imaging, and diffusion tensor imaging.
de Figueiredo, Eduardo H M S G; Borgonovi, Arthur F N G; Doring, Thomas M
2011-02-01
MR image contrast is based on intrinsic tissue properties and specific pulse sequences and parameter adjustments. A growing number of MRI imaging applications are based on diffusion properties of water. To better understand MRI diffusion-weighted imaging, a brief overview of MR physics is presented in this article followed by physics of the evolving techniques of diffusion MR imaging and diffusion tensor imaging. Copyright © 2011. Published by Elsevier Inc.
Diffusion Tensor Magnetic Resonance Imaging Strategies for Color Mapping of Human Brain Anatomy
Boujraf, Saïd
2018-01-01
Background: A color mapping of fiber tract orientation using diffusion tensor imaging (DTI) can be prominent in clinical practice. The goal of this paper is to perform a comparative study of visualized diffusion anisotropy in the human brain anatomical entities using three different color-mapping techniques based on diffusion-weighted imaging (DWI) and DTI. Methods: The first technique is based on calculating a color map from DWIs measured in three perpendicular directions. The second technique is based on eigenvalues derived from the diffusion tensor. The last technique is based on three eigenvectors corresponding to sorted eigenvalues derived from the diffusion tensor. All magnetic resonance imaging measurements were achieved using a 1.5 Tesla Siemens Vision whole body imaging system. A single-shot DW echoplanar imaging sequence used a Stejskal–Tanner approach. Trapezoidal diffusion gradients are used. The slice orientation was transverse. The basic measurement yielded a set of 13 images. Each series consists of a single image without diffusion weighting, besides two DWIs for each of the next six noncollinear magnetic field gradient directions. Results: The three types of color maps were calculated consequently using the DWI obtained and the DTI. Indeed, we established an excellent similarity between the image data in the color maps and the fiber directions of known anatomical structures (e.g., corpus callosum and gray matter). Conclusions: In the meantime, rotationally invariant quantities such as the eigenvectors of the diffusion tensor reflected better, the real orientation found in the studied tissue. PMID:29928631
Geometrical relationship for the Einstein and Ricci tensors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sida, D.W.
1976-08-01
Components of the Ricci and Einstein tensors are expressed in terms of the Gaussian curvatures of elementary two-spaces formed by the orthogonal coordinate planes, and the results are applied to some standard metrics.
A Mass Diffusion Model for Dry Snow Utilizing a Fabric Tensor to Characterize Anisotropy
NASA Astrophysics Data System (ADS)
Shertzer, Richard H.; Adams, Edward E.
2018-03-01
A homogenization algorithm for randomly distributed microstructures is applied to develop a mass diffusion model for dry snow. Homogenization is a multiscale approach linking constituent behavior at the microscopic level—among ice and air—to the macroscopic material—snow. Principles of continuum mechanics at the microscopic scale describe water vapor diffusion across an ice grain's surface to the air-filled pore space. Volume averaging and a localization assumption scale up and down, respectively, between microscopic and macroscopic scales. The model yields a mass diffusivity expression at the macroscopic scale that is, in general, a second-order tensor parameterized by both bulk and microstructural variables. The model predicts a mass diffusivity of water vapor through snow that is less than that through air. Mass diffusivity is expected to decrease linearly with ice volume fraction. Potential anisotropy in snow's mass diffusivity is captured due to the tensor representation. The tensor is built from directional data assigned to specific, idealized microstructural features. Such anisotropy has been observed in the field and laboratories in snow morphologies of interest such as weak layers of depth hoar and near-surface facets.
Tensor hypercontraction. II. Least-squares renormalization
NASA Astrophysics Data System (ADS)
Parrish, Robert M.; Hohenstein, Edward G.; Martínez, Todd J.; Sherrill, C. David
2012-12-01
The least-squares tensor hypercontraction (LS-THC) representation for the electron repulsion integral (ERI) tensor is presented. Recently, we developed the generic tensor hypercontraction (THC) ansatz, which represents the fourth-order ERI tensor as a product of five second-order tensors [E. G. Hohenstein, R. M. Parrish, and T. J. Martínez, J. Chem. Phys. 137, 044103 (2012)], 10.1063/1.4732310. Our initial algorithm for the generation of the THC factors involved a two-sided invocation of overlap-metric density fitting, followed by a PARAFAC decomposition, and is denoted PARAFAC tensor hypercontraction (PF-THC). LS-THC supersedes PF-THC by producing the THC factors through a least-squares renormalization of a spatial quadrature over the otherwise singular 1/r12 operator. Remarkably, an analytical and simple formula for the LS-THC factors exists. Using this formula, the factors may be generated with O(N^5) effort if exact integrals are decomposed, or O(N^4) effort if the decomposition is applied to density-fitted integrals, using any choice of density fitting metric. The accuracy of LS-THC is explored for a range of systems using both conventional and density-fitted integrals in the context of MP2. The grid fitting error is found to be negligible even for extremely sparse spatial quadrature grids. For the case of density-fitted integrals, the additional error incurred by the grid fitting step is generally markedly smaller than the underlying Coulomb-metric density fitting error. The present results, coupled with our previously published factorizations of MP2 and MP3, provide an efficient, robust O(N^4) approach to both methods. Moreover, LS-THC is generally applicable to many other methods in quantum chemistry.
Tensor hypercontraction. II. Least-squares renormalization.
Parrish, Robert M; Hohenstein, Edward G; Martínez, Todd J; Sherrill, C David
2012-12-14
The least-squares tensor hypercontraction (LS-THC) representation for the electron repulsion integral (ERI) tensor is presented. Recently, we developed the generic tensor hypercontraction (THC) ansatz, which represents the fourth-order ERI tensor as a product of five second-order tensors [E. G. Hohenstein, R. M. Parrish, and T. J. Martínez, J. Chem. Phys. 137, 044103 (2012)]. Our initial algorithm for the generation of the THC factors involved a two-sided invocation of overlap-metric density fitting, followed by a PARAFAC decomposition, and is denoted PARAFAC tensor hypercontraction (PF-THC). LS-THC supersedes PF-THC by producing the THC factors through a least-squares renormalization of a spatial quadrature over the otherwise singular 1∕r(12) operator. Remarkably, an analytical and simple formula for the LS-THC factors exists. Using this formula, the factors may be generated with O(N(5)) effort if exact integrals are decomposed, or O(N(4)) effort if the decomposition is applied to density-fitted integrals, using any choice of density fitting metric. The accuracy of LS-THC is explored for a range of systems using both conventional and density-fitted integrals in the context of MP2. The grid fitting error is found to be negligible even for extremely sparse spatial quadrature grids. For the case of density-fitted integrals, the additional error incurred by the grid fitting step is generally markedly smaller than the underlying Coulomb-metric density fitting error. The present results, coupled with our previously published factorizations of MP2 and MP3, provide an efficient, robust O(N(4)) approach to both methods. Moreover, LS-THC is generally applicable to many other methods in quantum chemistry.
Exact example of backreaction of small scale inhomogeneities in cosmology
NASA Astrophysics Data System (ADS)
Green, Stephen; Wald, Robert
2013-04-01
We construct a one-parameter family of polarized vacuum Gowdy spacetimes on a torus. In the limit as the parameter N goes to infinity, the metric uniformly approaches a smooth ``background metric.'' However, spacetime derivatives of the metric do not approach a limit. As a result, we find that the background metric itself is not a solution of the vacuum Einstein equation. Rather, it is a solution of the Einstein equation with an ``effective stress-energy tensor,'' which is traceless and satisfies the weak energy condition. This is an explicit example of backreaction due to small scale inhomogeneities. We comment on the non-vacuum case, where we have proven in previous work that, provided the matter stress-energy tensor satisfies the weak energy condition, no additional backreaction is possible.
NASA Astrophysics Data System (ADS)
Batista, Carlos
2015-04-01
The integrability conditions for the existence of Killing-Yano tensors or, equivalently, covariantly closed conformal Killing-Yano tensors, in the presence of torsion are worked out. As an application, all metrics and torsions compatible with the existence of a Killing-Yano tensor of order n -1 are obtained. Finally, the issue of defining a maximally symmetric space with respect to connections with torsion is addressed.
Diffusion tensor optical coherence tomography
NASA Astrophysics Data System (ADS)
Marks, Daniel L.; Blackmon, Richard L.; Oldenburg, Amy L.
2018-01-01
In situ measurements of diffusive particle transport provide insight into tissue architecture, drug delivery, and cellular function. Analogous to diffusion-tensor magnetic resonance imaging (DT-MRI), where the anisotropic diffusion of water molecules is mapped on the millimeter scale to elucidate the fibrous structure of tissue, here we propose diffusion-tensor optical coherence tomography (DT-OCT) for measuring directional diffusivity and flow of optically scattering particles within tissue. Because DT-OCT is sensitive to the sub-resolution motion of Brownian particles as they are constrained by tissue macromolecules, it has the potential to quantify nanoporous anisotropic tissue structure at micrometer resolution as relevant to extracellular matrices, neurons, and capillaries. Here we derive the principles of DT-OCT, relating the detected optical signal from a minimum of six probe beams with the six unique diffusion tensor and three flow vector components. The optimal geometry of the probe beams is determined given a finite numerical aperture, and a high-speed hardware implementation is proposed. Finally, Monte Carlo simulations are employed to assess the ability of the proposed DT-OCT system to quantify anisotropic diffusion of nanoparticles in a collagen matrix, an extracellular constituent that is known to become highly aligned during tumor development.
Tarumi, Takashi; de Jong, Daan L.K.; Zhu, David C.; Tseng, Benjamin Y.; Liu, Jie; Hill, Candace; Riley, Jonathan; Womack, Kyle B.; Kerwin, Diana R.; Lu, Hanzhang; Cullum, C. Munro; Zhang, Rong
2015-01-01
Cerebral hypoperfusion elevates the risk of brain white matter (WM) lesions and cognitive impairment. Central artery stiffness impairs baroreflex, which controls systemic arterial perfusion, and may deteriorate neuronal fiber integrity of brain WM. The purpose of this study was to examine the associations among brain WM neuronal fiber integrity, baroreflex sensitivity (BRS), and central artery stiffness in older adults. Fifty-four adults (65±6 years) with normal cognitive function or mild cognitive impairment (MCI) were tested. The neuronal fiber integrity of brain WM was assessed from diffusion metrics acquired by diffusion tensor imaging. BRS was measured in response to acute changes in blood pressure induced by bolus injections of vasoactive drugs. Central artery stiffness was measured by carotid-femoral pulse wave velocity (cfPWV). The WM diffusion metrics including fractional anisotropy (FA) and radial (RD) and axial (AD) diffusivities, BRS, and cfPWV were not different between the control and MCI groups. Thus, the data from both groups were combined for subsequent analyses. Across WM, fiber tracts with decreased FA and increased RD were associated with lower BRS and higher cfPWV, with many of the areas presenting spatial overlap. In particular, the BRS assessed during hypotension was strongly correlated with FA and RD when compared with hypertension. Executive function performance was associated with FA and RD in the areas that correlated with cfPWV and BRS. These findings suggest that baroreflex-mediated control of systemic arterial perfusion, especially during hypotension, may play a crucial role in maintaining neuronal fiber integrity of brain WM in older adults. PMID:25623500
Xue, Zhong; Li, Hai; Guo, Lei; Wong, Stephen T.C.
2010-01-01
It is a key step to spatially align diffusion tensor images (DTI) to quantitatively compare neural images obtained from different subjects or the same subject at different timepoints. Different from traditional scalar or multi-channel image registration methods, tensor orientation should be considered in DTI registration. Recently, several DTI registration methods have been proposed in the literature, but deformation fields are purely dependent on the tensor features not the whole tensor information. Other methods, such as the piece-wise affine transformation and the diffeomorphic non-linear registration algorithms, use analytical gradients of the registration objective functions by simultaneously considering the reorientation and deformation of tensors during the registration. However, only relatively local tensor information such as voxel-wise tensor-similarity, is utilized. This paper proposes a new DTI image registration algorithm, called local fast marching (FM)-based simultaneous registration. The algorithm not only considers the orientation of tensors during registration but also utilizes the neighborhood tensor information of each voxel to drive the deformation, and such neighborhood tensor information is extracted from a local fast marching algorithm around the voxels of interest. These local fast marching-based tensor features efficiently reflect the diffusion patterns around each voxel within a spherical neighborhood and can capture relatively distinctive features of the anatomical structures. Using simulated and real DTI human brain data the experimental results show that the proposed algorithm is more accurate compared with the FA-based registration and is more efficient than its counterpart, the neighborhood tensor similarity-based registration. PMID:20382233
White matter degeneration in schizophrenia: a comparative diffusion tensor analysis
NASA Astrophysics Data System (ADS)
Ingalhalikar, Madhura A.; Andreasen, Nancy C.; Kim, Jinsuh; Alexander, Andrew L.; Magnotta, Vincent A.
2010-03-01
Schizophrenia is a serious and disabling mental disorder. Diffusion tensor imaging (DTI) studies performed on schizophrenia have demonstrated white matter degeneration either due to loss of myelination or deterioration of fiber tracts although the areas where the changes occur are variable across studies. Most of the population based studies analyze the changes in schizophrenia using scalar indices computed from the diffusion tensor such as fractional anisotropy (FA) and relative anisotropy (RA). The scalar measures may not capture the complete information from the diffusion tensor. In this paper we have applied the RADTI method on a group of 9 controls and 9 patients with schizophrenia. The RADTI method converts the tensors to log-Euclidean space where a linear regression model is applied and hypothesis testing is performed between the control and patient groups. Results show that there is a significant difference in the anisotropy between patients and controls especially in the parts of forceps minor, superior corona radiata, anterior limb of internal capsule and genu of corpus callosum. To check if the tensor analysis gives a better idea of the changes in anisotropy, we compared the results with voxelwise FA analysis as well as voxelwise geodesic anisotropy (GA) analysis.
Killing-Yano tensors of order n - 1
NASA Astrophysics Data System (ADS)
Batista, Carlos
2014-08-01
The properties of a Killing-Yano tensor of order n-1 in an n-dimensional manifold are investigated. The integrability conditions are worked out and all metrics admitting a Killing-Yano tensor of order n-1 are found. A connection between such tensors and a generalization of the concept of angular momentum is pointed out. A theorem on how to generate closed conformal Killing vectors using the symmetries of a manifold is proved and used to find all Killing-Yano tensors of order n-1 of a maximally symmetric space.
Computer Tensor Codes to Design the War Drive
NASA Astrophysics Data System (ADS)
Maccone, C.
To address problems in Breakthrough Propulsion Physics (BPP) and design the Warp Drive one needs sheer computing capabilities. This is because General Relativity (GR) and Quantum Field Theory (QFT) are so mathematically sophisticated that the amount of analytical calculations is prohibitive and one can hardly do all of them by hand. In this paper we make a comparative review of the main tensor calculus capabilities of the three most advanced and commercially available “symbolic manipulator” codes. We also point out that currently one faces such a variety of different conventions in tensor calculus that it is difficult or impossible to compare results obtained by different scholars in GR and QFT. Mathematical physicists, experimental physicists and engineers have each their own way of customizing tensors, especially by using different metric signatures, different metric determinant signs, different definitions of the basic Riemann and Ricci tensors, and by adopting different systems of physical units. This chaos greatly hampers progress toward the design of the Warp Drive. It is thus suggested that NASA would be a suitable organization to establish standards in symbolic tensor calculus and anyone working in BPP should adopt these standards. Alternatively other institutions, like CERN in Europe, might consider the challenge of starting the preliminary implementation of a Universal Tensor Code to design the Warp Drive.
Spacetimes with Killing tensors. [for Einstein-Maxwell fields with certain spinor indices
NASA Technical Reports Server (NTRS)
Hughston, L. P.; Sommers, P.
1973-01-01
The characteristics of the Killing equation and the Killing tensor are discussed. A conformal Killing tensor is of interest inasmuch as it gives rise to a quadratic first integral for null geodesic orbits. The Einstein-Maxwell equations are considered together with the Bianchi identity and the conformal Killing tensor. Two examples for the application of the considered relations are presented, giving attention to the charged Kerr solution and the charged C-metric.
Effects of motion and b-matrix correction for high resolution DTI with short-axis PROPELLER-EPI
Aksoy, Murat; Skare, Stefan; Holdsworth, Samantha; Bammer, Roland
2010-01-01
Short-axis PROPELLER-EPI (SAP-EPI) has been proven to be very effective in providing high-resolution diffusion-weighted and diffusion tensor data. The self-navigation capabilities of SAP-EPI allow one to correct for motion, phase errors, and geometric distortion. However, in the presence of patient motion, the change in the effective diffusion-encoding direction (i.e. the b-matrix) between successive PROPELLER ‘blades’ can decrease the accuracy of the estimated diffusion tensors, which might result in erroneous reconstruction of white matter tracts in the brain. In this study, we investigate the effects of alterations in the b-matrix as a result of patient motion on the example of SAP-EPI DTI and eliminate these effects by incorporating our novel single-step non-linear diffusion tensor estimation scheme into the SAP-EPI post-processing procedure. Our simulations and in-vivo studies showed that, in the presence of patient motion, correcting the b-matrix is necessary in order to get more accurate diffusion tensor and white matter pathway reconstructions. PMID:20222149
Anisotropic mesoscale eddy transport in ocean general circulation models
NASA Astrophysics Data System (ADS)
Reckinger, Scott; Fox-Kemper, Baylor; Bachman, Scott; Bryan, Frank; Dennis, John; Danabasoglu, Gokhan
2014-11-01
In modern climate models, the effects of oceanic mesoscale eddies are introduced by relating subgrid eddy fluxes to the resolved gradients of buoyancy or other tracers, where the proportionality is, in general, governed by an eddy transport tensor. The symmetric part of the tensor, which represents the diffusive effects of mesoscale eddies, is universally treated isotropically. However, the diffusive processes that the parameterization approximates, such as shear dispersion and potential vorticity barriers, typically have strongly anisotropic characteristics. Generalizing the eddy diffusivity tensor for anisotropy extends the number of parameters from one to three: major diffusivity, minor diffusivity, and alignment. The Community Earth System Model (CESM) with the anisotropic eddy parameterization is used to test various choices for the parameters, which are motivated by observations and the eddy transport tensor diagnosed from high resolution simulations. Simply setting the ratio of major to minor diffusivities to a value of five globally, while aligning the major axis along the flow direction, improves biogeochemical tracer ventilation and reduces temperature and salinity biases. These effects can be improved by parameterizing the oceanic anisotropic transport mechanisms.
NASA Astrophysics Data System (ADS)
Kaewkhao, Narakorn; Gumjudpai, Burin
2018-06-01
We consider, in Palatini formalism, a modified gravity of which the scalar field derivative couples to Einstein tensor. In this scenario, Ricci scalar, Ricci tensor and Einstein tensor are functions of connection field. As a result, the connection field gives rise to relation, hμν = fgμν between effective metric, hμν and the usual metric gμν where f = 1 - κϕ,αϕ,α / 2. In FLRW universe, NMDC coupling constant is limited in a range of - 2 /ϕ˙2 < κ ≤ ∞ preserving Lorentz signature of the effective metric. Slowly-rolling regime provides κ < 0 forbidding graviton from traveling at superluminal speed. Effective gravitational coupling and entropy of blackhole's apparent horizon are derived. In case of negative coupling, acceleration could happen even with weff > - 1 / 3. Power-law potentials of chaotic inflation are considered. For V ∝ϕ2 and V ∝ϕ4, it is possible to obtain tensor-to-scalar ratio lower than that of GR so that it satisfies r < 0 . 12 as constrained by Planck 2015 (Ade et al., 2016). The V ∝ϕ2 case yields acceptable range of spectrum index and r values. The quartic potential's spectrum index is disfavored by the Planck results. Viable range of κ for V ∝ϕ2 case lies in positive region, resulting in less blackhole's entropy, superluminal metric, more amount of inflation, avoidance of super-Planckian field initial value and stronger gravitational constant.
NASA Astrophysics Data System (ADS)
Li, Huicong; Wang, Xuefeng; Wu, Yanxia
2014-11-01
We consider the logistic diffusion equation on a bounded domain, which has two components with a thin coating surrounding a body. The diffusion tensor is isotropic on the body, and anisotropic on the coating. The size of the diffusion tensor on these components may be very different; within the coating, the diffusion rates in the normal and tangent directions may be in different scales. We find effective boundary conditions (EBCs) that are approximately satisfied by the solution of the diffusion equation on the boundary of the body. We also prove that the lifespan of each EBC, which measures how long the EBC remains effective, is infinite. The EBCs enable us to see clearly the effect of the coating and ease the difficult task of solving the PDE in a thin region with a small diffusion tensor. The motivation of the mathematics includes a nature reserve surrounded by a buffer zone.
NASA Astrophysics Data System (ADS)
Dufty, J. W.
1984-09-01
Diffusion of a tagged particle in a fluid with uniform shear flow is described. The continuity equation for the probability density describing the position of the tagged particle is considered. The diffusion tensor is identified by expanding the irreversible part of the probability current to first order in the gradient of the probability density, but with no restriction on the shear rate. The tensor is expressed as the time integral of a nonequilibrium autocorrelation function for the velocity of the tagged particle in its local fluid rest frame, generalizing the Green-Kubo expression to the nonequilibrium state. The tensor is evaluated from results obtained previously for the velocity autocorrelation function that are exact for Maxwell molecules in the Boltzmann limit. The effects of viscous heating are included and the dependence on frequency and shear rate is displayed explicitly. The mode-coupling contributions to the frequency and shear-rate dependent diffusion tensor are calculated.
Bauer, Isabelle E.; Ouyang, Austin; Mwangi, Benson; Sanches, Marsal; Zunta-Soares, Giovana B.; Keefe, Richard S. E.; Huang, Hao; Soares, Jair C.
2015-01-01
Background Clinical evidence shows that bipolar disorder (BD) is characterized by white matter (WM) microstructural abnormalities. However, little is known about the biological mechanisms associated with these abnormalities and their relationship with cognitive functioning. Methods 49 adult BD patients ((M±SD): 29.27 ± 7.92 years; 17 males, 32 females; 34 BD-I, 10 BD-II, and 5 BD-NOS) and 28 age-matched normal subjects ((M±SD): 29.19 ± 7.35 years; 10 males and 18 females) underwent diffusion tensor imaging (DTI) imaging. DTI metrics were computed using whole-brain tract-based spatial statistics (TBSS) as part of the FMRIB Software Library. Measures of WM coherence (fractional anisotropy - FA) and axonal structure (mean, axial and radial diffusivity - MD, AD and RD) were employed to characterize the microstructural alterations in the limbic, commissural, association and projection fiber tracts. All participants performed the Brief Assessment of Cognition for Affective disorders (BAC-A). Results BD patients performed poorly on verbal fluency tasks and exhibited large clusters of altered FA, RD and MD values within the retrolenticular part of the internal capsule, the superior and anterior corona radiata, and the corpus callosum. Increased FA values in the left IFOF and the forceps minor correlated positively with verbal fluency scores. Altered RD parameters in the corticospinal tract and the forceps minor were associated with reduced visuomotor abilities. Conclusions The reported verbal fluency deficits and FA, RD and MD alterations in WM structures are potential cognitive and neural markers of BD. Abnormal RD values may be associated with progressive demyelination. PMID:25684152
Jirjis, Michael B; Valdez, Chris; Vedantam, Aditya; Schmit, Brian D; Kurpad, Shekar N
2017-02-01
OBJECTIVE The aims of this study were to determine if the morphological and functional changes induced by neural stem cell (NSC) grafts after transplantation into the rodent spinal cord can be detected using MR diffusion tensor imaging (DTI) and, furthermore, if the DTI-derived mean diffusivity (MD) metric could be a biomarker for cell transplantation in spinal cord injury (SCI). METHODS A spinal contusion was produced at the T-8 vertebral level in 40 Sprague Dawley rats that were separated into 4 groups, including a sham group (injury without NSC injection), NSC control group (injury with saline injection), co-injection control group (injury with Prograf), and the experimental group (injury with NSC and Prograf injection). The NSC injection was completed 1 week after injury into the site of injury and the rats in the experimental group were compared to the rats from the sham, NSC control, and co-injection groups. The DTI index, MD, was assessed in vivo at 2, 5, and 10 weeks and ex vivo at 10 weeks postinjury on a 9.4-T Bruker scanner using a spin-echo imaging sequence. DTI data of the cervical spinal cord from the sham surgery, injury with saline injection, injury with injection of Prograf only, and injury with C17.2 NSC and Prograf injection were examined to evaluate if cellular proliferation induced by intrathoracic C17.2 engraftment was detectable in a noninvasive manner. RESULTS At 5 weeks after injury, the average fractional anisotropy, longitudinal diffusion (LD) and radial diffusion (RD) coefficients, and MD of water (average of the RD and LD eigenvalues in the stem cell line-treated group) increased to an average of 1.44 × 10 -3 sec/mm 2 in the cervical segments, while the control groups averaged 0.98 × 10 -3 s/mm 2 . Post hoc Tukey's honest significant difference tests demonstrated that the transplanted stem cells had significantly higher MD values than the other groups (p = 0.032 at 5 weeks). In vivo and ex vivo findings at 10 weeks displayed similar results. This statistical difference between the stem cell line and the other groups was maintained at the 10-week postinjury in vivo and ex vivo time points. CONCLUSIONS These results indicate that the DTI-derived MD metric collected from noninvasive imaging techniques may provide useful biomarker indices for transplantation interventions that produce changes in the spinal cord structure and function. Though promising, the results demonstrated here suggest additional work is needed before implementation in a clinical setting.
Ryabov, Yaroslav; Fushman, David
2008-01-01
We present a simple and robust approach that uses the overall rotational diffusion tensor as a structural constraint for domain positioning in multidomain proteins and protein-protein complexes. This method offers the possibility to use NMR relaxation data for detailed structure characterization of such systems provided the structures of individual domains are available. The proposed approach extends the concept of using long-range information contained in the overall rotational diffusion tensor. In contrast to the existing approaches, we use both the principal axes and principal values of protein’s rotational diffusion tensor to determine not only the orientation but also the relative positioning of the individual domains in a protein. This is achieved by finding the domain arrangement in a molecule that provides the best possible agreement with all components of the overall rotational diffusion tensor derived from experimental data. The accuracy of the proposed approach is demonstrated for two protein systems with known domain arrangement and parameters of the overall tumbling: the HIV-1 protease homodimer and Maltose Binding Protein. The accuracy of the method and its sensitivity to domain positioning is also tested using computer-generated data for three protein complexes, for which the experimental diffusion tensors are not available. In addition, the proposed method is applied here to determine, for the first time, the structure of both open and closed conformations of Lys48-linked di-ubiquitin chain, where domain motions render impossible accurate structure determination by other methods. The proposed method opens new avenues for improving structure characterization of proteins in solution. PMID:17550252
1987-03-01
would be transcribed as L =AX - V where L, X, and V are the vectors of constant terms, parametric corrections , and b_o bresiduals, respectively. The...tensor. a Just as du’ represents the parametric corrections in tensor notations, the necessary associated metric tensor a’ corresponds to the variance...observations, n residuals, and 0 n- parametric corrections to X (an initial set of parameters), respectively. b 0 b The vctor L is formed as 1. L where
Renormalization of the diffusion tensor for high-frequency, electromagnetic modes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Litwin, C.; Sudan, R.N.
The resonance broadening theory is used to derive the diffusion tensor for resonant particles in a spectrum of electromagnetic modes propagating parallel to the magnetic field. The magnetic trapping limit for saturation of wave amplitudes is discussed.
Diffusion Tensor Imaging: Application to the Study of the Developing Brain
ERIC Educational Resources Information Center
Cascio, Carissa J.; Gerig, Guido; Piven, Joseph
2007-01-01
Objective: To provide an overview of diffusion tensor imaging (DTI) and its application to the study of white matter in the developing brain in both healthy and clinical samples. Method: The development of DTI and its application to brain imaging of white matter tracts is discussed. Forty-eight studies using DTI to examine diffusion properties of…
Van Hecke, Wim; Sijbers, Jan; De Backer, Steve; Poot, Dirk; Parizel, Paul M; Leemans, Alexander
2009-07-01
Although many studies are starting to use voxel-based analysis (VBA) methods to compare diffusion tensor images between healthy and diseased subjects, it has been demonstrated that VBA results depend heavily on parameter settings and implementation strategies, such as the applied coregistration technique, smoothing kernel width, statistical analysis, etc. In order to investigate the effect of different parameter settings and implementations on the accuracy and precision of the VBA results quantitatively, ground truth knowledge regarding the underlying microstructural alterations is required. To address the lack of such a gold standard, simulated diffusion tensor data sets are developed, which can model an array of anomalies in the diffusion properties of a predefined location. These data sets can be employed to evaluate the numerous parameters that characterize the pipeline of a VBA algorithm and to compare the accuracy, precision, and reproducibility of different post-processing approaches quantitatively. We are convinced that the use of these simulated data sets can improve the understanding of how different diffusion tensor image post-processing techniques affect the outcome of VBA. In turn, this may possibly lead to a more standardized and reliable evaluation of diffusion tensor data sets of large study groups with a wide range of white matter altering pathologies. The simulated DTI data sets will be made available online (http://www.dti.ua.ac.be).
Whitaker, Kirstie J; Kang, Xiaojian; Herron, Timothy J; Woods, David L; Robertson, Lynn C; Alvarez, Bryan D
2014-04-15
In this study we show, for the first time, a correlation between the neuroanatomy of the synesthetic brain and a metric that measures behavior not exclusive to the synesthetic experience. Grapheme-color synesthetes (n=20), who experience colors triggered by viewing or thinking of specific letters or numbers, showed altered white matter microstructure, as measured using diffusion tensor imaging, compared with carefully matched non-synesthetic controls. Synesthetes had lower fractional anisotropy and higher perpendicular diffusivity when compared to non-synesthetic controls. An analysis of the mode of anisotropy suggested that these differences were likely due to the presence of more crossing pathways in the brains of synesthetes. Additionally, these differences in white matter microstructure correlated negatively, and only for synesthetes, with a measure of the vividness of their visual imagery. Synesthetes who reported the most vivid visual imagery had the lowest fractional anisotropy and highest perpendicular diffusivity. We conclude that synesthetes as a population vary along a continuum while showing categorical differences in neuroanatomy and behavior compared to non-synesthetes. Copyright © 2013 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Ivanov, A. N.; Wellenzohn, M.
2016-09-01
We analyse the Einstein-Cartan gravity in its standard form { R }=R+{{ K }}2, where { R } {and} R are the Ricci scalar curvatures in the Einstein-Cartan and Einstein gravity, respectively, and {{ K }}2 is the quadratic contribution of torsion in terms of the contorsion tensor { K }. We treat torsion as an external (or background) field and show that its contribution to the Einstein equations can be interpreted in terms of the torsion energy-momentum tensor, local conservation of which in a curved spacetime with an arbitrary metric or an arbitrary gravitational field demands a proportionality of the torsion energy-momentum tensor to a metric tensor, a covariant derivative of which vanishes owing to the metricity condition. This allows us to claim that torsion can serve as an origin for the vacuum energy density, given by the cosmological constant or dark energy density in the universe. This is a model-independent result that may explain the small value of the cosmological constant, which is a long-standing problem in cosmology. We show that the obtained result is valid also in the Poincaré gauge gravitational theory of Kibble, where the Einstein-Hilbert action can be represented in the same form: { R }=R+{{ K }}2.
APPROXIMATING SYMMETRIC POSITIVE SEMIDEFINITE TENSORS OF EVEN ORDER*
BARMPOUTIS, ANGELOS; JEFFREY, HO; VEMURI, BABA C.
2012-01-01
Tensors of various orders can be used for modeling physical quantities such as strain and diffusion as well as curvature and other quantities of geometric origin. Depending on the physical properties of the modeled quantity, the estimated tensors are often required to satisfy the positivity constraint, which can be satisfied only with tensors of even order. Although the space P02m of 2mth-order symmetric positive semi-definite tensors is known to be a convex cone, enforcing positivity constraint directly on P02m is usually not straightforward computationally because there is no known analytic description of P02m for m > 1. In this paper, we propose a novel approach for enforcing the positivity constraint on even-order tensors by approximating the cone P02m for the cases 0 < m < 3, and presenting an explicit characterization of the approximation Σ2m ⊂ Ω2m for m ≥ 1, using the subset Ω2m⊂P02m of semi-definite tensors that can be written as a sum of squares of tensors of order m. Furthermore, we show that this approximation leads to a non-negative linear least-squares (NNLS) optimization problem with the complexity that equals the number of generators in Σ2m. Finally, we experimentally validate the proposed approach and we present an application for computing 2mth-order diffusion tensors from Diffusion Weighted Magnetic Resonance Images. PMID:23285313
White matter structure in loneliness: preliminary findings from diffusion tensor imaging.
Tian, Yin; Liang, Shanshan; Yuan, Zhen; Chen, Sifan; Xu, Peng; Yao, Dezhong
2014-08-06
A pilot study was carried out to determine individual differences in perceived loneliness using diffusion tensor imaging. To the best of our knowledge, this is the first preliminary diffusion tensor imaging evidence that the ventral attention network, generally activated by attentional reorienting, was also related to loneliness. Image reconstruction results indicated significantly decreased fractional anisotropy of white matter fibers and that associated nodes of the ventral attention network are highly correlated with increased loneliness ratings. By providing evidence on the structural level, our findings suggested that attention-reorienting capabilities play an important role in shaping an individual's loneliness.
Gravitational waves during inflation from a 5D large-scale repulsive gravity model
NASA Astrophysics Data System (ADS)
Reyes, Luz M.; Moreno, Claudia; Madriz Aguilar, José Edgar; Bellini, Mauricio
2012-10-01
We investigate, in the transverse traceless (TT) gauge, the generation of the relic background of gravitational waves, generated during the early inflationary stage, on the framework of a large-scale repulsive gravity model. We calculate the spectrum of the tensor metric fluctuations of an effective 4D Schwarzschild-de Sitter metric on cosmological scales. This metric is obtained after implementing a planar coordinate transformation on a 5D Ricci-flat metric solution, in the context of a non-compact Kaluza-Klein theory of gravity. We found that the spectrum is nearly scale invariant under certain conditions. One interesting aspect of this model is that it is possible to derive the dynamical field equations for the tensor metric fluctuations, valid not just at cosmological scales, but also at astrophysical scales, from the same theoretical model. The astrophysical and cosmological scales are determined by the gravity-antigravity radius, which is a natural length scale of the model, that indicates when gravity becomes repulsive in nature.
Henry, Roland G; Berman, Jeffrey I; Nagarajan, Srikantan S; Mukherjee, Pratik; Berger, Mitchel S
2004-02-01
The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain.
Henry, Roland G.; Berman, Jeffrey I.; Nagarajan, Srikantan S.; Mukherjee, Pratik; Berger, Mitchel S.
2014-01-01
The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain. PMID:14980564
Hidden symmetries on Kerr-NUT-(A)dS metrics of Einstein-Sasaki type
NASA Astrophysics Data System (ADS)
Visinescu, Mihai
2013-01-01
The hidden symmetries of higher dimensional Euclideanised Kerr-NUT-(A)dS metrics are investigated. In certain scaling limits these metrics are related to the Einstein-Sasaki ones. The complete set of Killing-Yano tensors of the Einstein-Sasaki spaces are presented. For this purpose the Killing forms of the Calabi-Yau cone over the Einstein-Sasaki manifold are constructed. Two new Killing forms on Einstein-Sasaki manifolds are identified associated with the complex volume form of the cone manifolds. As a concrete example we present the complete set of Killing-Yano tensors on the five-dimensional Einstein-Sasaki Y(p, q) spaces. The corresponding hidden symmetries are not anomalous and the geodesic equations are superintegrable.
An Exploration into Diffusion Tensor Imaging in the Bovine Ocular Lens
Vaghefi, Ehsan; Donaldson, Paul J.
2013-01-01
We describe our development of the diffusion tensor imaging modality for the bovine ocular lens. Diffusion gradients were added to a spin-echo pulse sequence and the relevant parameters of the sequence were refined to achieve good diffusion weighting in the lens tissue, which demonstrated heterogeneous regions of diffusive signal attenuation. Decay curves for b-value (loosely summarizes the strength of diffusion weighting) and TE (determines the amount of magnetic resonance imaging-obtained signal) were used to estimate apparent diffusion coefficients (ADC) and T2 in different lens regions. The ADCs varied by over an order of magnitude and revealed diffusive anisotropy in the lens. Up to 30 diffusion gradient directions, and 8 signal acquisition averages, were applied to lenses in culture in order to improve maps of diffusion tensor eigenvalues, equivalent to ADC, across the lens. From these maps, fractional anisotropy maps were calculated and compared to known spatial distributions of anisotropic molecular fluxes in the lens. This comparison suggested new hypotheses and experiments to quantitatively assess models of circulation in the avascular lens. PMID:23459990
Relativistic analysis of stochastic kinematics
NASA Astrophysics Data System (ADS)
Giona, Massimiliano
2017-10-01
The relativistic analysis of stochastic kinematics is developed in order to determine the transformation of the effective diffusivity tensor in inertial frames. Poisson-Kac stochastic processes are initially considered. For one-dimensional spatial models, the effective diffusion coefficient measured in a frame Σ moving with velocity w with respect to the rest frame of the stochastic process is inversely proportional to the third power of the Lorentz factor γ (w ) =(1-w2/c2) -1 /2 . Subsequently, higher-dimensional processes are analyzed and it is shown that the diffusivity tensor in a moving frame becomes nonisotropic: The diffusivities parallel and orthogonal to the velocity of the moving frame scale differently with respect to γ (w ) . The analysis of discrete space-time diffusion processes permits one to obtain a general transformation theory of the tensor diffusivity, confirmed by several different simulation experiments. Several implications of the theory are also addressed and discussed.
FLRW Cosmology from Yang-Mills Gravity
NASA Astrophysics Data System (ADS)
Katz, Daniel
2013-04-01
We extend to basic cosmology the subject of Yang-Mills gravity - a theory of gravity based on local translational gauge invariance in flat spacetime. It has been shown that this particular gauge invariance leads to tensor factors in the macroscopic limit of the equations of motion of particles which plays the same role as the metric tensor of General Relativity. The assumption that this ``effective metric" tensor takes on the standard FLRW form is our starting point. Equations analogous to the Friedman equations are derived and then solved in closed form for the three special cases of a universe dominated by 1) matter, 2) radiation, and 3) dark energy. We find that the solutions for the scale factor are similar to, but distinct from, those found in the corresponding GR based treatment.
Chen, Zhenrui; Tie, Yanmei; Olubiyi, Olutayo; Rigolo, Laura; Mehrtash, Alireza; Norton, Isaiah; Pasternak, Ofer; Rathi, Yogesh; Golby, Alexandra J; O'Donnell, Lauren J
2015-01-01
Diffusion imaging tractography is increasingly used to trace critical fiber tracts in brain tumor patients to reduce the risk of post-operative neurological deficit. However, the effects of peritumoral edema pose a challenge to conventional tractography using the standard diffusion tensor model. The aim of this study was to present a novel technique using a two-tensor unscented Kalman filter (UKF) algorithm to track the arcuate fasciculus (AF) in brain tumor patients with peritumoral edema. Ten right-handed patients with left-sided brain tumors in the vicinity of language-related cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-Tesla magnetic resonance imaging (MRI) including a diffusion-weighted dataset with 31 directions. Fiber tractography was performed using both single-tensor streamline and two-tensor UKF tractography. A two-regions-of-interest approach was applied to perform the delineation of the AF. Results from the two different tractography algorithms were compared visually and quantitatively. Using single-tensor streamline tractography, the AF appeared disrupted in four patients and contained few fibers in the remaining six patients. Two-tensor UKF tractography delineated an AF that traversed edematous brain areas in all patients. The volume of the AF was significantly larger on two-tensor UKF than on single-tensor streamline tractography (p < 0.01). Two-tensor UKF tractography provides the ability to trace a larger volume AF than single-tensor streamline tractography in the setting of peritumoral edema in brain tumor patients.
4.7-T diffusion tensor imaging of acute traumatic peripheral nerve injury
Boyer, Richard B.; Kelm, Nathaniel D.; Riley, D. Colton; Sexton, Kevin W.; Pollins, Alonda C.; Shack, R. Bruce; Dortch, Richard D.; Nanney, Lillian B.; Does, Mark D.; Thayer, Wesley P.
2015-01-01
Diagnosis and management of peripheral nerve injury is complicated by the inability to assess microstructural features of injured nerve fibers via clinical examination and electrophysiology. Diffusion tensor imaging (DTI) has been shown to accurately detect nerve injury and regeneration in crush models of peripheral nerve injury, but no prior studies have been conducted on nerve transection, a surgical emergency that can lead to permanent weakness or paralysis. Acute sciatic nerve injuries were performed microsurgically to produce multiple grades of nerve transection in rats that were harvested 1 hour after surgery. High-resolution diffusion tensor images from ex vivo sciatic nerves were obtained using diffusion-weighted spin-echo acquisitions at 4.7 T. Fractional anisotropy was significantly reduced at the injury sites of transected rats compared with sham rats. Additionally, minor eigenvalues and radial diffusivity were profoundly elevated at all injury sites and were negatively correlated to the degree of injury. Diffusion tensor tractography showed discontinuities at all injury sites and significantly reduced continuous tract counts. These findings demonstrate that high-resolution DTI is a promising tool for acute diagnosis and grading of traumatic peripheral nerve injuries. PMID:26323827
Wang, Po-Shan; Wu, Hsiu-Mei; Lin, Ching-Po; Soong, Bing-Wen
2011-07-01
We performed diffusion tensor imaging to determine if multiple system atrophy (MSA)-cerebellar (C) and MSA-Parkinsonism (P) show similar changes, as shown in pathological studies. Nineteen patients with MSA-C, 12 patients with MSA-P, 20 patients with Parkinson disease, and 20 healthy controls were evaluated with the use of voxel-based morphometry analysis of diffusion tensor imaging. There was an increase in apparent diffusion coefficient values in the middle cerebellar peduncles and cerebellum and a decrease in fractional anisotropy in the pyramidal tract, middle cerebellar peduncles, and white matter of the cerebellum in patients with MSA-C and MSA-P compared to the controls (P < 0.001). In addition, isotropic diffusion-weighted image values were reduced in the cerebellar cortex and deep cerebellar nuclei in patients with MSA-C and increased in the basal ganglia in patients with MSA-P. These results indicate that despite their disparate clinical manifestations, patients with MSA-C and MSA-P share similar diffusion tensor imaging features in the infratentorial region. Further, the combination of FA, ADC and iDWI images can be used to distinguish between MSA (either form) and Parkinson disease, which has potential therapeutic implications.
Vegas-Sanchez-Ferrero, G; Aja-Fernandez, S; Martin-Fernandez, M; Frangi, A F; Palencia, C
2010-01-01
A novel anisotropic diffusion filter is proposed in this work with application to cardiac ultrasonic images. It includes probabilistic models which describe the probability density function (PDF) of tissues and adapts the diffusion tensor to the image iteratively. For this purpose, a preliminary study is performed in order to select the probability models that best fit the stastitical behavior of each tissue class in cardiac ultrasonic images. Then, the parameters of the diffusion tensor are defined taking into account the statistical properties of the image at each voxel. When the structure tensor of the probability of belonging to each tissue is included in the diffusion tensor definition, a better boundaries estimates can be obtained instead of calculating directly the boundaries from the image. This is the main contribution of this work. Additionally, the proposed method follows the statistical properties of the image in each iteration. This is considered as a second contribution since state-of-the-art methods suppose that noise or statistical properties of the image do not change during the filter process.
Killing vector fields in three dimensions: a method to solve massive gravity field equations
NASA Astrophysics Data System (ADS)
Gürses, Metin
2010-10-01
Killing vector fields in three dimensions play an important role in the construction of the related spacetime geometry. In this work we show that when a three-dimensional geometry admits a Killing vector field then the Ricci tensor of the geometry is determined in terms of the Killing vector field and its scalars. In this way we can generate all products and covariant derivatives at any order of the Ricci tensor. Using this property we give ways to solve the field equations of topologically massive gravity (TMG) and new massive gravity (NMG) introduced recently. In particular when the scalars of the Killing vector field (timelike, spacelike and null cases) are constants then all three-dimensional symmetric tensors of the geometry, the Ricci and Einstein tensors, their covariant derivatives at all orders, and their products of all orders are completely determined by the Killing vector field and the metric. Hence, the corresponding three-dimensional metrics are strong candidates for solving all higher derivative gravitational field equations in three dimensions.
Hybrid Diffusion Imaging in Mild Traumatic Brain Injury.
Wu, Yu-Chien; Mustafi, Sourajit Mitra; Harezlak, Jaroslaw; Kodiweera, Chandana; Flashman, Laura A; McAllister, Thomas
2018-05-22
Mild traumatic brain injury (mTBI) is an important public health problem. Although conventional medical imaging techniques can detect moderate-to-severe injuries, they are relatively insensitive to mTBI. In this study, we used hybrid diffusion imaging (HYDI) to detect white-matter alterations in nineteen patients with mTBI and 23 other trauma-control patients. Within 15 days (SD=10) of brain injury, all subjects underwent magnetic-resonance HYDI and were assessed with battery of neuropsychological tests of sustained attention, memory, and executive function. Tract-based spatial statistics (TBSS) were used for voxelwise statistical analyses within the white-matter skeleton to study between-group differences in diffusion metrics, within-group correlations between diffusion metrics and clinical outcomes, and between group interaction effects. The advanced diffusion imaging techniques including neurite orientation dispersion and density imaging (NODDI) and q-space analyses appeared to be more sensitive then classic diffusion tensor imaging (DTI). Only NODDI-derived intra-axonal volume fraction (Vic) demonstrated significant group differences (i.e., 5% to 9% lower in the injured brain). Within the mTBI group, Vic and a q-space measure, P0, correlated with 6 of 10 neuropsychological tests including measures of attention, memory, and executive function. In addition, the direction of correlations differed significantly between the groups (R2 > 0.71 and Pinteration < 0.03). Specifically, in the control group, higher Vic and P0 were associated with better performances on clinical assessments, whereas in the mTBI group, higher Vic and P0 were associated with worse performances with correlation coefficients > 0.83. In summary, the NODDI-derived axonal density index and q-space measure for tissue restriction demonstrated superior sensitivity to white-matter changes shortly after mTBI. These techniques hold promise as a neuroimaging biomarker for mTBI.
Ng, Sze May; Turner, Mark A; Gamble, Carrol; Didi, Mohammed; Victor, Suresh; Atkinson, Jessica; Sluming, Vanessa; Parkes, Laura M; Tietze, Anna; Abernethy, Laurence J; Weindling, Alan Michael
2014-08-01
In order to assess relationships between thyroid hormone status and findings on brain MRI, a subset of babies was recruited to a multi-centre randomised, placebo-controlled trial of levothyroxine (LT4) supplementation for babies born before 28 weeks' gestation (known as the TIPIT study, for Thyroxine supplementation In Preterm InfanTs). These infants were imaged at term-equivalence. Forty-five TIPIT participants had brain MRI using diffusion tensor imaging (DTI) to estimate white matter development by apparent diffusion coefficient (ADC), fractional anisotropy (FA) and tractography metrics of number and length of streamlines. We made comparisons between babies with the lowest and highest plasma FT4 concentrations during the initial 4 weeks after birth. There were no differences in DTI metrics between babies who had received LT4 supplementation and those who had received a placebo. Among recipients of a placebo, babies in the lowest quartile of plasma-free thyroxine (FT4) concentrations had significantly higher apparent diffusion coefficient measurements in the posterior corpus callosum and streamlines that were shorter and less numerous in the right internal capsule. Among LT4-supplemented babies, those who had plasma FT4 concentrations in the highest quartile had significantly lower apparent diffusion coefficient values in the left occipital lobe, higher fractional anisotropy in the anterior corpus callosum and longer and more numerous streamlines in the anterior corpus callosum. DTI variables were not associated with allocation of placebo or thyroid supplementation. Markers of poorly organised brain microstructure were associated with low plasma FT4 concentrations after birth. The findings suggest that plasma FT4 concentrations affect brain development in very immature infants and that the effect of LT4 supplementation for immature babies with low FT4 plasma concentrations warrants further study.
Vaidya spacetime in the diagonal coordinates
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berezin, V. A., E-mail: berezin@inr.ac.ru; Dokuchaev, V. I., E-mail: dokuchaev@inr.ac.ru; Eroshenko, Yu. N., E-mail: eroshenko@inr.ac.ru
We have analyzed the transformation from initial coordinates (v, r) of the Vaidya metric with light coordinate v to the most physical diagonal coordinates (t, r). An exact solution has been obtained for the corresponding metric tensor in the case of a linear dependence of the mass function of the Vaidya metric on light coordinate v. In the diagonal coordinates, a narrow region (with a width proportional to the mass growth rate of a black hole) has been detected near the visibility horizon of the Vaidya accreting black hole, in which the metric differs qualitatively from the Schwarzschild metric andmore » cannot be represented as a small perturbation. It has been shown that, in this case, a single set of diagonal coordinates (t, r) is insufficient to cover the entire range of initial coordinates (v, r) outside the visibility horizon; at least three sets of diagonal coordinates are required, the domains of which are separated by singular surfaces on which the metric components have singularities (either g{sub 00} = 0 or g{sub 00} = ∞). The energy–momentum tensor diverges on these surfaces; however, the tidal forces turn out to be finite, which follows from an analysis of the deviation equations for geodesics. Therefore, these singular surfaces are exclusively coordinate singularities that can be referred to as false fire-walls because there are no physical singularities on them. We have also considered the transformation from the initial coordinates to other diagonal coordinates (η, y), in which the solution is obtained in explicit form, and there is no energy–momentum tensor divergence.« less
Geometry of Lax pairs: Particle motion and Killing-Yano tensors
NASA Astrophysics Data System (ADS)
Cariglia, Marco; Frolov, Valeri P.; Krtouš, Pavel; Kubizňák, David
2013-01-01
A geometric formulation of the Lax pair equation on a curved manifold is studied using the phase-space formalism. The corresponding (covariantly conserved) Lax tensor is defined and the method of generation of constants of motion from it is discussed. It is shown that when the Hamilton equations of motion are used, the conservation of the Lax tensor translates directly to the well-known Lax pair equation, with one matrix identified with components of the Lax tensor and the other matrix constructed from the (metric) connection. A generalization to Clifford objects is also discussed. Nontrivial examples of Lax tensors for geodesic and charged particle motion are found in spacetimes admitting a hidden symmetry of Killing-Yano tensors.
Retrospective correction of bias in diffusion tensor imaging arising from coil combination mode.
Sakaie, Ken; Lowe, Mark
2017-04-01
To quantify and retrospectively correct for systematic differences in diffusion tensor imaging (DTI) measurements due to differences in coil combination mode. Multi-channel coils are now standard among MRI systems. There are several options for combining signal from multiple coils during image reconstruction, including sum-of-squares (SOS) and adaptive combine (AC). This contribution examines the bias between SOS- and AC-derived measures of tissue microstructure and a strategy for limiting that bias. Five healthy subjects were scanned under an institutional review board-approved protocol. Each set of raw image data was reconstructed twice-once with SOS and once with AC. The diffusion tensor was calculated from SOS- and AC-derived data by two algorithms-standard log-linear least squares and an approach that accounts for the impact of coil combination on signal statistics. Systematic differences between SOS and AC in terms of tissue microstructure (axial diffusivity, radial diffusivity, mean diffusivity and fractional anisotropy) were evaluated on a voxel-by-voxel basis. SOS-based tissue microstructure values are systematically lower than AC-based measures throughout the brain in each subject when using the standard tensor calculation method. The difference between SOS and AC can be virtually eliminated by taking into account the signal statistics associated with coil combination. The impact of coil combination mode on diffusion tensor-based measures of tissue microstructure is statistically significant but can be corrected retrospectively. The ability to do so is expected to facilitate pooling of data among imaging protocols. Copyright © 2016 Elsevier Inc. All rights reserved.
Hidden symmetries of Eisenhart-Duval lift metrics and the Dirac equation with flux
NASA Astrophysics Data System (ADS)
Cariglia, Marco
2012-10-01
The Eisenhart-Duval lift allows embedding nonrelativistic theories into a Lorentzian geometrical setting. In this paper we study the lift from the point of view of the Dirac equation and its hidden symmetries. We show that dimensional reduction of the Dirac equation for the Eisenhart-Duval metric in general gives rise to the nonrelativistic Lévy-Leblond equation in lower dimension. We study in detail in which specific cases the lower dimensional limit is given by the Dirac equation, with scalar and vector flux, and the relation between lift, reduction, and the hidden symmetries of the Dirac equation. While there is a precise correspondence in the case of the lower dimensional massive Dirac equation with no flux, we find that for generic fluxes it is not possible to lift or reduce all solutions and hidden symmetries. As a by-product of this analysis, we construct new Lorentzian metrics with special tensors by lifting Killing-Yano and closed conformal Killing-Yano tensors and describe the general conformal Killing-Yano tensor of the Eisenhart-Duval lift metrics in terms of lower dimensional forms. Last, we show how, by dimensionally reducing the higher dimensional operators of the massless Dirac equation that are associated with shared hidden symmetries, it is possible to recover hidden symmetry operators for the Dirac equation with flux.
Duarte-Carvajalino, Julio M.; Sapiro, Guillermo; Harel, Noam; Lenglet, Christophe
2013-01-01
Registration of diffusion-weighted magnetic resonance images (DW-MRIs) is a key step for population studies, or construction of brain atlases, among other important tasks. Given the high dimensionality of the data, registration is usually performed by relying on scalar representative images, such as the fractional anisotropy (FA) and non-diffusion-weighted (b0) images, thereby ignoring much of the directional information conveyed by DW-MR datasets itself. Alternatively, model-based registration algorithms have been proposed to exploit information on the preferred fiber orientation(s) at each voxel. Models such as the diffusion tensor or orientation distribution function (ODF) have been used for this purpose. Tensor-based registration methods rely on a model that does not completely capture the information contained in DW-MRIs, and largely depends on the accurate estimation of tensors. ODF-based approaches are more recent and computationally challenging, but also better describe complex fiber configurations thereby potentially improving the accuracy of DW-MRI registration. A new algorithm based on angular interpolation of the diffusion-weighted volumes was proposed for affine registration, and does not rely on any specific local diffusion model. In this work, we first extensively compare the performance of registration algorithms based on (i) angular interpolation, (ii) non-diffusion-weighted scalar volume (b0), and (iii) diffusion tensor image (DTI). Moreover, we generalize the concept of angular interpolation (AI) to non-linear image registration, and implement it in the FMRIB Software Library (FSL). We demonstrate that AI registration of DW-MRIs is a powerful alternative to volume and tensor-based approaches. In particular, we show that AI improves the registration accuracy in many cases over existing state-of-the-art algorithms, while providing registered raw DW-MRI data, which can be used for any subsequent analysis. PMID:23596381
Leming, Matthew; Steiner, Rachel; Styner, Martin
2016-02-27
Tract-based spatial statistics (TBSS) 6 is a software pipeline widely employed in comparative analysis of the white matter integrity from diffusion tensor imaging (DTI) datasets. In this study, we seek to evaluate the relationship between different methods of atlas registration for use with TBSS and different measurements of DTI (fractional anisotropy, FA, axial diffusivity, AD, radial diffusivity, RD, and medial diffusivity, MD). To do so, we have developed a novel tool that builds on existing diffusion atlas building software, integrating it into an adapted version of TBSS called DAB-TBSS (DTI Atlas Builder-Tract-Based Spatial Statistics) by using the advanced registration offered in DTI Atlas Builder 7 . To compare the effectiveness of these two versions of TBSS, we also propose a framework for simulating population differences for diffusion tensor imaging data, providing a more substantive means of empirically comparing DTI group analysis programs such as TBSS. In this study, we used 33 diffusion tensor imaging datasets and simulated group-wise changes in this data by increasing, in three different simulations, the principal eigenvalue (directly altering AD), the second and third eigenvalues (RD), and all three eigenvalues (MD) in the genu, the right uncinate fasciculus, and the left IFO. Additionally, we assessed the benefits of comparing the tensors directly using a functional analysis of diffusion tensor tract statistics (FADTTS 10 ). Our results indicate comparable levels of FA-based detection between DAB-TBSS and TBSS, with standard TBSS registration reporting a higher rate of false positives in other measurements of DTI. Within the simulated changes investigated here, this study suggests that the use of DTI Atlas Builder's registration enhances TBSS group-based studies.
Duarte-Carvajalino, Julio M; Sapiro, Guillermo; Harel, Noam; Lenglet, Christophe
2013-01-01
Registration of diffusion-weighted magnetic resonance images (DW-MRIs) is a key step for population studies, or construction of brain atlases, among other important tasks. Given the high dimensionality of the data, registration is usually performed by relying on scalar representative images, such as the fractional anisotropy (FA) and non-diffusion-weighted (b0) images, thereby ignoring much of the directional information conveyed by DW-MR datasets itself. Alternatively, model-based registration algorithms have been proposed to exploit information on the preferred fiber orientation(s) at each voxel. Models such as the diffusion tensor or orientation distribution function (ODF) have been used for this purpose. Tensor-based registration methods rely on a model that does not completely capture the information contained in DW-MRIs, and largely depends on the accurate estimation of tensors. ODF-based approaches are more recent and computationally challenging, but also better describe complex fiber configurations thereby potentially improving the accuracy of DW-MRI registration. A new algorithm based on angular interpolation of the diffusion-weighted volumes was proposed for affine registration, and does not rely on any specific local diffusion model. In this work, we first extensively compare the performance of registration algorithms based on (i) angular interpolation, (ii) non-diffusion-weighted scalar volume (b0), and (iii) diffusion tensor image (DTI). Moreover, we generalize the concept of angular interpolation (AI) to non-linear image registration, and implement it in the FMRIB Software Library (FSL). We demonstrate that AI registration of DW-MRIs is a powerful alternative to volume and tensor-based approaches. In particular, we show that AI improves the registration accuracy in many cases over existing state-of-the-art algorithms, while providing registered raw DW-MRI data, which can be used for any subsequent analysis.
NASA Astrophysics Data System (ADS)
Brandenburg, John
2012-10-01
The GEM theory (1) links the EM stress tensor directly to the metric tensor by the principle of ``self censorship'' of the ZPF (2) where the definition of guv = FuwF^wv/ 4 for Planck scale fields makes the stress tensor vanish even when fields are present. The first order form of the metric is recovered as Lorentzian due to alternating regions of strong electric and magnetic fields similar to that seen in models of spacetime in ``Loop Gravity,'' where the model admits perturbations. The GEM ExB drift models of gravity is used The first order perturbations on the fields are considered to be of the order of the fine structure constant alpha. Radiation fields due to a single charged particle of mass M fall off as 1/r and give the values (G=c=1) gtt = 1-2M/r and grr = (1-2M/r). (1) Brandenburg, J.E. (2012)., (2) STAIF II Conference Albuquerque NM 2.Brandenburg, J.E. (2007). IEEE Transactions On Plasma Science, Vol. 35, No. 4., p845.
Diffusion Tensor Image Registration Using Hybrid Connectivity and Tensor Features
Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang
2014-01-01
Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. PMID:24293159
Multiple Echo Diffusion Tensor Acquisition Technique (MEDITATE) on a 3T clinical scanner
Baete, Steven H.; Cho, Gene; Sigmund, Eric E.
2013-01-01
This paper describes the concepts and implementation of an MRI method, Multiple Echo Diffusion Tensor Acquisition Technique (MEDITATE), which is capable of acquiring apparent diffusion tensor maps in two scans on a 3T clinical scanner. In each MEDITATE scan, a set of RF-pulses generates multiple echoes whose amplitudes are diffusion-weighted in both magnitude and direction by a pattern of diffusion gradients. As a result, two scans acquired with different diffusion weighting strengths suffice for accurate estimation of diffusion tensor imaging (DTI)-parameters. The MEDITATE variation presented here expands previous MEDITATE approaches to adapt to the clinical scanner platform, such as exploiting longitudinal magnetization storage to reduce T2-weighting. Fully segmented multi-shot Cartesian encoding is used for image encoding. MEDITATE was tested on isotropic (agar gel), anisotropic diffusion phantoms (asparagus), and in vivo skeletal muscle in healthy volunteers with cardiac-gating. Comparisons of accuracy were performed with standard twice-refocused spin echo (TRSE) DTI in each case and good quantitative agreement was found between diffusion eigenvalues, mean diffusivity, and fractional anisotropy derived from TRSE-DTI and from the MEDITATE sequence. Orientation patterns were correctly reproduced in both isotropic and anisotropic phantoms, and approximately so for in vivo imaging. This illustrates that the MEDITATE method of compressed diffusion encoding is feasible on the clinical scanner platform. With future development and employment of appropriate view-sharing image encoding this technique may be used in clinical applications requiring time-sensitive acquisition of DTI parameters such as dynamical DTI in muscle. PMID:23828606
MR Diffusion Tensor Imaging: A Window into White Matter Integrity of the Working Brain
Chanraud, Sandra; Zahr, Natalie; Pfefferbaum, Adolf
2010-01-01
As Norman Geschwind asserted in 1965, syndromes resulting from white matter lesions could produce deficits in higher-order functions and “disconnexion” or the interruption of connection between gray matter regions could be as disruptive as trauma to those regions per se. The advent of in vivo diffusion tensor imaging, which allows quantitative characterization of white matter fiber integrity in health and disease, has served to strengthen Geschwind's proposal. Here we present an overview of the principles of diffusion tensor imaging (DTI) and its contribution to progress in our current understanding of normal and pathological brain function. PMID:20422451
Tu, Tsang-Wei; Kim, Joong H.; Wang, Jian
2010-01-01
Abstract In vivo diffusion tensor imaging (DTI) derived indices have been demonstrated to quantify accurately white-matter injury after contusion spinal cord injury (SCI) in rodents. In general, a full diffusion tensor analysis requires the acquisition of diffusion-weighted images (DWI) along at least six independent directions of diffusion-sensitizing gradients. Thus, DTI measurements of the rodent central nervous system are time consuming. In this study, diffusion indices derived using the two-direction DWI (parallel and perpendicular to axonal tracts) were compared with those obtained using six-direction DTI in a mouse model of SCI. It was hypothesized that the mouse spinal cord ventral-lateral white-matter (VLWM) tracts, T8–T10 in this study, aligned with the main magnet axis (z) allowing the apparent diffusion coefficient parallel and perpendicular to the axis of the spine to be derived with diffusion-weighting gradients in the z and y axes of the magnet coordinate respectively. Compared with six-direction full tensor DTI, two-direction DWI provided comparable diffusion indices in mouse spinal cords. The measured extent of spared white matter after injury, estimated by anisotropy indices, using both six-direction DTI and two-direction DWI were in close agreement and correlated well with histological staining and behavioral assessment. The results suggest that the two-direction DWI derived indices may be used, with significantly reduced imaging time, to estimate accurately spared white matter in mouse SCI. PMID:19715399
Computational tools for Breakthrough Propulsion Physics: State of the art and future prospects
NASA Astrophysics Data System (ADS)
Maccone, Claudio
2000-01-01
To address problems in Breakthrough Propulsion Physics (BPP) one needs sheer computing capabilities. This is because General Relativity and Quantum Field Theory are so mathematically sophisticated that the amount of analytical calculations is prohibitive and one can hardly do all of them by hand. In this paper we make a comparative review of the main tensor calculus capabilities of the three most advanced and commercially available ``symbolic manipulator'' codes: Macsyma, Maple V and Mathematica. We also point out that currently one faces such a variety of different conventions in tensor calculus that it is difficult or impossible to compare results obtained by different scholars in General Relativity and Quantum Field Theory. Mathematical physicists, experimental physicists and engineers have each their own way of customizing tensors, especially by using the different metric signatures, different metric determinant signs, different definitions of the basic Riemann and Ricci tensors, and by adopting different systems of physical units. This chaos greatly hampers progress toward the chief NASA BPP goal: the design of the NASA Warp Drive. It is thus concluded that NASA should put order by establishing international standards in symbolic tensor calculus and enforcing anyone working in BPP to adopt these NASA BPP Standards. .
Longitudinal Study of White Matter Development and Outcomes in Children Born Very Preterm.
Young, Julia M; Morgan, Benjamin R; Whyte, Hilary E A; Lee, Wayne; Smith, Mary Lou; Raybaud, Charles; Shroff, Manohar M; Sled, John G; Taylor, Margot J
2017-08-01
Identifying trajectories of early white matter development is important for understanding atypical brain development and impaired functional outcomes in children born very preterm (<32 weeks gestational age [GA]). In this study, 161 diffusion images were acquired in children born very preterm (median GA: 29 weeks) shortly following birth (75), term-equivalent (39), 2 years (18), and 4 years of age (29). Diffusion tensors were computed to obtain measures of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), which were aligned and averaged. A paediatric atlas was applied to obtain diffusion metrics within 12 white matter tracts. Developmental trajectories across time points demonstrated age-related changes which plateaued between term-equivalent and 2 years of age in the majority of posterior tracts and between 2 and 4 years of age in anterior tracts. Between preterm and term-equivalent scans, FA rates of change were slower in anterior than posterior tracts. Partial least squares analyses revealed associations between slower MD and RD rates of change within the external and internal capsule with lower intelligence quotients and language scores at 4 years of age. These results uniquely demonstrate early white matter development and its linkage to cognitive functions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Scale-invariant curvature fluctuations from an extended semiclassical gravity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pinamonti, Nicola, E-mail: pinamont@dima.unige.it, E-mail: siemssen@dima.unige.it; INFN Sezione di Genova, Via Dodecaneso 33, 16146 Genova; Siemssen, Daniel, E-mail: pinamont@dima.unige.it, E-mail: siemssen@dima.unige.it
2015-02-15
We present an extension of the semiclassical Einstein equations which couple n-point correlation functions of a stochastic Einstein tensor to the n-point functions of the quantum stress-energy tensor. We apply this extension to calculate the quantum fluctuations during an inflationary period, where we take as a model a massive conformally coupled scalar field on a perturbed de Sitter space and describe how a renormalization independent, almost-scale-invariant power spectrum of the scalar metric perturbation is produced. Furthermore, we discuss how this model yields a natural basis for the calculation of non-Gaussianities of the considered metric fluctuations.
Nguyen, Thanh-Son; Selinger, Jonathan V
2017-09-01
In liquid crystal elastomers and polymer networks, the orientational order of liquid crystals is coupled with elastic distortions of crosslinked polymers. Previous theoretical research has described these materials through two different approaches: a neoclassical theory based on the liquid crystal director and the deformation gradient tensor, and a geometric elasticity theory based on the difference between the actual metric tensor and a reference metric. Here, we connect those two approaches using a formalism based on differential geometry. Through this connection, we determine how both the director and the geometry respond to a change of temperature.
FLRW Cosmology from Yang-Mills Gravity with Translational Gauge Symmetry
NASA Astrophysics Data System (ADS)
Katz, Daniel
2013-03-01
We extend to basic cosmology the subject of Yang-Mills gravity — a theory of gravity based on local translational gauge invariance in flat space-time. It has been shown that this particular gauge invariance leads to tensor factors in the macroscopic limit of the equations of motion of particles which plays the same role as the metric tensor of general relativity (GR). The assumption that this "effective metric" tensor takes on the standard FLRW form is our starting point. Equations analogous to the Friedmann equations are derived and then solved in closed form for the three special cases of a universe dominated by (1) matter, (2) radiation and (3) dark energy. We find that the solutions for the scale factor are similar to, but distinct from, those found in the corresponding GR based treatment.
Higher order first integrals, Killing tensors and Killing-Maxwell system
NASA Astrophysics Data System (ADS)
Visinescu, Mihai
2012-02-01
Higher order first integrals of motion of particles in the presence of external gauge fields in a covariant Hamiltonian approach are investigated. The special role of Stackel-Killing and Killing-Yano tensors is pointed out. A condition of the electromagnetic field to maintain the hidden symmetry of the system is stated. A concrete realization of this condition is given by the Killing-Maxwell system and exemplified with the Kerr metric. Another application of the gauge covariant approach is provided by a non relativistic point charge in the field of a Dirac monopole. The corresponding dynamical system possessing a Kepler type symmetry is associated with the Taub-NUT metric using a reduction procedure of symplectic manifolds with symmetries. The reverse of the reduction procedure can be used to investigate higher-dimensional spacetimes admitting Killing tensors.
Kubo formulas for dispersion in heterogeneous periodic nonequilibrium systems.
Guérin, T; Dean, D S
2015-12-01
We consider the dispersion properties of tracer particles moving in nonequilibrium heterogeneous periodic media. The tracer motion is described by a Fokker-Planck equation with arbitrary spatially periodic (but constant in time) local diffusion tensors and drifts, eventually with the presence of obstacles. We derive a Kubo-like formula for the time-dependent effective diffusion tensor valid in any dimension. From this general formula, we derive expressions for the late time effective diffusion tensor and drift in these systems. In addition, we find an explicit formula for the late finite-time corrections to these transport coefficients. In one dimension, we give a closed analytical formula for the transport coefficients. The formulas derived here are very general and provide a straightforward method to compute the dispersion properties in arbitrary nonequilibrium periodic advection-diffusion systems.
Taoka, Toshiaki; Masutani, Yoshitaka; Kawai, Hisashi; Nakane, Toshiki; Matsuoka, Kiwamu; Yasuno, Fumihiko; Kishimoto, Toshifumi; Naganawa, Shinji
2017-04-01
The activity of the glymphatic system is impaired in animal models of Alzheimer's disease (AD). We evaluated the activity of the human glymphatic system in cases of AD with a diffusion-based technique called diffusion tensor image analysis along the perivascular space (DTI-ALPS). Diffusion tensor images were acquired to calculate diffusivities in the x, y, and z axes of the plane of the lateral ventricle body in 31 patients. We evaluated the diffusivity along the perivascular spaces as well as projection fibers and association fibers separately, to acquire an index for diffusivity along the perivascular space (ALPS-index) and correlated them with the mini mental state examinations (MMSE) score. We found a significant negative correlation between diffusivity along the projection fibers and association fibers. We also observed a significant positive correlation between diffusivity along perivascular spaces shown as ALPS-index and the MMSE score, indicating lower water diffusivity along the perivascular space in relation to AD severity. Activity of the glymphatic system may be evaluated with diffusion images. Lower diffusivity along the perivascular space on DTI-APLS seems to reflect impairment of the glymphatic system. This method may be useful for evaluating the activity of the glymphatic system.
Kumar, Rajesh; Macey, Paul M; Woo, Mary A; Alger, Jeffry R; Harper, Ronald M
2008-09-01
Congenital central hypoventilation syndrome (CCHS) patients show reduced breathing drive during sleep, decreased hypoxic and hypercapnic ventilatory responses, and autonomic and affective deficits, suggesting both brainstem and forebrain injuries. Forebrain damage was previously described in CCHS, but methodological limitations precluded detection of brainstem injury, a concern because genetic mutations in CCHS target brainstem autonomic nuclei. To assess brainstem and cerebellar areas, we used diffusion tensor imaging-based measures, namely axial diffusivity, reflecting water diffusion parallel to fibers, and sensitive to axonal injury, and radial diffusivity, measuring diffusion perpendicular to fibers, and indicative of myelin injury. Diffusion tensor imaging was performed in 12 CCHS and 26 controls, and axial and radial diffusivity maps were compared between groups using analysis of covariance (covariates; age and gender). Increased axial diffusivity in CCHS appeared within the lateral medulla and clusters with injury extended from the dorsal midbrain through the periaqueductal gray, raphé, and superior cerebellar decussation, ventrally to the basal-pons. Cerebellar cortex and deep nuclei, and the superior and inferior cerebellar peduncles showed increased radial diffusivity. Midbrain, pontine, and lateral medullary structures, and the cerebellum and its fiber systems are injured in CCHS, likely contributing to the characteristics found in the syndrome.
Brain Imaging and Neurodevelopment in HIV-uninfected Thai Children Born to HIV-infected Mothers.
Jahanshad, Neda; Couture, Marie-Claude; Prasitsuebsai, Wasana; Nir, Talia M; Aurpibul, Linda; Thompson, Paul M; Pruksakaew, Kanchana; Lerdlum, Sukalaya; Visrutaratna, Pannee; Catella, Stephanie; Desai, Akash; Kerr, Stephen J; Puthanakit, Thanyawee; Paul, Robert; Ananworanich, Jintanat; Valcour, Victor G
2015-09-01
Perinatal use of combination antiretroviral therapy dramatically reduces vertical (mother-to-child) transmission of HIV but has led to a growing population of children with perinatal HIV-exposure but uninfected (HEU). HIV can cause neurological injury among children born with infection, but the neuroanatomical and developmental effects in HEU children are poorly understood. We used structural magnetic resonance imaging with diffusion tensor imaging to compare brain anatomy between 30 HEU and 33 age-matched HIV-unexposed and uninfected (HUU) children from Thailand. Maps of brain volume and microstructural anatomy were compared across groups; associations were tested between neuroimaging measures and concurrent neuropsychological test performance. Mean (standard deviation) age of children was 10.3 (2.8) years, and 58% were male. All were enrolled in school and lived with family members. Intelligence quotient (IQ) did not differ between groups. Caretaker education levels did not differ, but income was higher for HUU (P < 0.001). We did not detect group differences in brain volume or diffusion tensor imaging metrics, after controlling for sociodemographic factors. The mean (95% confidence interval) fractional anisotropy in the corpus callosum was 0.375 (0.368-0.381) in HEU compared with 0.370 (0.364-0.375) in HUU. Higher fractional anisotropy and lower mean diffusivity were each associated with higher IQ scores in analyses with both groups combined. No differences in neuroanatomical or brain integrity measures were detectable in HEU children compared with age-matched and sex-matched controls (HUU children). Expected associations between brain integrity measures and IQ scores were identified suggesting sufficient power to detect subtle associations that were present.
Villalon, Julio; Jahanshad, Neda; Beaton, Elliott; Toga, Arthur W.; Thompson, Paul M.; Simon, Tony J.
2014-01-01
Children with chromosome 22q11.2 Deletion Syndrome (22q11.2DS), Fragile X Syndrome (FXS), or Turner Syndrome (TS) are considered to belong to distinct genetic groups, as each disorder is caused by separate genetic alterations. Even so, they have similar cognitive and behavioral dysfunctions, particularly in visuospatial and numerical abilities. To assess evidence for common underlying neural microstructural alterations, we set out to determine whether these groups have partially overlapping white matter abnormalities, relative to typically developing controls. We scanned 101 female children between 7 and 14 years old: 25 with 22q11.2DS, 18 with FXS, 17 with TS, and 41 aged-matched controls using diffusion tensor imaging (DTI). Anisotropy and diffusivity measures were calculated and all brain scans were nonlinearly aligned to population and site-specific templates. We performed voxel-based statistical comparisons of the DTI-derived metrics between each disease group and the controls, while adjusting for age. Girls with 22q11.2DS showed lower fractional anisotropy (FA) than controls in the association fibers of the superior and inferior longitudinal fasciculi, the splenium of the corpus callosum, and the corticospinal tract. FA was abnormally lower in girls with FXS in the posterior limbs of the internal capsule, posterior thalami, and precentral gyrus. Girls with TS had lower FA in the inferior longitudinal fasciculus, right internal capsule and left cerebellar peduncle. Partially overlapping neurodevelopmental anomalies were detected in all three neurogenetic disorders. Altered white matter integrity in the superior and inferior longitudinal fasciculi and thalamic to frontal tracts may contribute to the behavioral characteristics of all of these disorders. PMID:23602925
Benson, Randall R; Gattu, Ramtilak; Cacace, Anthony T
2014-03-01
Diffusion tensor imaging (DTI) is a contemporary neuroimaging modality used to study connectivity patterns and microstructure of white matter tracts in the brain. The use of DTI in the study of tinnitus is a relatively unexplored methodology with no studies focusing specifically on tinnitus induced by noise exposure. In this investigation, participants were two groups of adults matched for etiology, age, and degree of peripheral hearing loss, but differed by the presence or absence (+/-) of tinnitus. It is assumed that matching individuals on the basis of peripheral hearing loss, allows for differentiating changes in white matter microstructure due to hearing loss from changes due to the effects of chronic tinnitus. Alterations in white matter tracts, using the fractional anisotropy (FA) metric, which measures directional diffusion of water, were quantified using tract-based spatial statistics (TBSS) with additional details provided by in vivo probabilistic tractography. Our results indicate that 10 voxel clusters differentiated the two groups, including 9 with higher FA in the group with tinnitus. A decrease in FA was found for a single cluster in the group with tinnitus. However, seven of the 9 clusters with higher FA were in left hemisphere thalamic, frontal, and parietal white matter. These foci were localized to the anterior thalamic radiations and the inferior and superior longitudinal fasciculi. The two right-sided clusters with increased FA were located in the inferior fronto-occipital fasciculus and superior longitudinal fasciculus. The only decrease in FA for the tinnitus-positive group was found in the superior longitudinal fasciculus of the left parietal lobe. Copyright © 2013 Elsevier B.V. All rights reserved.
Field, Aaron S; Alexander, Andrew L; Wu, Yu-Chien; Hasan, Khader M; Witwer, Brian; Badie, Behnam
2004-10-01
To categorize the varied appearances of tumor-altered white matter (WM) tracts on diffusion tensor eigenvector directional color maps. Diffusion tensor imaging (DTI) was obtained preoperatively in 13 patients with brain tumors ranging from benign to high-grade malignant, including primary and metastatic lesions, and maps of apparent diffusion coefficient (ADC), fractional anisotropy (FA), and major eigenvector direction were generated. Regions of interest (ROIs) were drawn within identifiable WM tracts affected by tumor, avoiding grossly cystic and necrotic regions, known fiber crossings, and gray matter. Patterns of WM tract alteration were categorized on the basis of qualitative analysis of directional color maps and correlation analysis of ADC and FA. Four basic patterns of WM alteration were identified: 1) normal or nearly normal FA and ADC, with abnormal tract location or tensor directions attributable to bulk mass displacement, 2) moderately decreased FA and increased ADC with normal tract locations and tensor directions, 3) moderately decreased FA and increased ADC with abnormal tensor directions, and 4) near isotropy. FA and ADC were inversely correlated for Patterns 1-3 but did not discriminate edema from infiltrating tumor. However, in the absence of mass displacement, infiltrating tumor was found to produce tensor directional changes that were not observed with vasogenic edema, suggesting the possibility of discrimination on the basis of directional statistics. Tumor alteration of WM tracts tends to produce one of four patterns on FA and directional color maps. Clinical application of these patterns must await further study. Copyright 2004 Wiley-Liss, Inc.
Diffusion tensor imaging, white matter lesions, the corpus callosum, and gait in the elderly
USDA-ARS?s Scientific Manuscript database
Gait impairment is common in the elderly, especially affected by stroke and white matter hyper intensities found in conventional brain magnetic resonance imaging (MRI). Diffusion tensor imaging (DTI) is more sensitive to white matter damage than conventional MRI. The relationship between DTI measure...
A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging.
Wu, Zhanxiong; Liu, Yang; Hong, Ming; Yu, Xiaohui
2018-06-01
The conductivity of brain tissues is not only essential for electromagnetic source estimation (ESI), but also a key reflector of the brain functional changes. Different from the other brain tissues, the conductivity of whiter matter (WM) is highly anisotropic and a tensor is needed to describe it. The traditional electrical property imaging methods, such as electrical impedance tomography (EIT) and magnetic resonance electrical impedance tomography (MREIT), usually fail to image the anisotropic conductivity tensor of WM with high spatial resolution. The diffusion tensor imaging (DTI) is a newly developed technique that can fulfill this purpose. This paper reviews the existing anisotropic conductivity models of WM based on the DTI and discusses their advantages and disadvantages, as well as identifies opportunities for future research on this subject. It is crucial to obtain the linear conversion coefficient between the eigenvalues of anisotropic conductivity tensor and diffusion tensor, since they share the same eigenvectors. We conclude that the electrochemical model is suitable for ESI analysis because the conversion coefficient can be directly obtained from the concentration of ions in extracellular liquid and that the volume fraction model is appropriate to study the influence of WM structural changes on electrical conductivity. Graphical abstract ᅟ.
Traumatic Brain Injury Diffusion Magnetic Resonance Imaging Research Roadmap Development Project
2011-10-01
promising technology on the horizon is the Diffusion Tensor Imaging ( DTI ). Diffusion tensor imaging ( DTI ) is a magnetic resonance imaging (MRI)-based...in the brain. The potential for DTI to improve our understanding of TBI has not been fully explored and challenges associated with non-existent...processing tools, quality control standards, and a shared image repository. The recommendations will be disseminated and pilot tested. A DTI of TBI
Nitkunan, Arani; Barrick, Tom R; Charlton, Rebecca A; Clark, Chris A; Markus, Hugh S
2008-07-01
Cerebral small vessel disease is the most common cause of vascular dementia. Interest in using MRI parameters as surrogate markers of disease to assess therapies is increasing. In patients with symptomatic sporadic small vessel disease, we determined which MRI parameters best correlated with cognitive function on cross-sectional analysis and which changed over a period of 1 year. Thirty-five patients with lacunar stroke and leukoaraiosis were recruited. They underwent multimodal MRI (brain volume, fluid-attenuated inversion recovery lesion load, lacunar infarct number, fractional anisotropy, and mean diffusivity from diffusion tensor imaging) and neuropsychological testing. Twenty-seven agreed to reattend for repeat MRI and neuropsychology at 1 year. An executive function score correlated most strongly with diffusion tensor imaging (fractional anisotropy histogram, r=-0.640, P=0.004) and brain volume (r=0.501, P=0.034). Associations with diffusion tensor imaging were stronger than with all other MRI parameters. On multiple regression of all imaging parameters, a model that contained brain volume and fractional anisotropy, together with age, gender, and premorbid IQ, explained 74% of the variance of the executive function score (P=0.0001). Changes in mean diffusivity and fractional anisotropy were detectable over the 1-year follow-up; in contrast, no change in other MRI parameters was detectable over this time period. A multimodal MRI model explains a large proportion of the variation in executive function in cerebral small vessel disease. In particular, diffusion tensor imaging correlates best with executive function and is the most sensitive to change. This supports the use of MRI, in particular diffusion tensor imaging, as a surrogate marker in treatment trials.
Kowalczyk, Natalia; Shi, Feng; Magnuski, Mikolaj; Skorko, Maciek; Dobrowolski, Pawel; Kossowski, Bartosz; Marchewka, Artur; Bielecki, Maksymilian; Kossut, Malgorzata; Brzezicka, Aneta
2018-06-20
Experienced video game players exhibit superior performance in visuospatial cognition when compared to non-players. However, very little is known about the relation between video game experience and structural brain plasticity. To address this issue, a direct comparison of the white matter brain structure in RTS (real time strategy) video game players (VGPs) and non-players (NVGPs) was performed. We hypothesized that RTS experience can enhance connectivity within and between occipital and parietal regions, as these regions are likely to be involved in the spatial and visual abilities that are trained while playing RTS games. The possible influence of long-term RTS game play experience on brain structural connections was investigated using diffusion tensor imaging (DTI) and a region of interest (ROI) approach in order to describe the experience-related plasticity of white matter. Our results revealed significantly more total white matter connections between occipital and parietal areas and within occipital areas in RTS players compared to NVGPs. Additionally, the RTS group had an altered topological organization of their structural network, expressed in local efficiency within the occipito-parietal subnetwork. Furthermore, the positive association between network metrics and time spent playing RTS games suggests a close relationship between extensive, long-term RTS game play and neuroplastic changes. These results indicate that long-term and extensive RTS game experience induces alterations along axons that link structures of the occipito-parietal loop involved in spatial and visual processing. © 2018 Wiley Periodicals, Inc.
Berlin, Konstantin; O’Leary, Dianne P.; Fushman, David
2011-01-01
We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. PMID:21604302
Berlin, Konstantin; O'Leary, Dianne P; Fushman, David
2011-07-01
We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. Copyright © 2011 Wiley-Liss, Inc.
Eckart frame vibration-rotation Hamiltonians: Contravariant metric tensor
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pesonen, Janne, E-mail: janne.pesonen@helsinki.fi
2014-02-21
Eckart frame is a unique embedding in the theory of molecular vibrations and rotations. It is defined by the condition that the Coriolis coupling of the reference structure of the molecule is zero for every choice of the shape coordinates. It is far from trivial to set up Eckart kinetic energy operators (KEOs), when the shape of the molecule is described by curvilinear coordinates. In order to obtain the KEO, one needs to set up the corresponding contravariant metric tensor. Here, I derive explicitly the Eckart frame rotational measuring vectors. Their inner products with themselves give the rotational elements, andmore » their inner products with the vibrational measuring vectors (which, in the absence of constraints, are the mass-weighted gradients of the shape coordinates) give the Coriolis elements of the contravariant metric tensor. The vibrational elements are given as the inner products of the vibrational measuring vectors with themselves, and these elements do not depend on the choice of the body-frame. The present approach has the advantage that it does not depend on any particular choice of the shape coordinates, but it can be used in conjunction with all shape coordinates. Furthermore, it does not involve evaluation of covariant metric tensors, chain rules of derivation, or numerical differentiation, and it can be easily modified if there are constraints on the shape of the molecule. Both the planar and non-planar reference structures are accounted for. The present method is particular suitable for numerical work. Its computational implementation is outlined in an example, where I discuss how to evaluate vibration-rotation energies and eigenfunctions of a general N-atomic molecule, the shape of which is described by a set of local polyspherical coordinates.« less
Pohl, Kilian M; Sullivan, Edith V; Rohlfing, Torsten; Chu, Weiwei; Kwon, Dongjin; Nichols, B Nolan; Zhang, Yong; Brown, Sandra A; Tapert, Susan F; Cummins, Kevin; Thompson, Wesley K; Brumback, Ty; Colrain, Ian M; Baker, Fiona C; Prouty, Devin; De Bellis, Michael D; Voyvodic, James T; Clark, Duncan B; Schirda, Claudiu; Nagel, Bonnie J; Pfefferbaum, Adolf
2016-04-15
Neurodevelopment continues through adolescence, with notable maturation of white matter tracts comprising regional fiber systems progressing at different rates. To identify factors that could contribute to regional differences in white matter microstructure development, large samples of youth spanning adolescence to young adulthood are essential to parse these factors. Recruitment of adequate samples generally relies on multi-site consortia but comes with the challenge of merging data acquired on different platforms. In the current study, diffusion tensor imaging (DTI) data were acquired on GE and Siemens systems through the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a multi-site study designed to track the trajectories of regional brain development during a time of high risk for initiating alcohol consumption. This cross-sectional analysis reports baseline Tract-Based Spatial Statistic (TBSS) of regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1), and radial diffusivity (LT) from the five consortium sites on 671 adolescents who met no/low alcohol or drug consumption criteria and 132 adolescents with a history of exceeding consumption criteria. Harmonization of DTI metrics across manufacturers entailed the use of human-phantom data, acquired multiple times on each of three non-NCANDA participants at each site's MR system, to determine a manufacturer-specific correction factor. Application of the correction factor derived from human phantom data measured on MR systems from different manufacturers reduced the standard deviation of the DTI metrics for FA by almost a half, enabling harmonization of data that would have otherwise carried systematic error. Permutation testing supported the hypothesis of higher FA and lower diffusivity measures in older adolescents and indicated that, overall, the FA, MD, and L1 of the boys were higher than those of the girls, suggesting continued microstructural development notable in the boys. The contribution of demographic and clinical differences to DTI metrics was assessed with General Additive Models (GAM) testing for age, sex, and ethnicity differences in regional skeleton mean values. The results supported the primary study hypothesis that FA skeleton mean values in the no/low-drinking group were highest at different ages. When differences in intracranial volume were covaried, FA skeleton mean reached a maximum at younger ages in girls than boys and varied in magnitude with ethnicity. Our results, however, did not support the hypothesis that youth who exceeded exposure criteria would have lower FA or higher diffusivity measures than the no/low-drinking group; detecting the effects of excessive alcohol consumption during adolescence on DTI metrics may require longitudinal study. Copyright © 2016 Elsevier Inc. All rights reserved.
Pohl, Kilian M.; Sullivan, Edith V.; Rohlfing, Torsten; Chu, Weiwei; Kwon, Dongjin; Nichols, B. Nolan; Zhang, Yong; Brown, Sandra A.; Tapert, Susan F.; Cummins, Kevin; Thompson, Wesley K.; Brumback, Ty; Colrain, Ian M.; Baker, Fiona C.; Prouty, Devin; De Bellis, Michael D.; Voyvodic, James T.; Clark, Duncan B.; Schirda, Claudiu; Nagel, Bonnie J.; Pfefferbaum, Adolf
2016-01-01
Neurodevelopment continues through adolescence, with notable maturation of white matter tracts comprising regional fiber systems progressing at different rates. To identify factors that could contribute to regional differences in white matter microstructure development, large samples of youth spanning adolescence to young adulthood are essential to parse these factors. Recruitment of adequate samples generally relies on multi-site consortia but comes with the challenge of merging data acquired on different platforms. In the current study, diffusion tensor imaging (DTI) data were acquired on GE and Siemens systems through the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a multi-site study designed to track the trajectories of regional brain development during a time of high risk for initiating alcohol consumption. This cross-sectional analysis reports baseline Tract-Based Spatial Statistic (TBSS) of regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1), and radial diffusivity (LT) from the five consortium sites on 671 adolescents who met no/low alcohol or drug consumption criteria and 132 adolescents with a history of exceeding consumption criteria. Harmonization of DTI metrics across manufacturers entailed the use of human-phantom data, acquired multiple times on each of three non-NCANDA participants at each site’s MR system, to determine a manufacturer-specific correction factor. Application of the correction factor derived from human phantom data measured on MR systems from different manufacturers reduced the standard deviation of the DTI metrics for FA by almost a half, enabling harmonization of data that would have otherwise carried systematic error. Permutation testing supported the hypothesis of higher FA and lower diffusivity measures in older adolescents and indicated that, overall, the FA, MD, and L1 of the boys was higher than that of the girls, suggesting continued microstructural development notable in the boys. The contribution of demographic and clinical differences to DTI metrics was assessed with General Additive Models (GAM) testing for age, sex, and ethnicity differences in regional skeleton mean values. The results supported the primary study hypothesis that FA skeleton mean values in the no/low-drinking group were highest at different ages. When differences in intracranial volume were covaried, FA skeleton mean reached a maximum at younger ages in girls than boys and varied in magnitude with ethnicity. Our results, however, did not support the hypothesis that youth who exceeded exposure criteria would have lower FA or higher diffusivity measures than the no/low-drinking group; detecting the effects of excessive alcohol consumption during adolescence on DTI metrics may require longitudinal study. PMID:26872408
Global diffusion of cosmic rays in random magnetic fields
NASA Astrophysics Data System (ADS)
Snodin, A. P.; Shukurov, A.; Sarson, G. R.; Bushby, P. J.; Rodrigues, L. F. S.
2016-04-01
The propagation of charged particles, including cosmic rays, in a partially ordered magnetic field is characterized by a diffusion tensor whose components depend on the particle's Larmor radius RL and the degree of order in the magnetic field. Most studies of the particle diffusion presuppose a scale separation between the mean and random magnetic fields (e.g. there being a pronounced minimum in the magnetic power spectrum at intermediate scales). Scale separation is often a good approximation in laboratory plasmas, but not in most astrophysical environments such as the interstellar medium (ISM). Modern simulations of the ISM have numerical resolution of the order of 1 pc, so the Larmor radius of the cosmic rays that dominate in energy density is at least 106 times smaller than the resolved scales. Large-scale simulations of cosmic ray propagation in the ISM thus rely on oversimplified forms of the diffusion tensor. We take the first steps towards a more realistic description of cosmic ray diffusion for such simulations, obtaining direct estimates of the diffusion tensor from test particle simulations in random magnetic fields (with the Larmor radius scale being fully resolved), for a range of particle energies corresponding to 10-2 ≲ RL/lc ≲ 103, where lc is the magnetic correlation length. We obtain explicit expressions for the cosmic ray diffusion tensor for RL/lc ≪ 1, that might be used in a sub-grid model of cosmic ray diffusion. The diffusion coefficients obtained are closely connected with existing transport theories that include the random walk of magnetic lines.
Scalar-Tensor Black Holes Embedded in an Expanding Universe
NASA Astrophysics Data System (ADS)
Tretyakova, Daria; Latosh, Boris
2018-02-01
In this review we focus our attention on scalar-tensor gravity models and their empirical verification in terms of black hole and wormhole physics. We focus on a black hole, embedded in an expanding universe, describing both cosmological and astrophysical scales. We show that in scalar-tensor gravity it is quite common that the local geometry is isolated from the cosmological expansion, so that it does not backreact on the black hole metric. We try to extract common features of scalar-tensor black holes in an expanding universe and point out the gaps that must be filled.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sajib, Saurav Z. K.; Jeong, Woo Chul; Oh, Tong In
Anisotropy of biological tissues is a low-frequency phenomenon that is associated with the function and structure of cell membranes. Imaging of anisotropic conductivity has potential for the analysis of interactions between electromagnetic fields and biological systems, such as the prediction of current pathways in electrical stimulation therapy. To improve application to the clinical environment, precise approaches are required to understand the exact responses inside the human body subjected to the stimulated currents. In this study, we experimentally evaluate the anisotropic conductivity tensor distribution of canine brain tissues, using a recently developed diffusion tensor-magnetic resonance electrical impedance tomography method. At lowmore » frequency, electrical conductivity of the biological tissues can be expressed as a product of the mobility and concentration of ions in the extracellular space. From diffusion tensor images of the brain, we can obtain directional information on diffusive movements of water molecules, which correspond to the mobility of ions. The position dependent scale factor, which provides information on ion concentration, was successfully calculated from the magnetic flux density, to obtain the equivalent conductivity tensor. By combining the information from both techniques, we can finally reconstruct the anisotropic conductivity tensor images of brain tissues. The reconstructed conductivity images better demonstrate the enhanced signal intensity in strongly anisotropic brain regions, compared with those resulting from previous methods using a global scale factor.« less
Dynamic field theory and equations of motion in cosmology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kopeikin, Sergei M., E-mail: kopeikins@missouri.edu; Petrov, Alexander N., E-mail: alex.petrov55@gmail.com
2014-11-15
We discuss a field-theoretical approach based on general-relativistic variational principle to derive the covariant field equations and hydrodynamic equations of motion of baryonic matter governed by cosmological perturbations of dark matter and dark energy. The action depends on the gravitational and matter Lagrangian. The gravitational Lagrangian depends on the metric tensor and its first and second derivatives. The matter Lagrangian includes dark matter, dark energy and the ordinary baryonic matter which plays the role of a bare perturbation. The total Lagrangian is expanded in an asymptotic Taylor series around the background cosmological manifold defined as a solution of Einstein’s equationsmore » in the form of the Friedmann–Lemaître–Robertson–Walker (FLRW) metric tensor. The small parameter of the decomposition is the magnitude of the metric tensor perturbation. Each term of the series expansion is gauge-invariant and all of them together form a basis for the successive post-Friedmannian approximations around the background metric. The approximation scheme is covariant and the asymptotic nature of the Lagrangian decomposition does not require the post-Friedmannian perturbations to be small though computationally it works the most effectively when the perturbed metric is close enough to the background FLRW metric. The temporal evolution of the background metric is governed by dark matter and dark energy and we associate the large scale inhomogeneities in these two components as those generated by the primordial cosmological perturbations with an effective matter density contrast δρ/ρ≤1. The small scale inhomogeneities are generated by the condensations of baryonic matter considered as the bare perturbations of the background manifold that admits δρ/ρ≫1. Mathematically, the large scale perturbations are given by the homogeneous solution of the linearized field equations while the small scale perturbations are described by a particular solution of these equations with the bare stress–energy tensor of the baryonic matter. We explicitly work out the covariant field equations of the successive post-Friedmannian approximations of Einstein’s equations in cosmology and derive equations of motion of large and small scale inhomogeneities of dark matter and dark energy. We apply these equations to derive the post-Friedmannian equations of motion of baryonic matter comprising stars, galaxies and their clusters.« less
Killing Forms on the Five-Dimensional Einstein-Sasaki Y(p, q) Spaces
NASA Astrophysics Data System (ADS)
Visinescu, Mihai
2012-12-01
We present the complete set of Killing-Yano tensors on the five-dimensional Einstein-Sasaki Y(p, q) spaces. Two new Killing-Yano tensors are identified, associated with the complex volume form of the Calabi-Yau metric cone. The corresponding hidden symmetries are not anomalous and the geodesic equations are superintegrable.
Diffusion Tensor Imaging Correlates of Reading Ability in Dysfluent and Non-Impaired Readers
ERIC Educational Resources Information Center
Lebel, Catherine; Shaywitz, Bennett; Holahan, John; Shaywitz, Sally; Marchione, Karen; Beaulieu, Christian
2013-01-01
Many children and adults have specific reading disabilities; insight into the brain structure underlying these difficulties is evolving from imaging. Previous research highlights the left temporal-parietal white matter as important in reading, yet the degree of involvement of other areas remains unclear. Diffusion tensor imaging (DTI) and…
Robotic Online Path Planning on Point Cloud.
Liu, Ming
2016-05-01
This paper deals with the path-planning problem for mobile wheeled- or tracked-robot which drive in 2.5-D environments, where the traversable surface is usually considered as a 2-D-manifold embedded in a 3-D ambient space. Specially, we aim at solving the 2.5-D navigation problem using raw point cloud as input. The proposed method is independent of traditional surface parametrization or reconstruction methods, such as a meshing process, which generally has high-computational complexity. Instead, we utilize the output of 3-D tensor voting framework on the raw point clouds. The computation of tensor voting is accelerated by optimized implementation on graphics computation unit. Based on the tensor voting results, a novel local Riemannian metric is defined using the saliency components, which helps the modeling of the latent traversable surface. Using the proposed metric, we prove that the geodesic in the 3-D tensor space leads to rational path-planning results by experiments. Compared to traditional methods, the results reveal the advantages of the proposed method in terms of smoothing the robot maneuver while considering the minimum travel distance.
Liouville action as path-integral complexity: from continuous tensor networks to AdS/CFT
NASA Astrophysics Data System (ADS)
Caputa, Pawel; Kundu, Nilay; Miyaji, Masamichi; Takayanagi, Tadashi; Watanabe, Kento
2017-11-01
We propose an optimization procedure for Euclidean path-integrals that evaluate CFT wave functionals in arbitrary dimensions. The optimization is performed by minimizing certain functional, which can be interpreted as a measure of computational complexity, with respect to background metrics for the path-integrals. In two dimensional CFTs, this functional is given by the Liouville action. We also formulate the optimization for higher dimensional CFTs and, in various examples, find that the optimized hyperbolic metrics coincide with the time slices of expected gravity duals. Moreover, if we optimize a reduced density matrix, the geometry becomes two copies of the entanglement wedge and reproduces the holographic entanglement entropy. Our approach resembles a continuous tensor network renormalization and provides a concrete realization of the proposed interpretation of AdS/CFT as tensor networks. The present paper is an extended version of our earlier report arXiv:1703.00456 and includes many new results such as evaluations of complexity functionals, energy stress tensor, higher dimensional extensions and time evolutions of thermofield double states.
Surfing gravitational waves: can bigravity survive growing tensor modes?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Amendola, Luca; Könnig, Frank; Martinelli, Matteo
The theory of bigravity offers one of the simplest possibilities to describe a massive graviton while having self-accelerating cosmological solutions without a cosmological constant. However, it has been shown recently that bigravity is affected by early-time fast growing modes on the tensor sector. Here we argue that we can only trust the linear analysis up to when perturbations are in the linear regime and use a cut-off to stop the growing of the metric perturbations. This analysis, although more consistent, still leads to growing tensor modes that are unacceptably large for the theory to be compatible with measurements of themore » cosmic microwave background (CMB), both in temperature and polarization spectra. In order to suppress the growing modes and make the model compatible with CMB spectra, we find it necessary to either fine-tune the initial conditions, modify the theory or set the cut-off for the tensor perturbations of the second metric much lower than unity. Initial conditions such that the growing mode is sufficiently suppresed can be achieved in scenarios in which inflation ends at the GeV scale.« less
NASA Astrophysics Data System (ADS)
Bookstein, Fred L.
1995-08-01
Recent advances in computational geometry have greatly extended the range of neuroanatomical questions that can be approached by rigorous quantitative methods. One of the major current challenges in this area is to describe the variability of human cortical surface form and its implications for individual differences in neurophysiological functioning. Existing techniques for representation of stochastically invaginated surfaces do not conduce to the necessary parametric statistical summaries. In this paper, following a hint from David Van Essen and Heather Drury, I sketch a statistical method customized for the constraints of this complex data type. Cortical surface form is represented by its Riemannian metric tensor and averaged according to parameters of a smooth averaged surface. Sulci are represented by integral trajectories of the smaller principal strains of this metric, and their statistics follow the statistics of that relative metric. The diagrams visualizing this tensor analysis look like alligator leather but summarize all aspects of cortical surface form in between the principal sulci, the reliable ones; no flattening is required.
Gravitoelectromagnetic analogy based on tidal tensors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Costa, L. Filipe O.; Herdeiro, Carlos A. R.
2008-07-15
We propose a new approach to a physical analogy between general relativity and electromagnetism, based on tidal tensors of both theories. Using this approach we write a covariant form for the gravitational analogues of the Maxwell equations, which makes transparent both the similarities and key differences between the two interactions. The following realizations of the analogy are given. The first one matches linearized gravitational tidal tensors to exact electromagnetic tidal tensors in Minkowski spacetime. The second one matches exact magnetic gravitational tidal tensors for ultrastationary metrics to exact magnetic tidal tensors of electromagnetism in curved spaces. In the third wemore » show that our approach leads to a two-step exact derivation of Papapetrou's equation describing the force exerted on a spinning test particle. Analogous scalar invariants built from tidal tensors of both theories are also discussed.« less
Extended vector-tensor theories
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kimura, Rampei; Naruko, Atsushi; Yoshida, Daisuke, E-mail: rampei@th.phys.titech.ac.jp, E-mail: naruko@th.phys.titech.ac.jp, E-mail: yoshida@th.phys.titech.ac.jp
Recently, several extensions of massive vector theory in curved space-time have been proposed in many literatures. In this paper, we consider the most general vector-tensor theories that contain up to two derivatives with respect to metric and vector field. By imposing a degeneracy condition of the Lagrangian in the context of ADM decomposition of space-time to eliminate an unwanted mode, we construct a new class of massive vector theories where five degrees of freedom can propagate, corresponding to three for massive vector modes and two for massless tensor modes. We find that the generalized Proca and the beyond generalized Procamore » theories up to the quartic Lagrangian, which should be included in this formulation, are degenerate theories even in curved space-time. Finally, introducing new metric and vector field transformations, we investigate the properties of thus obtained theories under such transformations.« less
Vector and tensor contributions to the curvature perturbation at second order
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carrilho, Pedro; Malik, Karim A., E-mail: p.gregoriocarrilho@qmul.ac.uk, E-mail: k.malik@qmul.ac.uk
2016-02-01
We derive the evolution equation for the second order curvature perturbation using standard techniques of cosmological perturbation theory. We do this for different definitions of the gauge invariant curvature perturbation, arising from different splits of the spatial metric, and compare the expressions. The results are valid at all scales and include all contributions from scalar, vector and tensor perturbations, as well as anisotropic stress, with all our results written purely in terms of gauge invariant quantities. Taking the large-scale approximation, we find that a conserved quantity exists only if, in addition to the non-adiabatic pressure, the transverse traceless part ofmore » the anisotropic stress tensor is also negligible. We also find that the version of the gauge invariant curvature perturbation which is exactly conserved is the one defined with the determinant of the spatial part of the inverse metric.« less
NASA Technical Reports Server (NTRS)
Ni, W.-T.
1972-01-01
Metric theories of gravity are compiled and classified according to the types of gravitational fields they contain, and the modes of interaction among those fields. The gravitation theories considered are classified as (1) general relativity, (2) scalar-tensor theories, (3) conformally flat theories, and (4) stratified theories with conformally flat space slices. The post-Newtonian limit of each theory is constructed and its Parametrized Post-Newtonian (PPN) values are obtained by comparing it with Will's version of the formalism. Results obtained here, when combined with experimental data and with recent work by Nordtvedt and Will and by Ni, show that, of all theories thus far examined by our group, the only currently viable ones are general relativity, the Bergmann-Wagoner scalar-tensor theory and its special cases (Nordtvedt; Brans-Dicke-Jordan), and a recent, new vector-tensor theory by Nordtvedt, Hellings, and Will.
Quantitative analysis of hypertrophic myocardium using diffusion tensor magnetic resonance imaging
Tran, Nicholas; Giannakidis, Archontis; Gullberg, Grant T.; Seo, Youngho
2016-01-01
Abstract. Systemic hypertension is a causative factor in left ventricular hypertrophy (LVH). This study is motivated by the potential to reverse or manage the dysfunction associated with structural remodeling of the myocardium in this pathology. Using diffusion tensor magnetic resonance imaging, we present an analysis of myocardial fiber and laminar sheet orientation in ex vivo hypertrophic (6 SHR) and normal (5 WKY) rat hearts using the covariance of the diffusion tensor. First, an atlas of normal cardiac microstructure was formed using the WKY b0 images. Then, the SHR and WKY b0 hearts were registered to the atlas. The acquired deformation fields were applied to the SHR and WKY heart tensor fields followed by the preservation of principal direction (PPD) reorientation strategy. A mean tensor field was then formed from the registered WKY tensor images. Calculating the covariance of the registered tensor images about this mean for each heart, the hypertrophic myocardium exhibited significantly increased myocardial fiber derangement (p=0.017) with a mean dispersion of 38.7 deg, and an increased dispersion of the laminar sheet normal (p=0.030) of 54.8 deg compared with 34.8 deg and 51.8 deg, respectively, in the normal hearts. Results demonstrate significantly altered myocardial fiber and laminar sheet structure in rats with hypertensive LVH. PMID:27872872
Development of a Human Brain Diffusion Tensor Template
Peng, Huiling; Orlichenko, Anton; Dawe, Robert J.; Agam, Gady; Zhang, Shengwei; Arfanakis, Konstantinos
2009-01-01
The development of a brain template for diffusion tensor imaging (DTI) is crucial for comparisons of neuronal structural integrity and brain connectivity across populations, as well as for the development of a white matter atlas. Previous efforts to produce a DTI brain template have been compromised by factors related to image quality, the effectiveness of the image registration approach, the appropriateness of subject inclusion criteria, the completeness and accuracy of the information summarized in the final template. The purpose of this work was to develop a DTI human brain template using techniques that address the shortcomings of previous efforts. Therefore, data containing minimal artifacts were first obtained on 67 healthy human subjects selected from an age-group with relatively similar diffusion characteristics (20–40 years of age), using an appropriate DTI acquisition protocol. Non-linear image registration based on mean diffusion-weighted and fractional anisotropy images was employed. DTI brain templates containing median and mean tensors were produced in ICBM-152 space and made publicly available. The resulting set of DTI templates is characterized by higher image sharpness, provides the ability to distinguish smaller white matter fiber structures, contains fewer image artifacts, than previously developed templates, and to our knowledge, is one of only two templates produced based on a relatively large number of subjects. Furthermore, median tensors were shown to better preserve the diffusion characteristics at the group level than mean tensors. Finally, white matter fiber tractography was applied on the template and several fiber-bundles were traced. PMID:19341801
Development of a human brain diffusion tensor template.
Peng, Huiling; Orlichenko, Anton; Dawe, Robert J; Agam, Gady; Zhang, Shengwei; Arfanakis, Konstantinos
2009-07-15
The development of a brain template for diffusion tensor imaging (DTI) is crucial for comparisons of neuronal structural integrity and brain connectivity across populations, as well as for the development of a white matter atlas. Previous efforts to produce a DTI brain template have been compromised by factors related to image quality, the effectiveness of the image registration approach, the appropriateness of subject inclusion criteria, and the completeness and accuracy of the information summarized in the final template. The purpose of this work was to develop a DTI human brain template using techniques that address the shortcomings of previous efforts. Therefore, data containing minimal artifacts were first obtained on 67 healthy human subjects selected from an age-group with relatively similar diffusion characteristics (20-40 years of age), using an appropriate DTI acquisition protocol. Non-linear image registration based on mean diffusion-weighted and fractional anisotropy images was employed. DTI brain templates containing median and mean tensors were produced in ICBM-152 space and made publicly available. The resulting set of DTI templates is characterized by higher image sharpness, provides the ability to distinguish smaller white matter fiber structures, contains fewer image artifacts, than previously developed templates, and to our knowledge, is one of only two templates produced based on a relatively large number of subjects. Furthermore, median tensors were shown to better preserve the diffusion characteristics at the group level than mean tensors. Finally, white matter fiber tractography was applied on the template and several fiber-bundles were traced.
Croall, Iain D.; Lohner, Valerie; Moynihan, Barry; Khan, Usman; Hassan, Ahamad; O’Brien, John T.; Morris, Robin G.; Tozer, Daniel J.; Cambridge, Victoria C.; Harkness, Kirsty; Werring, David J.; Blamire, Andrew M.; Ford, Gary A.; Barrick, Thomas R.
2017-01-01
Diffusion tensor imaging (DTI) metrics such as fractional anisotropy (FA) and mean diffusivity (MD) have been proposed as clinical trial markers of cerebral small vessel disease (SVD) due to their associations with outcomes such as cognition. However, studies investigating this have been predominantly single-centre. As clinical trials are likely to be multisite, further studies are required to determine whether associations with cognition of similar strengths can be detected in a multicentre setting. One hundred and nine patients (mean age =68 years) with symptomatic lacunar infarction and confluent white matter hyperintensities (WMH) on MRI was recruited across six sites as part of the PRESERVE DTI substudy. After handling missing data, 3T-MRI scanning was available from five sites on five scanner models (Siemens and Philips), alongside neuropsychological and quality of life (QoL) assessments. FA median and MD peak height were extracted from DTI histogram analysis. Multiple linear regressions were performed, including normalized brain volume, WMH lesion load, and n° lacunes as covariates, to investigate the association of FA and MD with cognition and QoL. DTI metrics from all white matter were significantly associated with global cognition (standardized β =0.268), mental flexibility (β =0.306), verbal fluency (β =0.376), and Montreal Cognitive Assessment (MoCA) (β =0.273). The magnitudes of these associations were comparable with those previously reported from single-centre studies found in a systematic literature review. In this multicentre study, we confirmed associations between DTI parameters and cognition, which were similar in strength to those found in previous single-centre studies. The present study supports the use of DTI metrics as biomarkers of disease progression in multicentre studies. PMID:28487471
Irfanoglu, M. Okan; Walker, Lindsay; Sarlls, Joelle; Marenco, Stefano; Pierpaoli, Carlo
2013-01-01
In this work we investigate the effects of echo planar imaging (EPI) distortions on diffusion tensor imaging (DTI) based fiber tractography results. We propose a simple experimental framework that would enable assessing the effects of EPI distortions on the accuracy and reproducibility of fiber tractography from a pilot study on a few subjects. We compare trajectories computed from two diffusion datasets collected on each subject that are identical except for the orientation of phase encode direction, either right–left (RL) or anterior–posterior (AP). We define metrics to assess potential discrepancies between RL and AP trajectories in association, commissural, and projection pathways. Results from measurements on a 3 Tesla clinical scanner indicated that the effects of EPI distortions on computed fiber trajectories are statistically significant and large in magnitude, potentially leading to erroneous inferences about brain connectivity. The correction of EPI distortion using an image-based registration approach showed a significant improvement in tract consistency and accuracy. Although obtained in the context of a DTI experiment, our findings are generally applicable to all EPI-based diffusion MRI tractography investigations, including high angular resolution (HARDI) methods. On the basis of our findings, we recommend adding an EPI distortion correction step to the diffusion MRI processing pipeline if the output is to be used for fiber tractography. PMID:22401760
Diffusion MRI and its role in neuropsychology
Mueller, Bryon A; Lim, Kelvin O; Hemmy, Laura; Camchong, Jazmin
2015-01-01
Diffusion Magnetic Resonance Imaging (dMRI) is a popular method used by neuroscientists to uncover unique information about the structural connections within the brain. dMRI is a non-invasive imaging methodology in which image contrast is based on the diffusion of water molecules in tissue. While applicable to many tissues in the body, this review focuses exclusively on the use of dMRI to examine white matter in the brain. In this review, we begin with a definition of diffusion and how diffusion is measured with MRI. Next we introduce the diffusion tensor model, the predominant model used in dMRI. We then describe acquisition issues related to acquisition parameters and scanner hardware and software. Sources of artifacts are then discussed, followed by a brief review of analysis approaches. We provide an overview of the limitations of the traditional diffusion tensor model, and highlight several more sophisticated non-tensor models that better describe the complex architecture of the brain’s white matter. We then touch on reliability and validity issues of diffusion measurements. Finally, we describe examples of ways in which dMRI has been applied to studies of brain disorders and how identified alterations relate to symptomatology and cognition. PMID:26255305
Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging.
Thomas, Cibu; Sadeghi, Neda; Nayak, Amrita; Trefler, Aaron; Sarlls, Joelle; Baker, Chris I; Pierpaoli, Carlo
2018-06-01
Diurnal fluctuations in MRI measures of structural and functional properties of the brain have been reported recently. These fluctuations may have a physiological origin, since they have been detected using different MRI modalities, and cannot be explained by factors that are typically known to confound MRI measures. While preliminary evidence suggests that measures of structural properties of the brain based on diffusion tensor imaging (DTI) fluctuate as a function of time-of-day (TOD), the underlying mechanism has not been investigated. Here, we used a longitudinal within-subjects design to investigate the impact of time-of-day on DTI measures. In addition to using the conventional monoexponential tensor model to assess TOD-related fluctuations, we used a dual compartment tensor model that allowed us to directly assess if any change in DTI measures is due to an increase in CSF/free-water volume fraction or due to an increase in water diffusivity within the parenchyma. Our results show that Trace or mean diffusivity, as measured using the conventional monoexponential tensor model tends to increase systematically from morning to afternoon scans at the interface of grey matter/CSF, most prominently in the major fissures and the sulci of the brain. Interestingly, in a recent study of the glymphatic system, these same regions were found to show late enhancement after intrathecal injection of a CSF contrast agent. The increase in Trace also impacts DTI measures of diffusivity such as radial and axial diffusivity, but does not affect fractional anisotropy. The dual compartment analysis revealed that the increase in diffusivity measures from PM to AM was driven by an increase in the volume fraction of CSF-like free-water. Taken together, our findings provide important insight into the likely physiological origins of diurnal fluctuations in MRI measurements of structural properties of the brain. Published by Elsevier Inc.
Diffusion properties of NAA in human corpus callosum as studied with diffusion tensor spectroscopy.
Upadhyay, Jaymin; Hallock, Kevin; Erb, Kelley; Kim, Dae-Shik; Ronen, Itamar
2007-11-01
In diffusion tensor imaging (DTI) the anisotropic movement of water is exploited to characterize microstructure. One confounding issue of DTI is the presence of intra- and extracellular components contributing to the measured diffusivity. This causes an ambiguity in determining the underlying cause of diffusion properties, particularly the fractional anisotropy (FA). In this study an intracellular constituent, N-acetyl aspartate (NAA), was used to probe intracellular diffusion, while water molecules were used to probe the combined intra- and extracellular diffusion. NAA and water diffusion measurements were made in anterior and medial corpus callosum (CC) regions, which are referred to as R1 and R2, respectively. FA(NAA) was found to be greater than FA(Water) in both CC regions, thus indicating a higher degree of anisotropy within the intracellular space in comparison to the combined intra- and extracellular spaces. A decreasing trend in the FA of NAA and water was observed between R1 and R2, while the radial diffusivity (RD) for both molecules increased. The increase in RD(NAA) is particularly significant, thus explaining the more significant decrease in FA(NAA) between the two regions. It is suggested that diffusion tensor spectroscopy of NAA can potentially be used to further characterize microscopic anatomic organization in white matter. Copyright 2007 Wiley-Liss, Inc.
Hidden symmetries in Sasaki-Einstein geometries
NASA Astrophysics Data System (ADS)
Slesar, V.; Visinescu, M.; Vîlcu, G. E.
2017-07-01
We describe a method for constructing Killing-Yano tensors on Sasaki spaces using their geometrical properties, without the need of solving intricate generalized Killing equations. We obtain the Killing-Yano tensors on toric Sasaki-Einstein spaces using the fact that the metric cones of these spaces are Calabi-Yau manifolds which in turn are described in terms of toric data. We extend the search of Killing-Yano tensors on mixed 3-Sasakian manifolds. We illustrate the method by explicit construction of Killing forms on some spaces of current interest.
Anisotropic Mesoscale Eddy Transport in Ocean General Circulation Models
NASA Astrophysics Data System (ADS)
Reckinger, S. J.; Fox-Kemper, B.; Bachman, S.; Bryan, F.; Dennis, J.; Danabasoglu, G.
2014-12-01
Modern climate models are limited to coarse-resolution representations of large-scale ocean circulation that rely on parameterizations for mesoscale eddies. The effects of eddies are typically introduced by relating subgrid eddy fluxes to the resolved gradients of buoyancy or other tracers, where the proportionality is, in general, governed by an eddy transport tensor. The symmetric part of the tensor, which represents the diffusive effects of mesoscale eddies, is universally treated isotropically in general circulation models. Thus, only a single parameter, namely the eddy diffusivity, is used at each spatial and temporal location to impart the influence of mesoscale eddies on the resolved flow. However, the diffusive processes that the parameterization approximates, such as shear dispersion, potential vorticity barriers, oceanic turbulence, and instabilities, typically have strongly anisotropic characteristics. Generalizing the eddy diffusivity tensor for anisotropy extends the number of parameters to three: a major diffusivity, a minor diffusivity, and the principal axis of alignment. The Community Earth System Model (CESM) with the anisotropic eddy parameterization is used to test various choices for the newly introduced parameters, which are motivated by observations and the eddy transport tensor diagnosed from high resolution simulations. Simply setting the ratio of major to minor diffusivities to a value of five globally, while aligning the major axis along the flow direction, improves biogeochemical tracer ventilation and reduces global temperature and salinity biases. These effects can be improved even further by parameterizing the anisotropic transport mechanisms in the ocean.
ERIC Educational Resources Information Center
Shukla, Dinesh K.; Keehn, Brandon; Muller, Ralph-Axel
2011-01-01
Background: Previous diffusion tensor imaging (DTI) studies have shown white matter compromise in children and adults with autism spectrum disorder (ASD), which may relate to reduced connectivity and impaired function of distributed networks. However, tract-specific evidence remains limited in ASD. We applied tract-based spatial statistics (TBSS)…
ERIC Educational Resources Information Center
Shukla, Dinesh K.; Keehn, Brandon; Lincoln, Alan J.; Muller, Ralph-Axel
2010-01-01
Objective: Autism spectrum disorder (ASD) is increasingly viewed as a disorder of functional networks, highlighting the importance of investigating white matter and interregional connectivity. We used diffusion tensor imaging (DTI) to examine white matter integrity for the whole brain and for corpus callosum, internal capsule, and middle…
Prosperini, Luca; Fanelli, Fulvia; Petsas, Nikolaos; Sbardella, Emilia; Tona, Francesca; Raz, Eytan; Fortuna, Deborah; De Angelis, Floriana; Pozzilli, Carlo; Pantano, Patrizia
2014-11-01
To determine if high-intensity, task-oriented, visual feedback training with a video game balance board (Nintendo Wii) induces significant changes in diffusion-tensor imaging ( DTI diffusion-tensor imaging ) parameters of cerebellar connections and other supratentorial associative bundles and if these changes are related to clinical improvement in patients with multiple sclerosis. The protocol was approved by local ethical committee; each participant provided written informed consent. In this 24-week, randomized, two-period crossover pilot study, 27 patients underwent static posturography and brain magnetic resonance (MR) imaging at study entry, after the first 12-week period, and at study termination. Thirteen patients started a 12-week training program followed by a 12-week period without any intervention, while 14 patients received the intervention in reverse order. Fifteen healthy subjects also underwent MR imaging once and underwent static posturography. Virtual dissection of white matter tracts was performed with streamline tractography; values of DTI diffusion-tensor imaging parameters were then obtained for each dissected tract. Repeated measures analyses of variance were performed to evaluate whether DTI diffusion-tensor imaging parameters significantly changed after intervention, with false discovery rate correction for multiple hypothesis testing. There were relevant differences between patients and healthy control subjects in postural sway and DTI diffusion-tensor imaging parameters (P < .05). Significant main effects of time by group interaction for fractional anisotropy and radial diffusivity of the left and right superior cerebellar peduncles were found (F2,23 range, 5.555-3.450; P = .036-.088 after false discovery rate correction). These changes correlated with objective measures of balance improvement detected at static posturography (r = -0.381 to 0.401, P < .05). However, both clinical and DTI diffusion-tensor imaging changes did not persist beyond 12 weeks after training. Despite the low statistical power (35%) due to the small sample size, the results showed that training with the balance board system modified the microstructure of superior cerebellar peduncles. The clinical improvement observed after training might be mediated by enhanced myelination-related processes, suggesting that high-intensity, task-oriented exercises could induce favorable microstructural changes in the brains of patients with multiple sclerosis.
Seamless Warping of Diffusion Tensor Fields
Hao, Xuejun; Bansal, Ravi; Plessen, Kerstin J.; Peterson, Bradley S.
2008-01-01
To warp diffusion tensor fields accurately, tensors must be reoriented in the space to which the tensors are warped based on both the local deformation field and the orientation of the underlying fibers in the original image. Existing algorithms for warping tensors typically use forward mapping deformations in an attempt to ensure that the local deformations in the warped image remains true to the orientation of the underlying fibers; forward mapping, however, can also create “seams” or gaps and consequently artifacts in the warped image by failing to define accurately the voxels in the template space where the magnitude of the deformation is large (e.g., |Jacobian| > 1). Backward mapping, in contrast, defines voxels in the template space by mapping them back to locations in the original imaging space. Backward mapping allows every voxel in the template space to be defined without the creation of seams, including voxels in which the deformation is extensive. Backward mapping, however, cannot reorient tensors in the template space because information about the directional orientation of fiber tracts is contained in the original, unwarped imaging space only, and backward mapping alone cannot transfer that information to the template space. To combine the advantages of forward and backward mapping, we propose a novel method for the spatial normalization of diffusion tensor (DT) fields that uses a bijection (a bidirectional mapping with one-to-one correspondences between image spaces) to warp DT datasets seamlessly from one imaging space to another. Once the bijection has been achieved and tensors have been correctly relocated to the template space, we can appropriately reorient tensors in the template space using a warping method based on Procrustean estimation. PMID:18334425
White matter tractography using diffusion tensor deflection.
Lazar, Mariana; Weinstein, David M; Tsuruda, Jay S; Hasan, Khader M; Arfanakis, Konstantinos; Meyerand, M Elizabeth; Badie, Benham; Rowley, Howard A; Haughton, Victor; Field, Aaron; Alexander, Andrew L
2003-04-01
Diffusion tensor MRI provides unique directional diffusion information that can be used to estimate the patterns of white matter connectivity in the human brain. In this study, the behavior of an algorithm for white matter tractography is examined. The algorithm, called TEND, uses the entire diffusion tensor to deflect the estimated fiber trajectory. Simulations and imaging experiments on in vivo human brains were performed to investigate the behavior of the tractography algorithm. The simulations show that the deflection term is less sensitive than the major eigenvector to image noise. In the human brain imaging experiments, estimated tracts were generated in corpus callosum, corticospinal tract, internal capsule, corona radiata, superior longitudinal fasciculus, inferior longitudinal fasciculus, fronto-occipital fasciculus, and uncinate fasciculus. This approach is promising for mapping the organizational patterns of white matter in the human brain as well as mapping the relationship between major fiber trajectories and the location and extent of brain lesions. Copyright 2003 Wiley-Liss, Inc.
The importance of correcting for signal drift in diffusion MRI.
Vos, Sjoerd B; Tax, Chantal M W; Luijten, Peter R; Ourselin, Sebastien; Leemans, Alexander; Froeling, Martijn
2017-01-01
To investigate previously unreported effects of signal drift as a result of temporal scanner instability on diffusion MRI data analysis and to propose a method to correct this signal drift. We investigated the signal magnitude of non-diffusion-weighted EPI volumes in a series of diffusion-weighted imaging experiments to determine whether signal magnitude changes over time. Different scan protocols and scanners from multiple vendors were used to verify this on phantom data, and the effects on diffusion kurtosis tensor estimation in phantom and in vivo data were quantified. Scalar metrics (eigenvalues, fractional anisotropy, mean diffusivity, mean kurtosis) and directional information (first eigenvectors and tractography) were investigated. Signal drift, a global signal decrease with subsequently acquired images in the scan, was observed in phantom data on all three scanners, with varying magnitudes up to 5% in a 15-min scan. The signal drift has a noticeable effect on the estimation of diffusion parameters. All investigated quantitative parameters as well as tractography were affected by this artifactual signal decrease during the scan. By interspersing the non-diffusion-weighted images throughout the session, the signal decrease can be estimated and compensated for before data analysis; minimizing the detrimental effects on subsequent MRI analyses. Magn Reson Med 77:285-299, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Rational first integrals of geodesic equations and generalised hidden symmetries
NASA Astrophysics Data System (ADS)
Aoki, Arata; Houri, Tsuyoshi; Tomoda, Kentaro
2016-10-01
We discuss novel generalisations of Killing tensors, which are introduced by considering rational first integrals of geodesic equations. We introduce the notion of inconstructible generalised Killing tensors, which cannot be constructed from ordinary Killing tensors. Moreover, we introduce inconstructible rational first integrals, which are constructed from inconstructible generalised Killing tensors, and provide a method for checking the inconstructibility of a rational first integral. Using the method, we show that the rational first integral of the Collinson-O’Donnell solution is not inconstructible. We also provide several examples of metrics admitting an inconstructible rational first integral in two and four-dimensions, by using the Maciejewski-Przybylska system. Furthermore, we attempt to generalise other hidden symmetries such as Killing-Yano tensors.
Salama, Gayle R; Heier, Linda A; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John
2017-01-01
In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.
Salama, Gayle R.; Heier, Linda A.; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John
2018-01-01
In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes. PMID:29403420
Lanzafame, S; Giannelli, M; Garaci, F; Floris, R; Duggento, A; Guerrisi, M; Toschi, N
2016-05-01
An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter. The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms. DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine. Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines.
Fast and Analytical EAP Approximation from a 4th-Order Tensor.
Ghosh, Aurobrata; Deriche, Rachid
2012-01-01
Generalized diffusion tensor imaging (GDTI) was developed to model complex apparent diffusivity coefficient (ADC) using higher-order tensors (HOTs) and to overcome the inherent single-peak shortcoming of DTI. However, the geometry of a complex ADC profile does not correspond to the underlying structure of fibers. This tissue geometry can be inferred from the shape of the ensemble average propagator (EAP). Though interesting methods for estimating a positive ADC using 4th-order diffusion tensors were developed, GDTI in general was overtaken by other approaches, for example, the orientation distribution function (ODF), since it is considerably difficult to recuperate the EAP from a HOT model of the ADC in GDTI. In this paper, we present a novel closed-form approximation of the EAP using Hermite polynomials from a modified HOT model of the original GDTI-ADC. Since the solution is analytical, it is fast, differentiable, and the approximation converges well to the true EAP. This method also makes the effort of computing a positive ADC worthwhile, since now both the ADC and the EAP can be used and have closed forms. We demonstrate our approach with 4th-order tensors on synthetic data and in vivo human data.
Fast and Analytical EAP Approximation from a 4th-Order Tensor
Ghosh, Aurobrata; Deriche, Rachid
2012-01-01
Generalized diffusion tensor imaging (GDTI) was developed to model complex apparent diffusivity coefficient (ADC) using higher-order tensors (HOTs) and to overcome the inherent single-peak shortcoming of DTI. However, the geometry of a complex ADC profile does not correspond to the underlying structure of fibers. This tissue geometry can be inferred from the shape of the ensemble average propagator (EAP). Though interesting methods for estimating a positive ADC using 4th-order diffusion tensors were developed, GDTI in general was overtaken by other approaches, for example, the orientation distribution function (ODF), since it is considerably difficult to recuperate the EAP from a HOT model of the ADC in GDTI. In this paper, we present a novel closed-form approximation of the EAP using Hermite polynomials from a modified HOT model of the original GDTI-ADC. Since the solution is analytical, it is fast, differentiable, and the approximation converges well to the true EAP. This method also makes the effort of computing a positive ADC worthwhile, since now both the ADC and the EAP can be used and have closed forms. We demonstrate our approach with 4th-order tensors on synthetic data and in vivo human data. PMID:23365552
ERIC Educational Resources Information Center
Hanaie, Ryuzo; Mohri, Ikuko; Kagitani-Shimono, Kuriko; Tachibana, Masaya; Matsuzaki, Junko; Watanabe, Yoshiyuki; Fujita, Norihiko; Taniike, Masako
2014-01-01
In addition to social and communicative deficits, many studies have reported motor deficits in autism spectrum disorder (ASD). This study investigated the macro and microstructural properties of the corpus callosum (CC) of 18 children with ASD and 12 typically developing controls using diffusion tensor imaging tractography. We aimed to explore…
An introduction to diffusion tensor image analysis.
O'Donnell, Lauren J; Westin, Carl-Fredrik
2011-04-01
Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses. Copyright © 2011 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Versace, Amelia; Ladouceur, Cecile D.; Romero, Soledad; Birmaher, Boris; Axelson, David A.; Kupfer, David J.; Phillips, Mary L.
2010-01-01
Objective: To study white matter (WM) development in youth at high familial risk for bipolar disorder (BD). WM alterations are reported in youth and adults with BD. WM undergoes important maturational changes in adolescence. Age-related changes in WM microstructure using diffusion tensor imaging with tract-based spatial statistics in healthy…
ERIC Educational Resources Information Center
Familiari, Giuseppe; Relucenti, Michela; Heyn, Rosemarie; Baldini, Rossella; D'Andrea, Giancarlo; Familiari, Pietro; Bozzao, Alessandro; Raco, Antonino
2013-01-01
Neuroanatomy is considered to be one of the most difficult anatomical subjects for students. To provide motivation and improve learning outcomes in this area, clinical cases and neurosurgical images from diffusion tensor imaging (DTI) tractographies produced using an intraoperative magnetic resonance imaging apparatus (MRI/DTI) were presented and…
Volume illustration of muscle from diffusion tensor images.
Chen, Wei; Yan, Zhicheng; Zhang, Song; Crow, John Allen; Ebert, David S; McLaughlin, Ronald M; Mullins, Katie B; Cooper, Robert; Ding, Zi'ang; Liao, Jun
2009-01-01
Medical illustration has demonstrated its effectiveness to depict salient anatomical features while hiding the irrelevant details. Current solutions are ineffective for visualizing fibrous structures such as muscle, because typical datasets (CT or MRI) do not contain directional details. In this paper, we introduce a new muscle illustration approach that leverages diffusion tensor imaging (DTI) data and example-based texture synthesis techniques. Beginning with a volumetric diffusion tensor image, we reformulate it into a scalar field and an auxiliary guidance vector field to represent the structure and orientation of a muscle bundle. A muscle mask derived from the input diffusion tensor image is used to classify the muscle structure. The guidance vector field is further refined to remove noise and clarify structure. To simulate the internal appearance of the muscle, we propose a new two-dimensional example based solid texture synthesis algorithm that builds a solid texture constrained by the guidance vector field. Illustrating the constructed scalar field and solid texture efficiently highlights the global appearance of the muscle as well as the local shape and structure of the muscle fibers in an illustrative fashion. We have applied the proposed approach to five example datasets (four pig hearts and a pig leg), demonstrating plausible illustration and expressiveness.
The tensor distribution function.
Leow, A D; Zhu, S; Zhan, L; McMahon, K; de Zubicaray, G I; Meredith, M; Wright, M J; Toga, A W; Thompson, P M
2009-01-01
Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.
Snow, Nicholas J; Peters, Sue; Borich, Michael R; Shirzad, Navid; Auriat, Angela M; Hayward, Kathryn S; Boyd, Lara A
2016-01-15
Diffusion-weighted magnetic resonance imaging (DW-MRI) is commonly used to assess white matter properties after stroke. Novel work is utilizing constrained spherical deconvolution (CSD) to estimate complex intra-voxel fiber architecture unaccounted for with tensor-based fiber tractography. However, the reliability of CSD-based tractography has not been established in people with chronic stroke. Establishing the reliability of CSD-based DW-MRI in chronic stroke. High-resolution DW-MRI was performed in ten adults with chronic stroke during two separate sessions. Deterministic region of interest-based fiber tractography using CSD was performed by two raters. Mean fractional anisotropy (FA), apparent diffusion coefficient (ADC), tract number, and tract volume were extracted from reconstructed fiber pathways in the corticospinal tract (CST) and superior longitudinal fasciculus (SLF). Callosal fiber pathways connecting the primary motor cortices were also evaluated. Inter-rater and test-retest reliability were determined by intra-class correlation coefficients (ICCs). ICCs revealed excellent reliability for FA and ADC in ipsilesional (0.86-1.00; p<0.05) and contralesional hemispheres (0.94-1.00; p<0.0001), for CST and SLF fibers; and excellent reliability for all metrics in callosal fibers (0.85-1.00; p<0.05). ICC ranged from poor to excellent for tract number and tract volume in ipsilesional (-0.11 to 0.92; p≤0.57) and contralesional hemispheres (-0.27 to 0.93; p≤0.64), for CST and SLF fibers. Like other select DW-MRI approaches, CSD-based tractography is a reliable approach to evaluate FA and ADC in major white matter pathways, in chronic stroke. Future work should address the reproducibility and utility of CSD-based metrics of tract number and tract volume. Copyright © 2015 Elsevier B.V. All rights reserved.
A no-hair theorem for black holes in f(R) gravity
NASA Astrophysics Data System (ADS)
Cañate, Pedro
2018-01-01
In this work we present a no-hair theorem which discards the existence of four-dimensional asymptotically flat, static and spherically symmetric or stationary axisymmetric, non-trivial black holes in the frame of f(R) gravity under metric formalism. Here we show that our no-hair theorem also can discard asymptotic de Sitter stationary and axisymmetric non-trivial black holes. The novelty is that this no-hair theorem is built without resorting to known mapping between f(R) gravity and scalar–tensor theory. Thus, an advantage will be that our no-hair theorem applies as well to metric f(R) models that cannot be mapped to scalar–tensor theory.
Separation of specular and diffuse components using tensor voting in color images.
Nguyen, Tam; Vo, Quang Nhat; Yang, Hyung-Jeong; Kim, Soo-Hyung; Lee, Guee-Sang
2014-11-20
Most methods for the detection and removal of specular reflections suffer from nonuniform highlight regions and/or nonconverged artifacts induced by discontinuities in the surface colors, especially when dealing with highly textured, multicolored images. In this paper, a novel noniterative and predefined constraint-free method based on tensor voting is proposed to detect and remove the highlight components of a single color image. The distribution of diffuse and specular pixels in the original image is determined using tensors' saliency analysis, instead of comparing color information among neighbor pixels. The achieved diffuse reflectance distribution is used to remove specularity components. The proposed method is evaluated quantitatively and qualitatively over a dataset of highly textured, multicolor images. The experimental results show that our result outperforms other state-of-the-art techniques.
ERIC Educational Resources Information Center
Marin Quintero, Maider J.
2013-01-01
The structure tensor for vector valued images is most often defined as the average of the scalar structure tensors in each band. The problem with this definition is the assumption that all bands provide the same amount of edge information giving them the same weights. As a result non-edge pixels can be reinforced and edges can be weakened…
Diffusion tensor imaging in evaluation of human skeletal muscle injury.
Zaraiskaya, Tatiana; Kumbhare, Dinesh; Noseworthy, Michael D
2006-08-01
To explore the capability and reliability of diffusion tensor magnetic resonance imaging (DTI) in the evaluation of human skeletal muscle injury. DTI of four patients with gastrocnemius and soleus muscles injuries was compared to eight healthy controls. Imaging was performed using a GE 3.0T short-bore scanner. A diffusion-weighted 2D spin echo echo-planar imaging (EPI) pulse sequence optimized for skeletal muscle was used. From a series of axially acquired diffusion tensor images the diffusion tensor eigenparameters (eigenvalues and eigenvectors), fractional anisotropy (FA), and apparent diffusion coefficient (ADC) were calculated and compared for injured and healthy calf muscles. Two dimensional (2D) projection maps of the principal eigenvectors were plotted to visualize the healthy and pathologic muscle fiber architectures. Clear differences in FA and ADC were observed in injured skeletal muscle, compared to healthy controls. Mean control FA was 0.23 +/- 0.02 for medial and lateral gastrocnemius (mg and lg) muscles, and 0.20 +/- 0.02 for soleus (sol) muscles. In all patients FA values were reduced compared to controls, to as low as 0.08 +/- 0.02. The ADC in controls ranged from 1.41 to 1.31 x 10(-9) m(2)/second, while in patients this was consistently higher. The 2D projection maps revealed muscle fiber disorder in injured calves, while in healthy controls the 2D projection maps show a well organized (ordered) fiber structure. DTI is a suitable method to assess human calf muscle injury.
Sharp metric obstructions for quasi-Einstein metrics
NASA Astrophysics Data System (ADS)
Case, Jeffrey S.
2013-02-01
Using the tractor calculus to study smooth metric measure spaces, we adapt results of Gover and Nurowski to give sharp metric obstructions to the existence of quasi-Einstein metrics on suitably generic manifolds. We do this by introducing an analogue of the Weyl tractor W to the setting of smooth metric measure spaces. The obstructions we obtain can be realized as tensorial invariants which are polynomial in the Riemann curvature tensor and its divergence. By taking suitable limits of their tensorial forms, we then find obstructions to the existence of static potentials, generalizing to higher dimensions a result of Bartnik and Tod, and to the existence of potentials for gradient Ricci solitons.
Comparison of Single-Shot Echo-Planar and Line Scan Protocols for Diffusion Tensor Imaging1
Kubicki, Marek; Maier, Stephan E.; Westin, Carl-Frederik; Mamata, Hatsuho; Ersner-Hershfield, Hal; Estepar, Raul; Kikinis, Ron; Jolesz, Ferenc A.
2009-01-01
Rationale and Objectives Both single-shot diffusion-weighted echo-planar imaging (EPI) and line scan diffusion imaging (LSDI) can be used to obtain magnetic resonance diffusion tensor data and to calculate directionally invariant diffusion anisotropy indices, ie, indirect measures of the organization and coherence of white matter fibers in the brain. To date, there has been no comparison of EPI and LSDI. Because EPI is the most commonly used technique for acquiring diffusion tensor data, it is important to understand the limitations and advantages of LSDI relative to EPI. Materials and Methods Five healthy volunteers underwent EPI and LSDI diffusion on a 1.5 Tesla magnet (General Electric Medical Systems, Milwaukee, WI). Four-mm thick coronal sections, covering the entire brain, were obtained. In addition, one subject was tested with both sequences over four sessions. For each image voxel, eigenvectors and eigenvalues of the diffusion tensor were calculated, and fractional anisotropy (FA) was derived. Several regions of interest were delineated, and for each, mean FA and estimated mean standard deviation were calculated and compared. Results Results showed no significant differences between EPI and LSDI for mean FA for the five subjects. When inter-session reproducibility for one subject was evaluated, there was a significant difference between EPI and LSDI in FA for the corpus callosum and the right uncinate fasciculus. Moreover, errors associated with each FA measure were larger for EPI than for LSDI. Conclusion Results indicate that both EPI- and LSDI-derived FA measures are sufficiently robust. However, when higher accuracy is needed, LSDI provides smaller error and smaller inter-subject and inter-session variability than EPI. PMID:14974598
Teruel, Jose R; Goa, Pål E; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F
2016-05-01
To compare "standard" diffusion weighted imaging, and diffusion tensor imaging (DTI) of 2(nd) and 4(th) -order for the differentiation of malignant and benign breast lesions. Seventy-one patients were imaged at 3 Tesla with a 16-channel breast coil. A diffusion weighted MRI sequence including b = 0 and b = 700 in 30 directions was obtained for all patients. The image data were fitted to three different diffusion models: isotropic model - apparent diffusion coefficient (ADC), 2(nd) -order tensor model (the standard model used for DTI) and a 4(th) -order tensor model, with increased degrees of freedom to describe anisotropy. The ability of the fitted parameters in the different models to differentiate between malignant and benign tumors was analyzed. Seventy-two breast lesions were analyzed, out of which 38 corresponded to malignant and 34 to benign tumors. ADC (using any model) presented the highest discriminative ability of malignant from benign tumors with a receiver operating characteristic area under the curve (AUC) of 0.968, and sensitivity and specificity of 94.1% and 94.7% respectively for a 1.33 × 10(-3) mm(2) /s cutoff. Anisotropy measurements presented high statistical significance between malignant and benign tumors (P < 0.001), but with lower discriminative ability of malignant from benign tumors than ADC (AUC of 0.896 and 0.897 for fractional anisotropy and generalized anisotropy respectively). Statistical significant difference was found between generalized anisotropy and fractional anisotropy for cancers (P < 0.001) but not for benign lesions (P = 0.87). While anisotropy parameters have the potential to provide additional value for breast applications as demonstrated in this study, ADC exhibited the highest differentiation power between malignant and benign breast tumors. © 2015 Wiley Periodicals, Inc.
Correlations of diffusion tensor imaging values and symptom scores in patients with schizophrenia.
Michael, Andrew M; Calhoun, Vince D; Pearlson, Godfrey D; Baum, Stefi A; Caprihan, Arvind
2008-01-01
Abnormalities in white matter (WM) brain regions are attributed as a possible biomarker for schizophrenia (SZ). Diffusion tensor imaging (DTI) is used to capture WM tracts. Psychometric tests that evaluate the severity of symptoms of SZ are clinically used in the diagnosis process. In this study we investigate the correlates of scalar DTI measures, such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity with behavioral test scores. The correlations were found by different schemes: mean correlation with WM atlas regions and multiple regression of DTI values with test scores. The corpus callosum, superior longitudinal fasciculus right and inferior longitudinal fasciculus left were found to be having high correlations with test scores.
Sun, Yu; Chen, Yu; Lee, Renick; Bezerianos, Anastasios; Collinson, Simon L; Sim, Kang
2016-03-01
Despite convergent neuroimaging evidence indicating a wide range of brain abnormalities in schizophrenia, our understanding of alterations in the topological architecture of brain anatomical networks and how they are modulated over time, is still rudimentary. Here, we employed graph theoretical analysis of longitudinal diffusion tensor imaging data (DTI) over a 5-year period to investigate brain network topology in schizophrenia and its relationship with clinical manifestations of the illness. Using deterministic tractography, weighted brain anatomical networks were constructed from 31 patients experiencing schizophrenia and 28 age- and gender-matched healthy control subjects. Although the overall small-world characteristics were observed at both baseline and follow-up, a scan-point independent significant deficit of global integration was found in patients compared to controls, suggesting dysfunctional integration of the brain and supporting the notion of schizophrenia as a disconnection syndrome. Specifically, several brain regions (e.g., the inferior frontal gyrus and the bilateral insula) that are crucial for cognitive and emotional integration were aberrant. Furthermore, a significant group-by-longitudinal scan interaction was revealed in the characteristic path length and global efficiency, attributing to a progressive aberration of global integration in patients compared to healthy controls. Moreover, the progressive disruptions of the brain anatomical network topology were associated with the clinical symptoms of the patients. Together, our findings provide insights into the substrates of anatomical dysconnectivity patterns for schizophrenia and highlight the potential for connectome-based metrics as neural markers of illness progression and clinical change with treatment. Copyright © 2016 Elsevier B.V. All rights reserved.
Kim, Jinna
2010-01-01
Purpose Diffusion tensor imaging provides better understanding of pathophysiology of congenital anomalies, involving central nervous system. This study was aimed to specify the pathogenetic mechanism of heterotopia, proved by diffusion tensor imaging, and establish new findings of heterotopia on fractional anisotropy maps. Materials and Methods Diffusion-weighted imaging data from 11 patients (M : F = 7 : 4, aged from 1 to 22 years, mean = 12.3 years) who visited the epilepsy clinic and received a routine seizure protocol MRI exam were retrospectively analyzed. Fractional anisotropy (FA) maps were generated from diffusion tensor imaging of 11 patients with heterotopia. Regions of interests (ROI) were placed in cerebral cortex, heterotopic gray matter and deep gray matter, including putamen. ANOVA analysis was performed for comparison of different gray matter tissues. Results Heterotopic gray matter showed signal intensities similar to normal gray matter on T1 and T2 weighted MRI. The measured FA of heterotopic gray matter was higher than that of cortical gray matter (0.236 ± 0.011 vs. 0.169 ± 0.015, p < 0.01, one way ANOVA), and slightly lower than that of deep gray matter (0.236 ± 0.011 vs. 0.259 ± 0.016, p < 0.01). Conclusion Increased FA of heterotopic gray matter suggests arrested neuron during radial migration and provides better understanding of neurodevelopment. PMID:20499428
ERIC Educational Resources Information Center
Rose, Jessica; Mirmiran, Majid; Butler, Erin E.; Lin, Cindy Y.; Barnes, Patrick D.; Kermoian, Rosanne; Stevenson, David K.
2007-01-01
Neonatal microstructural development in the posterior limbs of the internal capsule (PLIC) was assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA) in 24 very-low-birthweight preterm infants at 37 weeks' gestational age and compared with the children's gait and motor deficits at 4 years of age. There were 14 participants with…
Malyarenko, Dariya I; Ross, Brian D; Chenevert, Thomas L
2014-03-01
Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Copyright © 2013 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Miyaguchi, Tomoshige
2017-10-01
There have been increasing reports that the diffusion coefficient of macromolecules depends on time and fluctuates randomly. Here a method is developed to elucidate this fluctuating diffusivity from trajectory data. Time-averaged mean-square displacement (MSD), a common tool in single-particle-tracking (SPT) experiments, is generalized to a second-order tensor with which both magnitude and orientation fluctuations of the diffusivity can be clearly detected. This method is used to analyze the center-of-mass motion of four fundamental polymer models: the Rouse model, the Zimm model, a reptation model, and a rigid rodlike polymer. It is found that these models exhibit distinctly different types of magnitude and orientation fluctuations of diffusivity. This is an advantage of the present method over previous ones, such as the ergodicity-breaking parameter and a non-Gaussian parameter, because with either of these parameters it is difficult to distinguish the dynamics of the four polymer models. Also, the present method of a time-averaged MSD tensor could be used to analyze trajectory data obtained in SPT experiments.
Tissue signature characterisation of diffusion tensor abnormalities in cerebral gliomas.
Price, Stephen J; Peña, Alonso; Burnet, Neil G; Jena, Raj; Green, Hadrian A L; Carpenter, T Adrian; Pickard, John D; Gillard, Jonathan H
2004-10-01
The inherent invasiveness of malignant cells is a major determinant of the poor prognosis of cerebral gliomas. Diffusion tensor MRI (DTI) can identify white matter abnormalities in gliomas that are not seen on conventional imaging. By breaking down DTI into its isotropic (p) and anisotropic (q) components, we can determine tissue diffusion "signatures". In this study we have characterised these abnormalities in peritumoural white matter tracts. Thirty-five patients with cerebral gliomas and seven normal volunteers were imaged with DTI and T2-weighted sequences at 3 T. Displaced, infiltrated and disrupted white matter tracts were identified using fractional anisotropy (FA) maps and directionally encoded colour maps and characterised using tissue signatures. The diffusion tissue signatures were normal in ROIs where the white matter was displaced. Infiltrated white matter was characterised by an increase in the isotropic component of the tensor (p) and a less marked reduction of the anisotropic component (q). In disrupted white matter tracts, there was a marked reduction in q and increase in p. The direction of water diffusion was grossly abnormal in these cases. Diffusion tissue signatures may be a useful method of assessing occult white matter infiltration. Copyright 2004 Springer-Verlag
A new formulation of the dispersion tensor in homogeneous porous media
NASA Astrophysics Data System (ADS)
Valdés-Parada, Francisco J.; Lasseux, Didier; Bellet, Fabien
2016-04-01
Dispersion is the result of two mass transport processes, namely molecular diffusion, which is a pure mixing effect and hydrodynamic dispersion, which combines mixing and spreading. The identification of each contribution is crucial and is often misinterpreted. Traditionally, under a volume averaging framework, a single closure problem is solved and the resulting fields are substituted into diffusive and dispersive filters. However the diffusive filter (that leads to the effective diffusivity) allows passing information from convection, which leads to an incorrect definition of the effective medium coefficients composing the total dispersion tensor. In this work, we revisit the definitions of the effective diffusivity and hydrodynamic dispersion tensors using the method of volume averaging. Our analysis shows that, in the context of laminar flow with or without inertial effects, two closure problems need to be computed in order to correctly define the corresponding effective medium coefficients. The first closure problem is associated to momentum transport and needs to be solved for a prescribed Reynolds number and flow orientation. The second closure problem is related to mass transport and it is solved first with a zero Péclet number and second with the required Péclet number and flow orientation. All the closure problems are written using closure variables only as required by the upscaling method. The total dispersion tensor is shown to depend on the microstructure, macroscopic flow angles, the cell (or pore) Péclet number and the cell (or pore) Reynolds number. It is non-symmetric in the general case. The condition for quasi-symmetry is highlighted. The functionality of the longitudinal and transverse components of this tensor with the flow angle is investigated for a 2D model porous structure obtaining consistent results with previous studies.
Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J
2017-01-01
Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D , observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄ . When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model.
Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J.
2017-01-01
Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D, observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄. When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model. PMID:28989561
Kocevar, Gabriel; Stamile, Claudio; Hannoun, Salem; Cotton, François; Vukusic, Sandra; Durand-Dubief, Françoise; Sappey-Marinier, Dominique
2016-01-01
Purpose: In this work, we introduce a method to classify Multiple Sclerosis (MS) patients into four clinical profiles using structural connectivity information. For the first time, we try to solve this question in a fully automated way using a computer-based method. The main goal is to show how the combination of graph-derived metrics with machine learning techniques constitutes a powerful tool for a better characterization and classification of MS clinical profiles. Materials and Methods: Sixty-four MS patients [12 Clinical Isolated Syndrome (CIS), 24 Relapsing Remitting (RR), 24 Secondary Progressive (SP), and 17 Primary Progressive (PP)] along with 26 healthy controls (HC) underwent MR examination. T1 and diffusion tensor imaging (DTI) were used to obtain structural connectivity matrices for each subject. Global graph metrics, such as density and modularity, were estimated and compared between subjects' groups. These metrics were further used to classify patients using tuned Support Vector Machine (SVM) combined with Radial Basic Function (RBF) kernel. Results: When comparing MS patients to HC subjects, a greater assortativity, transitivity, and characteristic path length as well as a lower global efficiency were found. Using all graph metrics, the best F -Measures (91.8, 91.8, 75.6, and 70.6%) were obtained for binary (HC-CIS, CIS-RR, RR-PP) and multi-class (CIS-RR-SP) classification tasks, respectively. When using only one graph metric, the best F -Measures (83.6, 88.9, and 70.7%) were achieved for modularity with previous binary classification tasks. Conclusion: Based on a simple DTI acquisition associated with structural brain connectivity analysis, this automatic method allowed an accurate classification of different MS patients' clinical profiles.
Damion, Robin A.; Radjenovic, Aleksandra; Ingham, Eileen; Jin, Zhongmin; Ries, Michael E.
2013-01-01
We develop a curvilinear invariant set of the diffusion tensor which may be applied to Diffusion Tensor Imaging measurements on tissues and porous media. This new set is an alternative to the more common invariants such as fractional anisotropy and the diffusion mode. The alternative invariant set possesses a different structure to the other known invariant sets; the second and third members of the curvilinear set measure the degree of orthotropy and oblateness/prolateness, respectively. The proposed advantage of these invariants is that they may work well in situations of low diffusion anisotropy and isotropy, as is often observed in tissues such as cartilage. We also explore the other orthogonal invariant sets in terms of their geometry in relation to eigenvalue space; a cylindrical set, a spherical set (including fractional anisotropy and the mode), and a log-Euclidean set. These three sets have a common structure. The first invariant measures the magnitude of the diffusion, the second and third invariants capture aspects of the anisotropy; the magnitude of the anisotropy and the shape of the diffusion ellipsoid (the manner in which the anisotropy is realised). We also show a simple method to prove the orthogonality of the invariants within a set. PMID:24244366
Birkhoff theorem and conformal Killing-Yano tensors
NASA Astrophysics Data System (ADS)
Ferrando, Joan Josep; Sáez, Juan Antonio
2015-06-01
We analyze the main geometric conditions imposed by the hypothesis of the Jebsen-Birkhoff theorem. We show that the result (existence of an additional Killing vector) does not necessarily require a three-dimensional isometry group on two-dimensional orbits but only the existence of a conformal Killing-Yano tensor. In this approach the (additional) isometry appears as the known invariant Killing vector that the -metrics admit.
Heterotic reduction of Courant algebroid connections and Einstein-Hilbert actions
NASA Astrophysics Data System (ADS)
Jurčo, Branislav; Vysoký, Jan
2016-08-01
We discuss Levi-Civita connections on Courant algebroids. We define an appropriate generalization of the curvature tensor and compute the corresponding scalar curvatures in the exact and heterotic case, leading to generalized (bosonic) Einstein-Hilbert type of actions known from supergravity. In particular, we carefully analyze the process of the reduction for the generalized metric, connection, curvature tensor and the scalar curvature.
Newlander, Shawn M; Chu, Alan; Sinha, Usha S; Lu, Po H; Bartzokis, George
2014-02-01
To identify regional differences in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) using customized preprocessing before voxel-based analysis (VBA) in 14 normal subjects with the specific genes that decrease (apolipoprotein [APO] E ε2) and that increase (APOE ε4) the risk of Alzheimer's disease. Diffusion tensor images (DTI) acquired at 1.5 Tesla were denoised with a total variation tensor regularization algorithm before affine and nonlinear registration to generate a common reference frame for the image volumes of all subjects. Anisotropic and isotropic smoothing with varying kernel sizes was applied to the aligned data before VBA to determine regional differences between cohorts segregated by allele status. VBA on the denoised tensor data identified regions of reduced FA in APOE ε4 compared with the APOE ε2 healthy older carriers. The most consistent results were obtained using the denoised tensor and anisotropic smoothing before statistical testing. In contrast, isotropic smoothing identified regional differences for small filter sizes alone, emphasizing that this method introduces bias in FA values for higher kernel sizes. Voxel-based DTI analysis can be performed on low signal to noise ratio images to detect subtle regional differences in cohorts using the proposed preprocessing techniques. Copyright © 2013 Wiley Periodicals, Inc.
2016-10-01
including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and...SUBJECT TERMS Gulf war illness; magnetic resonance imaging; dopamine; diffusion tensor imaging 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...nigra, basal ganglia and cortex as markers of integrity of the nigro-striatal dopaminergic pathway using high resolution diffusion tensor imaging (DTI
BRIEF COMMUNICATION: A note on the Coulomb collision operator in curvilinear coordinates
NASA Astrophysics Data System (ADS)
Goncharov, P. R.
2010-10-01
The dynamic friction force, diffusion tensor, flux density in velocity space and Coulomb collision term are expressed in curvilinear coordinates via Trubnikov potential functions corresponding to each species of a background plasma. For comparison, explicit formulae are given for the dynamic friction force, diffusion tensor and collisional flux density in velocity space in curvilinear coordinates via Rosenbluth potential functions summed over all species of the background plasma.
ERIC Educational Resources Information Center
Pina-Camacho, Laura; Villero, Sonia; Fraguas, David; Boada, Leticia; Janssen, Joost; Navas-Sanchez, Francisco J.; Mayoral, Maria; Llorente, Cloe; Arango, Celso; Parellada, Mara
2012-01-01
A systematic review of 208 studies comprising functional magnetic resonance imaging and diffusion tensor imaging data in patients with "autism spectrum disorder" (ASD) was conducted, in order to determine whether these data support the forthcoming DSM-5 proposal of a social communication and behavioral symptom dyad. Studies consistently reported…
Jang, Sung Ho; Lee, Han Do
2014-12-01
This study reports on a patient with an intracerebral hemorrhage who showed recovery of an injured arcuate fasciculus (AF) in the dominant hemisphere, using follow-up diffusion tensor tractography. A 43-year-old right-handed man presented with severe aphasia and hemiparesis resulting from a spontaneous intracerebral hemorrhage in the left parietotemporal lobes. The patient showed severe aphasia at 1 month after onset, with an aphasia quotient of 5% on the Korean-Western Aphasia Battery. He underwent comprehensive rehabilitative therapy until 22 months after onset and his aphasia showed improvement, with an aphasia quotient of 58% on the Korean-Western Aphasia Battery. On 1-month diffusion tensor tractography, only the thin ascending part of the left AF from the Wernicke area remained. In contrast, on 16-month diffusion tensor tractography, the injured left AF was thickened and elongated to around the left Broca area; however, discontinuation of the left AF was observed around the left Broca area, and this continuation was elongated to the left Broca area on 22-month diffusion tensor tractography. This study reports on a patient who showed recovery from injury of the left AF along with improvement of aphasia. Recovery of the injured AF in the dominant hemisphere appears to be one of the mechanisms for recovery from aphasia.
Zhang, Shengwei; Arfanakis, Konstantinos
2012-01-01
Purpose To investigate the effect of standardized and study-specific human brain diffusion tensor templates on the accuracy of spatial normalization, without ignoring the important roles of data quality and registration algorithm effectiveness. Materials and Methods Two groups of diffusion tensor imaging (DTI) datasets, with and without visible artifacts, were normalized to two standardized diffusion tensor templates (IIT2, ICBM81) as well as study-specific templates, using three registration approaches. The accuracy of inter-subject spatial normalization was compared across templates, using the most effective registration technique for each template and group of data. Results It was demonstrated that, for DTI data with visible artifacts, the study-specific template resulted in significantly higher spatial normalization accuracy than standardized templates. However, for data without visible artifacts, the study-specific template and the standardized template of higher quality (IIT2) resulted in similar normalization accuracy. Conclusion For DTI data with visible artifacts, a carefully constructed study-specific template may achieve higher normalization accuracy than that of standardized templates. However, as DTI data quality improves, a high-quality standardized template may be more advantageous than a study-specific template, since in addition to high normalization accuracy, it provides a standard reference across studies, as well as automated localization/segmentation when accompanied by anatomical labels. PMID:23034880
NASA Astrophysics Data System (ADS)
Böbel, A.; Knapek, C. A.; Räth, C.
2018-05-01
Experiments of the recrystallization processes in two-dimensional complex plasmas are analyzed to rigorously test a recently developed scale-free phase transition theory. The "fractal-domain-structure" (FDS) theory is based on the kinetic theory of Frenkel. It assumes the formation of homogeneous domains, separated by defect lines, during crystallization and a fractal relationship between domain area and boundary length. For the defect number fraction and system energy a scale-free power-law relation is predicted. The long-range scaling behavior of the bond-order correlation function shows clearly that the complex plasma phase transitions are not of the Kosterlitz, Thouless, Halperin, Nelson, and Young type. Previous preliminary results obtained by counting the number of dislocations and applying a bond-order metric for structural analysis are reproduced. These findings are supplemented by extending the use of the bond-order metric to measure the defect number fraction and furthermore applying state-of-the-art analysis methods, allowing a systematic testing of the FDS theory with unprecedented scrutiny: A morphological analysis of lattice structure is performed via Minkowski tensor methods. Minkowski tensors form a complete family of additive, motion covariant and continuous morphological measures that are sensitive to nonlinear properties. The FDS theory is rigorously confirmed and predictions of the theory are reproduced extremely well. The predicted scale-free power-law relation between defect fraction number and system energy is verified for one more order of magnitude at high energies compared to the inherently discontinuous bond-order metric. It is found that the fractal relation between crystalline domain area and circumference is independent of the experiment, the particular Minkowski tensor method, and the particular choice of parameters. Thus, the fractal relationship seems to be inherent to two-dimensional phase transitions in complex plasmas. Minkowski tensor analysis turns out to be a powerful tool for investigations of crystallization processes. It is capable of revealing nonlinear local topological properties, however, still provides easily interpretable results founded on a solid mathematical framework.
Stochastic Gravity: Theory and Applications.
Hu, Bei Lok; Verdaguer, Enric
2004-01-01
Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. The noise kernel is the vacuum expectation value of the (operatorvalued) stress-energy bi-tensor which describes the fluctuations of quantum matter fields in curved spacetimes. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the stress-energy tensor to their correlation functions. The functional approach uses the Feynman-Vernon influence functional and the Schwinger-Keldysh closed-time-path effective action methods which are convenient for computations. It also brings out the open systems concepts and the statistical and stochastic contents of the theory such as dissipation, fluctuations, noise, and decoherence. We then focus on the properties of the stress-energy bi-tensor. We obtain a general expression for the noise kernel of a quantum field defined at two distinct points in an arbitrary curved spacetime as products of covariant derivatives of the quantum field's Green function. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime. We offer an analytical solution of the Einstein-Langevin equation and compute the two-point correlation functions for the linearized Einstein tensor and for the metric perturbations. Second, we discuss structure formation from the stochastic gravity viewpoint, which can go beyond the standard treatment by incorporating the full quantum effect of the inflaton fluctuations. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a quasi-static black hole (enclosed in a box). We derive a fluctuation-dissipation relation between the fluctuations in the radiation and the dissipative dynamics of metric fluctuations.
Mass Function of Galaxy Clusters in Relativistic Inhomogeneous Cosmology
NASA Astrophysics Data System (ADS)
Ostrowski, Jan J.; Buchert, Thomas; Roukema, Boudewijn F.
The current cosmological model (ΛCDM) with the underlying FLRW metric relies on the assumption of local isotropy, hence homogeneity of the Universe. Difficulties arise when one attempts to justify this model as an average description of the Universe from first principles of general relativity, since in general, the Einstein tensor built from the averaged metric is not equal to the averaged stress-energy tensor. In this context, the discrepancy between these quantities is called "cosmological backreaction" and has been the subject of scientific debate among cosmologists and relativists for more than 20 years. Here we present one of the methods to tackle this problem, i.e. averaging the scalar parts of the Einstein equations, together with its application, the cosmological mass function of galaxy clusters.
Tensor gauge condition and tensor field decomposition
NASA Astrophysics Data System (ADS)
Zhu, Ben-Chao; Chen, Xiang-Song
2015-10-01
We discuss various proposals of separating a tensor field into pure-gauge and gauge-invariant components. Such tensor field decomposition is intimately related to the effort of identifying the real gravitational degrees of freedom out of the metric tensor in Einstein’s general relativity. We show that as for a vector field, the tensor field decomposition has exact correspondence to and can be derived from the gauge-fixing approach. The complication for the tensor field, however, is that there are infinitely many complete gauge conditions in contrast to the uniqueness of Coulomb gauge for a vector field. The cause of such complication, as we reveal, is the emergence of a peculiar gauge-invariant pure-gauge construction for any gauge field of spin ≥ 2. We make an extensive exploration of the complete tensor gauge conditions and their corresponding tensor field decompositions, regarding mathematical structures, equations of motion for the fields and nonlinear properties. Apparently, no single choice is superior in all aspects, due to an awkward fact that no gauge-fixing can reduce a tensor field to be purely dynamical (i.e. transverse and traceless), as can the Coulomb gauge in a vector case.
Voxel-Wise Comparisons of the Morphology of Diffusion Tensors Across Groups of Experimental Subjects
Bansal, Ravi; Staib, Lawrence H.; Plessen, Kerstin J.; Xu, Dongrong; Royal, Jason; Peterson, Bradley S.
2007-01-01
Water molecules in the brain diffuse preferentially along the fiber tracts within white matter, which form the anatomical connections across spatially distant brain regions. A diffusion tensor (DT) is a probabilistic ellipsoid composed of 3 orthogonal vectors, each having a direction and an associated scalar magnitude, that represent the probability of water molecules diffusing in each of those directions. The 3D morphologies of DTs can be compared across groups of subjects to reveal disruptions in structural organization and neuroanatomical connectivity of the brains of persons with various neuropsychiatric illnesses. Comparisons of tensor morphology across groups have typically been performed on scalar measures of diffusivity, such as Fractional Anisotropy (FA), rather than directly on the complex 3D morphologies of DTs. Scalar measures, however, are related in nonlinear ways to the eigenvalues and eigenvectors that create the 3D morphologies of DTs. We present a mathematical framework that permits the direct comparison across groups of mean eigenvalues and eigenvectors of individual DTs. We show that group-mean eigenvalues and eigenvectors are multivariate Gaussian distributed, and we use the Delta method to compute their approximate covariance matrices. Our results show that the theoretically computed Mean Tensor (MT) eigenvectors and eigenvalues match well with their respective true values. Furthermore, a comparison of synthetically generated groups of DTs highlights the limitations of using FA to detect group differences. Finally, analyses of in vivo DT data using our method reveal significant between-group differences in diffusivity along fiber tracts within white matter, whereas analyses based on FA values failed to detect some of these differences. PMID:18006284
Killing-Yano tensor and supersymmetry of the self-dual Plebański-Demiański solution
NASA Astrophysics Data System (ADS)
Nozawa, Masato; Houri, Tsuyoshi
2016-06-01
We explore various aspects of the self-dual Plebański-Demiański (PD) family in the Euclidean Einstein-Maxwell-Λ system. The Killing-Yano tensor which was recently found by Yasui and one of the present authors allows us to prove that the self-dual PD metric can be brought into the self-dual Carter metric by an orientation-reversing coordinate transformation. We show that the self-dual PD solution admits two independent Killing spinors in the framework of N = 2 minimal gauged supergravity, whereas the non-self-dual solution admits only a single Killing spinor. This can be demonstrated by casting the self-dual PD metric into two distinct Przanowski-Tod forms. As a by-product, a new example of the three-dimensional Einstein-Weyl space is presented. We also prove that the self-dual PD metric falls into two different Calderbank-Pedersen families, which are determined by a single function subjected to a linear equation on the two-dimensional hyperbolic space. Furthermore, we consider the hyper-Kähler case for which the metric falls into the Gibbons-Hawking class. We find that the condition for the nonexistence of the Dirac-Misner string enforces the solution with a nonvanishing acceleration parameter to the Eguchi-Hanson space.
Spherically symmetric conformal gravity and ''gravitational bubbles''
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berezin, V.A.; Dokuchaev, V.I.; Eroshenko, Yu.N., E-mail: berezin@inr.ac.ru, E-mail: dokuchaev@inr.ac.ru, E-mail: eroshenko@inr.ac.ru
2016-01-01
The general structure of the spherically symmetric solutions in the Weyl conformal gravity is described. The corresponding Bach equations are derived for the special type of metrics, which can be considered as the representative of the general class. The complete set of the pure vacuum solutions is found. It consists of two classes. The first one contains the solutions with constant two-dimensional curvature scalar of our specific metrics, and the representatives are the famous Robertson-Walker metrics. One of them we called the ''gravitational bubbles'', which is compact and with zero Weyl tensor. Thus, we obtained the pure vacuum curved space-timesmore » (without any material sources, including the cosmological constant) what is absolutely impossible in General Relativity. Such a phenomenon makes it easier to create the universe from ''nothing''. The second class consists of the solutions with varying curvature scalar. We found its representative as the one-parameter family. It appears that it can be conformally covered by the thee-parameter Mannheim-Kazanas solution. We also investigated the general structure of the energy-momentum tensor in the spherical conformal gravity and constructed the vectorial equation that reveals clearly some features of non-vacuum solutions. Two of them are explicitly written, namely, the metrics à la Vaidya, and the electrovacuum space-time metrics.« less
Uncertainty in assessment of radiation-induced diffusion index changes in individual patients
NASA Astrophysics Data System (ADS)
Nazem-Zadeh, Mohammad-Reza; Chapman, Christopher H.; Lawrence, Theodore S.; Tsien, Christina I.; Cao, Yue
2013-06-01
The purpose of this study is to evaluate repeatability coefficients of diffusion tensor indices to assess whether longitudinal changes in diffusion indices were true changes beyond the uncertainty for individual patients undergoing radiation therapy (RT). Twenty-two patients who had low-grade or benign tumors and were treated by partial brain radiation therapy (PBRT) participated in an IRB-approved MRI protocol. The diffusion tensor images in the patients were acquired pre-RT, week 3 during RT, at the end of RT, and 1, 6, and 18 months after RT. As a measure of uncertainty, repeatability coefficients (RC) of diffusion indices in the segmented cingulum, corpus callosum, and fornix were estimated by using test-retest diffusion tensor datasets from the National Biomedical Imaging Archive (NBIA) database. The upper and lower limits of the 95% confidence interval of the estimated RC from the test and retest data were used to evaluate whether the longitudinal percentage changes in diffusion indices in the segmented structures in the individual patients were beyond the uncertainty and thus could be considered as true radiation-induced changes. Diffusion indices in different white matter structures showed different uncertainty ranges. The estimated RC for fractional anisotropy (FA) ranged from 5.3% to 9.6%, for mean diffusivity (MD) from 2.2% to 6.8%, for axial diffusivity (AD) from 2.4% to 5.5%, and for radial diffusivity (RD) from 2.9% to 9.7%. Overall, 23% of the patients treated by RT had FA changes, 44% had MD changes, 50% had AD changes, and 50% had RD changes beyond the uncertainty ranges. In the fornix, 85.7% and 100% of the patients showed changes beyond the uncertainty range at 6 and 18 months after RT, demonstrating that radiation has a pronounced late effect on the fornix compared to other segmented structures. It is critical to determine reliability of a change observed in an individual patient for clinical decision making. Assessments of the repeatability and confidence interval of diffusion tensor measurements in white matter structures allow us to determine the true longitudinal change in individual patients.
ApoE influences regional white-matter axonal density loss in Alzheimer's disease.
Slattery, Catherine F; Zhang, Jiaying; Paterson, Ross W; Foulkes, Alexander J M; Carton, Amelia; Macpherson, Kirsty; Mancini, Laura; Thomas, David L; Modat, Marc; Toussaint, Nicolas; Cash, David M; Thornton, John S; Henley, Susie M D; Crutch, Sebastian J; Alexander, Daniel C; Ourselin, Sebastien; Fox, Nick C; Zhang, Hui; Schott, Jonathan M
2017-09-01
Mechanisms underlying phenotypic heterogeneity in young onset Alzheimer disease (YOAD) are poorly understood. We used diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI) with tract-based spatial statistics to investigate apolipoprotein (APOE) ε4 modulation of white-matter damage in 37 patients with YOAD (22, 59% APOE ε4 positive) and 23 age-matched controls. Correlation between neurite density index (NDI) and neuropsychological performance was assessed in 4 white-matter regions of interest. White-matter disruption was more widespread in ε4+ individuals but more focal (posterior predominant) in the absence of an ε4 allele. NODDI metrics indicate fractional anisotropy changes are underpinned by combinations of axonal loss and morphological change. Regional NDI in parieto-occipital white matter correlated with visual object and spatial perception battery performance (right and left, both p = 0.02), and performance (nonverbal) intelligence (WASI matrices, right, p = 0.04). NODDI provides tissue-specific microstructural metrics of white-matter tract damage in YOAD, including NDI which correlates with focal cognitive deficits, and APOEε4 status is associated with different patterns of white-matter neurodegeneration. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
New non-naturally reductive Einstein metrics on exceptional simple Lie groups
NASA Astrophysics Data System (ADS)
Chen, Huibin; Chen, Zhiqi; Deng, Shaoqiang
2018-01-01
In this article, we construct several non-naturally reductive Einstein metrics on exceptional simple Lie groups, which are found through the decomposition arising from generalized Wallach spaces. Using the decomposition corresponding to the two involutions, we calculate the non-zero coefficients in the formulas of the components of Ricci tensor with respect to the given metrics. The Einstein metrics are obtained as solutions of a system of polynomial equations, which we manipulate by symbolic computations using Gröbner bases. In particular, we discuss the concrete numbers of non-naturally reductive Einstein metrics for each case up to isometry and homothety.
Memory binding and white matter integrity in familial Alzheimer’s disease
Saarimäki, Heini; Bastin, Mark E.; Londoño, Ana C.; Pettit, Lewis; Lopera, Francisco; Della Sala, Sergio; Abrahams, Sharon
2015-01-01
Binding information in short-term and long-term memory are functions sensitive to Alzheimer’s disease. They have been found to be affected in patients who meet criteria for familial Alzheimer’s disease due to the mutation E280A of the PSEN1 gene. However, only short-term memory binding has been found to be affected in asymptomatic carriers of this mutation. The neural correlates of this dissociation are poorly understood. The present study used diffusion tensor magnetic resonance imaging to investigate whether the integrity of white matter structures could offer an account. A sample of 19 patients with familial Alzheimer’s disease, 18 asymptomatic carriers and 21 non-carrier controls underwent diffusion tensor magnetic resonance imaging, neuropsychological and memory binding assessment. The short-term memory binding task required participants to detect changes across two consecutive screens displaying arrays of shapes, colours, or shape-colour bindings. The long-term memory binding task was a Paired Associates Learning Test. Performance on these tasks were entered into regression models. Relative to controls, patients with familial Alzheimer’s disease performed poorly on both memory binding tasks. Asymptomatic carriers differed from controls only in the short-term memory binding task. White matter integrity explained poor memory binding performance only in patients with familial Alzheimer’s disease. White matter water diffusion metrics from the frontal lobe accounted for poor performance on both memory binding tasks. Dissociations were found in the genu of corpus callosum which accounted for short-term memory binding impairments and in the hippocampal part of cingulum bundle which accounted for long-term memory binding deficits. The results indicate that white matter structures in the frontal and temporal lobes are vulnerable to the early stages of familial Alzheimer’s disease and their damage is associated with impairments in two memory binding functions known to be markers for Alzheimer’s disease. PMID:25762465
Sadeghi, Neda; Nayak, Amritha; Walker, Lindsay; Okan Irfanoglu, M; Albert, Paul S; Pierpaoli, Carlo
2015-04-01
Metrics derived from the diffusion tensor, such as fractional anisotropy (FA) and mean diffusivity (MD) have been used in many studies of postnatal brain development. A common finding of previous studies is that these tensor-derived measures vary widely even in healthy populations. This variability can be due to inherent inter-individual biological differences as well as experimental noise. Moreover, when comparing different studies, additional variability can be introduced by different acquisition protocols. In this study we examined scans of 61 individuals (aged 4-22 years) from the NIH MRI study of normal brain development. Two scans were collected with different protocols (low and high resolution). Our goal was to separate the contributions of biological variability and experimental noise to the overall measured variance, as well as to assess potential systematic effects related to the use of different protocols. We analyzed FA and MD in seventeen regions of interest. We found that biological variability for both FA and MD varies widely across brain regions; biological variability is highest for FA in the lateral part of the splenium and body of the corpus callosum along with the cingulum and the superior longitudinal fasciculus, and for MD in the optic radiations and the lateral part of the splenium. These regions with high inter-individual biological variability are the most likely candidates for assessing genetic and environmental effects in the developing brain. With respect to protocol-related effects, the lower resolution acquisition resulted in higher MD and lower FA values for the majority of regions compared with the higher resolution protocol. However, the majority of the regions did not show any age-protocol interaction, indicating similar trajectories were obtained irrespective of the protocol used. Published by Elsevier Inc.
Memory binding and white matter integrity in familial Alzheimer's disease.
Parra, Mario A; Saarimäki, Heini; Bastin, Mark E; Londoño, Ana C; Pettit, Lewis; Lopera, Francisco; Della Sala, Sergio; Abrahams, Sharon
2015-05-01
Binding information in short-term and long-term memory are functions sensitive to Alzheimer's disease. They have been found to be affected in patients who meet criteria for familial Alzheimer's disease due to the mutation E280A of the PSEN1 gene. However, only short-term memory binding has been found to be affected in asymptomatic carriers of this mutation. The neural correlates of this dissociation are poorly understood. The present study used diffusion tensor magnetic resonance imaging to investigate whether the integrity of white matter structures could offer an account. A sample of 19 patients with familial Alzheimer's disease, 18 asymptomatic carriers and 21 non-carrier controls underwent diffusion tensor magnetic resonance imaging, neuropsychological and memory binding assessment. The short-term memory binding task required participants to detect changes across two consecutive screens displaying arrays of shapes, colours, or shape-colour bindings. The long-term memory binding task was a Paired Associates Learning Test. Performance on these tasks were entered into regression models. Relative to controls, patients with familial Alzheimer's disease performed poorly on both memory binding tasks. Asymptomatic carriers differed from controls only in the short-term memory binding task. White matter integrity explained poor memory binding performance only in patients with familial Alzheimer's disease. White matter water diffusion metrics from the frontal lobe accounted for poor performance on both memory binding tasks. Dissociations were found in the genu of corpus callosum which accounted for short-term memory binding impairments and in the hippocampal part of cingulum bundle which accounted for long-term memory binding deficits. The results indicate that white matter structures in the frontal and temporal lobes are vulnerable to the early stages of familial Alzheimer's disease and their damage is associated with impairments in two memory binding functions known to be markers for Alzheimer's disease. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Oehr, Lucy; Anderson, Jacqueline
2017-11-01
To undertake a systematic review and meta-analysis of the relationship between microstructural damage and cognitive function after hospitalized mixed-mechanism (HMM) mild traumatic brain injury (mTBI). PsycInfo, EMBASE, and MEDLINE were used to find relevant empirical articles published between January 2002 and January 2016. Studies that examined the specific relationship between diffusion tensor imaging (DTI) and cognitive test performance were included. The final sample comprised previously medically and psychiatrically healthy adults with HMM mTBI. Specific data were extracted including mTBI definitional criteria, descriptive statistics, outcome measures, and specific results of associations between DTI metrics and cognitive test performance. Of the 248 original articles retrieved and reviewed, 8 studies met all inclusion criteria and were included in the meta-analysis. The meta-analysis revealed statistically significant associations between reduced white matter integrity and poor performance on measures of attention (fractional anisotropy [FA]: d=.413, P<.001; mean diffusivity [MD]: d=-.407, P=.001), memory (FA: d=.347, P<.001; MD: d=-.568, P<.001), and executive function (FA: d=.246, P<.05), which persisted beyond 1 month postinjury. The findings from the meta-analysis provide clear support for an association between in vivo markers of underlying neuropathology and cognitive function after mTBI. Furthermore, these results demonstrate clearly for the first time that in vivo markers of structural neuropathology are associated with cognitive dysfunction within the domains of attention, memory, and executive function. These findings provide an avenue for future research to examine the causal relationship between mTBI-related neuropathology and cognitive dysfunction. Furthermore, they have important implications for clinical management of patients with mTBI because they provide a more comprehensive understanding of factors that are associated with cognitive dysfunction after mTBI. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
Chronic Effects of Boxing: Diffusion Tensor Imaging and Cognitive Findings
Wilde, Elisabeth A.; Hunter, Jill V.; Li, Xiaoqi; Amador, Cristian; Hanten, Gerri; Newsome, Mary R.; Wu, Trevor C.; McCauley, Stephen R.; Vogt, Gregory S.; Chu, Zili David; Biekman, Brian
2016-01-01
Abstract We used magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) to evaluate the effects of boxing on brain structure and cognition in 10 boxers (8 retired, 2 active; mean age = 45.7 years; standard deviation [SD] = 9.71) and 9 participants (mean age = 43.44; SD = 9.11) in noncombative sports. Evans Index (maximum width of the anterior horns of the lateral ventricles/maximal width of the internal diameter of the skull) was significantly larger in the boxers (F = 4.52; p = 0.050; Cohen's f = 0.531). Word list recall was impaired in the boxers (F(1,14) = 10.70; p = 0.006; f = 0.84), whereas implicit memory measured by faster reaction time (RT) to a repeating sequence of numbers than to a random sequence was preserved (t = 2.52; p < 0.04). Fractional anisotropy (FA) and the apparent diffusion coefficient (ADC) measured by tractography did not significantly differ between groups. However, DTI metrics were significantly correlated with declarative memory (e.g., left ventral striatum ADC with delayed recall, r = −0.74; p = 0.02) and with RT to the repeating number sequence (r = 0.70; p = 0.04) in the boxers. Years of boxing had the most consistent, negative correlations with FA, ranging from −0.65 for the right ventral striatum to −0.92 for the right cerebral peduncle. Years of boxing was negatively related to the number of words consistently recalled over trials (r = −0.74; p = 0.02), delayed recall (r = −0.83; p = 0.003), and serial RT (r = 0.66; p = 0.05). We conclude that microstructural integrity of white matter tracts is related to declarative memory and response speed in boxers and to the extent of boxing exposure. Implications for chronic traumatic encephalopathy are discussed. PMID:26414735
Chronic Effects of Boxing: Diffusion Tensor Imaging and Cognitive Findings.
Wilde, Elisabeth A; Hunter, Jill V; Li, Xiaoqi; Amador, Cristian; Hanten, Gerri; Newsome, Mary R; Wu, Trevor C; McCauley, Stephen R; Vogt, Gregory S; Chu, Zili David; Biekman, Brian; Levin, Harvey S
2016-04-01
We used magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) to evaluate the effects of boxing on brain structure and cognition in 10 boxers (8 retired, 2 active; mean age = 45.7 years; standard deviation [SD] = 9.71) and 9 participants (mean age = 43.44; SD = 9.11) in noncombative sports. Evans Index (maximum width of the anterior horns of the lateral ventricles/maximal width of the internal diameter of the skull) was significantly larger in the boxers (F = 4.52; p = 0.050; Cohen's f = 0.531). Word list recall was impaired in the boxers (F(1,14) = 10.70; p = 0.006; f = 0.84), whereas implicit memory measured by faster reaction time (RT) to a repeating sequence of numbers than to a random sequence was preserved (t = 2.52; p < 0.04). Fractional anisotropy (FA) and the apparent diffusion coefficient (ADC) measured by tractography did not significantly differ between groups. However, DTI metrics were significantly correlated with declarative memory (e.g., left ventral striatum ADC with delayed recall, r = -0.74; p = 0.02) and with RT to the repeating number sequence (r = 0.70; p = 0.04) in the boxers. Years of boxing had the most consistent, negative correlations with FA, ranging from -0.65 for the right ventral striatum to -0.92 for the right cerebral peduncle. Years of boxing was negatively related to the number of words consistently recalled over trials (r = -0.74; p = 0.02), delayed recall (r = -0.83; p = 0.003), and serial RT (r = 0.66; p = 0.05). We conclude that microstructural integrity of white matter tracts is related to declarative memory and response speed in boxers and to the extent of boxing exposure. Implications for chronic traumatic encephalopathy are discussed.
Cosmic microwave background probes models of inflation
NASA Technical Reports Server (NTRS)
Davis, Richard L.; Hodges, Hardy M.; Smoot, George F.; Steinhardt, Paul J.; Turner, Michael S.
1992-01-01
Inflation creates both scalar (density) and tensor (gravity wave) metric perturbations. We find that the tensor-mode contribution to the cosmic microwave background anisotropy on large-angular scales can only exceed that of the scalar mode in models where the spectrum of perturbations deviates significantly from scale invariance. If the tensor mode dominates at large-angular scales, then the value of DeltaT/T predicted on 1 deg is less than if the scalar mode dominates, and, for cold-dark-matter models, bias factors greater than 1 can be made consistent with Cosmic Background Explorer (COBE) DMR results.
NASA Astrophysics Data System (ADS)
Robinson, Bruce H.; Dalton, Larry R.
1980-01-01
The stochastic Liouville equation for the spin density matrix is modified to consider the effects of Brownian anisotropic rotational diffusion upon electron paramagnetic resonance (EPR) and saturation transfer electron paramagnetic resonance (ST-EPR) spectra. Spectral shapes and the ST-EPR parameters L″/L, C'/C, and H″/H defined by Thomas, Dalton, and Hyde at X-band microwave frequencies [J. Chem. Phys. 65, 3006 (1976)] are examined and discussed in terms of the rotational times τ∥ and τ⊥ and in terms of other defined correlation times for systems characterized by magnetic tensors of axial symmetry and for systems characterized by nonaxially symmetric magnetic tensors. For nearly axially symmetric magnetic tensors, such as nitroxide spin labels studied employing 1-3 GHz microwaves, ST-EPR spectra for systems undergoing anisotropic rotational diffusion are virtually indistinguishable from spectra for systems characterized by isotropic diffusion. For nonaxially symmetric magnetic tensors, such as nitroxide spin labels studied employing 8-35 GHz microwaves, the high field region of the ST-EPR spectra, and hence the H″/H parameter, will be virtually indistinguishable from spectra, and parameter values, obtained for isotropic diffusion. On the other hand, the central spectral region at x-band microwave frequencies, and hence the C'/C parameter, is sensitive to the anisotropic diffusion model provided that a unique and static relationship exists between the magnetic and diffusion tensors. Random labeling or motion of the spin label relative to the biomolecule whose hydrodynamic properties are to be investigated will destroy spectral sensitivity to anisotropic motion. The sensitivity to anisotropic motion is enhanced in proceeding to 35 GHz with the increased sensitivity evident in the low field half of the EPR and ST-EPR spectra. The L″/L parameter is thus a meaningful indicator of anisotropic motion when compared with H″/H parameter analysis. However, consideration of spectral shapes suggests that the C'/C parameter definition is not meaningfully extended from 9.5 to 35 GHz. Alternative definitions of the L″/L and C'/C parameters are proposed for those microwave frequencies for which the electron Zeeman anisotropy is comparable to or greater than the electron-nitrogen nuclear hyperfine anisotropy.
Galbán, Craig J; Maderwald, Stefan; Uffmann, Kai; de Greiff, Armin; Ladd, Mark E
2004-12-01
The aim of this study was to examine the diffusive properties of adjacent muscles at rest, and to determine the relationship between diffusive and architectural properties, which are task-specific to muscles. The principle, second, and third eigenvalues, trace of the diffusion tensor, and two anisotropic parameters, ellipsoid eccentricity (e) and fractional anisotropy (FA), of various muscles in the human calf were calculated by diffusion tensor imaging (DTI). Linear correlations of the calculated parameters to the muscle physiological cross-sectional area (PCSA), which is proportional to maximum muscle force, were performed to ascertain any linear relation between muscle architecture and diffusivity. Images of the left calf were acquired from six healthy male volunteers. Seven muscles were investigated in this study. These comprised the soleus, lateral gastrocnemius, medial gastrocnemius, posterior tibialis, anterior tibialis, extensor digitorum longus, and peroneus longus. All data were presented as the mean and standard error of the mean (SEM). In general, differences in diffusive parameter values occurred primarily between functionally different muscles. A strong correlation was also found between PCSA and the third eigenvalue, e, and FA. A mathematical derivation revealed a linear relationship between PCSA and the third eigenvalue as a result of their dependence on the average radius of all fibers within a single muscle. These findings demonstrated the ability of DTI to differentiate between functionally different muscles in the same region of the body on the basis of their diffusive properties.
Differential invariants and exact solutions of the Einstein equations
NASA Astrophysics Data System (ADS)
Lychagin, Valentin; Yumaguzhin, Valeriy
2017-06-01
In this paper (cf. Lychagin and Yumaguzhin, in Anal Math Phys, 2016) a class of totally geodesics solutions for the vacuum Einstein equations is introduced. It consists of Einstein metrics of signature (1,3) such that 2-dimensional distributions, defined by the Weyl tensor, are completely integrable and totally geodesic. The complete and explicit description of metrics from these class is given. It is shown that these metrics depend on two functions in one variable and one harmonic function.
Ellington, Benjamin M; Schmit, Brian D; Gourab, Krishnaj; Sieber-Blum, Maya; Hu, Yao F; Schmainda, Kathleen M
2009-01-01
Diffusion weighted magnetic resonance imaging (DWI) is a powerful tool for evaluation of microstructural anomalies in numerous central nervous system pathologies. Diffusion tensor imaging (DTI) allows for the magnitude and direction of water self diffusion to be estimated by sampling the apparent diffusion coefficient (ADC) in various directions. Clinical DWI and DTI performed at a single level of diffusion weighting, however, does not allow for multiple diffusion compartments to be elicited. Furthermore, assumptions made regarding the precise number of diffusion compartments intrinsic to the tissue of interest have resulted in a lack of consensus between investigations. To overcome these challenges, a stretched-exponential model of diffusion was applied to examine the diffusion coefficient and "heterogeneity index" within highly compartmentalized brain tumors. The purpose of the current study is to expand on the stretched-exponential model of diffusion to include directionality of both diffusion heterogeneity and apparent diffusion coefficient. This study develops the mathematics of this new technique along with an initial application in quantifying spinal cord regeneration following acute injection of epidermal neural crest stem cell (EPI-NCSC) grafts.
NASA Astrophysics Data System (ADS)
Hervik, S.; Málek, T.; Pravda, V.; Pravdová, A.
2015-12-01
We study type II universal metrics of the Lorentzian signature. These metrics simultaneously solve vacuum field equations of all theories of gravitation with the Lagrangian being a polynomial curvature invariant constructed from the metric, the Riemann tensor and its covariant derivatives of an arbitrary order. We provide examples of type II universal metrics for all composite number dimensions. On the other hand, we have no examples for prime number dimensions and we prove the non-existence of type II universal spacetimes in five dimensions. We also present type II vacuum solutions of selected classes of gravitational theories, such as Lovelock, quadratic and L({{Riemann}}) gravities.
Curved manifolds with conserved Runge-Lenz vectors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ngome, J.-P.
2009-12-15
van Holten's algorithm is used to construct Runge-Lenz-type conserved quantities, induced by Killing tensors, on curved manifolds. For the generalized Taub-Newman-Unti-Tamburino metric, the most general external potential such that the combined system admits a conserved Runge-Lenz-type vector is found. In the multicenter case, the subclass of two-center metric exhibits a conserved Runge-Lenz-type scalar.
Curved manifolds with conserved Runge-Lenz vectors
NASA Astrophysics Data System (ADS)
Ngome, J.-P.
2009-12-01
van Holten's algorithm is used to construct Runge-Lenz-type conserved quantities, induced by Killing tensors, on curved manifolds. For the generalized Taub-Newman-Unti-Tamburino metric, the most general external potential such that the combined system admits a conserved Runge-Lenz-type vector is found. In the multicenter case, the subclass of two-center metric exhibits a conserved Runge-Lenz-type scalar.
NASA Astrophysics Data System (ADS)
Yamamoto, Utako; Kobayashi, Tetsuo; Kito, Shinsuke; Koga, Yoshihiko
We have analyzed cerebral white matter using magnetic resonance diffusion tensor imaging (MR-DTI) to measure the diffusion anisotropy of water molecules. The goal of this study is the quantitative evaluation of schizophrenia. Diffusion tensor images are acquired for patients with schizophrenia and healthy comparison subjects, group-matched for age, sex, and handedness. Fiber tracking is performed on the superior longitudinal fasciculus for the comparison between the patient and comparison groups. We have analysed and compared the cross-sectional area on the starting coronal plane and the mean and standard deviation of the fractional anisotropy and the apparent diffusion coefficient along fibers in the right and left hemispheres. In the right hemisphere, the cross-sectional areas in patient group are significantly smaller than those in the comparison group. Furthermore, in the comparison group, the cross-sectional areas in the right hemisphere are significantly larger than those in the left hemisphere, whereas there is no significant difference in the patient group. These results suggest that we may evaluate the disruption in white matter integrity in schizophrenic patients quantitatively by comparing the cross-sectional area of the superior longitudinal fasciculus in the right and left hemispheres.
Analysis and correction of gradient nonlinearity bias in ADC measurements
Malyarenko, Dariya I.; Ross, Brian D.; Chenevert, Thomas L.
2013-01-01
Purpose Gradient nonlinearity of MRI systems leads to spatially-dependent b-values and consequently high non-uniformity errors (10–20%) in ADC measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. Methods All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Results Spatial dependence of nonlinearity correction terms accounts for the bulk (75–95%) of ADC bias for FA = 0.3–0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. Conclusions The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. PMID:23794533
Chavez, Sofia; Viviano, Joseph; Zamyadi, Mojdeh; Kingsley, Peter B; Kochunov, Peter; Strother, Stephen; Voineskos, Aristotle
2018-02-01
To develop a quality assurance (QA) tool (acquisition guidelines and automated processing) for diffusion tensor imaging (DTI) data using a common agar-based phantom used for fMRI QA. The goal is to produce a comprehensive set of automated, sensitive and robust QA metrics. A readily available agar phantom was scanned with and without parallel imaging reconstruction. Other scanning parameters were matched to the human scans. A central slab made up of either a thick slice or an average of a few slices, was extracted and all processing was performed on that image. The proposed QA relies on the creation of two ROIs for processing: (i) a preset central circular region of interest (ccROI) and (ii) a signal mask for all images in the dataset. The ccROI enables computation of average signal for SNR calculations as well as average FA values. The production of the signal masks enables automated measurements of eddy current and B0 inhomogeneity induced distortions by exploiting the sphericity of the phantom. Also, the signal masks allow automated background localization to assess levels of Nyquist ghosting. The proposed DTI-QA was shown to produce eleven metrics which are robust yet sensitive to image quality changes within site and differences across sites. It can be performed in a reasonable amount of scan time (~15min) and the code for automated processing has been made publicly available. A novel DTI-QA tool has been proposed. It has been applied successfully on data from several scanners/platforms. The novelty lies in the exploitation of the sphericity of the phantom for distortion measurements. Other novel contributions are: the computation of an SNR value per gradient direction for the diffusion weighted images (DWIs) and an SNR value per non-DWI, an automated background detection for the Nyquist ghosting measurement and an error metric reflecting the contribution of EPI instability to the eddy current induced shape changes observed for DWIs. Copyright © 2017 Elsevier Inc. All rights reserved.
Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation.
Jiang, Rifeng; Jiang, Jingjing; Zhao, Lingyun; Zhang, Jiaxuan; Zhang, Shun; Yao, Yihao; Yang, Shiqi; Shi, Jingjing; Shen, Nanxi; Su, Changliang; Zhang, Ju; Zhu, Wenzhen
2015-12-08
Conventional diffusion imaging techniques are not sufficiently accurate for evaluating glioma grade and cellular proliferation, which are critical for guiding glioma treatment. Diffusion kurtosis imaging (DKI), an advanced non-Gaussian diffusion imaging technique, has shown potential in grading glioma; however, its applications in this tumor have not been fully elucidated. In this study, DKI and diffusion weighted imaging (DWI) were performed on 74 consecutive patients with histopathologically confirmed glioma. The kurtosis and conventional diffusion metric values of the tumor were semi-automatically obtained. The relationships of these metrics with the glioma grade and Ki-67 expression were evaluated. The diagnostic efficiency of these metrics in grading was further compared. It was demonstrated that compared with the conventional diffusion metrics, the kurtosis metrics were more promising imaging markers in distinguishing high-grade from low-grade gliomas and distinguishing among grade II, III and IV gliomas; the kurtosis metrics also showed great potential in the prediction of Ki-67 expression. To our best knowledge, we are the first to reveal the ability of DKI to assess the cellular proliferation of gliomas, and to employ the semi-automatic method for the accurate measurement of gliomas. These results could have a significant impact on the diagnosis and subsequent therapy of glioma.
Metric anisotropies and emergent anisotropic hydrodynamics
NASA Astrophysics Data System (ADS)
Dash, Ashutosh; Jaiswal, Amaresh
2018-05-01
Expansion of a locally equilibrated fluid is considered in an anisotropic space-time given by the Bianchi type-I metric. Starting from the isotropic equilibrium phase-space distribution function in the local rest frame, we obtain expressions for components of the energy-momentum tensor and conserved current, such as number density, energy density, and pressure components. In the case of an axissymmetric Bianchi type-I metric, we show that they are identical to those obtained within the setup of anisotropic hydrodynamics. We further consider the case in which the Bianchi type-I metric is a vacuum solution of the Einstein equation: the Kasner metric. For the axissymmetric Kasner metric, we discuss the implications of our results in the context of anisotropic hydrodynamics.
Director Field Analysis (DFA): Exploring Local White Matter Geometric Structure in Diffusion MRI.
Cheng, Jian; Basser, Peter J
2018-01-01
In Diffusion Tensor Imaging (DTI) or High Angular Resolution Diffusion Imaging (HARDI), a tensor field or a spherical function field (e.g., an orientation distribution function field), can be estimated from measured diffusion weighted images. In this paper, inspired by the microscopic theoretical treatment of phases in liquid crystals, we introduce a novel mathematical framework, called Director Field Analysis (DFA), to study local geometric structural information of white matter based on the reconstructed tensor field or spherical function field: (1) We propose a set of mathematical tools to process general director data, which consists of dyadic tensors that have orientations but no direction. (2) We propose Orientational Order (OO) and Orientational Dispersion (OD) indices to describe the degree of alignment and dispersion of a spherical function in a single voxel or in a region, respectively; (3) We also show how to construct a local orthogonal coordinate frame in each voxel exhibiting anisotropic diffusion; (4) Finally, we define three indices to describe three types of orientational distortion (splay, bend, and twist) in a local spatial neighborhood, and a total distortion index to describe distortions of all three types. To our knowledge, this is the first work to quantitatively describe orientational distortion (splay, bend, and twist) in general spherical function fields from DTI or HARDI data. The proposed DFA and its related mathematical tools can be used to process not only diffusion MRI data but also general director field data, and the proposed scalar indices are useful for detecting local geometric changes of white matter for voxel-based or tract-based analysis in both DTI and HARDI acquisitions. The related codes and a tutorial for DFA will be released in DMRITool. Copyright © 2017 Elsevier B.V. All rights reserved.
Afzali, Maryam; Fatemizadeh, Emad; Soltanian-Zadeh, Hamid
2015-09-30
Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure and can be used to evaluate fiber bundles. However, due to practical constraints, DWI data acquired in clinics are low resolution. This paper proposes a method for interpolation of orientation distribution functions (ODFs). To this end, fuzzy clustering is applied to segment ODFs based on the principal diffusion directions (PDDs). Next, a cluster is modeled by a tensor so that an ODF is represented by a mixture of tensors. For interpolation, each tensor is rotated separately. The method is applied on the synthetic and real DWI data of control and epileptic subjects. Both experiments illustrate capability of the method in increasing spatial resolution of the data in the ODF field properly. The real dataset show that the method is capable of reliable identification of differences between temporal lobe epilepsy (TLE) patients and normal subjects. The method is compared to existing methods. Comparison studies show that the proposed method generates smaller angular errors relative to the existing methods. Another advantage of the method is that it does not require an iterative algorithm to find the tensors. The proposed method is appropriate for increasing resolution in the ODF field and can be applied to clinical data to improve evaluation of white matter fibers in the brain. Copyright © 2015 Elsevier B.V. All rights reserved.
Quantitative analysis of diffusion tensor orientation: theoretical framework.
Wu, Yu-Chien; Field, Aaron S; Chung, Moo K; Badie, Benham; Alexander, Andrew L
2004-11-01
Diffusion-tensor MRI (DT-MRI) yields information about the magnitude, anisotropy, and orientation of water diffusion of brain tissues. Although white matter tractography and eigenvector color maps provide visually appealing displays of white matter tract organization, they do not easily lend themselves to quantitative and statistical analysis. In this study, a set of visual and quantitative tools for the investigation of tensor orientations in the human brain was developed. Visual tools included rose diagrams, which are spherical coordinate histograms of the major eigenvector directions, and 3D scatterplots of the major eigenvector angles. A scatter matrix of major eigenvector directions was used to describe the distribution of major eigenvectors in a defined anatomic region. A measure of eigenvector dispersion was developed to describe the degree of eigenvector coherence in the selected region. These tools were used to evaluate directional organization and the interhemispheric symmetry of DT-MRI data in five healthy human brains and two patients with infiltrative diseases of the white matter tracts. In normal anatomical white matter tracts, a high degree of directional coherence and interhemispheric symmetry was observed. The infiltrative diseases appeared to alter the eigenvector properties of affected white matter tracts, showing decreased eigenvector coherence and interhemispheric symmetry. This novel approach distills the rich, 3D information available from the diffusion tensor into a form that lends itself to quantitative analysis and statistical hypothesis testing. (c) 2004 Wiley-Liss, Inc.
The Weyl curvature tensor, Cotton-York tensor and gravitational waves: A covariant consideration
NASA Astrophysics Data System (ADS)
Osano, Bob
1 + 3 covariant approach to cosmological perturbation theory often employs the electric part (Eab), the magnetic part (Hab) of the Weyl tensor or the shear tensor (σab) in a phenomenological description of gravitational waves. The Cotton-York tensor is rarely mentioned in connection with gravitational waves in this approach. This tensor acts as a source for the magnetic part of the Weyl tensor which should not be neglected in studies of gravitational waves in the 1 + 3 formalism. The tensor is only mentioned in connection with studies of “silent model” but even there the connection with gravitational waves is not exhaustively explored. In this study, we demonstrate that the Cotton-York tensor encodes contributions from both electric and magnetic parts of the Weyl tensor and in directly from the shear tensor. In our opinion, this makes the Cotton-York tensor arguably the natural choice for linear gravitational waves in the 1 + 3 covariant formalism. The tensor is cumbersome to work with but that should negate its usefulness. It is conceivable that the tensor would equally be useful in the metric approach, although we have not demonstrated this in this study. We contend that the use of only one of the Weyl tensor or the shear tensor, although phenomenologically correct, leads to loss of information. Such information is vital particularly when examining the contribution of gravitational waves to the anisotropy of an almost-Friedmann-Lamitre-Robertson-Walker (FLRW) universe. The recourse to this loss is the use Cotton-York tensor.
Examples of backreaction of small-scale inhomogeneities in cosmology
NASA Astrophysics Data System (ADS)
Green, Stephen R.; Wald, Robert M.
2013-06-01
In previous work, we introduced a new framework to treat large-scale backreaction effects due to small-scale inhomogeneities in general relativity. We considered one-parameter families of spacetimes for which such backreaction effects can occur, and we proved that, provided the weak energy condition on matter is satisfied, the leading effect of small-scale inhomogeneities on large-scale dynamics is to produce a traceless effective stress-energy tensor that itself satisfies the weak energy condition. In this work, we illustrate the nature of our framework by providing two explicit examples of one-parameter families with backreaction. The first, based on previous work of Berger, is a family of polarized vacuum Gowdy spacetimes on a torus, which satisfies all of the assumptions of our framework. As the parameter approaches its limiting value, the metric uniformly approaches a smooth background metric, but spacetime derivatives of the deviation of the metric from the background metric do not converge uniformly to zero. The limiting metric has nontrivial backreaction from the small-scale inhomogeneities, with an effective stress energy that is traceless and satisfies the weak energy condition, in accord with our theorems. Our second one-parameter family consists of metrics which have a uniform Friedmann-Lemaître-Robertson-Walker limit. This family satisfies all of our assumptions with the exception of the weak energy condition for matter. In this case, the limiting metric has an effective stress-energy tensor which is not traceless. We emphasize the importance of imposing energy conditions on matter in studies of backreaction.
Moore, Elizabeth E; Liu, Dandan; Pechman, Kimberly R; Terry, James G; Nair, Sangeeta; Cambronero, Francis E; Bell, Susan P; Gifford, Katherine A; Anderson, Adam W; Hohman, Timothy J; Carr, John Jeffrey; Jefferson, Angela L
2018-06-26
Left ventricular (LV) hypertrophy is associated with cerebrovascular disease and cognitive decline. Increased LV mass index is a subclinical imaging marker that precedes overt LV hypertrophy. This study relates LV mass index to white matter microstructure and cognition among older adults with normal cognition and mild cognitive impairment. Vanderbilt Memory & Aging Project participants free of clinical stroke, dementia, and heart failure (n=318, 73±7 years, 58% male, 39% mild cognitive impairment) underwent brain magnetic resonance imaging, cardiac magnetic resonance, and neuropsychological assessment. Voxelwise analyses related LV mass index (g/m 2 ) to diffusion tensor imaging metrics. Models adjusted for age, sex, education, race/ethnicity, Framingham Stroke Risk Profile, cognitive diagnosis, and apolipoprotein E-ε4 status. Secondary analyses included a LV mass index×diagnosis interaction term with follow-up models stratified by diagnosis. With identical covariates, linear regression models related LV mass index to neuropsychological performances. Increased LV mass index related to altered white matter microstructure ( P <0.05). In models stratified by diagnosis, associations between LV mass index and diffusion tensor imaging were present among mild cognitive impairment participants only ( P <0.05). LV mass index was related only to worse visuospatial memory performance (β=-0.003, P =0.036), an observation that would not withstand correction for multiple testing. In the absence of prevalent heart failure and clinical stroke, increased LV mass index corresponds to altered white matter microstructure, particularly among older adults with clinical symptoms of prodromal dementia. Findings highlight the potential link between subclinical LV remodeling and cerebral white matter microstructure vulnerability. © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
Hayes, Dave J; Lipsman, Nir; Chen, David Q; Woodside, D Blake; Davis, Karen D; Lozano, Andres M; Hodaie, Mojgan
2015-01-01
Anorexia nervosa is characterized by extreme low body weight and alterations in affective processing. The subcallosal cingulate regulates affect through wide-spread white matter connections and is implicated in the pathophysiology of anorexia nervosa. We examined whether those with treatment refractory anorexia nervosa undergoing deep brain stimulation (DBS) of the subcallosal white matter (SCC) show: (1) altered anatomical SCC connectivity compared to healthy controls, (2) white matter microstructural changes, and (3) microstructural changes associated with clinically-measured affect. Diffusion magnetic resonance imaging (dMRI) and deterministic multi-tensor tractography were used to compare anatomical connectivity and microstructure in SCC-associated white matter tracts. Eight women with treatment-refractory anorexia nervosa were compared to 8 age- and sex-matched healthy controls. Anorexia nervosa patients also completed affect-related clinical assessments presurgically and 12 months post-surgery. (1) Higher (e.g., left parieto-occipital cortices) and lower (e.g., thalamus) connectivity in those with anorexia nervosa compared to controls. (2) Decreases in fractional anisotropy, and alterations in axial and radial diffusivities, in the left fornix crus, anterior limb of the internal capsule (ALIC), right anterior cingulum and left inferior fronto-occipital fasciculus. (3) Correlations between dMRI metrics and clinical assessments, such as low pre-surgical left fornix and right ALIC fractional anisotropy being related to post-DBS improvements in quality-of-life and depressive symptoms, respectively. We identified widely-distributed differences in SCC connectivity in anorexia nervosa patients consistent with heterogenous clinical disruptions, although these results should be considered with caution given the low number of subjects. Future studies should further explore the use of affect-related connectivity and behavioral assessments to assist with DBS target selection and treatment outcome. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Cyprien, Fabienne; de Champfleur, Nicolas Menjot; Deverdun, Jérémy; Olié, Emilie; Le Bars, Emmanuelle; Bonafé, Alain; Mura, Thibault; Jollant, Fabrice; Courtet, Philippe; Artero, Sylvaine
2016-12-01
Some MRI studies have noted alterations in the corpus callosum (CC) white matter integrity of individuals with mood disorders and also in patients with suicidal behavior. We investigated the specific impact of suicidal behavior on CC integrity in mood disorders. CC structural changes were assessed by diffusion tensor imaging (DTI) in 121 women 18-50-year-old): 41 with bipolar disorder (BD), 50 with major depressive disorder (MDD) and 30 healthy controls (HC). Fractional anisotropy (FA) and DTI metrics were calculated for the genu, body and splenium of CC and compared in the three groups by MANCOVA. Then, they were re-analyzed relative to the suicide attempt history within the MDD and BD groups and to the suicide number/severity. FA values for the CC genu and body were lower in non-suicide attempters with BD than with MDD and in HC. Conversely, FA values for all CC regions were significantly lower in suicide attempters with BD than in HC. Finally, higher number of suicide attempts (>2) and elevated Suicidal Intent Scale score were associated with significant splenium alterations. Limitations include the cross-sectional design (non-causal study), the potential influence of medications and concerns about the generalizability to men. Genu and body are altered in non-suicide attempters with BD, while splenium is specifically altered in suicide attempters, independently from their psychiatric status. History of suicide attempts may be a source of heterogeneity in the association between CC alterations and BD and may partially explain the variable results of previous studies. Copyright © 2016 Elsevier B.V. All rights reserved.
Goch, Caspar J; Stieltjes, Bram; Henze, Romy; Hering, Jan; Poustka, Luise; Meinzer, Hans-Peter; Maier-Hein, Klaus H
2014-05-01
Diagnosis of autism spectrum disorders (ASD) is difficult, as symptoms vary greatly and are difficult to quantify objectively. Recent work has focused on the assessment of non-invasive diffusion tensor imaging-based biomarkers that reflect the microstructural characteristics of neuronal pathways in the brain. While tractography-based approaches typically analyze specific structures of interest, a graph-based large-scale network analysis of the connectome can yield comprehensive measures of larger-scale architectural patterns in the brain. Commonly applied global network indices, however, do not provide any specificity with respect to functional areas or anatomical structures. Aim of this work was to assess the concept of network centrality as a tool to perform locally specific analysis without disregarding the global network architecture and compare it to other popular network indices. We create connectome networks from fiber tractographies and parcellations of the human brain and compute global network indices as well as local indices for Wernicke's Area, Broca's Area and the Motor Cortex. Our approach was evaluated on 18 children suffering from ASD and 18 typically developed controls using magnetic resonance imaging-based cortical parcellations in combination with diffusion tensor imaging tractography. We show that the network centrality of Wernicke's area is significantly (p<0.001) reduced in ASD, while the motor cortex, which was used as a control region, did not show significant alterations. This could reflect the reduced capacity for comprehension of language in ASD. The betweenness centrality could potentially be an important metric in the development of future diagnostic tools in the clinical context of ASD diagnosis. Our results further demonstrate the applicability of large-scale network analysis tools in the domain of region-specific analysis with a potential application in many different psychological disorders.
Rajagopalan, Venkateswaran; Das, Abhijit; Zhang, Luduan; Hillary, Frank; Wylie, Glenn R; Yue, Guang H
2018-06-16
Traumatic brain injury (TBI) is the main cause of disability in people younger than 35 in the United States. The mechanisms of TBI are complex resulting in both focal and diffuse brain damage. Fractal dimension (FD) is a measure that can characterize morphometric complexity and variability of brain structure especially white matter (WM) structure and may provide novel insights into the injuries evident following TBI. FD-based brain morphometry may provide information on WM structural changes after TBI that is more sensitive to subtle structural changes post injury compared to conventional MRI measurements. Anatomical and diffusion tensor imaging (DTI) data were obtained using a 3 T MRI scanner in subjects with moderate to severe TBI and in healthy controls (HC). Whole brain WM volume, grey matter volume, cortical thickness, cortical area, FD and DTI metrics were evaluated globally and for the left and right hemispheres separately. A neuropsychological test battery sensitive to cognitive impairment associated with traumatic brain injury was performed. TBI group showed lower structural complexity (FD) bilaterally (p < 0.05). No significant difference in either grey matter volume, cortical thickness or cortical area was observed in any of the brain regions between TBI and healthy controls. No significant differences in whole brain WM volume or DTI metrics between TBI and HC groups were observed. Behavioral data analysis revealed that WM FD accounted for a significant amount of variance in executive functioning and processing speed beyond demographic and DTI variables. FD therefore, may serve as a sensitive marker of injury and may play a role in outcome prediction in TBI.
Registration of High Angular Resolution Diffusion MRI Images Using 4th Order Tensors⋆
Barmpoutis, Angelos; Vemuri, Baba C.; Forder, John R.
2009-01-01
Registration of Diffusion Weighted (DW)-MRI datasets has been commonly achieved to date in literature by using either scalar or 2nd-order tensorial information. However, scalar or 2nd-order tensors fail to capture complex local tissue structures, such as fiber crossings, and therefore, datasets containing fiber-crossings cannot be registered accurately by using these techniques. In this paper we present a novel method for non-rigidly registering DW-MRI datasets that are represented by a field of 4th-order tensors. We use the Hellinger distance between the normalized 4th-order tensors represented as distributions, in order to achieve this registration. Hellinger distance is easy to compute, is scale and rotation invariant and hence allows for comparison of the true shape of distributions. Furthermore, we propose a novel 4th-order tensor re-transformation operator, which plays an essential role in the registration procedure and shows significantly better performance compared to the re-orientation operator used in literature for DTI registration. We validate and compare our technique with other existing scalar image and DTI registration methods using simulated diffusion MR data and real HARDI datasets. PMID:18051145
NASA Astrophysics Data System (ADS)
Barreto, A. B.; Pucheu, M. L.; Romero, C.
2018-02-01
We consider scalar–tensor theories of gravity defined in Weyl integrable space-time and show that for time-lapse extended Robertson–Walker metrics in the ADM formalism a class of Weyl transformations corresponding to change of frames induce canonical transformations between different representations of the phase space. In this context, we discuss the physical equivalence of two distinct Weyl frames at the classical level.
Software Toolbox for Low-Frequency Conductivity and Current Density Imaging Using MRI.
Sajib, Saurav Z K; Katoch, Nitish; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je
2017-11-01
Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes. Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes.
Estimation of integral curves from high angular resolution diffusion imaging (HARDI) data.
Carmichael, Owen; Sakhanenko, Lyudmila
2015-05-15
We develop statistical methodology for a popular brain imaging technique HARDI based on the high order tensor model by Özarslan and Mareci [10]. We investigate how uncertainty in the imaging procedure propagates through all levels of the model: signals, tensor fields, vector fields, and fibers. We construct asymptotically normal estimators of the integral curves or fibers which allow us to trace the fibers together with confidence ellipsoids. The procedure is computationally intense as it blends linear algebra concepts from high order tensors with asymptotical statistical analysis. The theoretical results are illustrated on simulated and real datasets. This work generalizes the statistical methodology proposed for low angular resolution diffusion tensor imaging by Carmichael and Sakhanenko [3], to several fibers per voxel. It is also a pioneering statistical work on tractography from HARDI data. It avoids all the typical limitations of the deterministic tractography methods and it delivers the same information as probabilistic tractography methods. Our method is computationally cheap and it provides well-founded mathematical and statistical framework where diverse functionals on fibers, directions and tensors can be studied in a systematic and rigorous way.
Estimation of integral curves from high angular resolution diffusion imaging (HARDI) data
Carmichael, Owen; Sakhanenko, Lyudmila
2015-01-01
We develop statistical methodology for a popular brain imaging technique HARDI based on the high order tensor model by Özarslan and Mareci [10]. We investigate how uncertainty in the imaging procedure propagates through all levels of the model: signals, tensor fields, vector fields, and fibers. We construct asymptotically normal estimators of the integral curves or fibers which allow us to trace the fibers together with confidence ellipsoids. The procedure is computationally intense as it blends linear algebra concepts from high order tensors with asymptotical statistical analysis. The theoretical results are illustrated on simulated and real datasets. This work generalizes the statistical methodology proposed for low angular resolution diffusion tensor imaging by Carmichael and Sakhanenko [3], to several fibers per voxel. It is also a pioneering statistical work on tractography from HARDI data. It avoids all the typical limitations of the deterministic tractography methods and it delivers the same information as probabilistic tractography methods. Our method is computationally cheap and it provides well-founded mathematical and statistical framework where diverse functionals on fibers, directions and tensors can be studied in a systematic and rigorous way. PMID:25937674
Palatini formulation of f( R, T) gravity theory, and its cosmological implications
NASA Astrophysics Data System (ADS)
Wu, Jimin; Li, Guangjie; Harko, Tiberiu; Liang, Shi-Dong
2018-05-01
We consider the Palatini formulation of f( R, T) gravity theory, in which a non-minimal coupling between the Ricci scalar and the trace of the energy-momentum tensor is introduced, by considering the metric and the affine connection as independent field variables. The field equations and the equations of motion for massive test particles are derived, and we show that the independent connection can be expressed as the Levi-Civita connection of an auxiliary, energy-momentum trace dependent metric, related to the physical metric by a conformal transformation. Similar to the metric case, the field equations impose the non-conservation of the energy-momentum tensor. We obtain the explicit form of the equations of motion for massive test particles in the case of a perfect fluid, and the expression of the extra force, which is identical to the one obtained in the metric case. The thermodynamic interpretation of the theory is also briefly discussed. We investigate in detail the cosmological implications of the theory, and we obtain the generalized Friedmann equations of the f( R, T) gravity in the Palatini formulation. Cosmological models with Lagrangians of the type f=R-α ^2/R+g(T) and f=R+α ^2R^2+g(T) are investigated. These models lead to evolution equations whose solutions describe accelerating Universes at late times.
Diffusion tensor imaging of hemispheric asymmetries in the developing brain.
Wilde, Elisabeth A; McCauley, Stephen R; Chu, Zili; Hunter, Jill V; Bigler, Erin D; Yallampalli, Ragini; Wang, Zhiyue J; Hanten, Gerri; Li, Xiaoqi; Ramos, Marco A; Sabir, Sharjeel H; Vasquez, Ana C; Menefee, Deleene; Levin, Harvey S
2009-02-01
Diffusion tensor imaging (DTI) was performed in 39 right-handed children to examine structural hemispheric differences and the impact of age, socioeconomic status, and sex on these differences. Apparent diffusion coefficient (ADC) values were smaller in the left than in the right temporal, prefrontal, anterior internal capsular and the thalamic regions, and fractional anisotropy (FA) values were larger in the left than in the right internal capsule, thalamus, and cingulate. Significant region-by-sex interactions disclosed that the relation of DTI asymmetries to performance depended on sex including the relation of temporal lobes to reading comprehension and the relation of frontal lobes to solving applied mathematical problems.
Filler, Aaron
2009-10-01
Methods were invented that made it possible to image peripheral nerves in the body and to image neural tracts in the brain. The history, physical basis, and dyadic tensor concept underlying the methods are reviewed. Over a 15-year period, these techniques-magnetic resonance neurography (MRN) and diffusion tensor imaging-were deployed in the clinical and research community in more than 2500 published research reports and applied to approximately 50,000 patients. Within this group, approximately 5000 patients having MRN were carefully tracked on a prospective basis. A uniform Neurography imaging methodology was applied in the study group, and all images were reviewed and registered by referral source, clinical indication, efficacy of imaging, and quality. Various classes of image findings were identified and subjected to a variety of small targeted prospective outcome studies. Those findings demonstrated to be clinically significant were then tracked in the larger clinical volume data set. MRN demonstrates mechanical distortion of nerves, hyperintensity consistent with nerve irritation, nerve swelling, discontinuity, relations of nerves to masses, and image features revealing distortion of nerves at entrapment points. These findings are often clinically relevant and warrant full consideration in the diagnostic process. They result in specific pathological diagnoses that are comparable to electrodiagnostic testing in clinical efficacy. A review of clinical outcome studies with diffusion tensor imaging also shows convincing utility. MRN and diffusion tensor imaging neural tract imaging have been validated as indispensable clinical diagnostic methods that provide reliable anatomic pathological information. There is no alternative diagnostic method in many situations. With the elapsing of 15 years, tens of thousands of imaging studies, and thousands of publications, these methods should no longer be considered experimental.
De Santis, Silvia; Bastiani, Matteo; Droby, Amgad; Kolber, Pierre; Zipp, Frauke; Pracht, Eberhard; Stoecker, Tony; Groppa, Sergiu; Roebroeck, Alard
2018-04-07
The recent introduction of advanced magnetic resonance (MR) imaging techniques to characterize focal and global degeneration in multiple sclerosis (MS), like the Composite Hindered and Restricted Model of Diffusion, or CHARMED, diffusional kurtosis imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI) made available new tools to image axonal pathology non-invasively in vivo. These methods already showed greater sensitivity and specificity compared to conventional diffusion tensor-based metrics (e.g., fractional anisotropy), overcoming some of its limitations. While previous studies uncovered global and focal axonal degeneration in MS patients compared to healthy controls, here our aim is to investigate and compare different diffusion MRI acquisition protocols in their ability to highlight microstructural differences between MS and control tissue over several much used models. For comparison, we contrasted the ability of fractional anisotropy measurements to uncover differences between lesion, normal-appearing white matter (WM), gray matter and healthy tissue under the same imaging protocols. We show that: (1) focal and diffuse differences in several microstructural parameters are observed under clinical settings; (2) advanced models (CHARMED, DKI and NODDI) have increased specificity and sensitivity to neurodegeneration when compared to fractional anisotropy measurements; and (3) both high (3 T) and ultra-high fields (7 T) are viable options for imaging tissue change in MS lesions and normal appearing WM, while higher b-values are less beneficial under the tested short-time (10 min acquisition) conditions. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.
White matter connectivity and Internet gaming disorder
Jeong, Bum Seok; Han, Doug Hyun; Kim, Sun Mi; Lee, Sang Won; Renshaw, Perry F.
2017-01-01
Internet use and on-line game play stimulate corticostriatal-limbic circuitry in both healthy subjects and subjects with Internet gaming disorder (IGD). We hypothesized that increased fractional anisotropy (FA) with decreased radial diffusivity (RD) would be observed in IGD subjects, compared with healthy control subjects, and that these white matter indices would be associated with clinical variables including duration of illness and executive function. We screened 181 male patients in order to recruit a large number (n = 58) of IGD subjects without psychiatric co-morbidity as well as 26 male healthy comparison subjects. Multiple diffusion-weighted images were acquired using a 3.0 Tesla magnetic resonance imaging scanner. Tract-based spatial statistics was applied to compare group differences in diffusion tensor imaging (DTI) metrics between IGD and healthy comparison subjects. IGD subjects had increased FA values within forceps minor, right anterior thalamic radiation, right corticospinal tract, right inferior longitudinal fasciculus, right cingulum to hippocampus and right inferior fronto-occipital fasciculus (IFOF) as well as parallel decreases in RD value within forceps minor, right anterior thalamic radiation and IFOF relative to healthy control subjects. In addition, the duration of illness in IGD subjects was positively correlated with the FA values (integrity of white matter fibers) and negatively correlated with RD scores (diffusivity of axonal density) of whole brain white matter. In IGD subjects without psychiatric co-morbidity, our DTI results suggest that increased myelination (increased FA and decreased RD values) in right-sided frontal fiber tracts may be the result of extended game play. PMID:25899390
NASA Astrophysics Data System (ADS)
Das, Ashok
1. Basics of geometry and relativity. 1.1. Two dimensional geometry. 1.2. Inertial and gravitational masses. 1.3. Relativity -- 2. Relativistic dynamics. 2.1. Relativistic point particle. 2.2. Current and charge densities. 2.3. Maxwell's equations in the presence of sources. 2.4. Motion of a charged particle in EM field. 2.5. Energy-momentum tensor. 2.6. Angular momentum -- 3. Principle of general covariance. 3.1. Principle of equivalence. 3.2. Principle of general covariance. 3.3. Tensor densities -- 4. Affine connection and covariant derivative. 4.1. Parallel transport of a vector. 4.2. Christoffel symbol. 4.3. Covariant derivative of contravariant tensors. 4.4. Metric compatibility. 4.5. Covariant derivative of covariant and mixed tensors. 4.6. Electromagnetic analogy. 4.7. Gradient, divergence and curl -- 5. Geodesic equation. 5.1. Covariant differentiation along a curve. 5.2. Curvature from derivatives. 5.3. Parallel transport along a closed curve. 5.4. Geodesic equation. 5.5. Derivation of geodesic equation from a Lagrangian -- 6. Applications of the geodesic equation. 6.1. Geodesic as representing gravitational effect. 6.2. Rotating coordinate system and the Coriolis force. 6.3. Gravitational red shift. 6.4. Twin paradox and general covariance. 6.5. Other equations in the presence of gravitation -- 7. Curvature tensor and Einstein's equation. 7.1. Curvilinear coordinates versus gravitational field. 7.2. Definition of an inertial coordinate frame. 7.3. Geodesic deviation. 7.4. Properties of the curvature tensor. 7.5. Einstein's equation. 7.6. Cosmological constant. 7.7. Initial value problem. 7.8. Einstein's equation from an action -- 8. Schwarzschild solution. 8.1. Line element. 8.2. Connection. 8.3. Solution of the Einstein equation. 8.4. Properties of the Schwarzschild solution. 8.5. Isotropic coordinates -- 9. Tests of general relativity. 9.1. Radar echo experiment. 9.2. Motion of a particle in a Schwarzschild background. 9.3. Motion of light rays in a Schwarzschild background. 9.4. Perihelion advance of Mercury -- 10. Black holes. 10.1. Singularities of the metric. 10.2. Singularities of the Schwarzschild metric. 10.3. Black holes -- 11. Cosmological models and the big bang theory. 11.1. Homogeneity and isotropy. 11.2. Different models of the universe. 11.3. Hubble's law. 11.4. Evolution equation. 11.5. Big bang theory and blackbody radiation.
Similar Tensor Arrays - A Framework for Storage of Tensor Array Data
NASA Astrophysics Data System (ADS)
Brun, Anders; Martin-Fernandez, Marcos; Acar, Burak; Munoz-Moreno, Emma; Cammoun, Leila; Sigfridsson, Andreas; Sosa-Cabrera, Dario; Svensson, Björn; Herberthson, Magnus; Knutsson, Hans
This chapter describes a framework for storage of tensor array data, useful to describe regularly sampled tensor fields. The main component of the framework, called Similar Tensor Array Core (STAC), is the result of a collaboration between research groups within the SIMILAR network of excellence. It aims to capture the essence of regularly sampled tensor fields using a minimal set of attributes and can therefore be used as a “greatest common divisor” and interface between tensor array processing algorithms. This is potentially useful in applied fields like medical image analysis, in particular in Diffusion Tensor MRI, where misinterpretation of tensor array data is a common source of errors. By promoting a strictly geometric perspective on tensor arrays, with a close resemblance to the terminology used in differential geometry, (STAC) removes ambiguities and guides the user to define all necessary information. In contrast to existing tensor array file formats, it is minimalistic and based on an intrinsic and geometric interpretation of the array itself, without references to other coordinate systems.
Chiang, Chia-Wen; Wang, Yong; Sun, Peng; Lin, Tsen-Hsuan; Trinkaus, Kathryn; Cross, Anne H.; Song, Sheng-Kwei
2014-01-01
The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA), increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice. PMID:25017446
Ye, Chuyang; Murano, Emi; Stone, Maureen; Prince, Jerry L
2015-10-01
The tongue is a critical organ for a variety of functions, including swallowing, respiration, and speech. It contains intrinsic and extrinsic muscles that play an important role in changing its shape and position. Diffusion tensor imaging (DTI) has been used to reconstruct tongue muscle fiber tracts. However, previous studies have been unable to reconstruct the crossing fibers that occur where the tongue muscles interdigitate, which is a large percentage of the tongue volume. To resolve crossing fibers, multi-tensor models on DTI and more advanced imaging modalities, such as high angular resolution diffusion imaging (HARDI) and diffusion spectrum imaging (DSI), have been proposed. However, because of the involuntary nature of swallowing, there is insufficient time to acquire a sufficient number of diffusion gradient directions to resolve crossing fibers while the in vivo tongue is in a fixed position. In this work, we address the challenge of distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging by using a multi-tensor model with a fixed tensor basis and incorporating prior directional knowledge. The prior directional knowledge provides information on likely fiber directions at each voxel, and is computed with anatomical knowledge of tongue muscles. The fiber directions are estimated within a maximum a posteriori (MAP) framework, and the resulting objective function is solved using a noise-aware weighted ℓ1-norm minimization algorithm. Experiments were performed on a digital crossing phantom and in vivo tongue diffusion data including three control subjects and four patients with glossectomies. On the digital phantom, effects of parameters, noise, and prior direction accuracy were studied, and parameter settings for real data were determined. The results on the in vivo data demonstrate that the proposed method is able to resolve interdigitated tongue muscles with limited gradient directions. The distributions of the computed fiber directions in both the controls and the patients were also compared, suggesting a potential clinical use for this imaging and image analysis methodology. Copyright © 2015 Elsevier Ltd. All rights reserved.
Thermodynamic metrics and optimal paths.
Sivak, David A; Crooks, Gavin E
2012-05-11
A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.
Molinuevo, José Luis; Ripolles, Pablo; Simó, Marta; Lladó, Albert; Olives, Jaume; Balasa, Mircea; Antonell, Anna; Rodriguez-Fornells, Antoni; Rami, Lorena
2014-12-01
The aim of this study was to use diffusion tensor imaging measures to determine the existence of white matter microstructural differences in the preclinical phases of Alzheimer's disease, assessing cognitively normal older individuals with positive amyloid β protein (Aβ42) levels (CN_Aβ42+) on the basis of normal cognition and cerebrospinal fluid Aβ42 levels below 500 pg/mL. Nineteen CN_Aβ42+ and 19 subjects with Aβ42 levels above 500 pg/mL (CN_Aβ42-) were included. We encountered increases in axial diffusivity (AxD) in CN_Aβ42+ relative to CN_Aβ42- in the corpus callosum, corona radiata, internal capsule, and superior longitudinal fasciculus bilaterally, and also in the left fornix, left uncinate fasciculus, and left inferior fronto-occipital fasciculus. However, no differences were found in other diffusion tensor imaging indexes. Cognitive reserve scores were positively associated with AxD exclusively in the CN_Aβ42+ group. The finding of AxD alteration together with preserved fractional anisotropy, mean diffusivity, and radial diffusivity indexes in the CN_Aβ42+ group may indicate that, subtle axonal changes may be happening in the preclinical phases of Alzheimer's disease, whereas white matter integrity is still widely preserved. Copyright © 2014 Elsevier Inc. All rights reserved.
Rodriguez Gutierrez, Daniel; Manita, Muftah; Jaspan, Tim; Dineen, Robert A.; Grundy, Richard G.; Auer, Dorothee P.
2013-01-01
Background Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response. Methods Eighteen patients (age range, 1.9–20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1–16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM). Results Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η2 = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis. Conclusions We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols. PMID:23585630
A general mass term for bigravity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cusin, Giulia; Durrer, Ruth; Guarato, Pietro
2016-04-01
We introduce a new formalism to study perturbations of Hassan-Rosen bigravity theory, around general backgrounds for the two dynamical metrics. In particular, we derive the general expression for the mass term of the perturbations and we explicitly compute it for cosmological settings. We study tensor perturbations in a specific branch of bigravity using this formalism. We show that the tensor sector is affected by a late-time instability, which sets in when the mass matrix is no longer positive definite.
Brain white matter microstructure is associated with susceptibility to motion-induced nausea.
Napadow, V; Sheehan, J; Kim, J; Dassatti, A; Thurler, A H; Surjanhata, B; Vangel, M; Makris, N; Schaechter, J D; Kuo, B
2013-05-01
Nausea is associated with significant morbidity, and there is a wide range in the propensity of individuals to experience nausea. The neural basis of the heterogeneity in nausea susceptibility is poorly understood. Our previous functional magnetic resonance imaging (fMRI) study in healthy adults showed that a visual motion stimulus caused activation in the right MT+/V5 area, and that increased sensation of nausea due to this stimulus was associated with increased activation in the right anterior insula. For the current study, we hypothesized that individual differences in visual motion-induced nausea are due to microstructural differences in the inferior fronto-occipital fasciculus (IFOF), the white matter tract connecting the right visual motion processing area (MT+/V5) and right anterior insula. To test this hypothesis, we acquired diffusion tensor imaging data from 30 healthy adults who were subsequently dichotomized into high and low nausea susceptibility groups based on the Motion Sickness Susceptibility Scale. We quantified diffusion along the IFOF for each subject based on axial diffusivity (AD); radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA), and evaluated between-group differences in these diffusion metrics. Subjects with high susceptibility to nausea rated significantly (P < 0.001) higher nausea intensity to visual motion stimuli and had significantly (P < 0.05) lower AD and MD along the right IFOF compared to subjects with low susceptibility to nausea. This result suggests that differences in white matter microstructure within tracts connecting visual motion and nausea-processing brain areas may contribute to nausea susceptibility or may have resulted from an increased history of nausea episodes. © 2013 Blackwell Publishing Ltd.
Experimental considerations for fast kurtosis imaging.
Hansen, Brian; Lund, Torben E; Sangill, Ryan; Stubbe, Ebbe; Finsterbusch, Jürgen; Jespersen, Sune Nørhøj
2016-11-01
The clinical use of kurtosis imaging is impeded by long acquisitions and postprocessing. Recently, estimation of mean kurtosis tensor W¯ and mean diffusivity ( D¯) was made possible from 13 distinct diffusion weighted MRI acquisitions (the 1-3-9 protocol) with simple postprocessing. Here, we analyze the effects of noise and nonideal diffusion encoding, and propose a new correction strategy. We also present a 1-9-9 protocol with increased robustness to experimental imperfections and minimal additional scan time. This refinement does not affect computation time and also provides a fast estimate of fractional anisotropy (FA). 1-3-9/1-9-9 data are acquired in rat and human brains, and estimates of D¯, FA, W¯ from human brains are compared with traditional estimates from an extensive diffusion kurtosis imaging data set. Simulations are used to evaluate the influence of noise and diffusion encodings deviating from the scheme, and the performance of the correction strategy. Optimal b-values are determined from simulations and data. Accuracy and precision in D¯ and W¯ are comparable to nonlinear least squares estimation, and is improved with the 1-9-9 protocol. The compensation strategy vastly improves parameter estimation in nonideal data. The framework offers a robust and compact method for estimating several diffusion metrics. The protocol is easily implemented. Magn Reson Med 76:1455-1468, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Diffusion of phonons through (along and across) the ultrathin crystalline films
NASA Astrophysics Data System (ADS)
Šetrajčić, J. P.; Jaćimovski, S. K.; Vučenović, S. M.
2017-11-01
Instead of usual approach, applying displacement-displacement Green's functions, the momentum-momentum Green's functions will be used to calculate the diffusion tensor. With this type of Green's function we have calculated and analyzed dispersion law in film-structures. A small number of phonon energy levels along the direction of boundary surfaces joint of the film are discrete-ones and in this case standing waves could occur. This is consequence of quantum size effects. These Green's functions enter into Kubo's formula defining diffusion properties of the system and possible heat transfer direction through observed structures. Calculation of the diffusion tensor for phonons in film-structure requires solving of the system of difference equations. Boundary conditions are included into mentioned system through the Hamiltonian of the film-structure. It has been shown that the diagonal elements of the diffusion tensor express discrete behavior of the dispersion law of elementary excitations. More important result is-that they are temperature independent and that their values are much higher comparing with bulk structures. This result favors better heat conduction of the film, but in direction which is perpendicular to boundary film surface. In the same time this significantly favors appearance 2D superconducting surfaces inside the ultra-thin crystal structure, which are parallel to the boundary surface.
Nenadić, Igor; Hoof, Anna; Dietzek, Maren; Langbein, Kerstin; Reichenbach, Jürgen R; Sauer, Heinrich; Güllmar, Daniel
2017-08-30
Both schizophrenia and bipolar disorder show abnormalities of white matter, as seen in diffusion tensor imaging (DTI) analyses of major brain fibre bundles. While studies in each of the two conditions have indicated possible overlap in anatomical location, there are few direct comparisons between the disorders. Also, it is unclear whether phenotypically similar subgroups (e.g. patients with bipolar disorder and psychotic features) might share white matter pathologies or be rather similar. Using region-of-interest (ROI) analysis of white matter with diffusion tensor imaging (DTI) at 3 T, we analysed fractional anisotropy (FA), radial diffusivity (RD), and apparent diffusion coefficient (ADC) of the corpus callosum and cingulum bundle in 33 schizophrenia patients, 17 euthymic (previously psychotic) bipolar disorder patients, and 36 healthy controls. ANOVA analysis showed significant main effects of group for RD and ADC (both elevated in schizophrenia). Across the corpus callosum ROIs, there was not group effect on FA, but for RD (elevated in schizophrenia, lower in bipolar disorder) and ADC (higher in schizophrenia, intermediate in bipolar disorder). Our findings show similarities and difference (some gradual) across regions of the two major fibre tracts implicated in these disorders, which would be consistent with a neurobiological overlap of similar clinical phenotypes. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.
Prasath, V B S; Pelapur, R; Glinskii, O V; Glinsky, V V; Huxley, V H; Palaniappan, K
2015-04-01
Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.
Geometry of matrix product states: Metric, parallel transport, and curvature
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haegeman, Jutho, E-mail: jutho.haegeman@gmail.com; Verstraete, Frank; Faculty of Physics and Astronomy, University of Ghent, Krijgslaan 281 S9, 9000 Gent
2014-02-15
We study the geometric properties of the manifold of states described as (uniform) matrix product states. Due to the parameter redundancy in the matrix product state representation, matrix product states have the mathematical structure of a (principal) fiber bundle. The total space or bundle space corresponds to the parameter space, i.e., the space of tensors associated to every physical site. The base manifold is embedded in Hilbert space and can be given the structure of a Kähler manifold by inducing the Hilbert space metric. Our main interest is in the states living in the tangent space to the base manifold,more » which have recently been shown to be interesting in relation to time dependence and elementary excitations. By lifting these tangent vectors to the (tangent space) of the bundle space using a well-chosen prescription (a principal bundle connection), we can define and efficiently compute an inverse metric, and introduce differential geometric concepts such as parallel transport (related to the Levi-Civita connection) and the Riemann curvature tensor.« less
Nonsymmetric gravity theories: Inconsistencies and a cure
NASA Astrophysics Data System (ADS)
Damour, T.; Deser, S.; McCarthy, J.
1993-02-01
Motivated by the apparent dependence of string σ models on the sum of spacetime metric and antisymmetric tensor fields, we reconsider gravity theories constructed from a nonsymmetric metric. We first show, by expanding in powers of the antisymmetric field, that all such ``geometrical'' theories homogeneous in second derivatives violate standard physical requirements: ghost freedom, absence of algebraic inconsistencies, or continuity of degree-of-freedom content. This no-go result applies in particular to the old unified theory of Einstein and its recent avatars. However, we find that the addition of nonderivative, ``cosmological'' terms formally restores consistency by giving a mass to the antisymmetric tensor field, thereby transmuting it into a fifth-force-like massive vector but with novel possible matter couplings. The resulting macroscopic models also exhibit ``van der Waals''-type gravitational effects, and may provide useful phenomenological foils to general relativity.
Hidden symmetries for ellipsoid-solitonic deformations of Kerr-Sen black holes and quantum anomalies
NASA Astrophysics Data System (ADS)
Vacaru, Sergiu I.
2013-02-01
We prove the existence of hidden symmetries in the general relativity theory defined by exact solutions with generic off-diagonal metrics, nonholonomic (non-integrable) constraints, and deformations of the frame and linear connection structure. A special role in characterization of such spacetimes is played by the corresponding nonholonomic generalizations of Stackel-Killing and Killing-Yano tensors. There are constructed new classes of black hole solutions and we study hidden symmetries for ellipsoidal and/or solitonic deformations of "prime" Kerr-Sen black holes into "target" off-diagonal metrics. In general, the classical conserved quantities (integrable and not-integrable) do not transfer to the quantized systems and produce quantum gravitational anomalies. We prove that such anomalies can be eliminated via corresponding nonholonomic deformations of fundamental geometric objects (connections and corresponding Riemannian and Ricci tensors) and by frame transforms.
Srivastava, Anshu; Chaturvedi, Saurabh; Gupta, Rakesh Kumar; Malik, Rohan; Mathias, Amrita; Jagannathan, Naranamangalam R; Jain, Sunil; Pandey, Chandra Mani; Yachha, Surender Kumar; Rathore, Ram Kishor Singh
2017-03-01
Data on minimal hepatic encephalopathy (MHE) in children is scarce. We aimed to study MHE in children with chronic liver disease (CLD) and to validate non-invasive objective tests which can assist in its diagnosis. We evaluated 67 children with CLD (38 boys; age 13 [7-18] years) and 37 healthy children to determine the prevalence of MHE. We also assessed the correlation of MHE with changes in brain metabolites by magnetic resonance spectroscopy ( 1 HMRS), diffusion tensor imaging (DTI) derived metrics, blood ammonia and inflammatory cytokines (interleukin-6 [IL6], tumor necrosis factor alpha [TNF-α]). In addition, the accuracy of MR-based investigations for diagnosis of MHE in comparison to neuropsychological tests was analysed. Thirty-four (50.7%) children with CLD had MHE on neuropsychological tests. MHE patients had higher BA (30.5 [6-74] vs. 14 [6-66]μmol/L; p=0.02), IL-6 (8.3 [4.7-28.7] vs. 7.6 [4.7-20.7]pg/ml; p=0.4) and TNF-α (17.8 [7.8-65.5] vs. 12.8 [7.5-35]pg/ml; p=0.06) than No-MHE. 1 HMRS showed higher glutamine (2.6 [2.1-3.3] vs. 2.4 [2.0-3.1]; p=0.02), and lower choline (0.20 [0.14-0.25] vs. 0.22 [0.17-0.28]; p=0.1) and myo-inositol (0.25 [0.14-0.41] vs. 0.29 [0.21-0.66]; p=0.2) in MHE patients than those without MHE. Mean diffusivity (MD) on DTI was significantly higher in 6/11 brain areas in patients with MHE vs. no MHE. Brain glutamine had a significant positive correlation with blood ammonia, IL-6, TNF-α and MD of various brain regions. Neuropsychological tests showed a negative correlation with blood ammonia, IL6, TNF-α, glutamine and MD. Frontal white matter MD had a sensitivity and specificity of 73.5% and 100% for diagnosing MHE. In children with CLD, 50% have MHE. There is a significant positive correlation between markers of hyperammonemia, inflammation and brain edema and these correlate negatively with neuropsychological tests. MD on DTI is a reliable tool for diagnosing MHE. Fifty percent of children with chronic liver disease develop minimal hepatic encephalopathy (MHE) and perform poorly on neuropsychological testing. These children have raised blood ammonia, inflammatory cytokines and mild cerebral edema on diffusion tensor imaging as compared to children without MHE. The higher the ammonia, inflammatory cytokines and cerebral edema levels the poorer the performance on neuropsychological assessment. The estimation of mean diffusivity on diffusion tensor imaging is an objective and reliable method for diagnosing MHE. Copyright © 2016 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Detailed stress tensor measurements in a centrifugal compressor vaneless diffuser
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pinarbasi, A.; Johnson, M.W.
1996-04-01
Detailed flow measurements have been made in the vaneless diffuser of a large low-speed centrifugal compressor using hot-wire anemometry. The three time mean velocity components and full stress tensor distributions have been determined on eight measurement plans within the diffuser. High levels of Reynolds stress result in the rapid mixing out of the blade wake. Although high levels of turbulent kinetic energy are found in the passage wake, they are not associated with strong Reynolds stresses and hence the passage wake mixes out only slowly. Low-frequency meandering of the wake position is therefore likely to be responsible for the highmore » kinetic energy levels. The anisotropic nature of the turbulence suggests that Reynolds stress turbulence models are required for CFD modeling of diffuser flows.« less
Motion Artifact Reduction in Pediatric Diffusion Tensor Imaging Using Fast Prospective Correction
Alhamud, A.; Taylor, Paul A.; Laughton, Barbara; van der Kouwe, André J.W.; Meintjes, Ernesta M.
2014-01-01
Purpose To evaluate the patterns of head motion in scans of young children and to examine the influence of corrective techniques, both qualitatively and quantitatively. We investigate changes that both retrospective (with and without diffusion table reorientation) and prospective (implemented with a short navigator sequence) motion correction induce in the resulting diffusion tensor measures. Materials and Methods Eighteen pediatric subjects (aged 5–6 years) were scanned using 1) a twice-refocused, 2D diffusion pulse sequence, 2) a prospectively motion-corrected, navigated diffusion sequence with reacquisition of a maximum of five corrupted diffusion volumes, and 3) a T1-weighted structural image. Mean fractional anisotropy (FA) values in white and gray matter regions, as well as tractography in the brainstem and projection fibers, were evaluated to assess differences arising from retrospective (via FLIRT in FSL) and prospective motion correction. In addition to human scans, a stationary phantom was also used for further evaluation. Results In several white and gray matter regions retrospective correction led to significantly (P < 0.05) reduced FA means and altered distributions compared to the navigated sequence. Spurious tractographic changes in the retrospectively corrected data were also observed in subject data, as well as in phantom and simulated data. Conclusion Due to the heterogeneity of brain structures and the comparatively low resolution (~2 mm) of diffusion data using 2D single shot sequencing, retrospective motion correction is susceptible to distortion from partial voluming. These changes often negatively bias diffusion tensor imaging parameters. Prospective motion correction was shown to produce smaller changes. PMID:24935904
Motion artifact reduction in pediatric diffusion tensor imaging using fast prospective correction.
Alhamud, A; Taylor, Paul A; Laughton, Barbara; van der Kouwe, André J W; Meintjes, Ernesta M
2015-05-01
To evaluate the patterns of head motion in scans of young children and to examine the influence of corrective techniques, both qualitatively and quantitatively. We investigate changes that both retrospective (with and without diffusion table reorientation) and prospective (implemented with a short navigator sequence) motion correction induce in the resulting diffusion tensor measures. Eighteen pediatric subjects (aged 5-6 years) were scanned using 1) a twice-refocused, 2D diffusion pulse sequence, 2) a prospectively motion-corrected, navigated diffusion sequence with reacquisition of a maximum of five corrupted diffusion volumes, and 3) a T1 -weighted structural image. Mean fractional anisotropy (FA) values in white and gray matter regions, as well as tractography in the brainstem and projection fibers, were evaluated to assess differences arising from retrospective (via FLIRT in FSL) and prospective motion correction. In addition to human scans, a stationary phantom was also used for further evaluation. In several white and gray matter regions retrospective correction led to significantly (P < 0.05) reduced FA means and altered distributions compared to the navigated sequence. Spurious tractographic changes in the retrospectively corrected data were also observed in subject data, as well as in phantom and simulated data. Due to the heterogeneity of brain structures and the comparatively low resolution (∼2 mm) of diffusion data using 2D single shot sequencing, retrospective motion correction is susceptible to distortion from partial voluming. These changes often negatively bias diffusion tensor imaging parameters. Prospective motion correction was shown to produce smaller changes. © 2014 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Meade, Brendan J.; DeVries, Phoebe M. R.; Faller, Jeremy; Viegas, Fernanda; Wattenberg, Martin
2017-11-01
Aftershocks may be triggered by the stresses generated by preceding mainshocks. The temporal frequency and maximum size of aftershocks are well described by the empirical Omori and Bath laws, but spatial patterns are more difficult to forecast. Coulomb failure stress is perhaps the most common criterion invoked to explain spatial distributions of aftershocks. Here we consider the spatial relationship between patterns of aftershocks and a comprehensive list of 38 static elastic scalar metrics of stress (including stress tensor invariants, maximum shear stress, and Coulomb failure stress) from 213 coseismic slip distributions worldwide. The rates of true-positive and false-positive classification of regions with and without aftershocks are assessed with receiver operating characteristic analysis. We infer that the stress metrics that are most consistent with observed aftershock locations are maximum shear stress and the magnitude of the second and third invariants of the stress tensor. These metrics are significantly better than random assignment at a significance level of 0.005 in over 80% of the slip distributions. In contrast, the widely used Coulomb failure stress criterion is distinguishable from random assignment in only 51-64% of the slip distributions. These results suggest that a number of alternative scalar metrics are better predictors of aftershock locations than classic Coulomb failure stress change.
Quantitative T2 mapping of white matter: applications for ageing and cognitive decline
NASA Astrophysics Data System (ADS)
Knight, Michael J.; McCann, Bryony; Tsivos, Demitra; Dillon, Serena; Coulthard, Elizabeth; Kauppinen, Risto A.
2016-08-01
In MRI, the coherence lifetime T2 is sensitive to the magnetic environment imposed by tissue microstructure and biochemistry in vivo. Here we explore the possibility that the use of T2 relaxometry may provide information complementary to that provided by diffusion tensor imaging (DTI) in ageing of healthy controls (HC), Alzheimer’s disease (AD) and mild cognitive impairment (MCI). T2 and diffusion MRI metrics were quantified in HC and patients with MCI and mild AD using multi-echo MRI and DTI. We used tract-based spatial statistics (TBSS) to evaluate quantitative MRI parameters in white matter (WM). A prolonged T2 in WM was associated with AD, and able to distinguish AD from MCI, and AD from HC. Shorter WM T2 was associated with better cognition and younger age in general. In no case was a reduction in T2 associated with poorer cognition. We also applied principal component analysis, showing that WM volume changes independently of T2, MRI diffusion indices and cognitive performance indices. Our data add to the evidence that age-related and AD-related decline in cognition is in part attributable to WM tissue state, and much less to WM quantity. These observations suggest that WM is involved in AD pathology, and that T2 relaxometry is a potential imaging modality for detecting and characterising WM in cognitive decline and dementia.
Diffusion-weighted imaging and diffusion tensor imaging of asymptomatic lumbar disc herniation.
Sakai, Toshinori; Miyagi, Ryo; Yamabe, Eiko; Fujinaga, Yasunari; N Bhatia, Nitin; Yoshioka, Hiroshi
2014-01-01
Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) were performed on a healthy 31-year-old man with asymptomatic lumbar disc herniation. Although the left S1 nerve root was obviously entrapped by a herniated mass, neither DWI nor DTI showed any significant findings for the nerve root. Decreased apparent diffusion coefficient (ADC) values and increased fractional anisotropy (FA) values were found. These results are contrary to those in previously published studies of symptomatic patients, in which a combination of increased ADC and decreased FA seem to have a relationship with nerve injury and subsequent symptoms, such as leg pain or palsy. Our results seen in an asymptomatic subject suggest that the compressed nerve with no injury, such as edema, demyelination, or persistent axonal injury, may be indicated by a combination of decreased ADC and increased FA. ADC and FA could therefore be potential tools to elucidate the pathomechanism of radiculopathy.
Mild traumatic brain injury: is diffusion imaging ready for primetime in forensic medicine?
Grossman, Elan J; Inglese, Matilde; Bammer, Roland
2010-12-01
Mild traumatic brain injury (MTBI) is difficult to accurately assess with conventional imaging because such approaches usually fail to detect any evidence of brain damage. Recent studies of MTBI patients using diffusion-weighted imaging and diffusion tensor imaging suggest that these techniques have the potential to help grade tissue damage severity, track its development, and provide prognostic markers for clinical outcome. Although these results are promising and indicate that the forensic diagnosis of MTBI might eventually benefit from the use of diffusion-weighted imaging and diffusion tensor imaging, healthy skepticism and caution should be exercised with regard to interpreting their meaning because there is no consensus about which methods of data analysis to use and very few investigations have been conducted, of which most have been small in sample size and examined patients at only one time point after injury.
NASA Astrophysics Data System (ADS)
Zhao, L.; Zank, G. P.; Adhikari, L.
2017-12-01
The radial and rigidity dependence of cosmic ray (CR) diffusion tensor is investigated on the basis of the recently developed 2D and slab turbulence transport model using nearly incompressible (NI) theory (Zank et al. 2017; Adhikari et al. 2017). We use the energy in forward propagating modes from 0.29 to 1 AU and in backward propagating modes from 1 to 75 AU. We employ the quasi-linear theory (QLT) and nonlinear guiding center (NLGC) theory, respectively, to determine the parallel and perpendicular elements of CR diffusion tensor. We also present the effect of both weak and moderately strong turbulence on the drift element of CR diffusion tensor. We find that (1) from 0.29 to 1 AU the radial mean free path (mfp) is dominated by the parallel component, both increase slowly after 0.4 AU; (2) from 1 to 75 AU the radial mfp starts with a rapid increase and then decreases after a peak at about 3.5 AU, mainly caused by pick-up ion sources of turbulence model; (3) after 20 AU the perpendicular mfp is nearly constant and begin to dominate the radial mfp; (4) the rigidity dependence of the parallel mfp is proportional to at 1 AU from 0.1 to 10 GV and the perpendicular mfp is weakly influenced by the rigidity; (5) turbulence does more than suppress the traditional drift element but introduces a new component normal to the magnetic field. This study shows that a proper two-component turbulence model is necessary to produce the complexity of diffusion coefficient for CR modulation throughout the heliosphere.
Müller, Hans-Peter; Grön, Georg; Sprengelmeyer, Reiner; Kassubek, Jan; Ludolph, Albert C; Hobbs, Nicola; Cole, James; Roos, Raymund A C; Duerr, Alexandra; Tabrizi, Sarah J; Landwehrmeyer, G Bernhard; Süssmuth, Sigurd D
2013-01-01
Assessment of the feasibility to average diffusion tensor imaging (DTI) metrics of MRI data acquired in the course of a multicenter study. Sixty-one early stage Huntington's disease patients and forty healthy controls were studied using four different MR scanners at four European sites with acquisition protocols as close as possible to a given standard protocol. The potential and feasibility of averaging data acquired at different sites was evaluated quantitatively by region-of-interest (ROI) based statistical comparisons of coefficients of variation (CV) across centers, as well as by testing for significant group-by-center differences on averaged fractional anisotropy (FA) values between patients and controls. In addition, a whole-brain based statistical between-group comparison was performed using FA maps. The ex post facto statistical evaluation of CV and FA-values in a priori defined ROIs showed no differences between sites above chance indicating that data were not systematically biased by center specific factors. Averaging FA-maps from DTI data acquired at different study sites and different MR scanner types does not appear to be systematically biased. A suitable recipe for testing on the possibility to pool multicenter DTI data is provided to permit averaging of DTI-derived metrics to differentiate patients from healthy controls at a larger scale.
Crossing Fibers Detection with an Analytical High Order Tensor Decomposition
Megherbi, T.; Kachouane, M.; Oulebsir-Boumghar, F.; Deriche, R.
2014-01-01
Diffusion magnetic resonance imaging (dMRI) is the only technique to probe in vivo and noninvasively the fiber structure of human brain white matter. Detecting the crossing of neuronal fibers remains an exciting challenge with an important impact in tractography. In this work, we tackle this challenging problem and propose an original and efficient technique to extract all crossing fibers from diffusion signals. To this end, we start by estimating, from the dMRI signal, the so-called Cartesian tensor fiber orientation distribution (CT-FOD) function, whose maxima correspond exactly to the orientations of the fibers. The fourth order symmetric positive definite tensor that represents the CT-FOD is then analytically decomposed via the application of a new theoretical approach and this decomposition is used to accurately extract all the fibers orientations. Our proposed high order tensor decomposition based approach is minimal and allows recovering the whole crossing fibers without any a priori information on the total number of fibers. Various experiments performed on noisy synthetic data, on phantom diffusion, data and on human brain data validate our approach and clearly demonstrate that it is efficient, robust to noise and performs favorably in terms of angular resolution and accuracy when compared to some classical and state-of-the-art approaches. PMID:25246940
NASA Astrophysics Data System (ADS)
Akhtar, S. S.; Hussain, T.; Bokhari, A. H.; Khan, F.
2018-04-01
We provide a complete classification of static plane symmetric space-times according to conformal Ricci collineations (CRCs) and conformal matter collineations (CMCs) in both the degenerate and nondegenerate cases. In the case of a nondegenerate Ricci tensor, we find a general form of the vector field generating CRCs in terms of unknown functions of t and x subject to some integrability conditions. We then solve the integrability conditions in different cases depending upon the nature of the Ricci tensor and conclude that the static plane symmetric space-times have a 7-, 10- or 15-dimensional Lie algebra of CRCs. Moreover, we find that these space-times admit an infinite number of CRCs if the Ricci tensor is degenerate. We use a similar procedure to study CMCs in the case of a degenerate or nondegenerate matter tensor. We obtain the exact form of some static plane symmetric space-time metrics that admit nontrivial CRCs and CMCs. Finally, we present some physical applications of our obtained results by considering a perfect fluid as a source of the energy-momentum tensor.
On Anholonomic Deformation, Geometry, and Differentiation
2013-02-01
αβχ are not necessarily Levi - Civita connection coefficients). The vector cross product × obeys, for two vectors V and W and two covectors α and β , V...three-dimensional space. 2.2.5. Euclidean space. Let GAB(X ) = GA · GB be the metric tensor of the space. The Levi - Civita connection coefficients of GAB...curvature tensor of the Levi - Civita connection vanishes identically: G R A BCD = 2 ( ∂[B G A C]D + G A[B|E|G EC]D ) = 0. (43) In n
Hidden symmetries on toric Sasaki-Einstein spaces
NASA Astrophysics Data System (ADS)
Slesar, V.; Visinescu, M.; Vîlcu, G. E.
2015-05-01
We describe the construction of Killing-Yano tensors on toric Sasaki-Einstein manifolds. We use the fact that the metric cones of these spaces are Calabi-Yau manifolds. The description of the Calabi-Yau manifolds in terms of toric data, using the Delzant approach to toric geometries, allows us to find explicitly the complex coordinates and write down the Killing-Yano tensors. As a concrete example we present the complete set of special Killing forms on the five-dimensional homogeneous Sasaki-Einstein manifold T 1,1.
2010-09-01
how personal protective equipment affects the brain’s response to blasts. In this study we investigated the effect of the Advanced Combat...analyzing stress wave propagation, which is the main dynamic effect loading the brain tissue during a blast event. We consider two key metrics of stress ...Cauchy stress tensor, and sij ¼ σij − 13σkkδij are the compo- nents of the deviatoric stress tensor (24). Fig. 1 shows snapshots of the pressure
Chen, Xiaobo; Zhang, Han; Zhang, Lichi; Shen, Celina; Lee, Seong-Whan; Shen, Dinggang
2017-10-01
Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for diagnosing various neurodegenerative diseases, including Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Current studies mainly construct the FC networks between grey matter (GM) regions of the brain based on temporal co-variations of the blood oxygenation level-dependent (BOLD) signals, which reflects the synchronized neural activities. However, it was rarely investigated whether the FC detected within the white matter (WM) could provide useful information for diagnosis. Motivated by the recently proposed functional correlation tensors (FCT) computed from RS-fMRI and used to characterize the structured pattern of local FC in the WM, we propose in this article a novel MCI classification method based on the information conveyed by both the FC between the GM regions and that within the WM regions. Specifically, in the WM, the tensor-based metrics (e.g., fractional anisotropy [FA], similar to the metric calculated based on diffusion tensor imaging [DTI]) are first calculated based on the FCT and then summarized along each of the major WM fiber tracts connecting each pair of the brain GM regions. This could capture the functional information in the WM, in a similar network structure as the FC network constructed for the GM, based only on the same RS-fMRI data. Moreover, a sliding window approach is further used to partition the voxel-wise BOLD signal into multiple short overlapping segments. Then, both the FC and FCT between each pair of the brain regions can be calculated based on the BOLD signal segments in the GM and WM, respectively. In such a way, our method can generate dynamic FC and dynamic FCT to better capture functional information in both GM and WM and further integrate them together by using our developed feature extraction, selection, and ensemble learning algorithms. The experimental results verify that the dynamic FCT can provide valuable functional information in the WM; by combining it with the dynamic FC in the GM, the diagnosis accuracy for MCI subjects can be significantly improved even using RS-fMRI data alone. Hum Brain Mapp 38:5019-5034, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
A note on stress-driven anisotropic diffusion and its role in active deformable media.
Cherubini, Christian; Filippi, Simonetta; Gizzi, Alessio; Ruiz-Baier, Ricardo
2017-10-07
We introduce a new model to describe diffusion processes within active deformable media. Our general theoretical framework is based on physical and mathematical considerations, and it suggests to employ diffusion tensors directly influenced by the coupling with mechanical stress. The proposed generalised reaction-diffusion-mechanics model reveals that initially isotropic and homogeneous diffusion tensors turn into inhomogeneous and anisotropic quantities due to the intrinsic structure of the nonlinear coupling. We study the physical properties leading to these effects, and investigate mathematical conditions for its occurrence. Together, the mathematical model and the numerical results obtained using a mixed-primal finite element method, clearly support relevant consequences of stress-driven diffusion into anisotropy patterns, drifting, and conduction velocity of the resulting excitation waves. Our findings also indicate the applicability of this novel approach in the description of mechano-electric feedback in actively deforming bio-materials such as the cardiac tissue. Copyright © 2017. Published by Elsevier Ltd.
Investigating Musical Disorders with Diffusion Tensor Imaging: a Comparison of Imaging Parameters
Loui, Psyche; Schlaug, Gottfried
2009-01-01
The Arcuate Fasciculus (AF) is a bundle of white matter traditionally thought to be responsible for language function. However, its role in music is not known. Here we investigate the connectivity of the AF using Diffusion Tensor Imaging (DTI) and show that musically tone-deaf individuals, who show impairments in pitch discrimination, have reduced connectivity in the AF relative to musically normal-functioning control subjects. Results were robust to variations in imaging parameters and emphasize the importance of brain connectivity in para-linguistic processes such as music. PMID:19673766
The physical and biological basis of quantitative parameters derived from diffusion MRI
2012-01-01
Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy). Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses. The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times. In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information. PMID:23289085
Khan, Ahmad Raza; Hansen, Brian; Wiborg, Ove; Kroenke, Christopher D; Jespersen, Sune Nørhøj
2018-02-15
Chronic mild stress (CMS) induced depression elicits several debilitating symptoms and causes a significant economic burden on society. High variability in the symptomatology of depression poses substantial impediment to accurate diagnosis and therapy outcome. CMS exposure induces significant metabolic and microstructural alterations in the hippocampus (HP), prefrontal cortex (PFC), caudate-putamen (CP) and amygdala (AM), however, recovery from these maladaptive changes are limited and this may provide negative effects on the therapeutic treatment and management of depression. The present study utilized anhedonic rats from the unpredictable CMS model of depression to study metabolic recovery in the ventral hippocampus (vHP) and microstructural recovery in the HP, AM, CP, and PFC. The study employed 1 H MR spectroscopy ( 1 H MRS) and in-vivo diffusion MRI (d-MRI) at the age of week 18 (week 1 post CMS exposure) week 20 (week 3 post CMS) and week 25 (week 8 post CMS exposure) in the anhedonic group, and at the age of week 18 and week 22 in the control group. The d-MRI data have provided an array of diffusion tensor metrics (FA, MD, AD, and RD), and fast kurtosis metrics (MKT, W L and W T ). CMS exposure induced a significant metabolic alteration in vHP, and significant microstructural alterations were observed in the HP, AM, and PFC in comparison to the age match control and within the anhedonic group. A significantly high level of N-acetylaspartate (NAA) was observed in vHP at the age of week 18 in comparison to age match control and week 20 and week 25 of the anhedonic group. HP and AM showed significant microstructural alterations up to the age of week 22 in the anhedonic group. PFC showed significant microstructural alterations only at the age of week 18, however, most of the metrics showed significantly higher value at the age of week 20 in the anhedonic group. The significantly increased NAA concentration may indicate impaired catabolism due to astrogliosis or oxidative stress. The significantly increased W L in the AM and HP may indicate hypertrophy of AM and reduced volume of HP. Such metabolic and microstructural alterations could be useful in disease diagnosis and follow-up treatment intervention in depression and similar disorders. Copyright © 2017 Elsevier Inc. All rights reserved.
NASA Technical Reports Server (NTRS)
Smalley, L. L.
1975-01-01
The coordinate independence of gravitational radiation and the parameterized post-Newtonian approximation from which it is extended are described. The general consistency of the field equations with Bianchi identities, gauge conditions, and the Newtonian limit of the perfect fluid equations of hydrodynamics are studied. A technique of modification is indicated for application to vector-metric or double metric theories, as well as to scalar-tensor theories.
NASA Astrophysics Data System (ADS)
Leow, Alex D.; Zhu, Siwei
2008-03-01
Diffusion weighted MR imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitizing gradients along a minimum of 6 directions, second-order tensors (represetnted by 3-by-3 positive definiite matrices) can be computed to model dominant diffusion processes. However, it has been shown that conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g. crossing fiber tracts. More recently, High Angular Resolution Diffusion Imaging (HARDI) seeks to address this issue by employing more than 6 gradient directions. To account for fiber crossing when analyzing HARDI data, several methodologies have been introduced. For example, q-ball imaging was proposed to approximate Orientation Diffusion Function (ODF). Similarly, the PAS method seeks to reslove the angular structure of displacement probability functions using the maximum entropy principle. Alternatively, deconvolution methods extract multiple fiber tracts by computing fiber orientations using a pre-specified single fiber response function. In this study, we introduce Tensor Distribution Function (TDF), a probability function defined on the space of symmetric and positive definite matrices. Using calculus of variations, we solve for the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, ODF can easily be computed by analytical integration of the resulting displacement probability function. Moreover, principle fiber directions can also be directly derived from the TDF.
Hidden Symmetries of Euclideanised Kerr-NUT-(A)dS Metrics in Certain Scaling Limits
NASA Astrophysics Data System (ADS)
Visinescu, Mihai; Vîlcu, Eduard
2012-08-01
The hidden symmetries of higher dimensional Kerr-NUT-(A)dS metrics are investigated. In certain scaling limits these metrics are related to the Einstein-Sasaki ones. The complete set of Killing-Yano tensors of the Einstein-Sasaki spaces are presented. For this purpose the Killing forms of the Calabi-Yau cone over the Einstein-Sasaki manifold are constructed. Two new Killing forms on Einstein-Sasaki manifolds are identified associated with the complex volume form of the cone manifolds. Finally the Killing forms on mixed 3-Sasaki manifolds are briefly described.
White matter structural connectivity is associated with sensorimotor function in stroke survivors☆
Kalinosky, Benjamin T.; Schindler-Ivens, Sheila; Schmit, Brian D.
2013-01-01
Purpose Diffusion tensor imaging (DTI) provides functionally relevant information about white matter structure. Local anatomical connectivity information combined with fractional anisotropy (FA) and mean diffusivity (MD) may predict functional outcomes in stroke survivors. Imaging methods for predicting functional outcomes in stroke survivors are not well established. This work uses DTI to objectively assess the effects of a stroke lesion on white matter structure and sensorimotor function. Methods A voxel-based approach is introduced to assess a stroke lesion's global impact on motor function. Anatomical T1-weighted and diffusion tensor images of the brain were acquired for nineteen subjects (10 post-stroke and 9 age-matched controls). A manually selected volume of interest was used to alleviate the effects of stroke lesions on image registration. Images from all subjects were registered to the images of the control subject that was anatomically closest to Talairach space. Each subject's transformed image was uniformly seeded for DTI tractography. Each seed was inversely transformed into the individual subject space, where DTI tractography was conducted and then the results were transformed back to the reference space. A voxel-wise connectivity matrix was constructed from the fibers, which was then used to calculate the number of directly and indirectly connected neighbors of each voxel. A novel voxel-wise indirect structural connectivity (VISC) index was computed as the average number of direct connections to a voxel's indirect neighbors. Voxel-based analyses (VBA) were performed to compare VISC, FA, and MD for the detection of lesion-induced changes in sensorimotor function. For each voxel, a t-value was computed from the differences between each stroke brain and the 9 controls. A series of linear regressions was performed between Fugl-Meyer (FM) assessment scores of sensorimotor impairment and each DTI metric's log number of voxels that differed from the control group. Results Correlation between the logarithm of the number of significant voxels in the ipsilesional hemisphere and total Fugl-Meyer score was moderate for MD (R2 = 0.512), and greater for VISC (R2 = 0.796) and FA (R2 = 0.674). The slopes of FA (p = 0.0036), VISC (p = 0.0005), and MD (p = 0.0199) versus the total FM score were significant. However, these correlations were driven by the upper extremity motor component of the FM score (VISC: R2 = 0.879) with little influence of the lower extremity motor component (FA: R2 = 0.177). Conclusion The results suggest that a voxel-wise metric based on DTI tractography can predict upper extremity sensorimotor function of stroke survivors, and that supraspinal intraconnectivity may have a less dominant role in lower extremity function. PMID:24179827
Scherfler, Christoph; Esterhammer, Regina; Nocker, Michael; Mahlknecht, Philipp; Stockner, Heike; Warwitz, Boris; Spielberger, Sabine; Pinter, Bernadette; Donnemiller, Eveline; Decristoforo, Clemens; Virgolini, Irene; Schocke, Michael; Poewe, Werner; Seppi, Klaus
2013-10-01
Signal abnormalities of the substantia nigra and the olfactory tract detected either by diffusion tensor imaging, including measurements of mean diffusivity, a parameter of brain tissue integrity, and fractional anisotropy, a parameter of neuronal fibre integrity, or transcranial sonography, were recently reported in the early stages of Parkinson's disease. In this study, changes in the nigral and olfactory diffusion tensor signal, as well as nigral echogenicity, were correlated with clinical scales of motor disability, odour function and putaminal dopamine storage capacity measured with 6-[(18)F] fluorolevodopa positron emission tomography in early and advanced stages of Parkinson's disease. Diffusion tensor imaging, transcranial sonography and positron emission tomography were performed on 16 patients with Parkinson's disease (mean disease duration 3.7 ± 3.7 years, Hoehn and Yahr stage 1 to 4) and 14 age-matched healthy control subjects. Odour function was measured by the standardized Sniffin' Sticks Test. Mean putaminal 6-[(18)F] fluorolevodopa influx constant, mean nigral echogenicity, mean diffusivity and fractional anisotropy values of the substantia nigra and the olfactory tract were identified by region of interest analysis. When compared with the healthy control group, the Parkinson's disease group showed significant signal changes in the caudate and putamen by 6-[(18)F] fluorolevodopa positron emission tomography, in the substantia nigra by transcranial sonography, mean diffusivity and fractional anisotropy (P < 0.001, P < 0.01, P < 0.05, respectively) and in the olfactory tract by mean diffusivity (P < 0.05). Regional mean diffusivity values of the substantia nigra and the olfactory tract correlated significantly with putaminal 6-[(18)F] fluorolevodopa uptake (r = -0.52, P < 0.05 and r = -0.71, P < 0.01). Significant correlations were also found between nigral mean diffusivity values and the Unified Parkinson's Disease Rating Scale motor score (r = -0.48, P < 0.01) and between mean putaminal 6-[(18)F] fluorolevodopa uptake and the total odour score (r = 0.58; P < 0.05) as well as the Unified Parkinson's Disease Rating Scale motor score (r = -0.53, P < 0.05). This study reports a significant association between increased mean diffusivity signal and decreased 6-[(18)F] fluorolevodopa uptake, indicating that microstructural degradation of the substantia nigra and the olfactory tract parallels progression of putaminal dopaminergic dysfunction in Parkinson's disease. Since increases in nigral mean diffusivity signal also correlated with motor dysfunction, diffusion tensor imaging may serve as a surrogate marker for disease progression in future studies of putative disease modifying therapies.
NASA Astrophysics Data System (ADS)
Anderson, David; Yunes, Nicolás
2017-09-01
Scalar-tensor theories of gravity modify general relativity by introducing a scalar field that couples nonminimally to the metric tensor, while satisfying the weak-equivalence principle. These theories are interesting because they have the potential to simultaneously suppress modifications to Einstein's theory on Solar System scales, while introducing large deviations in the strong field of neutron stars. Scalar-tensor theories can be classified through the choice of conformal factor, a scalar that regulates the coupling between matter and the metric in the Einstein frame. The class defined by a Gaussian conformal factor with a negative exponent has been studied the most because it leads to spontaneous scalarization (i.e. the sudden activation of the scalar field in neutron stars), which consequently leads to large deviations from general relativity in the strong field. This class, however, has recently been shown to be in conflict with Solar System observations when accounting for the cosmological evolution of the scalar field. We here study whether this remains the case when the exponent of the conformal factor is positive, as well as in another class of theories defined by a hyperbolic conformal factor. We find that in both of these scalar-tensor theories, Solar System tests are passed only in a very small subset of coupling parameter space, for a large set of initial conditions compatible with big bang nucleosynthesis. However, while we find that it is possible for neutron stars to scalarize, one must carefully select the coupling parameter to do so, and even then, the scalar charge is typically 2 orders of magnitude smaller than in the negative-exponent case. Our study suggests that future work on scalar-tensor gravity, for example in the context of tests of general relativity with gravitational waves from neutron star binaries, should be carried out within the positive coupling parameter class.
Spherical shock waves in general relativity
NASA Astrophysics Data System (ADS)
Nutku, Y.
1991-11-01
We present the metric appropriate to a spherical shock wave in the framework of general relativity. This is a Petrov type-N vacuum solution of the Einstein field equations where the metric is continuous across the shock and the Riemann tensor suffers a step-function discontinuity. Spherical gravitational waves are described by type-N Robinson-Trautman metrics. However, for shock waves the Robinson-Trautman solutions are unacceptable because the metric becomes discontinuous in the Robinson-Trautman coordinate system. Other coordinate systems that have so far been introduced for describing Robinson-Trautman solutions also suffer from the same defect. We shall present the C0-form of the metric appropriate to spherical shock waves using Penrose's approach of identification with warp. Further extensions of Penrose's method yield accelerating, as well as coupled electromagnetic-gravitational shock-wave solutions.
Static models with conformal symmetry
NASA Astrophysics Data System (ADS)
Manjonjo, A. M.; Maharaj, S. D.; Moopanar, S.
2018-02-01
We study static spherically symmetric spacetimes with a spherical conformal symmetry and a nonstatic conformal factor associated with the conformal Killing field. With these assumptions we find an explicit relationship relating two metric components of the metric tensor field. This leads to the general solution of the Einstein field equations with a conformal symmetry in a static spherically symmetric spacetime. For perfect fluids we can find all metrics explicitly and show that the models always admit a barotropic equation of state. Contained within this class of spacetimes are the well known metrics of (interior) Schwarzschild, Tolman, Kuchowicz, Korkina and Orlyanskii, Patwardhan and Vaidya, and Buchdahl and Land. The isothermal metric of Saslaw et al also admits a conformal symmetry. For imperfect fluids an infinite family of exact solutions to the field equations can be generated.
Boundary term in metric f ( R) gravity: field equations in the metric formalism
NASA Astrophysics Data System (ADS)
Guarnizo, Alejandro; Castañeda, Leonardo; Tejeiro, Juan M.
2010-11-01
The main goal of this paper is to get in a straightforward form the field equations in metric f ( R) gravity, using elementary variational principles and adding a boundary term in the action, instead of the usual treatment in an equivalent scalar-tensor approach. We start with a brief review of the Einstein-Hilbert action, together with the Gibbons-York-Hawking boundary term, which is mentioned in some literature, but is generally missing. Next we present in detail the field equations in metric f ( R) gravity, including the discussion about boundaries, and we compare with the Gibbons-York-Hawking term in General Relativity. We notice that this boundary term is necessary in order to have a well defined extremal action principle under metric variation.
Using Perturbation Theory to Compute the Morphological Similarity of Diffusion Tensors
Bansal, Ravi; Staib, Lawrence H.; Xu, Dongrong; Laine, Andrew F.; Royal, Jason; Peterson, Bradley S.
2008-01-01
Computing the morphological similarity of Diffusion Tensors (DTs) at neighboring voxels within a DT image, or at corresponding locations across different DT images, is a fundamental and ubiquitous operation in the post-processing of DT images. The morphological similarity of DTs typically has been computed using either the Principal Directions (PDs) of DTs (i.e., the direction along which water molecules diffuse preferentially) or their tensor elements. Although comparing PDs allows the similarity of one morphological feature of DTs to be visualized directly in eigenspace, this method takes into account only a single eigenvector, and it is therefore sensitive to the presence of noise in the images that can introduce error into the estimation of that vector. Although comparing tensor elements, rather than PDs, is comparatively more robust to the effects of noise, the individual elements of a given tensor do not directly reflect the diffusion properties of water molecules. We propose a measure for computing the morphological similarity of DTs that uses both their eigenvalues and eigenvectors, and that also accounts for the noise levels present in DT images. Our measure presupposes that DTs in a homogeneous region within or across DT images are random perturbations of one another in the presence of noise. The similarity values that are computed using our method are smooth (in the sense that small changes in eigenvalues and eigenvectors cause only small changes in similarity), and they are symmetric when differences in eigenvalues and eigenvectors are also symmetric. In addition, our method does not presuppose that the corresponding eigenvectors across two DTs have been identified accurately, an assumption that is problematic in the presence of noise. Because we compute the similarity between DTs using their eigenspace components, our similarity measure relates directly to both the magnitude and the direction of the diffusion of water molecules. The favorable performance characteristics of our measure offer the prospect of substantially improving additional post-processing operations that are commonly performed on DTI datasets, such as image segmentation, fiber tracking, noise filtering, and spatial normalization. PMID:18450533
Kassubek, Jan; Müller, Hans-Peter; Del Tredici, Kelly; Brettschneider, Johannes; Pinkhardt, Elmar H; Lulé, Dorothée; Böhm, Sarah; Braak, Heiko; Ludolph, Albert C
2014-06-01
Diffusion tensor imaging can identify amyotrophic lateral sclerosis-associated patterns of brain alterations at the group level. Recently, a neuropathological staging system for amyotrophic lateral sclerosis has shown that amyotrophic lateral sclerosis may disseminate in a sequential regional pattern during four disease stages. The objective of the present study was to apply a new methodological diffusion tensor imaging-based approach to automatically analyse in vivo the fibre tracts that are prone to be involved at each neuropathological stage of amyotrophic lateral sclerosis. Two data samples, consisting of 130 diffusion tensor imaging data sets acquired at 1.5 T from 78 patients with amyotrophic lateral sclerosis and 52 control subjects; and 55 diffusion-tensor imaging data sets at 3.0 T from 33 patients with amyotrophic lateral sclerosis and 22 control subjects, were analysed by a tract of interest-based fibre tracking approach to analyse five tracts that become involved during the course of amyotrophic lateral sclerosis: the corticospinal tract (stage 1); the corticorubral and the corticopontine tracts (stage 2); the corticostriatal pathway (stage 3); the proximal portion of the perforant path (stage 4); and two reference pathways. The statistical analyses of tracts of interest showed differences between patients with amyotrophic lateral sclerosis and control subjects for all tracts. The significance level of the comparisons at the group level was lower, the higher the disease stage with corresponding involved fibre tracts. Both the clinical phenotype as assessed by the amyotrophic lateral sclerosis functional rating scale-revised and disease duration correlated significantly with the resulting staging scheme. In summary, the tract of interest-based technique allowed for individual analysis of predefined tract structures, thus making it possible to image in vivo the disease stages in amyotrophic lateral sclerosis. This approach can be used not only for individual clinical work-up purposes, but enlarges the spectrum of potential non-invasive surrogate markers as a neuroimaging-based read-out for amyotrophic lateral sclerosis studies within a clinical context. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Metamaterial devices for molding the flow of diffuse light (Conference Presentation)
NASA Astrophysics Data System (ADS)
Wegener, Martin
2016-09-01
Much of optics in the ballistic regime is about designing devices to mold the flow of light. This task is accomplished via specific spatial distributions of the refractive index or the refractive-index tensor. For light propagating in turbid media, a corresponding design approach has not been applied previously. Here, we review our corresponding recent work in which we design spatial distributions of the light diffusivity or the light-diffusivity tensor to accomplish specific tasks. As an application, we realize cloaking of metal contacts on large-area OLEDs, eliminating the contacts' shadows, thereby homogenizing the diffuse light emission. In more detail, metal contacts on large-area organic light-emitting diodes (OLEDs) are mandatory electrically, but they cast optical shadows, leading to unwanted spatially inhomogeneous diffuse light emission. We show that the contacts can be made invisible either by (i) laminate metamaterials designed by coordinate transformations of the diffusion equation or by (ii) triangular-shaped regions with piecewise constant diffusivity, hence constant concentration of scattering centers. These structures are post-optimized in regard to light throughput by Monte-Carlo ray-tracing simulations and successfully validated by model experiments.
Susceptibility Tensor Imaging (STI) of the Brain
Li, Wei; Liu, Chunlei; Duong, Timothy Q.; van Zijl, Peter C.M.; Li, Xu
2016-01-01
Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility (MMS) and magnetic susceptibility anisotropy (MSA) can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping (QSM) to remove such dependence. Similar to diffusion tensor imaging (DTI), STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of susceptibility anisotropy in brain white matter is myelin. Another unique feature of susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. PMID:27120169
Poveda, Ferran; Gil, Debora; Martí, Enric; Andaluz, Albert; Ballester, Manel; Carreras, Francesc
2013-10-01
Deeper understanding of the myocardial structure linking the morphology and function of the heart would unravel crucial knowledge for medical and surgical clinical procedures and studies. Several conceptual models of myocardial fiber organization have been proposed but the lack of an automatic and objective methodology prevented an agreement. We sought to deepen this knowledge through advanced computer graphical representations of the myocardial fiber architecture by diffusion tensor magnetic resonance imaging. We performed automatic tractography reconstruction of unsegmented diffusion tensor magnetic resonance imaging datasets of canine heart from the public database of the Johns Hopkins University. Full-scale tractographies have been built with 200 seeds and are composed by streamlines computed on the vector field of primary eigenvectors at the diffusion tensor volumes. We also introduced a novel multiscale visualization technique in order to obtain a simplified tractography. This methodology retains the main geometric features of the fiber tracts, making it easier to decipher the main properties of the architectural organization of the heart. Output analysis of our tractographic representations showed exact correlation with low-level details of myocardial architecture, but also with the more abstract conceptualization of a continuous helical ventricular myocardial fiber array. Objective analysis of myocardial architecture by an automated method, including the entire myocardium and using several 3-dimensional levels of complexity, reveals a continuous helical myocardial fiber arrangement of both right and left ventricles, supporting the anatomical model of the helical ventricular myocardial band described by F. Torrent-Guasp. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.
Kawadler, Jamie M; Kirkham, Fenella J; Clayden, Jonathan D; Hollocks, Matthew J; Seymour, Emma L; Edey, Rosanna; Telfer, Paul; Robins, Andrew; Wilkey, Olu; Barker, Simon; Cox, Tim C S; Clark, Chris A
2015-07-01
Sickle cell anemia is associated with compromised oxygen-carrying capability of hemoglobin and a high incidence of overt and silent stroke. However, in children with no evidence of cerebral infarction, there are changes in brain morphometry relative to healthy controls, which may be related to chronic anemia and oxygen desaturation. A whole-brain tract-based spatial statistics analysis was carried out in 25 children with sickle cell anemia with no evidence of abnormality on T2-weighted magnetic resonance imaging (13 male, age range: 8-18 years) and 14 age- and race-matched controls (7 male, age range: 10-19 years) to determine the extent of white matter injury. The hypotheses that white matter damage is related to daytime peripheral oxygen saturation and steady-state hemoglobin were tested. Fractional anisotropy was found to be significantly lower in patients in the subcortical white matter (corticospinal tract and cerebellum), whereas mean diffusivity and radial diffusivity were higher in patients in widespread areas. There was a significant negative relationship between radial diffusivity and oxygen saturation (P<0.05) in the anterior corpus callosum and a trend-level negative relationship between radial diffusivity and hemoglobin (P<0.1) in the midbody of the corpus callosum. These data show widespread white matter abnormalities in a sample of asymptomatic children with sickle cell anemia, and provides for the first time direct evidence of a relationship between brain microstructure and markers of disease severity (eg, peripheral oxygen saturation and steady-state hemoglobin). This study suggests that diffusion tensor imaging metrics may serve as a biomarker for future trials of reducing hypoxic exposure. © 2015 American Heart Association, Inc.
Marcuzzo, Stefania; Bonanno, Silvia; Padelli, Francesco; Moreno-Manzano, Victoria; García-Verdugo, José Manuel; Bernasconi, Pia; Mantegazza, Renato; Bruzzone, Maria Grazia; Zucca, Ileana
2016-01-01
Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios and the mean value and variability of Diffusion Tensor metrics were evaluated in healthy controls. For the estimation of fractional anisotropy less variability was provided by protocols with more diffusion directions, for the estimation of mean, axial and radial diffusivity by protocols with fewer diffusion directions and higher diffusion weighting. Intermediate features (12 directions, b = 1200 s/mm2) provided the overall minimum inter- and intra-subject variability in most cases. In order to test the diagnostic sensitivity of the protocols, 7 G93A-SOD1 mice (model of amyotrophic lateral sclerosis) at 10 and 17 weeks of age were scanned and the derived diffusion parameters compared with those estimated in age-matched healthy animals. The protocols with an intermediate or high number of diffusion directions provided the best differentiation between the two groups at week 17, whereas only few local significant differences were highlighted at week 10. According to our results, a dMRI protocol with an intermediate number of diffusion gradient directions and a relatively high diffusion weighting is optimal for spinal cord imaging. Further work is needed to confirm these results and for a finer tuning of acquisition parameters. Nevertheless, our findings could be important for the optimization of acquisition protocols for preclinical and clinical dMRI studies on the spinal cord. PMID:27560686
Vessel Enhancement and Segmentation of 4D CT Lung Image Using Stick Tensor Voting
NASA Astrophysics Data System (ADS)
Cong, Tan; Hao, Yang; Jingli, Shi; Xuan, Yang
2016-12-01
Vessel enhancement and segmentation plays a significant role in medical image analysis. This paper proposes a novel vessel enhancement and segmentation method for 4D CT lung image using stick tensor voting algorithm, which focuses on addressing the vessel distortion issue of vessel enhancement diffusion (VED) method. Furthermore, the enhanced results are easily segmented using level-set segmentation. In our method, firstly, vessels are filtered using Frangi's filter to reduce intrapulmonary noises and extract rough blood vessels. Secondly, stick tensor voting algorithm is employed to estimate the correct direction along the vessel. Then the estimated direction along the vessel is used as the anisotropic diffusion direction of vessel in VED algorithm, which makes the intensity diffusion of points locating at the vessel wall be consistent with the directions of vessels and enhance the tubular features of vessels. Finally, vessels can be extracted from the enhanced image by applying level-set segmentation method. A number of experiments results show that our method outperforms traditional VED method in vessel enhancement and results in satisfied segmented vessels.
Dynamic coupling between coordinates in a model for biomolecular isomerization
NASA Astrophysics Data System (ADS)
Ma, Ao; Nag, Ambarish; Dinner, Aaron R.
2006-04-01
To understand a complex reaction, it is necessary to project the dynamics of the system onto a low-dimensional subspace of physically meaningful coordinates. We recently introduced an automatic method for identifying coordinates that relate closely to stable-state commitment probabilities and successfully applied it to a model for biomolecular isomerization, the C7eq→αR transition of the alanine dipeptide [A. Ma and A. R. Dinner, J. Phys. Chem. B 109, 6769 (2005)]. Here, we explore approximate means for estimating diffusion tensors for systems subject to restraints in one and two dimensions and then use the results together with an extension of Kramers theory for unimolecular reaction rates [A. Berezhkovskii and A. Szabo, J. Chem. Phys. 122, 014503 (2005)] to show explicitly that both the potential of mean force and the diffusion tensor are essential for describing the dynamics of the alanine dipeptide quantitatively. In particular, the signficance of off-diagonal elements of the diffusion tensor suggests that the coordinates of interest are coupled by the hydrodynamic-like response of the bath of remaining degrees of freedom.
Parcellating the neuroanatomical basis of impaired decision-making in traumatic brain injury.
Newcombe, Virginia F J; Outtrim, Joanne G; Chatfield, Doris A; Manktelow, Anne; Hutchinson, Peter J; Coles, Jonathan P; Williams, Guy B; Sahakian, Barbara J; Menon, David K
2011-03-01
Cognitive dysfunction is a devastating consequence of traumatic brain injury that affects the majority of those who survive with moderate-to-severe injury, and many patients with mild head injury. Disruption of key monoaminergic neurotransmitter systems, such as the dopaminergic system, may play a key role in the widespread cognitive dysfunction seen after traumatic axonal injury. Manifestations of injury to this system may include impaired decision-making and impulsivity. We used the Cambridge Gambling Task to characterize decision-making and risk-taking behaviour, outside of a learning context, in a cohort of 44 patients at least six months post-traumatic brain injury. These patients were found to have broadly intact processing of risk adjustment and probability judgement, and to bet similar amounts to controls. However, a patient preference for consistently early bets indicated a higher level of impulsiveness. These behavioural measures were compared with imaging findings on diffusion tensor magnetic resonance imaging. Performance in specific domains of the Cambridge Gambling Task correlated inversely and specifically with the severity of diffusion tensor imaging abnormalities in regions that have been implicated in these cognitive processes. Thus, impulsivity was associated with increased apparent diffusion coefficient bilaterally in the orbitofrontal gyrus, insula and caudate; abnormal risk adjustment with increased apparent diffusion coefficient in the right thalamus and dorsal striatum and left caudate; and impaired performance on rational choice with increased apparent diffusion coefficient in the bilateral dorsolateral prefrontal cortices, and the superior frontal gyri, right ventrolateral prefrontal cortex, the dorsal and ventral striatum, and left hippocampus. Importantly, performance in specific cognitive domains of the task did not correlate with diffusion tensor imaging abnormalities in areas not implicated in their performance. The ability to dissociate the location and extent of damage with performance on the various task components using diffusion tensor imaging allows important insights into the neuroanatomical basis of impulsivity following traumatic brain injury. The ability to detect such damage in vivo may have important implications for patient management, patient selection for trials, and to help understand complex neurocognitive pathways.
Parcellating the neuroanatomical basis of impaired decision-making in traumatic brain injury
Outtrim, Joanne G.; Chatfield, Doris A.; Manktelow, Anne; Hutchinson, Peter J.; Coles, Jonathan P.; Williams, Guy B.; Sahakian, Barbara J.; Menon, David K.
2011-01-01
Cognitive dysfunction is a devastating consequence of traumatic brain injury that affects the majority of those who survive with moderate-to-severe injury, and many patients with mild head injury. Disruption of key monoaminergic neurotransmitter systems, such as the dopaminergic system, may play a key role in the widespread cognitive dysfunction seen after traumatic axonal injury. Manifestations of injury to this system may include impaired decision-making and impulsivity. We used the Cambridge Gambling Task to characterize decision-making and risk-taking behaviour, outside of a learning context, in a cohort of 44 patients at least six months post-traumatic brain injury. These patients were found to have broadly intact processing of risk adjustment and probability judgement, and to bet similar amounts to controls. However, a patient preference for consistently early bets indicated a higher level of impulsiveness. These behavioural measures were compared with imaging findings on diffusion tensor magnetic resonance imaging. Performance in specific domains of the Cambridge Gambling Task correlated inversely and specifically with the severity of diffusion tensor imaging abnormalities in regions that have been implicated in these cognitive processes. Thus, impulsivity was associated with increased apparent diffusion coefficient bilaterally in the orbitofrontal gyrus, insula and caudate; abnormal risk adjustment with increased apparent diffusion coefficient in the right thalamus and dorsal striatum and left caudate; and impaired performance on rational choice with increased apparent diffusion coefficient in the bilateral dorsolateral prefrontal cortices, and the superior frontal gyri, right ventrolateral prefrontal cortex, the dorsal and ventral striatum, and left hippocampus. Importantly, performance in specific cognitive domains of the task did not correlate with diffusion tensor imaging abnormalities in areas not implicated in their performance. The ability to dissociate the location and extent of damage with performance on the various task components using diffusion tensor imaging allows important insights into the neuroanatomical basis of impulsivity following traumatic brain injury. The ability to detect such damage in vivo may have important implications for patient management, patient selection for trials, and to help understand complex neurocognitive pathways. PMID:21310727
Wolf, Dominik; Fischer, Florian U; Scheurich, Armin; Fellgiebel, Andreas
2015-01-01
Cerebral amyloid-β accumulation and changes in white matter (WM) microstructure are imaging characteristics in clinical Alzheimer's disease and have also been reported in cognitively healthy older adults. However, the relationship between amyloid deposition and WM microstructure is not well understood. Here, we investigated the impact of quantitative cerebral amyloid load on WM microstructure in a group of cognitively healthy older adults. AV45-positron emission tomography and diffusion tensor imaging (DTI) scans of forty-four participants (age-range: 60 to 89 years) from the Alzheimer's Disease Neuroimaging Initiative were analyzed. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (DR), and axial diffusivity (DA) were calculated to characterize WM microstructure. Regression analyses demonstrated non-linear (quadratic) relationships between amyloid deposition and FA, MD, as well as RD in widespread WM regions. At low amyloid burden, higher deposition was associated with increased FA as well as decreased MD and DR. At higher amyloid burden, higher deposition was associated with decreased FA as well as increased MD and DR. Additional regression analyses demonstrated an interaction effect between amyloid load and global WM FA, MD, DR, and DA on cognition, suggesting that cognition is only affected when amyloid is increasing and WM integrity is decreasing. Thus, increases in FA and decreases in MD and RD with increasing amyloid load at low levels of amyloid burden may indicate compensatory processes that preserve cognitive functioning. Potential mechanisms underlying the observed non-linear association between amyloid deposition and DTI metrics of WM microstructure are discussed.
Spaceflight Effect on White Matter Structural Integrity
NASA Technical Reports Server (NTRS)
Lee, Jessica K.; Kopplemans, Vincent; Paternack, Ofer; Bloomberg, Jacob J.; Mulavara, Ajitkumar P.; Seidler, Rachael D.
2017-01-01
Recent reports of elevated brain white matter hyperintensity (WMH) counts and volume in postflight astronaut MRIs suggest that further examination of spaceflight's impact on the microstructure of brain white matter is warranted. To this end, retrospective longitudinal diffusion-weighted MRI scans obtained from 15 astronauts were evaluated. In light of the recent reports of microgravity-induced cephalad fluid shift and gray matter atrophy seen in astronauts, we applied a technique to estimate diffusion tensor imaging (DTI) metrics corrected for free water contamination. This approach enabled the analysis of white matter tissue-specific alterations that are unrelated to fluid shifts, occurring from before spaceflight to after landing. After spaceflight, decreased fractional anisotropy (FA) values were detected in an area encompassing the superior and inferior longitudinal fasciculi and the inferior fronto-occipital fasciculus. Increased radial diffusivity (RD) and decreased axial diffusivity (AD) were also detected within overlapping regions. In addition, FA values in the corticospinal tract decreased and RD measures in the precentral gyrus white matter increased from before to after flight. The results show disrupted structural connectivity of white matter in tracts involved in visuospatial processing, vestibular function, and movement control as a result of spaceflight. The findings may help us understand the structural underpinnings of the extensive spaceflight-induced sensorimotor remodeling. Prospective longitudinal assessment of the white matter integrity in astronauts is needed to characterize the evolution of white matter microstructural changes associated with spaceflight, their behavioral consequences, and the time course of recovery. Supported by a grant from the National Space Biomedical Research Institute, NASA NCC 9-58.
Liu, Xiaozheng; Yuan, Zhenming; Guo, Zhongwei; Xu, Dongrong
2015-05-01
Diffusion tensor imaging is widely used for studying neural fiber trajectories in white matter and for quantifying changes in tissue using diffusion properties at each voxel in the brain. To better model the nature of crossing fibers within complex architectures, rather than using a simplified tensor model that assumes only a single fiber direction at each image voxel, a model mixing multiple diffusion tensors is used to profile diffusion signals from high angular resolution diffusion imaging (HARDI) data. Based on the HARDI signal and a multiple tensors model, spherical deconvolution methods have been developed to overcome the limitations of the diffusion tensor model when resolving crossing fibers. The Richardson-Lucy algorithm is a popular spherical deconvolution method used in previous work. However, it is based on a Gaussian distribution, while HARDI data are always very noisy, and the distribution of HARDI data follows a Rician distribution. This current work aims to present a novel solution to address these issues. By simultaneously considering both the Rician bias and neighbor correlation in HARDI data, the authors propose a localized Richardson-Lucy (LRL) algorithm to estimate fiber orientations for HARDI data. The proposed method can simultaneously reduce noise and correct the Rician bias. Mean angular error (MAE) between the estimated Fiber orientation distribution (FOD) field and the reference FOD field was computed to examine whether the proposed LRL algorithm offered any advantage over the conventional RL algorithm at various levels of noise. Normalized mean squared error (NMSE) was also computed to measure the similarity between the true FOD field and the estimated FOD filed. For MAE comparisons, the proposed LRL approach obtained the best results in most of the cases at different levels of SNR and b-values. For NMSE comparisons, the proposed LRL approach obtained the best results in most of the cases at b-value = 3000 s/mm(2), which is the recommended schema for HARDI data acquisition. In addition, the FOD fields estimated by the proposed LRL approach in regions of fiber crossing regions using real data sets also showed similar fiber structures which agreed with common acknowledge in these regions. The novel spherical deconvolution method for improved accuracy in investigating crossing fibers can simultaneously reduce noise and correct Rician bias. With the noise smoothed and bias corrected, this algorithm is especially suitable for estimation of fiber orientations in HARDI data. Experimental results using both synthetic and real imaging data demonstrated the success and effectiveness of the proposed LRL algorithm.
Modified gravity (MOG), the speed of gravitational radiation and the event GW170817/GRB170817A
NASA Astrophysics Data System (ADS)
Green, M. A.; Moffat, J. W.; Toth, V. T.
2018-05-01
Modified gravity (MOG) is a covariant, relativistic, alternative gravitational theory whose field equations are derived from an action that supplements the spacetime metric tensor with vector and scalar fields. Both gravitational (spin 2) and electromagnetic waves travel on null geodesics of the theory's one metric. MOG satisfies the weak equivalence principle and is consistent with observations of the neutron star merger and gamma ray burster event GW170817/GRB170817A.
A deformation of Sasakian structure in the presence of torsion and supergravity solutions
NASA Astrophysics Data System (ADS)
Houri, Tsuyoshi; Takeuchi, Hiroshi; Yasui, Yukinori
2013-07-01
A deformation of Sasakian structure in the presence of totally skew-symmetric torsion is discussed on odd-dimensional manifolds whose metric cones are Kähler with torsion. It is shown that such a geometry inherits similar properties to those of Sasakian geometry. As their example, we present an explicit expression of local metrics. It is also demonstrated that our example of the metrics admits the existence of hidden symmetry described by non-trivial odd-rank generalized closed conformal Killing-Yano tensors. Furthermore, using these metrics as an ansatz, we construct exact solutions in five-dimensional minimal gauged/ungauged supergravity and 11-dimensional supergravity. Finally, the global structures of the solutions are discussed. We obtain regular metrics on compact manifolds in five dimensions, which give natural generalizations of Sasaki-Einstein manifolds Yp, q and La, b, c. We also briefly discuss regular metrics on non-compact manifolds in 11 dimensions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Esteban, E.P.
In this thesis some properties of the Ernst metric are studied. This metric could provide a model for a Schwarzschild black hole immersed in a magnetic field. In chapter I, some standard propertiess of the Ernst's metric such as the affine connections, the Riemann, the Ricci, and the Weyl conformal tensor are calculated. In chapter II, the geodesics described by test particles in the Ernst space-time are studied. As an application a formula for the perihelion shift is derived. In the last chapter a null tetrad analysis of the Ernst metric is carried out and the resulting formalism applied tomore » the study of three problems. First, the algebraic classification of the Ernst metric is determined to be of type I in the Petrov scheme. Secondly, an explicit formula for the Gaussian curvature for the event horizon is derived. Finally, the form of the electromagnetic field is evaluated.« less
Self-gravity, Resonances, and Orbital Diffusion in Stellar Disks
NASA Astrophysics Data System (ADS)
Fouvry, Jean-Baptiste; Binney, James; Pichon, Christophe
2015-06-01
Fluctuations in a stellar system's gravitational field cause the orbits of stars to evolve. The resulting evolution of the system can be computed with the orbit-averaged Fokker-Planck equation once the diffusion tensor is known. We present the formalism that enables one to compute the diffusion tensor from a given source of noise in the gravitational field when the system's dynamical response to that noise is included. In the case of a cool stellar disk we are able to reduce the computation of the diffusion tensor to a one-dimensional integral. We implement this formula for a tapered Mestel disk that is exposed to shot noise and find that we are able to explain analytically the principal features of a numerical simulation of such a disk. In particular the formation of narrow ridges of enhanced density in action space is recovered. As the disk's value of Toomre's Q is reduced and the disk becomes more responsive, there is a transition from a regime of heating in the inner regions of the disk through the inner Lindblad resonance to one of radial migration of near-circular orbits via the corotation resonance in the intermediate regions of the disk. The formalism developed here provides the ideal framework in which to study the long-term evolution of all kinds of stellar disks.
Seizeur, Romuald; Magro, Elsa; Prima, Sylvain; Wiest-Daesslé, Nicolas; Maumet, Camille; Morandi, Xavier
2014-03-01
Cerebral hemispheres represent both structural and functional asymmetry, which differs among right- and left-handers. The left hemisphere is specialised for language and task execution of the right hand in right-handers. We studied the corticospinal tract in right- and left-handers by diffusion tensor imaging and tractography. The present study aimed at revealing a morphological difference resulting from a region of interest (ROI) obtained by functional MRI (fMRI). Twenty-five healthy participants (right-handed: 15, left-handed: 10) were enrolled in our assessment of morphological, functional and diffusion tensor MRI. Assessment of brain fibre reconstruction (tractography) was done using a deterministic algorithm. Fractional anisotropy (FA) and mean diffusivity (MD) were studied on the tractography traces of the reference slices. We observed a significant difference in number of leftward fibres based on laterality. The significant difference in regard to FA and MD was based on the slices obtained at different levels and the laterality index. We found left-hand asymmetry and right-hand asymmetry, respectively, for the MD and FA. Our study showed the presence of hemispheric asymmetry based on laterality index in right- and left-handers. These results are inconsistent with some studies and consistent with others. The reported difference in hemispheric asymmetry could be related to dexterity (manual skill).
Nissan, Noam; Furman-Haran, Edna; Shapiro-Feinberg, Myra; Grobgeld, Dov; Degani, Hadassa
2017-09-01
Lactation and the return to the pre-conception state during post-weaning are regulated by hormonal induced processes that modify the microstructure of the mammary gland, leading to changes in the features of the ductal / glandular tissue, the stroma and the fat tissue. These changes create a challenge in the radiological workup of breast disorder during lactation and early post-weaning. Here we present non-invasive MRI protocols designed to record in vivo high spatial resolution, T 2 -weighted images and diffusion tensor images of the entire mammary gland. Advanced imaging processing tools enabled tracking the changes in the anatomical and microstructural features of the mammary gland from the time of lactation to post-weaning. Specifically, by using diffusion tensor imaging (DTI) it was possible to quantitatively distinguish between the ductal / glandular tissue distention during lactation and the post-weaning involution. The application of the T 2 -weighted imaging and DTI is completely safe, non-invasive and uses intrinsic contrast based on differences in transverse relaxation rates and water diffusion rates in various directions, respectively. This study provides a basis for further in-vivo monitoring of changes during the mammary developmental stages, as well as identifying changes due to malignant transformation in patients with pregnancy associated breast cancer (PABC).
NASA Astrophysics Data System (ADS)
Noel, Jean; Prieto, Juan C.; Styner, Martin
2017-03-01
Functional Analysis of Diffusion Tensor Tract Statistics (FADTTS) is a toolbox for analysis of white matter (WM) fiber tracts. It allows associating diffusion properties along major WM bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these WM tract properties. However, to use this toolbox, a user must have an intermediate knowledge in scripting languages (MATLAB). FADTTSter was created to overcome this issue and make the statistical analysis accessible to any non-technical researcher. FADTTSter is actively being used by researchers at the University of North Carolina. FADTTSter guides non-technical users through a series of steps including quality control of subjects and fibers in order to setup the necessary parameters to run FADTTS. Additionally, FADTTSter implements interactive charts for FADTTS' outputs. This interactive chart enhances the researcher experience and facilitates the analysis of the results. FADTTSter's motivation is to improve usability and provide a new analysis tool to the community that complements FADTTS. Ultimately, by enabling FADTTS to a broader audience, FADTTSter seeks to accelerate hypothesis testing in neuroimaging studies involving heterogeneous clinical data and diffusion tensor imaging. This work is submitted to the Biomedical Applications in Molecular, Structural, and Functional Imaging conference. The source code of this application is available in NITRC.
Rasova, Kamila; Prochazkova, Marie; Tintera, Jaroslav; Ibrahim, Ibrahim; Zimova, Denisa; Stetkarova, Ivana
2015-03-01
There is still little scientific evidence for the efficacy of neurofacilitation approaches and their possible influence on brain plasticity and adaptability. In this study, the outcome of a new kind of neurofacilitation approach, motor programme activating therapy (MPAT), was evaluated on the basis of a set of clinical functions and with MRI. Eighteen patients were examined four times with standardized clinical tests and diffusion tensor imaging to monitor changes without therapy, immediately after therapy and 1 month after therapy. Moreover, the strength of effective connectivity was analysed before and after therapy. Patients underwent a 1-h session of MPAT twice a week for 2 months. The data were analysed by nonparametric tests of association and were subsequently statistically evaluated. The therapy led to significant improvement in clinical functions, significant increment of fractional anisotropy and significant decrement of mean diffusivity, and decrement of effective connectivity at supplementary motor areas was observed immediately after the therapy. Changes in clinical functions and diffusion tensor images persisted 1 month after completing the programme. No statistically significant changes in clinical functions and no differences in MRI-diffusion tensor images were observed without physiotherapy. Positive immediate and long-term effects of MPAT on clinical and brain functions, as well as brain microstructure, were confirmed.
Clinical application of diffusion tensor magnetic resonance imaging in skeletal muscle
Longwei, Xu
2012-01-01
Summary Diffusion tensor magnetic resonance imaging (DTI) is increasingly applied in the detection and characterization of skeletal muscle. This promising technique has aroused much enthusiasm and generated high expectations, because it is able to provide some specific information of skeletal muscle that is not available from other imaging modalities. Compared with conventional MRI, DTI could reconstruct the trajectories of skeletal muscle fibers. It makes it possible to non-invasively detect several physiological values (diffusion values), like fractional anisotropy (FA) and apparent diffusion coefficient (ADC), which have a great association with the muscle physiology and pathology. Furthermore, other advantages of DTI are the capability of investigating the muscle biomechanics and also investigate the pathological condition of skeletal muscle. Finally, several challenges, which limit the wide application of DTI in skeletal muscle, were discussed. It is believed that this review may arouse in-depth studies on the clinical application of DTI in skeletal muscle in future. PMID:23738269
Change-point analysis data of neonatal diffusion tensor MRI in preterm and term-born infants.
Wu, Dan; Chang, Linda; Akazawa, Kentaro; Oishi, Kumiko; Skranes, Jon; Ernst, Thomas; Oishi, Kenichi
2017-06-01
The data presented in this article are related to the research article entitled "Mapping the Critical Gestational Age at Birth that Alters Brain Development in Preterm-born Infants using Multi-Modal MRI" (Wu et al., 2017) [1]. Brain immaturity at birth poses critical neurological risks in the preterm-born infants. We used a novel change-point model to analyze the critical gestational age at birth (GAB) that could affect postnatal development, based on diffusion tensor MRI (DTI) acquired from 43 preterm and 43 term-born infants in 126 brain regions. In the corresponding research article, we presented change-point analysis of fractional anisotropy (FA) and mean diffusivities (MD) measurements in these infants. In this article, we offered the relative changes of axonal and radial diffusivities (AD and RD) in relation to the change of FA and FA-based change-points, and we also provided the AD- and RD-based change-point results.
NASA Technical Reports Server (NTRS)
Hizanidis, Kyriakos
1989-01-01
The relativistic motion of electrons in an intense electromagnetic wave packet propagating obliquely to a uniform magnetic field is analytically studied on the basis of the Fokker-Planck-Kolmogorov (FPK) approach. The wavepacket consists of circularly polarized electron-cyclotron waves. The dynamical system in question is shown to be reducible to one with three degrees of freedom. Within the framework of the Hamiltonian analysis the nonlinear diffusion tensor is derived, and it is shown that this tensor can be separated into zeroth-, first-, and second-order parts with respect to the relative bandwidth. The zeroth-order part describes diffusive acceleration along lines of constant unperturbed Hamiltonian. The second-order part, which corresponds to the longest time scale, describes diffusion across those lines. A possible transport theory is outlined on the basis of this separation of the time scales.
Leading non-Gaussian corrections for diffusion orientation distribution function.
Jensen, Jens H; Helpern, Joseph A; Tabesh, Ali
2014-02-01
An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed from the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves on the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common. 2013 John Wiley & Sons, Ltd.
Leading Non-Gaussian Corrections for Diffusion Orientation Distribution Function
Jensen, Jens H.; Helpern, Joseph A.; Tabesh, Ali
2014-01-01
An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed out of the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves upon the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common. PMID:24738143
Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation
Budde, Matthew D.; Skinner, Nathan P.; Muftuler, L. Tugan; Schmit, Brian D.; Kurpad, Shekar N.
2017-01-01
Diffusion tensor imaging (DTI) is a promising biomarker of spinal cord injury (SCI). In the acute aftermath, DTI in SCI animal models consistently demonstrates high sensitivity and prognostic performance, yet translation of DTI to acute human SCI has been limited. In addition to technical challenges, interpretation of the resulting metrics is ambiguous, with contributions in the acute setting from both axonal injury and edema. Novel diffusion MRI acquisition strategies such as double diffusion encoding (DDE) have recently enabled detection of features not available with DTI or similar methods. In this work, we perform a systematic optimization of DDE using simulations and an in vivo rat model of SCI and subsequently implement the protocol to the healthy human spinal cord. First, two complementary DDE approaches were evaluated using an orientationally invariant or a filter-probe diffusion encoding approach. While the two methods were similar in their ability to detect acute SCI, the filter-probe DDE approach had greater predictive power for functional outcomes. Next, the filter-probe DDE was compared to an analogous single diffusion encoding (SDE) approach, with the results indicating that in the spinal cord, SDE provides similar contrast with improved signal to noise. In the SCI rat model, the filter-probe SDE scheme was coupled with a reduced field of view (rFOV) excitation, and the results demonstrate high quality maps of the spinal cord without contamination from edema and cerebrospinal fluid, thereby providing high sensitivity to injury severity. The optimized protocol was demonstrated in the healthy human spinal cord using the commercially-available diffusion MRI sequence with modifications only to the diffusion encoding directions. Maps of axial diffusivity devoid of CSF partial volume effects were obtained in a clinically feasible imaging time with a straightforward analysis and variability comparable to axial diffusivity derived from DTI. Overall, the results and optimizations describe a protocol that mitigates several difficulties with DTI of the spinal cord. Detection of acute axonal damage in the injured or diseased spinal cord will benefit the optimized filter-probe diffusion MRI protocol outlined here. PMID:29311786
New two-metric theory of gravity with prior geometry
NASA Technical Reports Server (NTRS)
Lightman, A. P.; Lee, D. L.
1973-01-01
A Lagrangian-based metric theory of gravity is developed with three adjustable constants and two tensor fields, one of which is a nondynamic 'flat space metric' eta. With a suitable cosmological model and a particular choice of the constants, the 'post-Newtonian limit' of the theory agrees, in the current epoch, with that of general relativity theory (GRT); consequently the theory is consistent with current gravitation experiments. Because of the role of eta, the gravitational 'constant' G is time-dependent and gravitational waves travel null geodesics of eta rather than the physical metric g. Gravitational waves possess six degrees of freedom. The general exact static spherically-symmetric solution is a four-parameter family. Future experimental tests of the theory are discussed.
NASA Astrophysics Data System (ADS)
Schilling, Kurt G.; Nath, Vishwesh; Blaber, Justin; Harrigan, Robert L.; Ding, Zhaohua; Anderson, Adam W.; Landman, Bennett A.
2017-02-01
High-angular-resolution diffusion-weighted imaging (HARDI) MRI acquisitions have become common for use with higher order models of diffusion. Despite successes in resolving complex fiber configurations and probing microstructural properties of brain tissue, there is no common consensus on the optimal b-value and number of diffusion directions to use for these HARDI methods. While this question has been addressed by analysis of the diffusion-weighted signal directly, it is unclear how this translates to the information and metrics derived from the HARDI models themselves. Using a high angular resolution data set acquired at a range of b-values, and repeated 11 times on a single subject, we study how the b-value and number of diffusion directions impacts the reproducibility and precision of metrics derived from Q-ball imaging, a popular HARDI technique. We find that Q-ball metrics associated with tissue microstructure and white matter fiber orientation are sensitive to both the number of diffusion directions and the spherical harmonic representation of the Q-ball, and often are biased when under sampled. These results can advise researchers on appropriate acquisition and processing schemes, particularly when it comes to optimizing the number of diffusion directions needed for metrics derived from Q-ball imaging.
Valette, Julien; Giraudeau, Céline; Marchadour, Charlotte; Djemai, Boucif; Geffroy, Françoise; Ghaly, Mohamed Ahmed; Le Bihan, Denis; Hantraye, Philippe; Lebon, Vincent; Lethimonnier, Franck
2012-12-01
Diffusion-weighted spectroscopy is a unique tool for exploring the intracellular microenvironment in vivo. In living systems, diffusion may be anisotropic, when biological membranes exhibit particular orientation patterns. In this work, a volume selective diffusion-weighted sequence is proposed, allowing single-shot measurement of the trace of the diffusion tensor, which does not depend on tissue anisotropy. With this sequence, the minimal echo time is only three times the diffusion time. In addition, cross-terms between diffusion gradients and other gradients are cancelled out. An adiabatic version, similar to localization by adiabatic selective refocusing sequence, is then derived, providing partial immunity against cross-terms. Proof of concept is performed ex vivo on chicken skeletal muscle by varying tissue orientation and intra-voxel shim. In vivo performance of the sequence is finally illustrated in a U87 glioblastoma mouse model, allowing the measurement of the trace apparent diffusion coefficient for six metabolites, including J-modulated metabolites. Although measurement performed along three separate orthogonal directions would bring similar accuracy on trace apparent diffusion coefficient under ideal conditions, the method described here should be useful for probing intimate properties of the cells with minimal experimental bias. Copyright © 2012 Wiley Periodicals, Inc.
Atomic-batched tensor decomposed two-electron repulsion integrals
NASA Astrophysics Data System (ADS)
Schmitz, Gunnar; Madsen, Niels Kristian; Christiansen, Ove
2017-04-01
We present a new integral format for 4-index electron repulsion integrals, in which several strategies like the Resolution-of-the-Identity (RI) approximation and other more general tensor-decomposition techniques are combined with an atomic batching scheme. The 3-index RI integral tensor is divided into sub-tensors defined by atom pairs on which we perform an accelerated decomposition to the canonical product (CP) format. In a first step, the RI integrals are decomposed to a high-rank CP-like format by repeated singular value decompositions followed by a rank reduction, which uses a Tucker decomposition as an intermediate step to lower the prefactor of the algorithm. After decomposing the RI sub-tensors (within the Coulomb metric), they can be reassembled to the full decomposed tensor (RC approach) or the atomic batched format can be maintained (ABC approach). In the first case, the integrals are very similar to the well-known tensor hypercontraction integral format, which gained some attraction in recent years since it allows for quartic scaling implementations of MP2 and some coupled cluster methods. On the MP2 level, the RC and ABC approaches are compared concerning efficiency and storage requirements. Furthermore, the overall accuracy of this approach is assessed. Initial test calculations show a good accuracy and that it is not limited to small systems.
Atomic-batched tensor decomposed two-electron repulsion integrals.
Schmitz, Gunnar; Madsen, Niels Kristian; Christiansen, Ove
2017-04-07
We present a new integral format for 4-index electron repulsion integrals, in which several strategies like the Resolution-of-the-Identity (RI) approximation and other more general tensor-decomposition techniques are combined with an atomic batching scheme. The 3-index RI integral tensor is divided into sub-tensors defined by atom pairs on which we perform an accelerated decomposition to the canonical product (CP) format. In a first step, the RI integrals are decomposed to a high-rank CP-like format by repeated singular value decompositions followed by a rank reduction, which uses a Tucker decomposition as an intermediate step to lower the prefactor of the algorithm. After decomposing the RI sub-tensors (within the Coulomb metric), they can be reassembled to the full decomposed tensor (RC approach) or the atomic batched format can be maintained (ABC approach). In the first case, the integrals are very similar to the well-known tensor hypercontraction integral format, which gained some attraction in recent years since it allows for quartic scaling implementations of MP2 and some coupled cluster methods. On the MP2 level, the RC and ABC approaches are compared concerning efficiency and storage requirements. Furthermore, the overall accuracy of this approach is assessed. Initial test calculations show a good accuracy and that it is not limited to small systems.
2015-04-01
of unit length: da = F L a αδ α Ad A , da = F L−1αaδ A α dA . (2.12) The metric tensor associated with the deformed... A spatial density tensor θ and Frank vector ω̂ of the following forms are consistent with geometry of the problem: θ = θzzgz ⊗ gz = ω̂δ(r)gz ⊗ gz = δ...stress depends quadratically on strain, with the elastic potential cubic in strain and including elastic constants of
Martin, Allan R.; Aleksanderek, Izabela; Cohen-Adad, Julien; Tarmohamed, Zenovia; Tetreault, Lindsay; Smith, Nathaniel; Cadotte, David W.; Crawley, Adrian; Ginsberg, Howard; Mikulis, David J.; Fehlings, Michael G.
2015-01-01
Background A recent meeting of international imaging experts sponsored by the International Spinal Research Trust (ISRT) and the Wings for Life Foundation identified 5 state-of-the-art MRI techniques with potential to transform the field of spinal cord imaging by elucidating elements of the microstructure and function: diffusion tensor imaging (DTI), magnetization transfer (MT), myelin water fraction (MWF), MR spectroscopy (MRS), and functional MRI (fMRI). However, the progress toward clinical translation of these techniques has not been established. Methods A systematic review of the English literature was conducted using MEDLINE, MEDLINE-in-Progress, Embase, and Cochrane databases to identify all human studies that investigated utility, in terms of diagnosis, correlation with disability, and prediction of outcomes, of these promising techniques in pathologies affecting the spinal cord. Data regarding study design, subject characteristics, MRI methods, clinical measures of impairment, and analysis techniques were extracted and tabulated to identify trends and commonalities. The studies were assessed for risk of bias, and the overall quality of evidence was assessed for each specific finding using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Results A total of 6597 unique citations were identified in the database search, and after full-text review of 274 articles, a total of 104 relevant studies were identified for final inclusion (97% from the initial database search). Among these, 69 studies utilized DTI and 25 used MT, with both techniques showing an increased number of publications in recent years. The review also identified 1 MWF study, 11 MRS studies, and 8 fMRI studies. Most of the studies were exploratory in nature, lacking a priori hypotheses and showing a high (72%) or moderately high (20%) risk of bias, due to issues with study design, acquisition techniques, and analysis methods. The acquisitions for each technique varied widely across studies, rendering direct comparisons of metrics invalid. The DTI metric fractional anisotropy (FA) had the strongest evidence of utility, with moderate quality evidence for its use as a biomarker showing correlation with disability in several clinical pathologies, and a low level of evidence that it identifies tissue injury (in terms of group differences) compared with healthy controls. However, insufficient evidence exists to determine its utility as a sensitive and specific diagnostic test or as a tool to predict clinical outcomes. Very low quality evidence suggests that other metrics also show group differences compared with controls, including DTI metrics mean diffusivity (MD) and radial diffusivity (RD), the diffusional kurtosis imaging (DKI) metric mean kurtosis (MK), MT metrics MT ratio (MTR) and MT cerebrospinal fluid ratio (MTCSF), and the MRS metric of N-acetylaspartate (NAA) concentration, although these results were somewhat inconsistent. Conclusions State-of-the-art spinal cord MRI techniques are emerging with great potential to improve the diagnosis and management of various spinal pathologies, but the current body of evidence has only showed limited clinical utility to date. Among these imaging tools DTI is the most mature, but further work is necessary to standardize and validate its use before it will be adopted in the clinical realm. Large, well-designed studies with a priori hypotheses, standardized acquisition methods, detailed clinical data collection, and robust automated analysis techniques are needed to fully demonstrate the potential of these rapidly evolving techniques. PMID:26862478
Binocular stereo matching method based on structure tensor
NASA Astrophysics Data System (ADS)
Song, Xiaowei; Yang, Manyi; Fan, Yubo; Yang, Lei
2016-10-01
In a binocular visual system, to recover the three-dimensional information of the object, the most important step is to acquire matching points. Structure tensor is the vector representation of each point in its local neighborhood. Therefore, structure tensor performs well in region detection of local structure, and it is very suitable for detecting specific graphics such as pedestrians, cars and road signs in the image. In this paper, the structure tensor is combined with the luminance information to form the extended structure tensor. The directional derivatives of luminance in x and y directions are calculated, so that the local structure of the image is more prominent. Meanwhile, the Euclidean distance between the eigenvectors of key points is used as the similarity determination metric of key points in the two images. By matching, the coordinates of the matching points in the detected target are precisely acquired. In this paper, experiments were performed on the captured left and right images. After the binocular calibration, image matching was done to acquire the matching points, and then the target depth was calculated according to these matching points. By comparison, it is proved that the structure tensor can accurately acquire the matching points in binocular stereo matching.
Ho, Leon C.; Wang, Bo; Conner, Ian P.; van der Merwe, Yolandi; Bilonick, Richard A.; Kim, Seong-Gi; Wu, Ed X.; Sigal, Ian A.; Wollstein, Gadi; Schuman, Joel S.; Chan, Kevin C.
2015-01-01
Purpose. Excitotoxicity has been linked to the pathogenesis of ocular diseases and injuries and may involve early degeneration of both anterior and posterior visual pathways. However, their spatiotemporal relationships remain unclear. We hypothesized that the effects of excitotoxic retinal injury (ERI) on the visual system can be revealed in vivo by diffusion tensor magnetic resonance imagining (DTI), manganese-enhanced magnetic resonance imagining (MRI), and optical coherence tomography (OCT). Methods. Diffusion tensor MRI was performed at 9.4 Tesla to monitor white matter integrity changes after unilateral N-methyl-D-aspartate (NMDA)-induced ERI in six Sprague-Dawley rats and six C57BL/6J mice. Additionally, four rats and four mice were intravitreally injected with saline to compare with NMDA-injected animals. Optical coherence tomography of the retina and manganese-enhanced MRI of anterograde transport were evaluated and correlated with DTI parameters. Results. In the rat optic nerve, the largest axial diffusivity decrease and radial diffusivity increase occurred within the first 3 and 7 days post ERI, respectively, suggestive of early axonal degeneration and delayed demyelination. The optic tract showed smaller directional diffusivity changes and weaker DTI correlations with retinal thickness compared with optic nerve, indicative of anterograde degeneration. The splenium of corpus callosum was also reorganized at 4 weeks post ERI. The DTI profiles appeared comparable between rat and mouse models. Furthermore, the NMDA-injured visual pathway showed reduced anterograde manganese transport, which correlated with diffusivity changes along but not perpendicular to optic nerve. Conclusions. Diffusion tensor MRI, manganese-enhanced MRI, and OCT provided an in vivo model system for characterizing the spatiotemporal changes in white matter integrity, the eye–brain relationships and structural–physiological relationships in the visual system after ERI. PMID:26066747
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chapman, Christopher H., E-mail: chchap@umich.edu; Nagesh, Vijaya; Sundgren, Pia C.
Purpose: To determine whether early assessment of cerebral white matter degradation can predict late delayed cognitive decline after radiotherapy (RT). Methods and Materials: Ten patients undergoing conformal fractionated brain RT participated in a prospective diffusion tensor magnetic resonance imaging study. Magnetic resonance imaging studies were acquired before RT, at 3 and 6 weeks during RT, and 10, 30, and 78 weeks after starting RT. The diffusivity variables in the parahippocampal cingulum bundle and temporal lobe white matter were computed. A quality-of-life survey and neurocognitive function tests were administered before and after RT at the magnetic resonance imaging follow-up visits. Results:more » In both structures, longitudinal diffusivity ({lambda}{sub Double-Vertical-Line }) decreased and perpendicular diffusivity ({lambda}{sub Up-Tack }) increased after RT, with early changes correlating to later changes (p < .05). The radiation dose correlated with an increase in cingulum {lambda}{sub Up-Tack} at 3 weeks, and patients with >50% of cingula volume receiving >12 Gy had a greater increase in {lambda}{sub Up-Tack} at 3 and 6 weeks (p < .05). The post-RT changes in verbal recall scores correlated linearly with the late changes in cingulum {lambda}{sub Double-Vertical-Line} (30 weeks, p < .02). Using receiver operating characteristic curves, early cingulum {lambda}{sub Double-Vertical-Line} changes predicted for post-RT changes in verbal recall scores (3 and 6 weeks, p < .05). The neurocognitive test scores correlated significantly with the quality-of-life survey results. Conclusions: The correlation between early diffusivity changes in the parahippocampal cingulum and the late decline in verbal recall suggests that diffusion tensor imaging might be useful as a biomarker for predicting late delayed cognitive decline.« less
FADTTS: functional analysis of diffusion tensor tract statistics.
Zhu, Hongtu; Kong, Linglong; Li, Runze; Styner, Martin; Gerig, Guido; Lin, Weili; Gilmore, John H
2011-06-01
The aim of this paper is to present a functional analysis of a diffusion tensor tract statistics (FADTTS) pipeline for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. The FADTTS integrates five statistical tools: (i) a multivariate varying coefficient model for allowing the varying coefficient functions in terms of arc length to characterize the varying associations between fiber bundle diffusion properties and a set of covariates, (ii) a weighted least squares estimation of the varying coefficient functions, (iii) a functional principal component analysis to delineate the structure of the variability in fiber bundle diffusion properties, (iv) a global test statistic to test hypotheses of interest, and (v) a simultaneous confidence band to quantify the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FADTTS. We apply FADTTS to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. FADTTS can be used to facilitate the understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modeling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands. However, FADTTS is not crucial for estimation and reduces to the functional analysis method for the single measure. Copyright © 2011 Elsevier Inc. All rights reserved.
Memedyarov, A M; Namazova-Baranova, L S; Ermolina, Y V; Anikin, A V; Maslova, O I; Karkashadze, M Z; Klochkova, O A
2014-01-01
Diffusion tensor tractography--a new method of magnetic resonance imaging, that allows to visualize the pathways of the brain and to study their structural-functional state. The authors investigated the changes in motor and sensory pathways of brain in children with cerebral palsy using routine magnetic resonance imaging and diffusion-tensor tractography. The main group consisted of 26 patients with various forms of cerebral palsy and the comparison group was 25 people with normal psychomotor development (aged 2 to 6 years) and MR-picture of the brain. Magnetic resonance imaging was performed on the scanner with the induction of a magnetic field of 1,5 Tesla. Coefficients of fractional anisotropy and average diffusion coefficient estimated in regions of the brain containing the motor and sensory pathways: precentral gyrus, posterior limb of the internal capsule, thalamus, posterior thalamic radiation and corpus callosum. Statistically significant differences (p < 0.05) values of fractional anisotropy and average diffusion coefficient in patients with cerebral palsy in relation to the comparison group. All investigated regions, the coefficients of fractional anisotropy in children with cerebral palsy were significantly lower, and the average diffusion coefficient, respectively, higher. These changes indicate a lower degree of ordering of the white matter tracts associated with damage and subsequent development of gliosis of varying severity in children with cerebral palsy. It is shown that microstructural damage localized in both motor and sensory tracts that plays a leading role in the development of the clinical picture of cerebral palsy.
Kim, Dong Gyu; Kim, Seong Ho; Kim, Oh Lyong; Cho, Yun Woo; Son, Su Min; Jang, Sung Ho
2009-01-01
There have been no studies on motor recovery in severe quadriplegic patients with traumatic brain injury (TBI) resulting from combined causes of weakness; this type of patient is often seen in rehabilitation clinics. We report on a quadriplegic patient who showed long-term motor recovery from severe weakness caused by a diffuse axonal injury (DAI) on the brainstem and a traumatic intracerebral hemorrhage (ICH) on left cerebral peduncle, as evaluated by diffuse tensor imaging (DTI) and functional MRI (fMRI). A 17-year-old male patient presented with quadriparesis at the onset of TBI. Over the 28-month period following the onset of the injury, the motor function of the four extremities slowly recovered to a range that was nearly normal. Two longitudinal DTIs (at 11 and 28 months from onset) and fMRI (at 28 months) were performed. Fractional anisotropy and an apparent diffusion coefficient were measured using the region of interest method, and diffusion tensor tractography was conducted using a DTI/fMRI combination. Fractional anisotrophy values in the brainstem, which were markedly decreased on the 11-month DTI, were increased on the 28-month DTI. On the fMRI performed at 28 months, the contralateral primary sensori-motor cortex was activated by the movement of either the right or left hand. Diffusion tensor tractography showed that fiber tracts originating from the motor-sensory cortex passed through the known corticospinal tract pathway to the pons. It seems that the weakness of this patient recovered due to the recovery of the damaged corticospinal tracts.
Spherical shock waves in general relativity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nutku, Y.
1991-11-15
We present the metric appropriate to a spherical shock wave in the framework of general relativity. This is a Petrov type-{ital N} vacuum solution of the Einstein field equations where the metric is continuous across the shock and the Riemann tensor suffers a step-function discontinuity. Spherical gravitational waves are described by type-{ital N} Robinson-Trautman metrics. However, for shock waves the Robinson-Trautman solutions are unacceptable because the metric becomes discontinuous in the Robinson-Trautman coordinate system. Other coordinate systems that have so far been introduced for describing Robinson-Trautman solutions also suffer from the same defect. We shall present the {ital C}{sup 0}-formmore » of the metric appropriate to spherical shock waves using Penrose's approach of identification with warp. Further extensions of Penrose's method yield accelerating, as well as coupled electromagnetic-gravitational shock-wave solutions.« less
ERIC Educational Resources Information Center
Warlop, Nele P.; Achten, Eric; Fieremans, Els; Debruyne, Jan; Vingerhoets, Guy
2009-01-01
This study investigated the relation between cerebral damage related to multiple sclerosis (MS) and cognitive decline as determined by two classical mental tracking tests. Cerebral damage in 15 relapsing-remitting MS patients was measured by diffusion tensor imaging (DTI). Fractional anisotropy, longitudinal and transverse diffusivity were defined…
Effect of respiratory and cardiac gating on the major diffusion-imaging metrics.
Hamaguchi, Hiroyuki; Tha, Khin Khin; Sugimori, Hiroyuki; Nakanishi, Mitsuhiro; Nakagawa, Shin; Fujiwara, Taro; Yoshida, Hirokazu; Takamori, Sayaka; Shirato, Hiroki
2016-08-01
The effect of respiratory gating on the major diffusion-imaging metrics and that of cardiac gating on mean kurtosis (MK) are not known. For evaluation of whether the major diffusion-imaging metrics-MK, fractional anisotropy (FA), and mean diffusivity (MD) of the brain-varied between gated and non-gated acquisitions, respiratory-gated, cardiac-gated, and non-gated diffusion-imaging of the brain were performed in 10 healthy volunteers. MK, FA, and MD maps were constructed for all acquisitions, and the histograms were constructed. The normalized peak height and location of the histograms were compared among the acquisitions by use of Friedman and post hoc Wilcoxon tests. The effect of the repetition time (TR) on the diffusion-imaging metrics was also tested, and we corrected for its variation among acquisitions, if necessary. The results showed a shift in the peak location of the MK and MD histograms to the right with an increase in TR (p ≤ 0.01). The corrected peak location of the MK histograms, the normalized peak height of the FA histograms, the normalized peak height and the corrected peak location of the MD histograms varied significantly between the gated and non-gated acquisitions (p < 0.05). These results imply an influence of respiration and cardiac pulsation on the major diffusion-imaging metrics. The gating conditions must be kept identical if reproducible results are to be achieved. © The Author(s) 2016.
Lockwood Estrin, G; Kyriakopoulou, V; Makropoulos, A; Ball, G; Kuhendran, L; Chew, A; Hagberg, B; Martinez-Biarge, M; Allsop, J; Fox, M; Counsell, S J; Rutherford, M A
2016-01-01
Ventriculomegaly (VM) is the most common central nervous system abnormality diagnosed antenatally, and is associated with developmental delay in childhood. We tested the hypothesis that antenatally diagnosed isolated VM represents a biological marker for altered white matter (WM) and cortical grey matter (GM) development in neonates. 25 controls and 21 neonates with antenatally diagnosed isolated VM had magnetic resonance imaging at 41.97(± 2.94) and 45.34(± 2.14) weeks respectively. T2-weighted scans were segmented for volumetric analyses of the lateral ventricles, WM and cortical GM. Diffusion tensor imaging (DTI) measures were assessed using voxel-wise methods in WM and cortical GM; comparisons were made between cohorts. Ventricular and cortical GM volumes were increased, and WM relative volume was reduced in the VM group. Regional decreases in fractional anisotropy (FA) and increases in mean diffusivity (MD) were demonstrated in WM of the VM group compared to controls. No differences in cortical DTI metrics were observed. At 2 years, neurodevelopmental delays, especially in language, were observed in 6/12 cases in the VM cohort. WM alterations in isolated VM cases may be consistent with abnormal development of WM tracts involved in language and cognition. Alterations in WM FA and MD may represent neural correlates for later neurodevelopmental deficits.
Regional microstructural organization of the cerebral cortex is affected by preterm birth.
Bouyssi-Kobar, Marine; Brossard-Racine, Marie; Jacobs, Marni; Murnick, Jonathan; Chang, Taeun; Limperopoulos, Catherine
2018-01-01
To compare regional cerebral cortical microstructural organization between preterm infants at term-equivalent age (TEA) and healthy full-term newborns, and to examine the impact of clinical risk factors on cerebral cortical micro-organization in the preterm cohort. We prospectively enrolled very preterm infants (gestational age (GA) at birth<32 weeks; birthweight<1500 g) and healthy full-term controls. Using non-invasive 3T diffusion tensor imaging (DTI) metrics, we quantified regional micro-organization in ten cerebral cortical areas: medial/dorsolateral prefrontal cortex, anterior/posterior cingulate cortex, insula, posterior parietal cortex, motor/somatosensory/auditory/visual cortex. ANCOVA analyses were performed controlling for sex and postmenstrual age at MRI. We studied 91 preterm infants at TEA and 69 full-term controls. Preterm infants demonstrated significantly higher diffusivity in the prefrontal, parietal, motor, somatosensory, and visual cortices suggesting delayed maturation of these cortical areas. Additionally, postnatal hydrocortisone treatment was related to accelerated microstructural organization in the prefrontal and somatosensory cortices. Preterm birth alters regional microstructural organization of the cerebral cortex in both neurocognitive brain regions and areas with primary sensory/motor functions. We also report for the first time a potential protective effect of postnatal hydrocortisone administration on cerebral cortical development in preterm infants.
Fjell, Anders M.; Tamnes, Christian K.; Grydeland, Håkon; Due-Tønnessen, Paulina; Bjørnerud, Atle; Sampaio-Baptista, Cassandra; Andersson, Jesper; Johansen-Berg, Heidi; Walhovd, Kristine B.
2018-01-01
Working memory capacity is pivotal for a broad specter of cognitive tasks and develops throughout childhood. This must in part rely on development of neural connections and white matter microstructure maturation, but there is scarce knowledge of specific relations between this and different aspects of working memory. Diffusion tensor imaging (DTI) enables us to study development of brain white matter microstructure. In a longitudinal DTI study of 148 healthy children between 4 and 11 years scanned twice with an on average 1.6 years interval, we characterized change in fractional anisotropy (FA), mean (MD), radial (RD) and axial diffusivity (AD) in 10 major white matter tracts hypothesized to be of importance for working memory. The results showed relationships between change in several tracts and change in visuospatial working memory. Specifically, improvement in visuospatial working memory capacity was significantly associated with decreased MD, RD and AD in inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF) and uncinate fasciculus (UF) in the right hemisphere, as well as forceps major (FMaj). No significant relationships were found between change in DTI metrics and change in verbal working memory capacity. These findings yield new knowledge about brain development and corresponding working memory improvements in childhood. PMID:29689058
NASA Astrophysics Data System (ADS)
Venkateswarlu, R.; Sreenivas, K.
2014-06-01
The LRS Bianchi type-I and type-II string cosmological models are studied when the source for the energy momentum tensor is a bulk viscous stiff fluid containing one dimensional strings together with zero-mass scalar field. We have obtained the solutions of the field equations assuming a functional relationship between metric coefficients when the metric is Bianchi type-I and constant deceleration parameter in case of Bianchi type-II metric. The physical and kinematical properties of the models are discussed in each case. The effects of Viscosity on the physical and kinematical properties are also studied.
The Diffusion Tensor Imaging Toolbox
Alger, Jeffry R.
2012-01-01
During the past few years, the Journal of Neuroscience has published over 30 articles that describe investigations that used Diffusion Tensor Imaging (DTI) and related techniques as a primary observation method. This illustrates a growing interest in DTI within the basic and clinical neuroscience communities. This article summarizes DTI methodology in terms that can be immediately understood by the neuroscientist who has little previous exposure to DTI. It describes the fundamentals of water molecular diffusion coefficient measurement in brain tissue and illustrates how these fundamentals can be used to form vivid and useful depictions of white matter macroscopic and microscopic anatomy. It also describes current research applications and the technique’s attributes and limitations. It is hoped that this article will help the readers of this Journal to more effectively evaluate neuroscience studies that use DTI. PMID:22649222
Black holes in vector-tensor theories
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heisenberg, Lavinia; Kase, Ryotaro; Tsujikawa, Shinji
We study static and spherically symmetric black hole (BH) solutions in second-order generalized Proca theories with nonminimal vector field derivative couplings to the Ricci scalar, the Einstein tensor, and the double dual Riemann tensor. We find concrete Lagrangians which give rise to exact BH solutions by imposing two conditions of the two identical metric components and the constant norm of the vector field. These exact solutions are described by either Reissner-Nordström (RN), stealth Schwarzschild, or extremal RN solutions with a non-trivial longitudinal mode of the vector field. We then numerically construct BH solutions without imposing these conditions. For cubic andmore » quartic Lagrangians with power-law couplings which encompass vector Galileons as the specific cases, we show the existence of BH solutions with the difference between two non-trivial metric components. The quintic-order power-law couplings do not give rise to non-trivial BH solutions regular throughout the horizon exterior. The sixth-order and intrinsic vector-mode couplings can lead to BH solutions with a secondary hair. For all the solutions, the vector field is regular at least at the future or past horizon. The deviation from General Relativity induced by the Proca hair can be potentially tested by future measurements of gravitational waves in the nonlinear regime of gravity.« less
NASA Astrophysics Data System (ADS)
Wen, Hongwei; Liu, Yue; Wang, Jieqiong; Zhang, Jishui; Peng, Yun; He, Huiguang
2016-03-01
Tourette syndrome (TS) is a developmental neuropsychiatric disorder with the cardinal symptoms of motor and vocal tics which emerges in early childhood and fluctuates in severity in later years. To date, the neural basis of TS is not fully understood yet and TS has a long-term prognosis that is difficult to accurately estimate. Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy children and TS children. Here we apply Tract-Based Spatial Statistics (TBSS) method to 44 TS children and 48 age and gender matched healthy children in order to extract the diffusion values from each voxel in the white matter (WM) skeleton, and a feature selection algorithm (ReliefF) was used to select the most salient voxels for subsequent classification with support vector machine (SVM). We use a nested cross validation to yield an unbiased assessment of the classification method and prevent overestimation. The accuracy (88.04%), sensitivity (88.64%) and specificity (87.50%) were achieved in our method as peak performance of the SVM classifier was achieved using the axial diffusion (AD) metric, demonstrating the potential of a joint TBSS and SVM pipeline for fast, objective classification of healthy and TS children. These results support that our methods may be useful for the early identification of subjects with TS, and hold promise for predicting prognosis and treatment outcome for individuals with TS.
Nissan, Noam; Furman-Haran, Edna; Feinberg-Shapiro, Myra; Grobgeld, Dov; Eyal, Erez; Zehavi, Tania; Degani, Hadassa
2014-12-15
Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.
Knoll, Florian; Raya, José G; Halloran, Rafael O; Baete, Steven; Sigmund, Eric; Bammer, Roland; Block, Tobias; Otazo, Ricardo; Sodickson, Daniel K
2015-01-01
Radial spin echo diffusion imaging allows motion-robust imaging of tissues with very low T2 values like articular cartilage with high spatial resolution and signal-to-noise ratio (SNR). However, in vivo measurements are challenging due to the significantly slower data acquisition speed of spin-echo sequences and the less efficient k-space coverage of radial sampling, which raises the demand for accelerated protocols by means of undersampling. This work introduces a new reconstruction approach for undersampled DTI. A model-based reconstruction implicitly exploits redundancies in the diffusion weighted images by reducing the number of unknowns in the optimization problem and compressed sensing is performed directly in the target quantitative domain by imposing a Total Variation (TV) constraint on the elements of the diffusion tensor. Experiments were performed for an anisotropic phantom and the knee and brain of healthy volunteers (3 and 2 volunteers, respectively). Evaluation of the new approach was conducted by comparing the results to reconstructions performed with gridding, combined parallel imaging and compressed sensing, and a recently proposed model-based approach. The experiments demonstrated improvement in terms of reduction of noise and streaking artifacts in the quantitative parameter maps as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps. This may enable an essential reduction of the acquisition time in radial spin echo diffusion tensor imaging without degrading parameter quantification and/or SNR. PMID:25594167
Tensor non-Gaussianity from axion-gauge-fields dynamics: parameter search
NASA Astrophysics Data System (ADS)
Agrawal, Aniket; Fujita, Tomohiro; Komatsu, Eiichiro
2018-06-01
We calculate the bispectrum of scale-invariant tensor modes sourced by spectator SU(2) gauge fields during inflation in a model containing a scalar inflaton, a pseudoscalar axion and SU(2) gauge fields. A large bispectrum is generated in this model at tree-level as the gauge fields contain a tensor degree of freedom, and its production is dominated by self-coupling of the gauge fields. This is a unique feature of non-Abelian gauge theory. The shape of the tensor bispectrum is approximately an equilateral shape for 3lesssim mQlesssim 4, where mQ is an effective dimensionless mass of the SU(2) field normalised by the Hubble expansion rate during inflation. The amplitude of non-Gaussianity of the tensor modes, characterised by the ratio Bh/P2h, is inversely proportional to the energy density fraction of the gauge field. This ratio can be much greater than unity, whereas the ratio from the vacuum fluctuation of the metric is of order unity. The bispectrum is effective at constraining large mQ regions of the parameter space, whereas the power spectrum constrains small mQ regions.
Robust estimation of adaptive tensors of curvature by tensor voting.
Tong, Wai-Shun; Tang, Chi-Keung
2005-03-01
Although curvature estimation from a given mesh or regularly sampled point set is a well-studied problem, it is still challenging when the input consists of a cloud of unstructured points corrupted by misalignment error and outlier noise. Such input is ubiquitous in computer vision. In this paper, we propose a three-pass tensor voting algorithm to robustly estimate curvature tensors, from which accurate principal curvatures and directions can be calculated. Our quantitative estimation is an improvement over the previous two-pass algorithm, where only qualitative curvature estimation (sign of Gaussian curvature) is performed. To overcome misalignment errors, our improved method automatically corrects input point locations at subvoxel precision, which also rejects outliers that are uncorrectable. To adapt to different scales locally, we define the RadiusHit of a curvature tensor to quantify estimation accuracy and applicability. Our curvature estimation algorithm has been proven with detailed quantitative experiments, performing better in a variety of standard error metrics (percentage error in curvature magnitudes, absolute angle difference in curvature direction) in the presence of a large amount of misalignment noise.
Hidden symmetries of the Kerr metric and Goldstone’s theorem
NASA Astrophysics Data System (ADS)
Penna, Robert F.
2011-12-01
Perturbations of the Kerr metric admit a spectrum of massless excitations, which we interpret as Goldstone modes coming from the metric’s broken spherical symmetry. The zero-frequency mode is related to the conformal Yano-Killing tensor which encodes Carter’s constant and the Killing vectors of the spacetime. The modes are described by a conformal field theory, which becomes two-dimensional Liouville theory in the near-horizon limit. Directly counting the quantum microstates of this theory reproduces the Bekenstein-Hawking area law.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sivak, David; Crooks, Gavin
A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.
Chan, Rachel W; Von Deuster, Constantin; Stoeck, Christian T; Harmer, Jack; Punwani, Shonit; Ramachandran, Navin; Kozerke, Sebastian; Atkinson, David
2014-01-01
Fractional anisotropy (FA) obtained by diffusion tensor imaging (DTI) can be used to image the kidneys without any contrast media. FA of the medulla has been shown to correlate with kidney function. It is expected that higher spatial resolution would improve the depiction of small structures within the kidney. However, the achievement of high spatial resolution in renal DTI remains challenging as a result of respiratory motion and susceptibility to diffusion imaging artefacts. In this study, a targeted field of view (TFOV) method was used to obtain high-resolution FA maps and colour-coded diffusion tensor orientations, together with measures of the medullary and cortical FA, in 12 healthy subjects. Subjects were scanned with two implementations (dual and single kidney) of a TFOV DTI method. DTI scans were performed during free breathing with a navigator-triggered sequence. Results showed high consistency in the greyscale FA, colour-coded FA and diffusion tensors across subjects and between dual- and single-kidney scans, which have in-plane voxel sizes of 2 × 2 mm2 and 1.2 × 1.2 mm2, respectively. The ability to acquire multiple contiguous slices allowed the medulla and cortical FA to be quantified over the entire kidney volume. The mean medulla and cortical FA values were 0.38 ± 0.017 and 0.21 ± 0.019, respectively, for the dual-kidney scan, and 0.35 ± 0.032 and 0.20 ± 0.014, respectively, for the single-kidney scan. The mean FA between the medulla and cortex was significantly different (p < 0.001) for both dual- and single-kidney implementations. High-spatial-resolution DTI shows promise for improving the characterization and non-invasive assessment of kidney function. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd. PMID:25219683
Chan, Rachel W; Von Deuster, Constantin; Stoeck, Christian T; Harmer, Jack; Punwani, Shonit; Ramachandran, Navin; Kozerke, Sebastian; Atkinson, David
2014-11-01
Fractional anisotropy (FA) obtained by diffusion tensor imaging (DTI) can be used to image the kidneys without any contrast media. FA of the medulla has been shown to correlate with kidney function. It is expected that higher spatial resolution would improve the depiction of small structures within the kidney. However, the achievement of high spatial resolution in renal DTI remains challenging as a result of respiratory motion and susceptibility to diffusion imaging artefacts. In this study, a targeted field of view (TFOV) method was used to obtain high-resolution FA maps and colour-coded diffusion tensor orientations, together with measures of the medullary and cortical FA, in 12 healthy subjects. Subjects were scanned with two implementations (dual and single kidney) of a TFOV DTI method. DTI scans were performed during free breathing with a navigator-triggered sequence. Results showed high consistency in the greyscale FA, colour-coded FA and diffusion tensors across subjects and between dual- and single-kidney scans, which have in-plane voxel sizes of 2 × 2 mm(2) and 1.2 × 1.2 mm(2) , respectively. The ability to acquire multiple contiguous slices allowed the medulla and cortical FA to be quantified over the entire kidney volume. The mean medulla and cortical FA values were 0.38 ± 0.017 and 0.21 ± 0.019, respectively, for the dual-kidney scan, and 0.35 ± 0.032 and 0.20 ± 0.014, respectively, for the single-kidney scan. The mean FA between the medulla and cortex was significantly different (p < 0.001) for both dual- and single-kidney implementations. High-spatial-resolution DTI shows promise for improving the characterization and non-invasive assessment of kidney function. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.
Callot, Virginie; Duhamel, Guillaume; Cozzone, Patrick J; Kober, Frank
2008-10-01
Mouse spinal cord (SC) diffusion-weighted imaging (DWI) provides important information on tissue morphology and structural changes that may occur during pathologies such as multiple sclerosis or SC injury. The acquisition scheme of the commonly used DWI techniques is based on conventional spin-echo encoding, which is time-consuming. The purpose of this work was to investigate whether the use of echo planar imaging (EPI) would provide good-quality diffusion MR images of mouse SC, as well as accurate measurements of diffusion-derived metrics, and thus enable diffusion tensor imaging (DTI) and highly resolved DWI within reasonable scan times. A four-shot diffusion-weighted spin-echo EPI (SE-EPI) sequence was evaluated at 11.75 T on a group of healthy mice (n = 10). SE-EPI-derived apparent diffusion coefficients of gray and white matter were compared with those obtained using a conventional spin-echo sequence (c-SE) to validate the accuracy of the method. To take advantage of the reduction in acquisition time offered by the EPI sequence, multi-slice DTI acquisitions were performed covering the cervical segments (six slices, six diffusion-encoding directions, three b values) within 30 min (vs 2 h for c-SE). From these measurements, fractional anisotropy and mean diffusivities were calculated, and fiber tracking along the C1 to C6 cervical segments was performed. In addition, high-resolution images (74 x 94 microm(2)) were acquired within 5 min per direction. Clear delineation of gray and white matter and identical apparent diffusion coefficient values were obtained, with a threefold reduction in acquisition time compared with c-SE. While overcoming the difficulties associated with high spatially and temporally resolved DTI measurements, the present SE-EPI approach permitted identification of reliable quantitative parameters with a reproducibility compatible with the detection of pathologies. The SE-EPI method may be particularly valuable when multiple sets of images from the SC are needed, in cases of rapidly evolving conditions, to decrease the duration of anesthesia or to improve MR exploration by including additional MR measurements. Copyright (c) 2008 John Wiley & Sons, Ltd.
Branzoli, Francesca; Ercan, Ece; Valabrègue, Romain; Wood, Emily T; Buijs, Mathijs; Webb, Andrew; Ronen, Itamar
2016-11-01
Diffusion-tensor imaging and single voxel diffusion-weighted magnetic resonance spectroscopy were used at 7T to explore in vivo age-related microstructural changes in the corpus callosum. Sixteen healthy elderly (age range 60-71 years) and 13 healthy younger controls (age range 23-32 years) were included in the study. In healthy elderly, we found lower water fractional anisotropy and higher water mean diffusivity and radial diffusivity in the corpus callosum, indicating the onset of demyelination processes with healthy aging. These changes were not associated with a concomitant significant difference in the cytosolic diffusivity of the intra-axonal metabolite N-acetylaspartate (p = 0.12), the latter representing a pure measure of intra-axonal integrity. It was concluded that the possible intra-axonal changes associated with normal aging processes are below the detection level of diffusion-weighted magnetic resonance spectroscopy in our experiment (e.g., smaller than 10%) in the age range investigated. Lower axial diffusivity of total creatine was observed in the elderly group (p = 0.058), possibly linked to a dysfunction in the energy metabolism associated with a deficit in myelin synthesis. Copyright © 2016 Elsevier Inc. All rights reserved.
Zikou, Anastasia K; Xydis, Vasileios G; Astrakas, Loukas G; Nakou, Iliada; Tzarouchi, Loukia C; Tzoufi, Meropi; Argyropoulou, Maria I
2016-07-01
There is evidence of microstructural changes in normal-appearing white matter of patients with tuberous sclerosis complex. To evaluate major white matter tracts in children with tuberous sclerosis complex using tract-based spatial statistics diffusion tensor imaging (DTI) analysis. Eight children (mean age ± standard deviation: 8.5 ± 5.5 years) with an established diagnosis of tuberous sclerosis complex and 8 age-matched controls were studied. The imaging protocol consisted of T1-weighted high-resolution 3-D spoiled gradient-echo sequence and a spin-echo, echo-planar diffusion-weighted sequence. Differences in the diffusion indices were evaluated using tract-based spatial statistics. Tract-based spatial statistics showed increased axial diffusivity in the children with tuberous sclerosis complex in the superior and anterior corona radiata, the superior longitudinal fascicle, the inferior fronto-occipital fascicle, the uncinate fascicle and the anterior thalamic radiation. No significant differences were observed in fractional anisotropy, mean diffusivity and radial diffusivity between patients and control subjects. No difference was found in the diffusion indices between the baseline and follow-up examination in the patient group. Patients with tuberous sclerosis complex have increased axial diffusivity in major white matter tracts, probably related to reduced axonal integrity.
Conventions and nomenclature for double diffusion encoding NMR and MRI.
Shemesh, Noam; Jespersen, Sune N; Alexander, Daniel C; Cohen, Yoram; Drobnjak, Ivana; Dyrby, Tim B; Finsterbusch, Jurgen; Koch, Martin A; Kuder, Tristan; Laun, Fredrik; Lawrenz, Marco; Lundell, Henrik; Mitra, Partha P; Nilsson, Markus; Özarslan, Evren; Topgaard, Daniel; Westin, Carl-Fredrik
2016-01-01
Stejskal and Tanner's ingenious pulsed field gradient design from 1965 has made diffusion NMR and MRI the mainstay of most studies seeking to resolve microstructural information in porous systems in general and biological systems in particular. Methods extending beyond Stejskal and Tanner's design, such as double diffusion encoding (DDE) NMR and MRI, may provide novel quantifiable metrics that are less easily inferred from conventional diffusion acquisitions. Despite the growing interest on the topic, the terminology for the pulse sequences, their parameters, and the metrics that can be derived from them remains inconsistent and disparate among groups active in DDE. Here, we present a consensus of those groups on terminology for DDE sequences and associated concepts. Furthermore, the regimes in which DDE metrics appear to provide microstructural information that cannot be achieved using more conventional counterparts (in a model-free fashion) are elucidated. We highlight in particular DDE's potential for determining microscopic diffusion anisotropy and microscopic fractional anisotropy, which offer metrics of microscopic features independent of orientation dispersion and thus provide information complementary to the standard, macroscopic, fractional anisotropy conventionally obtained by diffusion MR. Finally, we discuss future vistas and perspectives for DDE. © 2015 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Visinescu, Mihai
2011-04-01
We give an overview of the first integrals of motion of particles in the presence of external gauge fields in a covariant Hamiltonian approach. The special role of Stäckel-Killing and Killing-Yano tensors is pointed out. Some nontrivial examples involving Runge-Lenz type conserved quantities are explicitly worked out. A condition of the electromagnetic field to maintain the hidden symmetry of the system is stated. A concrete realization of this condition is given by the Killing-Maxwell system and exemplified with the Kerr metric. Quantum symmetry operators for the Klein-Gordon and Dirac equations are constructed from Killing tensors. The transfer of the classical conserved quantities to the quantum mechanical level is analyzed in connection with quantum anomalies.
Müller, Hans-Peter; Grön, Georg; Sprengelmeyer, Reiner; Kassubek, Jan; Ludolph, Albert C.; Hobbs, Nicola; Cole, James; Roos, Raymund A.C.; Duerr, Alexandra; Tabrizi, Sarah J.; Landwehrmeyer, G. Bernhard; Süssmuth, Sigurd D.
2013-01-01
Purpose Assessment of the feasibility to average diffusion tensor imaging (DTI) metrics of MRI data acquired in the course of a multicenter study. Materials and methods Sixty-one early stage Huntington's disease patients and forty healthy controls were studied using four different MR scanners at four European sites with acquisition protocols as close as possible to a given standard protocol. The potential and feasibility of averaging data acquired at different sites was evaluated quantitatively by region-of-interest (ROI) based statistical comparisons of coefficients of variation (CV) across centers, as well as by testing for significant group-by-center differences on averaged fractional anisotropy (FA) values between patients and controls. In addition, a whole-brain based statistical between-group comparison was performed using FA maps. Results The ex post facto statistical evaluation of CV and FA-values in a priori defined ROIs showed no differences between sites above chance indicating that data were not systematically biased by center specific factors. Conclusion Averaging FA-maps from DTI data acquired at different study sites and different MR scanner types does not appear to be systematically biased. A suitable recipe for testing on the possibility to pool multicenter DTI data is provided to permit averaging of DTI-derived metrics to differentiate patients from healthy controls at a larger scale. PMID:24179771
Liu, Hua-Shan; Chou, Ming-Chung; Chung, Hsiao-Wen; Cho, Nai-Yu; Chiang, Shih-Wei; Wang, Chao-Ying; Kao, Hung-Wen; Huang, Guo-Shu; Chen, Cheng-Yu
2011-08-01
To investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA, commonly known as "ecstasy") on the alterations of brain metabolites and anatomic tissue integrity related to the function of the basal ganglia-thalamocortical circuit by using proton magnetic resonance (MR) spectroscopy and diffusion-tensor MR imaging. This study was approved by a local institutional review board, and written informed consent was obtained from all subjects. Thirty-one long-term (>1 year) MDMA users and 33 healthy subjects were enrolled. Proton MR spectroscopy from the middle frontal cortex and bilateral basal ganglia and whole-brain diffusion-tensor MR imaging were performed with a 3.0-T system. Absolute concentrations of metabolites were computed, and diffusion-tensor data were registered to the International Consortium for Brain Mapping template to facilitate voxel-based group comparison. The mean myo-inositol level in the basal ganglia of MDMA users (left: 4.55 mmol/L ± 2.01 [standard deviation], right: 4.48 mmol/L ± 1.33) was significantly higher than that in control subjects (left: 3.25 mmol/L ± 1.30, right: 3.31 mmol/L ± 1.19) (P < .001). Cumulative lifetime MDMA dose showed a positive correlation with the levels of choline-containing compounds (Cho) in the right basal ganglia (r = 0.47, P = .02). MDMA users also showed a significant increase in fractional anisotropy (FA) in the bilateral thalami and significant changes in water diffusion in several regions related to the basal ganglia-thalamocortical circuit as compared with control subjects (P < .05; cluster size, >50 voxels). Increased myo-inositol and Cho concentrations in the basal ganglia of MDMA users are suggestive of glial response to degenerating serotonergic functions. The abnormal metabolic changes in the basal ganglia may consequently affect the inhibitory effect of the basal ganglia to the thalamus, as suggested by the increased FA in the thalamus and abnormal changes in water diffusion in the corresponding basal ganglia-thalamocortical circuit. © RSNA, 2011.
Zhao, Xuefeng; Raghavan, Madhavan L; Lu, Jia
2011-05-01
Knowledge of elastic properties of cerebral aneurysms is crucial for understanding the biomechanical behavior of the lesion. However, characterizing tissue properties using in vivo motion data presents a tremendous challenge. Aside from the limitation of data accuracy, a pressing issue is that the in vivo motion does not expose the stress-free geometry. This is compounded by the nonlinearity, anisotropy, and heterogeneity of the tissue behavior. This article introduces a method for identifying the heterogeneous properties of aneurysm wall tissue under unknown stress-free configuration. In the proposed approach, an accessible configuration is taken as the reference; the unknown stress-free configuration is represented locally by a metric tensor describing the prestrain from the stress-free configuration to the reference configuration. Material parameters are identified together with the metric tensor pointwisely. The paradigm is tested numerically using a forward-inverse analysis loop. An image-derived sac is considered. The aneurysm tissue is modeled as an eightply laminate whose constitutive behavior is described by an anisotropic hyperelastic strain-energy function containing four material parameters. The parameters are assumed to vary continuously in two assigned patterns to represent two types of material heterogeneity. Nine configurations between the diastolic and systolic pressures are generated by forward quasi-static finite element analyses. These configurations are fed to the inverse analysis to delineate the material parameters and the metric tensor. The recovered and the assigned distributions are in good agreement. A forward verification is conducted by comparing the displacement solutions obtained from the recovered and the assigned material parameters at a different pressure. The nodal displacements are found in excellent agreement.
A Riemannian framework for orientation distribution function computing.
Cheng, Jian; Ghosh, Aurobrata; Jiang, Tianzi; Deriche, Rachid
2009-01-01
Compared with Diffusion Tensor Imaging (DTI), High Angular Resolution Imaging (HARDI) can better explore the complex microstructure of white matter. Orientation Distribution Function (ODF) is used to describe the probability of the fiber direction. Fisher information metric has been constructed for probability density family in Information Geometry theory and it has been successfully applied for tensor computing in DTI. In this paper, we present a state of the art Riemannian framework for ODF computing based on Information Geometry and sparse representation of orthonormal bases. In this Riemannian framework, the exponential map, logarithmic map and geodesic have closed forms. And the weighted Frechet mean exists uniquely on this manifold. We also propose a novel scalar measurement, named Geometric Anisotropy (GA), which is the Riemannian geodesic distance between the ODF and the isotropic ODF. The Renyi entropy H1/2 of the ODF can be computed from the GA. Moreover, we present an Affine-Euclidean framework and a Log-Euclidean framework so that we can work in an Euclidean space. As an application, Lagrange interpolation on ODF field is proposed based on weighted Frechet mean. We validate our methods on synthetic and real data experiments. Compared with existing Riemannian frameworks on ODF, our framework is model-free. The estimation of the parameters, i.e. Riemannian coordinates, is robust and linear. Moreover it should be noted that our theoretical results can be used for any probability density function (PDF) under an orthonormal basis representation.
Jacquesson, Timothée; Frindel, Carole; Cotton, Francois
2017-04-01
A 24-year-old woman was hit by a bus and suffered an isolated complete oculomotor nerve palsy. Computed tomography scan did not show a skull base fracture. T2*-weighted magnetic resonance imaging revealed petechial cerebral hemorrhages sparing the brainstem. T2 constructive interference in steady state suggested a partial sectioning of the left oculomotor nerve just before entering the superior orbital fissure. Diffusion tensor imaging fiber tractography confirmed a sharp arrest of the left oculomotor nerve. This recent imaging technique could be of interest to assess white fiber damage and help make a diagnosis or prognosis. Copyright © 2017 Elsevier Inc. All rights reserved.
Revealing the cerebello-ponto-hypothalamic pathway in the human brain.
Kamali, Arash; Karbasian, Niloofar; Rabiei, Pejman; Cano, Andres; Riascos, Roy F; Tandon, Nitin; Arevalo, Octavio; Ocasio, Laura; Younes, Kyan; Khayat-Khoei, Mahsa; Mirbagheri, Saeedeh; Hasan, Khader M
2018-06-11
The cerebellum is shown to be involved in some limbic functions of the human brain such as emotion and affect. The major connection of the cerebellum with the limbic system is known to be through the cerebello-hypothalamic pathways. The consensus is that the projections from the cerebellar nuclei to the limbic system, and particularly the hypothalamus, or from the hypothalamus to the cerebellar nuclei, are through multisynaptic pathways in the bulbar reticular formation. The detailed anatomy of the pathways responsible for mediating these responses, however, is yet to be determined. Diffusion tensor imaging may be helpful in better visualizing the surgical anatomy of the cerebello-ponto-hypothalamic (CPH) pathway. This study aimed to investigate the utility of high-spatial-resolution diffusion tensor tractography for mapping the trajectory of the CPH tract in the human brain. Fifteen healthy adults were studied. We delineated, for the first time, the detailed trajectory of the CPH tract of the human brain in fifteen normal adult subjects using high-spatial-resolution diffusion tensor tractography. We further revealed the close relationship of the CPH tract with the optic tract, temporo-pontine tract, amygdalofugal tract and the fornix in the human brain. Copyright © 2018 Elsevier B.V. All rights reserved.
White matter fiber tracking computation based on diffusion tensor imaging for clinical applications.
Dellani, Paulo R; Glaser, Martin; Wille, Paulo R; Vucurevic, Goran; Stadie, Axel; Bauermann, Thomas; Tropine, Andrei; Perneczky, Axel; von Wangenheim, Aldo; Stoeter, Peter
2007-03-01
Fiber tracking allows the in vivo reconstruction of human brain white matter fiber trajectories based on magnetic resonance diffusion tensor imaging (MR-DTI), but its application in the clinical routine is still in its infancy. In this study, we present a new software for fiber tracking, developed on top of a general-purpose DICOM (digital imaging and communications in medicine) framework, which can be easily integrated into existing picture archiving and communication system (PACS) of radiological institutions. Images combining anatomical information and the localization of different fiber tract trajectories can be encoded and exported in DICOM and Analyze formats, which are valuable resources in the clinical applications of this method. Fiber tracking was implemented based on existing line propagation algorithms, but it includes a heuristic for fiber crossings in the case of disk-shaped diffusion tensors. We successfully performed fiber tracking on MR-DTI data sets from 26 patients with different types of brain lesions affecting the corticospinal tracts. In all cases, the trajectories of the central spinal tract (pyramidal tract) were reconstructed and could be applied at the planning phase of the surgery as well as in intraoperative neuronavigation.
Rice, Lauren J; Lagopoulos, Jim; Brammer, Michael; Einfeld, Stewart L
2017-09-01
Prader-Willi Syndrome (PWS) is a genetic disorder characterized by infantile hypotonia, hyperphagia, hypogonadism, growth hormone deficiency, intellectual disability, and severe emotional and behavioral problems. The brain mechanisms that underpin these disturbances are unknown. Diffusion tensor imaging (DTI) enables in vivo investigation of the microstructural integrity of white matter pathways. To date, only one study has used DTI to examine white matter alterations in PWS. However, that study used selected regions of interest, rather than a whole brain analysis. In the present study, we used diffusion tensor and magnetic resonance (T 1-weighted) imaging to examine microstructural white matter changes in 15 individuals with PWS (17-30 years) and 15 age-and-gender-matched controls. Whole-brain voxel-wise statistical analysis of FA was carried out using tract-based spatial statistics (TBSS). Significantly decreased fractional anisotropy was found localized to the left hemisphere in individuals with PWS within the splenium of the corpus callosum, the internal capsule including the posterior thalamic radiation and the inferior frontal occipital fasciculus (IFOF). Reduced integrity of these white matter pathways in individuals with PWS may relate to orientating attention, emotion recognition, semantic processing, and sensorimotor dysfunction. © 2017 Wiley Periodicals, Inc.
The metric on field space, functional renormalization, and metric–torsion quantum gravity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reuter, Martin, E-mail: reuter@thep.physik.uni-mainz.de; Schollmeyer, Gregor M., E-mail: schollmeyer@thep.physik.uni-mainz.de
Searching for new non-perturbatively renormalizable quantum gravity theories, functional renormalization group (RG) flows are studied on a theory space of action functionals depending on the metric and the torsion tensor, the latter parameterized by three irreducible component fields. A detailed comparison with Quantum Einstein–Cartan Gravity (QECG), Quantum Einstein Gravity (QEG), and “tetrad-only” gravity, all based on different theory spaces, is performed. It is demonstrated that, over a generic theory space, the construction of a functional RG equation (FRGE) for the effective average action requires the specification of a metric on the infinite-dimensional field manifold as an additional input. A modifiedmore » FRGE is obtained if this metric is scale-dependent, as it happens in the metric–torsion system considered.« less
NASA Astrophysics Data System (ADS)
Wisniewski, Nicholas Andrew
This dissertation is divided into two parts. First we present an exact solution to a generalization of the Behrens-Fisher problem by embedding the problem in the Riemannian manifold of Normal distributions. From this we construct a geometric hypothesis testing scheme. Secondly we investigate the most commonly used geometric methods employed in tensor field interpolation for DT-MRI analysis and cardiac computer modeling. We computationally investigate a class of physiologically motivated orthogonal tensor invariants, both at the full tensor field scale and at the scale of a single interpolation by doing a decimation/interpolation experiment. We show that Riemannian-based methods give the best results in preserving desirable physiological features.
Sinha, Usha; Csapo, Robert; Malis, Vadim; Xue, Yanjie; Sinha, Shantanu
2014-01-01
Purpose To investigate age related changes in diffusion tensor indices and fiber architecture of the medial and lateral gastrocnemius (MG and LG) muscles using diffusion tensor imaging (DTI). Materials and Methods The lower leg of five young and five senior subjects was scanned at 3T and DTI indices extracted using three methods: ROI, histogram and tract based. Tracked fibers were automatically edited to ensure physiologically relevant tracks. Pennation angles were measured with respect to the deep and superficial aponeuroses of both muscles. Results The three methods provided internally consistent measures of the DTI indices (correlation coefficient in the range of 0.90-0.99). The primary, secondary and tertiary eigenvalues in the MG and LG increased significantly in the senior cohort (p<0.05), while the small increase in fractional anisotropy (FA) with age was not significant (MG/LG: p=0.39/0.85; 95% CI:[ −0.059/-0.056, 0.116/0.064]). Fiber lengths of MG fibers originating distally were significantly decreased in seniors (p<0.05) while pennation angles decreased with age in the MG and LG but this was not significant. Conclusion Fiber atrophy and increased fibrosis have opposing effects on the diffusion indices resulting in a complicated dependence with aging. Fiber architectural changes could play a role in determining aging muscle function. PMID:24771672
Sinha, Usha; Csapo, Robert; Malis, Vadim; Xue, Yanjie; Sinha, Shantanu
2015-04-01
To investigate age related changes in diffusion tensor indices and fiber architecture of the medial and lateral gastrocnemius (MG and LG) muscles using diffusion tensor imaging (DTI). The lower leg of five young and five senior subjects was scanned at 3 Tesla and DTI indices extracted using three methods: region of interest, histogram, and tract based. Tracked fibers were automatically edited to ensure physiologically relevant tracks. Pennation angles were measured with respect to the deep and superficial aponeuroses of both muscles. The three methods provided internally consistent measures of the DTI indices (correlation coefficient in the range of 0.90-0.99). The primary, secondary, and tertiary eigenvalues in the MG and LG increased significantly in the senior cohort (P < 0.05), while the small increase in fractional anisotropy with age was not significant (MG/LG: P = 0.39/0.85; 95% confidence interval: [-0.059/-0.056, 0.116/0.064]). Fiber lengths of MG fibers originating distally were significantly decreased in seniors (P < 0.05) while pennation angles decreased with age in the MG and LG but this was not significant. Fiber atrophy and increased fibrosis have opposing effects on the diffusion indices resulting in a complicated dependence with aging. Fiber architectural changes could play a role in determining aging muscle function. © 2014 Wiley Periodicals, Inc.
Peng, Syu-Jyun; Harnod, Tomor; Tsai, Jang-Zern; Huang, Chien-Chun; Ker, Ming-Dou; Chiou, Jun-Chern; Chiueh, Herming; Wu, Chung-Yu; Hsin, Yue-Loong
2014-01-01
To investigate white matter (WM) abnormalities in neocortical epilepsy, we extract supratentorial WM parameters from raw tensor magnetic resonance images (MRI) with automated region-of-interest (ROI) registrations. Sixteen patients having neocortical seizures with secondarily generalised convulsions and 16 age-matched normal subjects were imaged with high-resolution and diffusion tensor MRIs. Automated demarcation of supratentorial fibers was accomplished with personalized fiber-labeled atlases. From the individual atlases, we observed significant elevation of mean diffusivity (MD) in fornix (cres)/stria terminalis (FX/ST) and sagittal stratum (SS) and a significant difference in fractional anisotropy (FA) among FX/ST, SS, posterior limb of the internal capsule (PLIC), and posterior thalamic radiation (PTR). For patients with early-onset epilepsy, the diffusivities of the SS and the retrolenticular part of the internal capsule were significantly elevated, and the anisotropies of the FX/ST and SS were significantly decreased. In the drug-resistant subgroup, the MDs of SS and PTR and the FAs of SS and PLIC were significantly different. Onset age was positively correlated with increases in FAs of the genu of the corpus callosum. Patients with neocortical seizures and secondary generalisation had microstructural anomalies in WM. The changes in WM are relevant to early onset, progression, and severity of epilepsy. PMID:24883310
Anjari, Mustafa; Srinivasan, Latha; Allsop, Joanna M; Hajnal, Joseph V; Rutherford, Mary A; Edwards, A David; Counsell, Serena J
2007-04-15
Infants born preterm have a high incidence of neurodevelopmental impairment in later childhood, often associated with poorly defined cerebral white matter abnormalities. Diffusion tensor imaging quantifies the diffusion of water within tissues and can assess microstructural abnormalities in the developing preterm brain. Tract-based spatial statistics (TBSS) is an automated observer-independent method of aligning fractional anisotropy (FA) images from multiple subjects to allow groupwise comparisons of diffusion tensor imaging data. We applied TBSS to test the hypothesis that preterm infants have reduced fractional anisotropy in specific regions of white matter compared to term-born controls. We studied 26 preterm infants with no evidence of focal lesions on conventional magnetic resonance imaging (MRI) at term equivalent age and 6 healthy term-born control infants. We found that the centrum semiovale, frontal white matter and the genu of the corpus callosum showed significantly lower FA in the preterm group. Infants born at less than or equal to 28 weeks gestational age (n=11) displayed additional reductions in FA in the external capsule, the posterior aspect of the posterior limb of the internal capsule and the isthmus and middle portion of the body of the corpus callosum. This study demonstrates that TBSS provides an observer-independent method of identifying white matter abnormalities in the preterm brain at term equivalent age in the absence of focal lesions.
DWI filtering using joint information for DTI and HARDI.
Tristán-Vega, Antonio; Aja-Fernández, Santiago
2010-04-01
The filtering of the Diffusion Weighted Images (DWI) prior to the estimation of the diffusion tensor or other fiber Orientation Distribution Functions (ODF) has been proved to be of paramount importance in the recent literature. More precisely, it has been evidenced that the estimation of the diffusion tensor without a previous filtering stage induces errors which cannot be recovered by further regularization of the tensor field. A number of approaches have been intended to overcome this problem, most of them based on the restoration of each DWI gradient image separately. In this paper we propose a methodology to take advantage of the joint information in the DWI volumes, i.e., the sum of the information given by all DWI channels plus the correlations between them. This way, all the gradient images are filtered together exploiting the first and second order information they share. We adapt this methodology to two filters, namely the Linear Minimum Mean Squared Error (LMMSE) and the Unbiased Non-Local Means (UNLM). These new filters are tested over a wide variety of synthetic and real data showing the convenience of the new approach, especially for High Angular Resolution Diffusion Imaging (HARDI). Among the techniques presented, the joint LMMSE is proved a very attractive approach, since it shows an accuracy similar to UNLM (or even better in some situations) with a much lighter computational load. Copyright 2009 Elsevier B.V. All rights reserved.
Covariant Conformal Decomposition of Einstein Equations
NASA Astrophysics Data System (ADS)
Gourgoulhon, E.; Novak, J.
It has been shown1,2 that the usual 3+1 form of Einstein's equations may be ill-posed. This result has been previously observed in numerical simulations3,4. We present a 3+1 type formalism inspired by these works to decompose Einstein's equations. This decomposition is motivated by the aim of stable numerical implementation and resolution of the equations. We introduce the conformal 3-``metric'' (scaled by the determinant of the usual 3-metric) which is a tensor density of weight -2/3. The Einstein equations are then derived in terms of this ``metric'', of the conformal extrinsic curvature and in terms of the associated derivative. We also introduce a flat 3-metric (the asymptotic metric for isolated systems) and the associated derivative. Finally, the generalized Dirac gauge (introduced by Smarr and York5) is used in this formalism and some examples of formulation of Einstein's equations are shown.
Evaluation of non-Gaussian diffusion in cardiac MRI.
McClymont, Darryl; Teh, Irvin; Carruth, Eric; Omens, Jeffrey; McCulloch, Andrew; Whittington, Hannah J; Kohl, Peter; Grau, Vicente; Schneider, Jürgen E
2017-09-01
The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non-Gaussian modeling. The aim of this study was to investigate non-Gaussian diffusion in healthy and hypertrophic hearts. Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion-weighted images were acquired at b-values up to 10,000 s/mm 2 . Models of diffusion were fit to the data and ranked based on the Akaike information criterion. The diffusion tensor was ranked best at b-values up to 2000 s/mm 2 but reflected the signal poorly in the high b-value regime, in which the best model was a non-Gaussian "beta distribution" model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet-normal directions. Non-Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174-1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Invariant quantities in the scalar-tensor theories of gravitation
NASA Astrophysics Data System (ADS)
Järv, Laur; Kuusk, Piret; Saal, Margus; Vilson, Ott
2015-01-01
We consider the general scalar-tensor gravity without derivative couplings. By rescaling of the metric and reparametrization of the scalar field, the theory can be presented in different conformal frames and parametrizations. In this work we argue that while due to the freedom to transform the metric and the scalar field, the scalar field itself does not carry a physical meaning (in a generic parametrization), there are functions of the scalar field and its derivatives which remain invariant under the transformations. We put forward a scheme to construct these invariants, discuss how to formulate the theory in terms of the invariants, and show how the observables like parametrized post-Newtonian parameters and characteristics of the cosmological solutions can be neatly expressed in terms of the invariants. In particular, we describe the scalar field solutions in Friedmann-Lemaître-Robertson-Walker cosmology in Einstein and Jordan frames and explain their correspondence despite the approximate equations turning out to be linear and nonlinear in different frames.
NASA Astrophysics Data System (ADS)
Adler, Stephen L.
In earlier work we showed that a frame dependent effective action motivated by the postulates of three-space general coordinate invariance and Weyl scaling invariance exactly mimics a cosmological constant in Robertson-Walker (RW) spacetimes. Here we study the implications of this effective action for small fluctuations around a spatially flat RW background geometry. The equations for the conserving extension of the modified stress-energy tensor can be integrated in closed form, and involve only the metric perturbation h00. Hence the equations for tensor and vector perturbations are unmodified, but there are Hubble scale additions to the scalar perturbation equations, which nonetheless admit no propagating wave solutions. Consequently, there are no modifications to standard gravitational wave propagation theory, but there may be observable implications for cosmology. We give a self-contained discussion, including an analysis of the restricted class of gauge transformations that act when a frame dependent effective action is present.
Novel symmetries in Weyl-invariant gravity with massive gauge field
NASA Astrophysics Data System (ADS)
Abhinav, K.; Shukla, A.; Panigrahi, P. K.
2016-11-01
The background field method is used to linearize the Weyl-invariant scalar-tensor gravity, coupled with a Stückelberg field. For a generic background metric, this action is found not to be invariant, under both a diffeomorphism and generalized Weyl symmetry, the latter being a combination of gauge and Weyl transformations. Interestingly, the quadratic Lagrangian, emerging from a background of Minkowski metric, respects both transformations independently. The Becchi-Rouet-Stora-Tyutin symmetry of scalar-tensor gravity coupled with a Stückelberg-like massive gauge particle, possessing a diffeomorphism and generalized Weyl symmetry, reveals that in both cases negative-norm states with unphysical degrees of freedom do exist. We then show that, by combining diffeomorphism and generalized Weyl symmetries, all the ghost states decouple, thereby removing the unphysical redundancies of the theory. During this process, the scalar field does not represent any dynamic mode, yet modifies the usual harmonic gauge condition through non-minimal coupling with gravity.
Fouré, Alexandre; Ogier, Augustin C; Le Troter, Arnaud; Vilmen, Christophe; Feiweier, Thorsten; Guye, Maxime; Gondin, Julien; Besson, Pierre; Bendahan, David
2018-05-01
Purpose To demonstrate the reproducibility of the diffusion properties and three-dimensional structural organization measurements of the lower leg muscles by using diffusion-tensor imaging (DTI) assessed with ultra-high-field-strength (7.0-T) magnetic resonance (MR) imaging and tractography of skeletal muscle fibers. On the basis of robust statistical mapping analyses, this study also aimed at determining the sensitivity of the measurements to sex difference and intramuscular variability. Materials and Methods All examinations were performed with ethical review board approval; written informed consent was obtained from all volunteers. Reproducibility of diffusion tensor indexes assessment including eigenvalues, mean diffusivity, and fractional anisotropy (FA) as well as muscle volume and architecture (ie, fiber length and pennation angle) were characterized in lower leg muscles (n = 8). Intramuscular variability and sex differences were characterized in young healthy men and women (n = 10 in each group). Student t test, statistical parametric mapping, correlation coefficients (Spearman rho and Pearson product-moment) and coefficient of variation (CV) were used for statistical data analysis. Results High reproducibility of measurements (mean CV ± standard deviation, 4.6% ± 3.8) was determined in diffusion properties and architectural parameters. Significant sex differences were detected in FA (4.2% in women for the entire lower leg; P = .001) and muscle volume (21.7% in men for the entire lower leg; P = .008), whereas architecture parameters were almost identical across sex. Additional differences were found independently of sex in diffusion properties and architecture along several muscles of the lower leg. Conclusion The high-spatial-resolution DTI assessed with 7.0-T MR imaging allows a reproducible assessment of structural organization of superficial and deep muscles, giving indirect information on muscle function. © RSNA, 2018 Online supplemental material is available for this article.
Simplifying the EFT of Inflation: generalized disformal transformations and redundant couplings
NASA Astrophysics Data System (ADS)
Bordin, Lorenzo; Cabass, Giovanni; Creminelli, Paolo; Vernizzi, Filippo
2017-09-01
We study generalized disformal transformations, including derivatives of the metric, in the context of the Effective Field Theory of Inflation. All these transformations do not change the late-time cosmological observables but change the coefficients of the operators in the action: some couplings are effectively redundant. At leading order in derivatives and up to cubic order in perturbations, one has 6 free functions that can be used to set to zero 6 of the 17 operators at this order. This is used to show that the tensor three-point function cannot be modified at leading order in derivatives, while the scalar-tensor-tensor correlator can only be modified by changing the scalar dynamics. At higher order in derivatives there are transformations that do not affect the Einstein-Hilbert action: one can find 6 additional transformations that can be used to simplify the inflaton action, at least when the dynamics is dominated by the lowest derivative terms. We also identify the leading higher-derivative corrections to the tensor power spectrum and bispectrum.
Brain tumor classification using the diffusion tensor image segmentation (D-SEG) technique.
Jones, Timothy L; Byrnes, Tiernan J; Yang, Guang; Howe, Franklyn A; Bell, B Anthony; Barrick, Thomas R
2015-03-01
There is an increasing demand for noninvasive brain tumor biomarkers to guide surgery and subsequent oncotherapy. We present a novel whole-brain diffusion tensor imaging (DTI) segmentation (D-SEG) to delineate tumor volumes of interest (VOIs) for subsequent classification of tumor type. D-SEG uses isotropic (p) and anisotropic (q) components of the diffusion tensor to segment regions with similar diffusion characteristics. DTI scans were acquired from 95 patients with low- and high-grade glioma, metastases, and meningioma and from 29 healthy subjects. D-SEG uses k-means clustering of the 2D (p,q) space to generate segments with different isotropic and anisotropic diffusion characteristics. Our results are visualized using a novel RGB color scheme incorporating p, q and T2-weighted information within each segment. The volumetric contribution of each segment to gray matter, white matter, and cerebrospinal fluid spaces was used to generate healthy tissue D-SEG spectra. Tumor VOIs were extracted using a semiautomated flood-filling technique and D-SEG spectra were computed within the VOI. Classification of tumor type using D-SEG spectra was performed using support vector machines. D-SEG was computationally fast and stable and delineated regions of healthy tissue from tumor and edema. D-SEG spectra were consistent for each tumor type, with constituent diffusion characteristics potentially reflecting regional differences in tissue microstructure. Support vector machines classified tumor type with an overall accuracy of 94.7%, providing better classification than previously reported. D-SEG presents a user-friendly, semiautomated biomarker that may provide a valuable adjunct in noninvasive brain tumor diagnosis and treatment planning. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.
Ward, Phil; Counsell, Serena; Allsop, Joanna; Cowan, Frances; Shen, Yuji; Edwards, David; Rutherford, Mary
2006-04-01
Apparent diffusion coefficients (ADC) that are measured by diffusion-weighted imaging are reduced in severe white matter (WM) and in some severe basal ganglia and thalamic (BGT) injury in infants who present with hypoxic-ischemic encephalopathy (HIE). However, ADC values may pseudonormalize or even be high during this time in some less severe but clinically significant injuries. We hypothesized that fractional anisotropy (FA), a measure of the directional diffusivity of water made using diffusion tensor imaging, may be abnormal in these less severe injuries; therefore, the objective of this study was to use diffusion tensor imaging to measure ADC and FA in infants with moderate and severe hypoxic-ischemic brain injury. Twenty infants with HIE and 7 normal control infants were studied. All infants were born at >36 weeks' gestational age, and MRI scans were obtained within 3 weeks of delivery. Data were examined for normality, and comparisons were made using analysis of variance or Kruskal-Wallis as appropriate. During the first week, FA values were decreased with both severe and moderate WM and BGT injury as assessed by conventional imaging, whereas ADC values were reduced only in severe WM injury and some severe BGT injury. Abnormal ADC values pseudonormalized during the second week, whereas FA values continued to decrease. FA is reduced in moderate brain injury after HIE. A low FA may reflect a breakdown in WM organization. Moderate BGT injury may result in atrophy but not overt infarction; it is possible that delayed apoptosis is more marked than immediate necrosis, and this may account for normal early ADC values. The accompanying low FA within some severe and all moderate gray matter lesions, which is associated with significant later impairment, may help to confirm clinically significant abnormality in infants with normal ADC values.
Diffusion Tensor Analysis by Two-Dimensional Pair Correlation of Fluorescence Fluctuations in Cells.
Di Rienzo, Carmine; Cardarelli, Francesco; Di Luca, Mariagrazia; Beltram, Fabio; Gratton, Enrico
2016-08-23
In a living cell, the movement of biomolecules is highly regulated by the cellular organization into subcompartments that impose barriers to diffusion, can locally break the spatial isotropy, and ultimately guide these molecules to their targets. Despite the pivotal role of these processes, experimental tools to fully probe the complex connectivity (and accessibility) of the cell interior with adequate spatiotemporal resolution are still lacking. Here, we show how the heterogeneity of molecular dynamics and the location of barriers to molecular motion can be mapped in live cells by exploiting a two-dimensional (2D) extension of the pair correlation function (pCF) analysis. Starting from a time series of images collected for the same field of view, the resulting 2D pCF is calculated in the proximity of each point for each time delay and allows us to probe the spatial distribution of the molecules that started from a given pixel. This 2D pCF yields an accurate description of the preferential diffusive routes. Furthermore, we combine this analysis with the image-derived mean-square displacement approach and gain information on the average nanoscopic molecular displacements in different directions. Through these quantities, we build a fluorescence-fluctuation-based diffusion tensor that contains information on speed and directionality of the local dynamical processes. Contrary to classical fluorescence correlation spectroscopy and related methods, this combined approach can distinguish between isotropic and anisotropic local diffusion. We argue that the measurement of this iMSD tensor will contribute to advance our understanding of the role played by the intracellular environment in the regulation of molecular diffusion at the nanoscale. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Liu, Gang; Peng, Kangqiang; Dang, Chao; Tan, Shuangquan; Chen, Hongbing; Xie, Chuanmiao; Xing, Shihui; Zeng, Jinsheng
2018-01-01
Secondary degeneration of the fiber tract of the motor pathway below infarct foci and functional recovery after stroke have been well demonstrated, but the role of the fiber tract above stroke foci remains unclear. This study aimed to investigate diffusion changes in motor fibers above the lesion and identify predictors of motor improvement within 12 weeks after subcortical infarction. Diffusion tensor imaging and the Fugl-Meyer (FM) scale were conducted 1, 4, and 12 weeks (W) after a subcortical infarct. Proportional recovery model residuals were used to assign patients to proportional recovery and poor recovery groups. Region of interest analysis was used to assess diffusion changes in the motor pathway above and below a stroke lesion. Multivariable linear regression was employed to identify predictors of motor improvement within 12 weeks after stroke. Axial diffusivity (AD) in the underlying white matter of the ipsilesional primary motor area (PMA) and cerebral peduncle (CP) in both proportional and poor recovery groups was lower at W1 compared to the controls and values in the contralesional PMA and CP (all P < 0.05). Subsequently, AD in the ipsilesional CP became relatively stable, while AD in the ipsilesional PMA significantly increased from W4 to W12 after stroke (P < 0.05). In all of the patients, changes in the FM scores were greater in those with higher changes in AD of the ipsilesional PMA. Only initial impairment or lesion volume was predictive of motor improvement within 12 weeks after stroke in patients with proportional or poor recovery. Increases of AD in the motor pathway above stroke foci may be associated with motor recovery after subcortical infarction. Early measurement of diffusion metrics in the ipsilesional non-ischemic motor pathway has limited value in predicting future motor improvement patterns (proportional or poor recovery).
Monitoring the refinement of crystal structures with {sup 15}N solid-state NMR shift tensor data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kalakewich, Keyton; Eloranta, Harriet; Harper, James K.
The {sup 15}N chemical shift tensor is shown to be extremely sensitive to lattice structure and a powerful metric for monitoring density functional theory refinements of crystal structures. These refinements include lattice effects and are applied here to five crystal structures. All structures improve based on a better agreement between experimental and calculated {sup 15}N tensors, with an average improvement of 47.0 ppm. Structural improvement is further indicated by a decrease in forces on the atoms by 2–3 orders of magnitude and a greater similarity in atom positions to neutron diffraction structures. These refinements change bond lengths by more thanmore » the diffraction errors including adjustments to X–Y and X–H bonds (X, Y = C, N, and O) of 0.028 ± 0.002 Å and 0.144 ± 0.036 Å, respectively. The acquisition of {sup 15}N tensors at natural abundance is challenging and this limitation is overcome by improved {sup 1}H decoupling in the FIREMAT method. This decoupling dramatically narrows linewidths, improves signal-to-noise by up to 317%, and significantly improves the accuracy of measured tensors. A total of 39 tensors are measured with shifts distributed over a range of more than 400 ppm. Overall, experimental {sup 15}N tensors are at least 5 times more sensitive to crystal structure than {sup 13}C tensors due to nitrogen’s greater polarizability and larger range of chemical shifts.« less