diffusion tensor imaging-based: Topics by Science.gov

Sample records for diffusion tensor imaging-based

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.…
Basic concepts of MR imaging, diffusion MR imaging, and diffusion tensor imaging.

PubMed

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.
Fluid Registration of Diffusion Tensor Images Using Information Theory

PubMed Central

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
Diffusion Tensor Magnetic Resonance Imaging Strategies for Color Mapping of Human Brain Anatomy

PubMed Central

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
Spatial Mapping of Translational Diffusion Coefficients Using Diffusion Tensor Imaging: A Mathematical Description

PubMed Central

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
MRI diffusion tensor reconstruction with PROPELLER data acquisition.

PubMed

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.
A Local Fast Marching-Based Diffusion Tensor Image Registration Algorithm by Simultaneously Considering Spatial Deformation and Tensor Orientation

PubMed Central

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
Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

PubMed Central

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
Traumatic Brain Injury Diffusion Magnetic Resonance Imaging Research Roadmap Development Project

DTIC Science & Technology

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
A Framework for Linear and Non-Linear Registration of Diffusion-Weighted MRIs Using Angular Interpolation

PubMed Central

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
A Framework for Linear and Non-Linear Registration of Diffusion-Weighted MRIs Using Angular Interpolation.

PubMed

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.
Diffusion tensor imaging with direct cytopathological validation: characterisation of decorin treatment in experimental juvenile communicating hydrocephalus.

PubMed

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.
Longitudinal brain white matter alterations in minimal hepatic encephalopathy before and after liver transplantation.

PubMed

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.
Diffusion Tensor Image Registration Using Hybrid Connectivity and Tensor Features

PubMed Central

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
Retrospective correction of bias in diffusion tensor imaging arising from coil combination mode.

PubMed

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 Â© 2016 Elsevier Inc. All rights reserved.
Structural differences in interictal migraine attack after epilepsy: A diffusion tensor imaging analysis.

PubMed

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.
Development of a Human Brain Diffusion Tensor Template

PubMed Central

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.

PubMed

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.
[An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].

PubMed

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.
Use of diffusion tensor imaging to identify similarities and differences between cerebellar and Parkinsonism forms of multiple system atrophy.

PubMed

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.

Determining anisotropic conductivity using diffusion tensor imaging data in magneto-acoustic tomography with magnetic induction

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.
A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging.

PubMed

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.
Retrospective Correction of Physiological Noise in DTI Using an Extended Tensor Model and Peripheral Measurements

PubMed Central

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
A framework for incorporating DTI Atlas Builder registration into Tract-Based Spatial Statistics and a simulated comparison to standard TBSS.

PubMed

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.
Neurocognitive Effects of Radiotherapy

DTIC Science & Technology

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
Seamless Warping of Diffusion Tensor Fields

PubMed Central

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
Tract-Specific Analyses of Diffusion Tensor Imaging Show Widespread White Matter Compromise in Autism Spectrum Disorder

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)…
Separation of specular and diffuse components using tensor voting in color images.

PubMed

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.
Assessment of MRI-Based Marker of Dopaminergic Integrity as a Biological Indicator of Gulf War Illness

DTIC Science & Technology

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
Altered Development of White Matter in Youth at High Familial Risk for Bipolar Disorder: A Diffusion Tensor Imaging Study

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…
Volume illustration of muscle from diffusion tensor images.

PubMed

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.
Methodological improvements in voxel-based analysis of diffusion tensor images: applications to study the impact of apolipoprotein E on white matter integrity.

PubMed

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.
b matrix errors in echo planar diffusion tensor imaging

PubMed Central

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
Groupwise Registration and Atlas Construction of 4th-Order Tensor Fields Using the ℝ+ Riemannian Metric*

PubMed Central

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
A diffusion tensor imaging tractography algorithm based on Navier-Stokes fluid mechanics.

PubMed

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

PubMed Central

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
Software Toolbox for Low-Frequency Conductivity and Current Density Imaging Using MRI.

PubMed

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.
Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla.

PubMed

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.
Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer's disease cases.

PubMed

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.
Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging.

PubMed

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.

Mild hypothermia for treatment of diffuse axonal injury: a quantitative analysis of diffusion tensor imaging

PubMed Central

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
DR-TAMAS: Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures

PubMed Central

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.

PubMed

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.
Motion immune diffusion imaging using augmented MUSE (AMUSE) for high-resolution multi-shot EPI

PubMed Central

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
On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods.

PubMed

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).
Diffusion tensor imaging demonstrates brainstem and cerebellar abnormalities in congenital central hypoventilation syndrome.

PubMed

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.
Novel region of interest interrogation technique for diffusion tensor imaging analysis in the canine brain.

PubMed

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.
Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging Based on a Riemannian Manifold Approach.

PubMed

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.
MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.

PubMed

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.
The physical and biological basis of quantitative parameters derived from diffusion MRI

PubMed Central

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
Diffusion tensor imaging analysis of sequential spreading of disease in amyotrophic lateral sclerosis confirms patterns of TDP-43 pathology.

PubMed

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.
Diffusion MRI and its role in neuropsychology

PubMed Central

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
Automatic deformable diffusion tensor registration for fiber population analysis.

PubMed

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.
A model-based reconstruction for undersampled radial spin echo DTI with variational penalties on the diffusion tensor

PubMed Central

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
Probabilistic-driven oriented Speckle reducing anisotropic diffusion with application to cardiac ultrasonic images.

PubMed

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.
White matter fiber tracking computation based on diffusion tensor imaging for clinical applications.

PubMed

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.
Contribution of cardiac-induced brain pulsation to the noise of the diffusion tensor in Turboprop diffusion tensor imaging (DTI).

PubMed

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.
Estimation of integral curves from high angular resolution diffusion imaging (HARDI) data.

PubMed

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

PubMed Central

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
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…

Director Field Analysis (DFA): Exploring Local White Matter Geometric Structure in Diffusion MRI.

PubMed

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.
Diffusion Tensor Imaging Tractography Detecting Isolated Oculomotor Nerve Damage After Traumatic Brain Injury.

PubMed

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.
White matter structure in loneliness: preliminary findings from diffusion tensor imaging.

PubMed

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.
Diffusion tensor imaging in children with tuberous sclerosis complex: tract-based spatial statistics assessment of brain microstructural changes.

PubMed

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.
Weighted Mean of Signal Intensity for Unbiased Fiber Tracking of Skeletal Muscles: Development of a New Method and Comparison With Other Correction Techniques.

PubMed

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.
Geodesic-loxodromes for diffusion tensor interpolation and difference measurement.

PubMed

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.
Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain.

PubMed

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.
Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants.

PubMed

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.
Assessment of diffusion tensor image quality across sites and vendors using the American College of Radiology head phantom.

PubMed

Wang, Zhiyue J; Seo, Youngseob; Babcock, Evelyn; Huang, Hao; Bluml, Stefan; Wisnowski, Jessica; Holshouser, Barbara; Panigrahy, Ashok; Shaw, Dennis W W; Altman, Nolan; McColl, Roderick W; Rollins, Nancy K

2016-05-08

The purpose of this study was to explore the feasibility of assessing quality of diffusion tensor imaging (DTI) from multiple sites and vendors using American College of Radiology (ACR) phantom. Participating sites (Siemens (n = 2), GE (n= 2), and Philips (n = 4)) reached consensus on parameters for DTI and used the widely available ACR phantom. Tensor data were processed at one site. B0 and eddy current distortions were assessed using grid line displacement on phantom Slice 5; signal-to-noise ratio (SNR) was measured at the center and periphery of the b = 0 image; fractional anisotropy (FA) and mean diffusivity (MD) were assessed using phantom Slice 7. Variations of acquisition parameters and deviations from specified sequence parameters were recorded. Nonlinear grid line distortion was higher with linear shimming and could be corrected using the 2nd order shimming. Following image registration, eddy current distortion was consistently smaller than acquisi-tion voxel size. SNR was consistently higher in the image periphery than center by a factor of 1.3-2.0. ROI-based FA ranged from 0.007 to 0.024. ROI-based MD ranged from 1.90 × 10-3 to 2.33 × 10-3 mm2/s (median = 2.04 × 10-3 mm2/s). Two sites had image void artifacts. The ACR phantom can be used to compare key qual-ity measures of diffusion images acquired from multiple vendors at multiple sites.
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...
The Value of Neurosurgical and Intraoperative Magnetic Resonance Imaging and Diffusion Tensor Imaging Tractography in Clinically Integrated Neuroanatomy Modules: A Cross-Sectional Study

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…
Q-space trajectory imaging for multidimensional diffusion MRI of the human brain

PubMed Central

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
Brain structural changes in spasmodic dysphonia: A multimodal magnetic resonance imaging study.

PubMed

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.
Comparison of scalar measures used in magnetic resonance diffusion tensor imaging.

PubMed

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.
Adaptive distance metric learning for diffusion tensor image segmentation.

PubMed

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

PubMed Central

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
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…
Combining Diffusion Tensor Metrics and DSC Perfusion Imaging: Can It Improve the Diagnostic Accuracy in Differentiating Tumefactive Demyelination from High-Grade Glioma?

PubMed

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.
Quantitative MRI of the spinal cord and brain in adrenomyeloneuropathy: in vivo assessment of structural changes.

PubMed

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.
Monitoring In-Vivo the Mammary Gland Microstructure during Morphogenesis from Lactation to Post-Weaning Using Diffusion Tensor MRI.

PubMed

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).

Spin echo versus stimulated echo diffusion tensor imaging of the in vivo human heart

PubMed Central

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
Condition Number as a Measure of Noise Performance of Diffusion Tensor Data Acquisition Schemes with MRI

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.
Susceptibility Tensor Imaging (STI) of the Brain

PubMed Central

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
Image Corruption Detection in Diffusion Tensor Imaging for Post-Processing and Real-Time Monitoring

PubMed Central

Li, Yue; Shea, Steven M.; Lorenz, Christine H.; Jiang, Hangyi; Chou, Ming-Chung; Mori, Susumu

2013-01-01

Due to the high sensitivity of diffusion tensor imaging (DTI) to physiological motion, clinical DTI scans often suffer a significant amount of artifacts. Tensor-fitting-based, post-processing outlier rejection is often used to reduce the influence of motion artifacts. Although it is an effective approach, when there are multiple corrupted data, this method may no longer correctly identify and reject the corrupted data. In this paper, we introduce a new criterion called “corrected Inter-Slice Intensity Discontinuity” (cISID) to detect motion-induced artifacts. We compared the performance of algorithms using cISID and other existing methods with regard to artifact detection. The experimental results show that the integration of cISID into fitting-based methods significantly improves the retrospective detection performance at post-processing analysis. The performance of the cISID criterion, if used alone, was inferior to the fitting-based methods, but cISID could effectively identify severely corrupted images with a rapid calculation time. In the second part of this paper, an outlier rejection scheme was implemented on a scanner for real-time monitoring of image quality and reacquisition of the corrupted data. The real-time monitoring, based on cISID and followed by post-processing, fitting-based outlier rejection, could provide a robust environment for routine DTI studies. PMID:24204551
MR Diffusion Tensor Imaging: A Window into White Matter Integrity of the Working Brain

PubMed Central

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
Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future.

PubMed

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.
Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma—Foundations and Future

PubMed Central

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
Tensor scale: An analytic approach with efficient computation and applications☆

PubMed Central

Xu, Ziyue; Saha, Punam K.; Dasgupta, Soura

2015-01-01

Scale is a widely used notion in computer vision and image understanding that evolved in the form of scale-space theory where the key idea is to represent and analyze an image at various resolutions. Recently, we introduced a notion of local morphometric scale referred to as “tensor scale” using an ellipsoidal model that yields a unified representation of structure size, orientation and anisotropy. In the previous work, tensor scale was described using a 2-D algorithmic approach and a precise analytic definition was missing. Also, the application of tensor scale in 3-D using the previous framework is not practical due to high computational complexity. In this paper, an analytic definition of tensor scale is formulated for n-dimensional (n-D) images that captures local structure size, orientation and anisotropy. Also, an efficient computational solution in 2- and 3-D using several novel differential geometric approaches is presented and the accuracy of results is experimentally examined. Also, a matrix representation of tensor scale is derived facilitating several operations including tensor field smoothing to capture larger contextual knowledge. Finally, the applications of tensor scale in image filtering and n-linear interpolation are presented and the performance of their results is examined in comparison with respective state-of-art methods. Specifically, the performance of tensor scale based image filtering is compared with gradient and Weickert’s structure tensor based diffusive filtering algorithms. Also, the performance of tensor scale based n-linear interpolation is evaluated in comparison with standard n-linear and windowed-sinc interpolation methods. PMID:26236148
Experimental evaluation of electrical conductivity imaging of anisotropic brain tissues using a combination of diffusion tensor imaging and magnetic resonance electrical impedance tomography

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
Leading non-Gaussian corrections for diffusion orientation distribution function.

PubMed

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

PubMed Central

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
Multimodal MRI in cerebral small vessel disease: its relationship with cognition and sensitivity to change over time.

PubMed

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.
A brain MRI atlas of the common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.

2014-03-01

The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.
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.
An introduction to diffusion tensor image analysis.

PubMed

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.
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.
Multiple sclerosis: changes in microarchitecture of white matter tracts after training with a video game balance board.

PubMed

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.
Diffusion-weighted imaging and demyelinating diseases: new aspects of an old advanced sequence.

PubMed

Rueda-Lopes, Fernanda C; Hygino da Cruz, Luiz C; Doring, Thomas M; Gasparetto, Emerson L

2014-01-01

The purpose of this article is to discuss classic applications in diffusion-weighted imaging (DWI) in demyelinating disease and progression of DWI in the near future. DWI is an advanced technique used in the follow-up of demyelinating disease patients, focusing on the diagnosis of a new lesion before contrast enhancement. With technical advances, diffusion-tensor imaging; new postprocessing techniques, such as tract-based spatial statistics; new ways of calculating diffusion, such as kurtosis; and new applications for DWI and its spectrum are about to arise.
Autism Spectrum Disorder: Does Neuroimaging Support the DSM-5 Proposal for a Symptom Dyad? A Systematic Review of Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging Studies

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…
Quantitative analysis of hypertrophic myocardium using diffusion tensor magnetic resonance imaging

PubMed Central

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

Improved olefinic fat suppression in skeletal muscle DTI using a magnitude-based dixon method.

PubMed

Burakiewicz, Jedrzej; Hooijmans, Melissa T; Webb, Andrew G; Verschuuren, Jan J G M; Niks, Erik H; Kan, Hermien E

2018-01-01

To develop a method of suppressing the multi-resonance fat signal in diffusion-weighted imaging of skeletal muscle. This is particularly important when imaging patients with muscular dystrophies, a group of diseases which cause gradual replacement of muscle tissue by fat. The signal from the olefinic fat peak at 5.3 ppm can significantly confound diffusion-tensor imaging measurements. Dixon olefinic fat suppression (DOFS), a magnitude-based chemical-shift-based method of suppressing the olefinic peak, is proposed. It is verified in vivo by performing diffusion tensor imaging (DTI)-based quantification in the lower leg of seven healthy volunteers, and compared to two previously described fat-suppression techniques in regions with and without fat contamination. In the region without fat contamination, DOFS produces similar results to existing techniques, whereas in muscle contaminated by subcutaneous fat signal moved due to the chemical shift artefact, it consistently showed significantly higher (P = 0.018) mean diffusivity (MD). Because fat presence lowers MD, this suggests improved fat suppression. DOFS offers superior fat suppression and enhances quantitative measurements in the muscle in the presence of fat. DOFS is an alternative to spectral olefinic fat suppression. Magn Reson Med 79:152-159, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
An Exploration into Diffusion Tensor Imaging in the Bovine Ocular Lens

PubMed Central

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
Intermediate Templates Guided Groupwise Registration of Diffusion Tensor Images

PubMed Central

Jia, Hongjun; Yap, Pew-Thian; Wu, Guorong; Wang, Qian; Shen, Dinggang

2010-01-01

Registration of a population of diffusion tensor images (DTIs) is one of the key steps in medical image analysis, and it plays an important role in the statistical analysis of white matter related neurological diseases. However, pairwise registration with respect to a pre-selected template may not give precise results if the selected template deviates significantly from the distribution of images. To cater for more accurate and consistent registration, a novel framework is proposed for groupwise registration with the guidance from one or more intermediate templates determined from the population of images. Specifically, we first use a Euclidean distance, defined as a combinative measure based on the FA map and ADC map, for gauging the similarity of each pair of DTIs. A fully connected graph is then built with each node denoting an image and each edge denoting the distance between a pair of images. The root template image is determined automatically as the image with the overall shortest path length to all other images on the minimum spanning tree (MST) of the graph. Finally, a sequence of registration steps is applied to progressively warping each image towards the root template image with the help of intermediate templates distributed along its path to the root node on the MST. Extensive experimental results using diffusion tensor images of real subjects indicate that registration accuracy and fiber tract alignment are significantly improved, compared with the direct registration from each image to the root template image. PMID:20851197
The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI)

PubMed Central

Makris, Nikos; Gasic, Gregory P.; Garrido, Leoncio

2014-01-01

Measurements of water molecule diffusion along fiber tracts in CNS by diffusion tensor imaging (DTI) provides a static map of neural connections between brain centers, but does not capture the electrical activity along axons for these fiber tracts. Here, a modification of the DTI method is presented to enable the mapping of active fibers. It is termed dynamic diffusion tensor imaging (dDTI) and is based on a hypothesized “anisotropy reduction due to axonal excitation” (“AREX”). The potential changes in water mobility accompanying the movement of ions during the propagation of action potentials along axonal tracts are taken into account. Specifically, the proposed model, termed “ionic DTI model”, was formulated as follows.•First, based on theoretical calculations, we calculated the molecular water flow accompanying the ionic flow perpendicular to the principal axis of fiber tracts produced by electrical conduction along excited myelinated and non-myelinated axons.•Based on the changes in molecular water flow we estimated the signal changes as well as the changes in fractional anisotropy of axonal tracts while performing a functional task.•The variation of fractional anisotropy in axonal tracts could allow mapping the active fiber tracts during a functional task. Although technological advances are necessary to enable the robust and routine measurement of this electrical activity-dependent movement of water molecules perpendicular to axons, the proposed model of dDTI defines the vectorial parameters that will need to be measured to bring this much needed technique to fruition. PMID:25431757
Using Perturbation Theory to Reduce Noise in Diffusion Tensor Fields

PubMed Central

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
Full Tensor Diffusion Imaging Is Not Required To Assess the White-Matter Integrity in Mouse Contusion Spinal Cord Injury

PubMed Central

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
Magnetic resonance neurography and diffusion tensor imaging: origins, history, and clinical impact of the first 50,000 cases with an assessment of efficacy and utility in a prospective 5000-patient study group.

PubMed

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.
A localized Richardson-Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging.

PubMed

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.
4.7-T diffusion tensor imaging of acute traumatic peripheral nerve injury

PubMed Central

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
White Matter Microstructure in Subjects with Attention-Deficit/Hyperactivity Disorder and Their Siblings

ERIC Educational Resources Information Center

Lawrence, Katherine E.; Levitt, Jennifer G.; Loo, Sandra K.; Ly, Ronald; Yee, Victor; O'Neill, Joseph; Alger, Jeffry; Narr, Katherine L.

2013-01-01

Objective: Previous voxel-based and regions-of-interest (ROI)-based diffusion tensor imaging (DTI) studies have found above-normal mean diffusivity (MD) and below-normal fractional anisotropy (FA) in subjects with attention-deficit/hyperactivity disorder (ADHD). However, findings remain mixed, and few studies have examined the contribution of ADHD…
Advances in magnetic resonance neuroimaging techniques in the evaluation of neonatal encephalopathy.

PubMed

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.
Quantification of diffusion tensor imaging in normal white matter maturation of early childhood using an automated processing pipeline.

PubMed

Loh, K B; Ramli, N; Tan, L K; Roziah, M; Rahmat, K; Ariffin, H

2012-07-01

The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.
Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.
Multiple Echo Diffusion Tensor Acquisition Technique (MEDITATE) on a 3T clinical scanner

PubMed Central

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
White Matter Compromise of Callosal and Subcortical Fiber Tracts in Children with Autism Spectrum Disorder: A Diffusion Tensor Imaging Study

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…
Diffusion weighted imaging for the differentiation of breast tumors: From apparent diffusion coefficient to high order diffusion tensor imaging.

PubMed

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.
DWI filtering using joint information for DTI and HARDI.

PubMed

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.
Diffusion tensor imaging and voxel based morphometry study in amyotrophic lateral sclerosis: relationships with motor disability

PubMed Central

Thivard, Lionel; Pradat, Pierre‐François; Lehéricy, Stéphane; Lacomblez, Lucette; Dormont, Didier; Chiras, Jacques; Benali, Habib; Meininger, Vincent

2007-01-01

The aim of this study was to investigate the extent of cortical and subcortical lesions in amyotrophic lateral sclerosis (ALS) using, in combination, voxel based diffusion tensor imaging (DTI) and voxel based morphometry (VBM). We included 15 patients with definite or probable ALS and 25 healthy volunteers. Patients were assessed using the revised ALS Functional Rating Scale (ALSFRS‐R). In patients, reduced fractional anisotropy was found in bilateral corticospinal tracts, the left insula/ventrolateral premotor cortex, the right parietal cortex and the thalamus, which correlated with the ALSFRS‐R. Increased mean diffusivity (MD) was found bilaterally in the motor cortex, the ventrolateral premotor cortex/insula, the hippocampal formations and the right superior temporal gyrus, which did not correlate with the ALSFRS‐R. VBM analysis showed no changes in white matter but widespread volume decreases in grey matter in several regions exhibiting MD abnormalities. In ALS patients, our results show that subcortical lesions extend beyond the corticospinal tract and are clinically relevant. PMID:17635981
Diffusion tensor imaging and voxel based morphometry study in amyotrophic lateral sclerosis: relationships with motor disability.

PubMed

Thivard, Lionel; Pradat, Pierre-François; Lehéricy, Stéphane; Lacomblez, Lucette; Dormont, Didier; Chiras, Jacques; Benali, Habib; Meininger, Vincent

2007-08-01

The aim of this study was to investigate the extent of cortical and subcortical lesions in amyotrophic lateral sclerosis (ALS) using, in combination, voxel based diffusion tensor imaging (DTI) and voxel based morphometry (VBM). We included 15 patients with definite or probable ALS and 25 healthy volunteers. Patients were assessed using the revised ALS Functional Rating Scale (ALSFRS-R). In patients, reduced fractional anisotropy was found in bilateral corticospinal tracts, the left insula/ventrolateral premotor cortex, the right parietal cortex and the thalamus, which correlated with the ALSFRS-R. Increased mean diffusivity (MD) was found bilaterally in the motor cortex, the ventrolateral premotor cortex/insula, the hippocampal formations and the right superior temporal gyrus, which did not correlate with the ALSFRS-R. VBM analysis showed no changes in white matter but widespread volume decreases in grey matter in several regions exhibiting MD abnormalities. In ALS patients, our results show that subcortical lesions extend beyond the corticospinal tract and are clinically relevant.
Diffusion Tensor Imaging of Heterotopia: Changes of Fractional Anisotropy during Radial Migration of Neurons

PubMed Central

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

Diffusion tensor imaging in evaluation of human skeletal muscle injury.

PubMed

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.
Ultrasound elastic tensor imaging: comparison with MR diffusion tensor imaging in the myocardium

NASA Astrophysics Data System (ADS)

Lee, Wei-Ning; Larrat, Benoît; Pernot, Mathieu; Tanter, Mickaël

2012-08-01

We have previously proven the feasibility of ultrasound-based shear wave imaging (SWI) to non-invasively characterize myocardial fiber orientation in both in vitro porcine and in vivo ovine hearts. The SWI-estimated results were in good correlation with histology. In this study, we proposed a new and robust fiber angle estimation method through a tensor-based approach for SWI, coined together as elastic tensor imaging (ETI), and compared it with magnetic resonance diffusion tensor imaging (DTI), a current gold standard and extensively reported non-invasive imaging technique for mapping fiber architecture. Fresh porcine (n = 5) and ovine (n = 5) myocardial samples (20 × 20 × 30 mm3) were studied. ETI was firstly performed to generate shear waves and to acquire the wave events at ultrafast frame rate (8000 fps). A 2.8 MHz phased array probe (pitch = 0.28 mm), connected to a prototype ultrasound scanner, was mounted on a customized MRI-compatible rotation device, which allowed both the rotation of the probe from -90° to 90° at 5° increments and co-registration between two imaging modalities. Transmural shear wave speed at all propagation directions realized was firstly estimated. The fiber angles were determined from the shear wave speed map using the least-squares method and eigen decomposition. The test myocardial sample together with the rotation device was then placed inside a 7T MRI scanner. Diffusion was encoded in six directions. A total of 270 diffusion-weighted images (b = 1000 s mm-2, FOV = 30 mm, matrix size = 60 × 64, TR = 6 s, TE = 19 ms, 24 averages) and 45 B0 images were acquired in 14 h 30 min. The fiber structure was analyzed by the fiber-tracking module in software, MedINRIA. The fiber orientation in the overlapped myocardial region which both ETI and DTI accessed was therefore compared, thanks to the co-registered imaging system. Results from all ten samples showed good correlation (r2 = 0.81, p < 0.0001) and good agreement (3.05° bias) between ETI and DTI fiber angle estimates. The average ETI-estimated fractional anisotropy (FA) values decreased from subendocardium to subepicardium (p < 0.05, unpaired, one-tailed t-test, N = 10) by 33%, whereas the corresponding DTI-estimated FA values presented a change of -10% (p > 0.05, unpaired, one-tailed t-test, N = 10). In conclusion, we have demonstrated that the fiber orientation estimated by ETI, which assesses the shear wave speed (and thus the stiffness), was comparable to that measured by DTI, which evaluates the preferred direction of water diffusion, and have validated this concept within the myocardium. Moreover, ETI was shown capable of mapping the transmural fiber angles with as few as seven shear wave propagation directions.
Abnormal Corpus Callosum Connectivity, Socio-Communicative Deficits, and Motor Deficits in Children with Autism Spectrum Disorder: A Diffusion Tensor Imaging Study

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…
Single-shot spiral imaging enabled by an expanded encoding model: Demonstration in diffusion MRI.

PubMed

Wilm, Bertram J; Barmet, Christoph; Gross, Simon; Kasper, Lars; Vannesjo, S Johanna; Haeberlin, Max; Dietrich, Benjamin E; Brunner, David O; Schmid, Thomas; Pruessmann, Klaas P

2017-01-01

The purpose of this work was to improve the quality of single-shot spiral MRI and demonstrate its application for diffusion-weighted imaging. Image formation is based on an expanded encoding model that accounts for dynamic magnetic fields up to third order in space, nonuniform static B 0 , and coil sensitivity encoding. The encoding model is determined by B 0 mapping, sensitivity mapping, and concurrent field monitoring. Reconstruction is performed by iterative inversion of the expanded signal equations. Diffusion-tensor imaging with single-shot spiral readouts is performed in a phantom and in vivo, using a clinical 3T instrument. Image quality is assessed in terms of artefact levels, image congruence, and the influence of the different encoding factors. Using the full encoding model, diffusion-weighted single-shot spiral imaging of high quality is accomplished both in vitro and in vivo. Accounting for actual field dynamics, including higher orders, is found to be critical to suppress blurring, aliasing, and distortion. Enhanced image congruence permitted data fusion and diffusion tensor analysis without coregistration. Use of an expanded signal model largely overcomes the traditional vulnerability of spiral imaging with long readouts. It renders single-shot spirals competitive with echo-planar readouts and thus deploys shorter echo times and superior readout efficiency for diffusion imaging and further prospective applications. Magn Reson Med 77:83-91, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
White matter tractography using diffusion tensor deflection.

PubMed

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.
Effects of Orientation and Anisometry of Magnetic Resonance Imaging Acquisitions on Diffusion Tensor Imaging and Structural Connectomes.

PubMed

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.
Development of a High Angular Resolution Diffusion Imaging Human Brain Template

PubMed Central

Varentsova, Anna; Zhang, Shengwei; Arfanakis, Konstantinos

2014-01-01

Brain diffusion templates contain rich information about the microstructure of the brain, and are used as references in spatial normalization or in the development of brain atlases. The accuracy of diffusion templates constructed based on the diffusion tensor (DT) model is limited in regions with complex neuronal micro-architecture. High angular resolution diffusion imaging (HARDI) overcomes limitations of the DT model and is capable of resolving intravoxel heterogeneity. However, when HARDI is combined with multiple-shot sequences to minimize image artifacts, the scan time becomes inappropriate for human brain imaging. In this work, an artifact-free HARDI template of the human brain was developed from low angular resolution multiple-shot diffusion data. The resulting HARDI template was produced in ICBM-152 space based on Turboprop diffusion data, was shown to resolve complex neuronal micro-architecture in regions with intravoxel heterogeneity, and contained fiber orientation information consistent with known human brain anatomy. PMID:24440528
Joint eigenvector estimation from mutually anisotropic tensors improves susceptibility tensor imaging of the brain, kidney, and heart.

PubMed

Dibb, Russell; Liu, Chunlei

2017-06-01

To develop a susceptibility-based MRI technique for probing microstructure and fiber architecture of magnetically anisotropic tissues-such as central nervous system white matter, renal tubules, and myocardial fibers-in three dimensions using susceptibility tensor imaging (STI) tools. STI can probe tissue microstructure, but is limited by reconstruction artifacts because of absent phase information outside the tissue and noise. STI accuracy may be improved by estimating a joint eigenvector from mutually anisotropic susceptibility and relaxation tensors. Gradient-recalled echo image data were simulated using a numerical phantom and acquired from the ex vivo mouse brain, kidney, and heart. Susceptibility tensor data were reconstructed using STI, regularized STI, and the proposed algorithm of mutually anisotropic and joint eigenvector STI (MAJESTI). Fiber map and tractography results from each technique were compared with diffusion tensor data. MAJESTI reduced the estimated susceptibility tensor orientation error by 30% in the phantom, 36% in brain white matter, 40% in the inner medulla of the kidney, and 45% in myocardium. This improved the continuity and consistency of susceptibility-based fiber tractography in each tissue. MAJESTI estimation of the susceptibility tensors yields lower orientation errors for susceptibility-based fiber mapping and tractography in the intact brain, kidney, and heart. Magn Reson Med 77:2331-2346, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Microstructural white matter tract alteration in Prader-Willi syndrome: A diffusion tensor imaging study.

PubMed

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.
Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging.

PubMed

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.
Assessment of diffusion tensor imaging indices in calf muscles following postural change from standing to supine position.

PubMed

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.
Whole brain fiber-based comparison (FBC)-A tool for diffusion tensor imaging-based cohort studies.

PubMed

Zimmerman-Moreno, Gali; Ben Bashat, Dafna; Artzi, Moran; Nefussy, Beatrice; Drory, Vivian; Aizenstein, Orna; Greenspan, Hayit

2016-02-01

We present a novel method for fiber-based comparison of diffusion tensor imaging (DTI) scans of groups of subjects. The method entails initial preprocessing and fiber reconstruction by tractography of each brain in its native coordinate system. Several diffusion parameters are sampled along each fiber and used in subsequent comparisons. A spatial correspondence between subjects is established based on geometric similarity between fibers in a template set (several choices for template are explored), and fibers in all other subjects. Diffusion parameters between groups are compared statistically for each template fiber. Results are presented at single fiber resolution. As an initial exploratory step in neurological population studies this method points to the locations affected by the pathology of interest, without requiring a hypothesis. It does not make any grouping assumptions on the fibers and no manual intervention is needed. The framework was applied here to 18 healthy subjects and 23 amyotrophic lateral sclerosis (ALS) patients. The results are compatible with previous findings and with the tract based spatial statistics (TBSS) method. Hum Brain Mapp 37:477-490, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging.

PubMed

Nair, Shalini Rajandran; Tan, Li Kuo; Mohd Ramli, Norlisah; Lim, Shen Yang; Rahmat, Kartini; Mohd Nor, Hazman

2013-06-01

To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD). 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.
An Adaptive Spectrally Weighted Structure Tensor Applied to Tensor Anisotropic Nonlinear Diffusion for Hyperspectral Images

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…
Interpolation of orientation distribution functions in diffusion weighted imaging using multi-tensor model.

PubMed

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.
Improvement of Reliability of Diffusion Tensor Metrics in Thigh Skeletal Muscles.

PubMed

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.
Quantitative assessments of traumatic axonal injury in human brain: concordance of microdialysis and advanced MRI.

PubMed

Magnoni, Sandra; Mac Donald, Christine L; Esparza, Thomas J; Conte, Valeria; Sorrell, James; Macrì, Mario; Bertani, Giulio; Biffi, Riccardo; Costa, Antonella; Sammons, Brian; Snyder, Abraham Z; Shimony, Joshua S; Triulzi, Fabio; Stocchetti, Nino; Brody, David L

2015-08-01

Axonal injury is a major contributor to adverse outcomes following brain trauma. However, the extent of axonal injury cannot currently be assessed reliably in living humans. Here, we used two experimental methods with distinct noise sources and limitations in the same cohort of 15 patients with severe traumatic brain injury to assess axonal injury. One hundred kilodalton cut-off microdialysis catheters were implanted at a median time of 17 h (13-29 h) after injury in normal appearing (on computed tomography scan) frontal white matter in all patients, and samples were collected for at least 72 h. Multiple analytes, such as the metabolic markers glucose, lactate, pyruvate, glutamate and tau and amyloid-β proteins, were measured every 1-2 h in the microdialysis samples. Diffusion tensor magnetic resonance imaging scans at 3 T were performed 2-9 weeks after injury in 11 patients. Stability of diffusion tensor imaging findings was verified by repeat scans 1-3 years later in seven patients. An additional four patients were scanned only at 1-3 years after injury. Imaging abnormalities were assessed based on comparisons with five healthy control subjects for each patient, matched by age and sex (32 controls in total). No safety concerns arose during either microdialysis or scanning. We found that acute microdialysis measurements of the axonal cytoskeletal protein tau in the brain extracellular space correlated well with diffusion tensor magnetic resonance imaging-based measurements of reduced brain white matter integrity in the 1-cm radius white matter-masked region near the microdialysis catheter insertion sites. Specifically, we found a significant inverse correlation between microdialysis measured levels of tau 13-36 h after injury and anisotropy reductions in comparison with healthy controls (Spearman's r = -0.64, P = 0.006). Anisotropy reductions near microdialysis catheter insertion sites were highly correlated with reductions in multiple additional white matter regions. We interpret this result to mean that both microdialysis and diffusion tensor magnetic resonance imaging accurately reflect the same pathophysiological process: traumatic axonal injury. This cross-validation increases confidence in both methods for the clinical assessment of axonal injury. However, neither microdialysis nor diffusion tensor magnetic resonance imaging have been validated versus post-mortem histology in humans. Furthermore, future work will be required to determine the prognostic significance of these assessments of traumatic axonal injury when combined with other clinical and radiological measures. © 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.
Mild traumatic brain injury: is diffusion imaging ready for primetime in forensic medicine?

PubMed

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.
Dimensions of Attention Associated With the Microstructure of Corona Radiata White Matter.

PubMed

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

PubMed Central

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

Minimisation of Signal Intensity Differences in Distortion Correction Approaches of Brain Magnetic Resonance Diffusion Tensor Imaging.

PubMed

Lee, Dong-Hoon; Lee, Do-Wan; Henry, David; Park, Hae-Jin; Han, Bong-Soo; Woo, Dong-Cheol

2018-04-12

To evaluate the effects of signal intensity differences between the b0 image and diffusion tensor imaging (DTI) in the image registration process. To correct signal intensity differences between the b0 image and DTI data, a simple image intensity compensation (SIMIC) method, which is a b0 image re-calculation process from DTI data, was applied before the image registration. The re-calculated b0 image (b0 ext ) from each diffusion direction was registered to the b0 image acquired through the MR scanning (b0 nd ) with two types of cost functions and their transformation matrices were acquired. These transformation matrices were then used to register the DTI data. For quantifications, the dice similarity coefficient (DSC) values, diffusion scalar matrix, and quantified fibre numbers and lengths were calculated. The combined SIMIC method with two cost functions showed the highest DSC value (0.802 ± 0.007). Regarding diffusion scalar values and numbers and lengths of fibres from the corpus callosum, superior longitudinal fasciculus, and cortico-spinal tract, only using normalised cross correlation (NCC) showed a specific tendency toward lower values in the brain regions. Image-based distortion correction with SIMIC for DTI data would help in image analysis by accounting for signal intensity differences as one additional option for DTI analysis. • We evaluated the effects of signal intensity differences at DTI registration. • The non-diffusion-weighted image re-calculation process from DTI data was applied. • SIMIC can minimise the signal intensity differences at DTI registration.
Neonatal Microstructural Development of the Internal Capsule on Diffusion Tensor Imaging Correlates with Severity of Gait and Motor Deficits

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…
Contemporary imaging of mild TBI: the journey toward diffusion tensor imaging to assess neuronal damage.

PubMed

Fox, W Christopher; Park, Min S; Belverud, Shawn; Klugh, Arnett; Rivet, Dennis; Tomlin, Jeffrey M

2013-04-01

To follow the progression of neuroimaging as a means of non-invasive evaluation of mild traumatic brain injury (mTBI) in order to provide recommendations based on reproducible, defined imaging findings. A comprehensive literature review and analysis of contemporary published articles was performed to study the progression of neuroimaging findings as a non-invasive 'biomarker' for mTBI. Multiple imaging modalities exist to support the evaluation of patients with mTBI, including ultrasound (US), computed tomography (CT), single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI). These techniques continue to evolve with the development of fractional anisotropy (FA), fiber tractography (FT), and diffusion tensor imaging (DTI). Modern imaging techniques, when applied in the appropriate clinical setting, may serve as a valuable tool for diagnosis and management of patients with mTBI. An understanding of modern neuroanatomical imaging will enhance our ability to analyse injury and recognize the manifestations of mTBI.
A Bayesian approach to distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging.

PubMed

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.
Innovative anisotropic phantoms for calibration of diffusion tensor imaging sequences.

PubMed

Kłodowski, Krzysztof; Krzyżak, Artur Tadeusz

2016-05-01

The paper describes a novel type of anisotropic phantoms designed for b-matrix spatial distribution diffusion tensor imaging (BSD-DTI). Cubic plate anisotropic phantom, cylinder capillary phantom and water reference phantom are described as a complete set necessary for calibration, validation and normalization of BSD-DTI. An innovative design of the phantoms basing on enclosing the anisotropic cores in glass balls filled with liquid made for the first time possible BSD calibration with usage of echo planar imaging (EPI) sequence. Susceptibility artifacts prone to occur in EPI sequences were visibly reduced in the central region of the phantoms. The phantoms were designed for usage in a clinical scanner's head coil, but can be scaled for other coil or scanner types. The phantoms can be also used for a pre-calibration of imaging of other types of phantoms having more specific applications. Copyright © 2015 Elsevier Inc. All rights reserved.
Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements.

PubMed

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.
Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

PubMed

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.
Investigating Musical Disorders with Diffusion Tensor Imaging: a Comparison of Imaging Parameters

PubMed Central

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
White matter involvement in sporadic Creutzfeldt-Jakob disease

PubMed Central

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
Free-breathing diffusion tensor imaging and tractography of the human heart in healthy volunteers using wavelet-based image fusion.

PubMed

Wei, Hongjiang; Viallon, Magalie; Delattre, Benedicte M A; Moulin, Kevin; Yang, Feng; Croisille, Pierre; Zhu, Yuemin

2015-01-01

Free-breathing cardiac diffusion tensor imaging (DTI) is a promising but challenging technique for the study of fiber structures of the human heart in vivo. This work proposes a clinically compatible and robust technique to provide three-dimensional (3-D) fiber architecture properties of the human heart. To this end, 10 short-axis slices were acquired across the entire heart using a multiple shifted trigger delay (TD) strategy under free breathing conditions. Interscan motion was first corrected automatically using a nonrigid registration method. Then, two post-processing schemes were optimized and compared: an algorithm based on principal component analysis (PCA) filtering and temporal maximum intensity projection (TMIP), and an algorithm that uses the wavelet-based image fusion (WIF) method. The two methods were applied to the registered diffusion-weighted (DW) images to cope with intrascan motion-induced signal loss. The tensor fields were finally calculated, from which fractional anisotropy (FA), mean diffusivity (MD), and 3-D fiber tracts were derived and compared. The results show that the comparison of the FA values (FA(PCATMIP) = 0.45 ±0.10, FA(WIF) = 0.42 ±0.05, P=0.06) showed no significant difference, while the MD values ( MD(PCATMIP)=0.83 ±0.12×10(-3) mm (2)/s, MD(WIF)=0.74±0.05×10(-3) mm (2)/s, P=0.028) were significantly different. Improved helix angle variations through the myocardium wall reflecting the rotation characteristic of cardiac fibers were observed with WIF. This study demonstrates that the combination of multiple shifted TD acquisitions and dedicated post-processing makes it feasible to retrieve in vivo cardiac tractographies from free-breathing DTI acquisitions. The substantial improvements were observed using the WIF method instead of the previously published PCATMIP technique.
DTI and VBM reveal white matter changes without associated gray matter changes in patients with idiopathic restless legs syndrome

PubMed Central

Belke, Marcus; Heverhagen, Johannes T; Keil, Boris; Rosenow, Felix; Oertel, Wolfgang H; Stiasny-Kolster, Karin; Knake, Susanne; Menzler, Katja

2015-01-01

Background and Purpose We evaluated cerebral white and gray matter changes in patients with iRLS in order to shed light on the pathophysiology of this disease. Methods Twelve patients with iRLS were compared to 12 age- and sex-matched controls using whole-head diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) techniques. Evaluation of the DTI scans included the voxelwise analysis of the fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). Results Diffusion tensor imaging revealed areas of altered FA in subcortical white matter bilaterally, mainly in temporal regions as well as in the right internal capsule, the pons, and the right cerebellum. These changes overlapped with changes in RD. Voxel-based morphometry did not reveal any gray matter alterations. Conclusions We showed altered diffusion properties in several white matter regions in patients with iRLS. White matter changes could mainly be attributed to changes in RD, a parameter thought to reflect altered myelination. Areas with altered white matter microstructure included areas in the internal capsule which include the corticospinal tract to the lower limbs, thereby supporting studies that suggest changes in sensorimotor pathways associated with RLS. PMID:26442748
Subcortical pathways serving cortical language sites: initial experience with diffusion tensor imaging fiber tracking combined with intraoperative language mapping.

PubMed

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.
Subcortical pathways serving cortical language sites: initial experience with diffusion tensor imaging fiber tracking combined with intraoperative language mapping

PubMed Central

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
Comparison of Single-Shot Echo-Planar and Line Scan Protocols for Diffusion Tensor Imaging1

PubMed Central

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
Tracking down the footprints of bad paternal relationships in dissociative disorders: A diffusion tensor imaging study.

PubMed

Basmacı Kandemir, Sultan; Bayazıt, Hüseyin; Selek, Salih; Kılıçaslan, Nihat; Kandemir, Hasan; Karababa, İbrahim Fatih; Katı, Mahmut; Çeçe, Hasan

2016-01-01

Preclinical studies indicate that stress early in life can cause long-term alterations in brain development. Studies have shown alterations in the brain functions of patients after experiencing trauma. Our aim is to examine whether the integrity of white matter tracts might be affected in dissociative disorder (DD) patients. A total of 15 DD patients and 15 healthy controls were studied, with the groups matched by age and gender. Diffusion-weighted echoplanar brain images were obtained using a 1.5 Tesla magnetic resonance imaging scanner. Regions of interest were manually placed on directional maps based on principal anisotropy. Apparent diffusion coefficient and fractional anisotropy (FA) values of white matter were measured bilaterally in the anterior corona radiata (ACR) and by diffusion tensor imaging in the genu and splenium of the corpus callosum. Significantly lower FA values were observed in the right ACR of DD patients versus healthy individuals. We also found an association between bad paternal relationships and lower FA in the genu of the corpus callosum in female patients. Alterations in the right ACR suggest that diffusion anisotropy measurement can be used as a quantitative biomarker for DD. Paternal relationships may also affect the brain's microstructure in women with DD.
Development of a high angular resolution diffusion imaging human brain template.

PubMed

Varentsova, Anna; Zhang, Shengwei; Arfanakis, Konstantinos

2014-05-01

Brain diffusion templates contain rich information about the microstructure of the brain, and are used as references in spatial normalization or in the development of brain atlases. The accuracy of diffusion templates constructed based on the diffusion tensor (DT) model is limited in regions with complex neuronal micro-architecture. High angular resolution diffusion imaging (HARDI) overcomes limitations of the DT model and is capable of resolving intravoxel heterogeneity. However, when HARDI is combined with multiple-shot sequences to minimize image artifacts, the scan time becomes inappropriate for human brain imaging. In this work, an artifact-free HARDI template of the human brain was developed from low angular resolution multiple-shot diffusion data. The resulting HARDI template was produced in ICBM-152 space based on Turboprop diffusion data, was shown to resolve complex neuronal micro-architecture in regions with intravoxel heterogeneity, and contained fiber orientation information consistent with known human brain anatomy. Copyright © 2014 Elsevier Inc. All rights reserved.
Correlations of diffusion tensor imaging values and symptom scores in patients with schizophrenia.

PubMed

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.
Diffusion-weighted imaging and diffusion tensor imaging of asymptomatic lumbar disc herniation.

PubMed

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.
Analysis and correction of gradient nonlinearity bias in ADC measurements

PubMed Central

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
Advanced Magnetic Resonance Imaging techniques to probe muscle structure and function

NASA Astrophysics Data System (ADS)

Malis, Vadim

Structural and functional Magnetic Resonance Imaging (MRI) studies of skeletal muscle allow the elucidation of muscle physiology under normal and pathological conditions. Continuing on the efforts of the Muscle Imaging and Modeling laboratory, the focus of the thesis is to (i) extend and refine two challenging imaging modalities: structural imaging using Diffusion Tensor Imaging (DTI) and functional imaging based on Velocity Encoded Phase Contrast Imaging (VE-PC) and (ii) apply these methods to explore age related structure and functional differences of the gastrocnemius muscle. Diffusion Tensor Imaging allows the study of tissue microstructure as well as muscle fiber architecture. The images, based on an ultrafast single shot Echo Planar Imaging (EPI) sequence, suffer from geometric distortions and low signal to noise ratio. A processing pipeline was developed to correct for distortions and to improve image Signal to Noise Ratio (SNR). DTI acquired on a senior and young cohort of subjects were processed through the pipeline and differences in DTI derived indices and fiber architecture between the two cohorts were explored. The DTI indices indicated that at the microstructural level, fiber atrophy was accompanied with a reduction in fiber volume fraction. At the fiber architecture level, fiber length and pennation angles decreased with age that potentially contribute to the loss of muscle force with age. Velocity Encoded Phase Contrast imaging provides tissue (e.g. muscle) velocity at each voxel which allows the study of strain and Strain Rate (SR) under dynamic conditions. The focus of the thesis was to extract 2D strain rate tensor maps from the velocity images and apply the method to study age related differences. The tensor mapping can potentially provide unique information on the extracellular matrix and lateral transmission the role of these two elements has recently emerged as important determinants of force loss with age. In the cross sectional study on aging, strain rate during isometric contraction was significantly reduced in the seniors; presumably from decrease in muscle slack and increase in stiffness with age. Other parameters of interest from this study that allow inferences on the ECM and lateral transmission are the asymmetry of deformation in the fiber cross section as well as the angle between the SR and muscle fiber. The last part of thesis, which is a 'work-in-progress', is the extension to 3D SR tensor mapping using a 3D spatial, 3D velocity encoded imaging sequence. This is combined with Diffusion Tensor Imaging to obtain the lead eigenvector (muscle fiber direction) at each voxel. The 3D SR is then rotated to the basis of the DTI to obtain a 'Fiber Aligned Strain rate: FASR'. The off diagonal elements of FASR are shear strain terms. Detailed analysis of the shear strain will provide a unique non-invasive method to probe lateral transmission.

Quantifying the ultrastructure of carotid arteries using high-resolution micro-diffusion tensor imaging—comparison of intact versus open cut tissue

NASA Astrophysics Data System (ADS)

Salman Shahid, Syed; Gaul, Robert T.; Kerskens, Christian; Flamini, Vittoria; Lally, Caitríona

2017-12-01

Diffusion magnetic resonance imaging (dMRI) can provide insights into the microstructure of intact arterial tissue. The current study employed high magnetic field MRI to obtain ultra-high resolution dMRI at an isotropic voxel resolution of 117 µm3 in less than 2 h of scan time. A parameter selective single shell (128 directions) diffusion-encoding scheme based on Stejskel-Tanner sequence with echo-planar imaging (EPI) readout was used. EPI segmentation was used to reduce the echo time (TE) and to minimise the susceptibility-induced artefacts. The study utilised the dMRI analysis with diffusion tensor imaging (DTI) framework to investigate structural heterogeneity in intact arterial tissue and to quantify variations in tissue composition when the tissue is cut open and flattened. For intact arterial samples, the region of interest base comparison showed significant differences in fractional anisotropy and mean diffusivity across the media layer (p < 0.05). For open cut flat samples, DTI based directionally invariant indices did not show significant differences across the media layer. For intact samples, fibre tractography based indices such as calculated helical angle and fibre dispersion showed near circumferential alignment and a high degree of fibre dispersion, respectively. This study demonstrates the feasibility of fast dMRI acquisition with ultra-high spatial and angular resolution at 7 T. Using the optimised sequence parameters, this study shows that DTI based markers are sensitive to local structural changes in intact arterial tissue samples and these markers may have clinical relevance in the diagnosis of atherosclerosis and aneurysm.
White Matter Microstructure in Transsexuals and Controls Investigated by Diffusion Tensor Imaging

PubMed Central

Kranz, Georg S.; Hahn, Andreas; Kaufmann, Ulrike; Küblböck, Martin; Hummer, Allan; Ganger, Sebastian; Seiger, Rene; Winkler, Dietmar; Swaab, Dick F.; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-01-01

Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects’ sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development. PMID:25392513
Reconstruction of the arcuate fasciculus for surgical planning in the setting of peritumoral edema using two-tensor unscented Kalman filter tractography.

PubMed

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.
Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder.

PubMed

Landin-Romero, Ramón; Canales-Rodríguez, Erick J; Kumfor, Fiona; Moreno-Alcázar, Ana; Madre, Mercè; Maristany, Teresa; Pomarol-Clotet, Edith; Amann, Benedikt L

2017-01-01

The profile of grey matter abnormalities and related white-matter pathology in schizoaffective disorder has only been studied to a limited extent. The aim of this study was to identify grey- and white-matter abnormalities in patients with schizoaffective disorder using complementary structural imaging techniques. Forty-five patients meeting Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition criteria and Research Diagnostic Criteria for schizoaffective disorder and 45 matched healthy controls underwent structural-T1 and diffusion magnetic resonance imaging to enable surface-based brain morphometry and diffusion tensor imaging analyses. Analyses were conducted to determine group differences in cortical volume, cortical thickness and surface area, as well as in fractional anisotropy and mean diffusivity. At a threshold of p = 0.05 corrected, all measures revealed significant differences between patients and controls at the group level. Spatial overlap of abnormalities was observed across the various structural neuroimaging measures. In grey matter, patients with schizoaffective disorder showed abnormalities in the frontal and temporal lobes, striatum, fusiform, cuneus, precuneus, lingual and limbic regions. White-matter abnormalities were identified in tracts connecting these areas, including the corpus callosum, superior and inferior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus and cingulum bundle. The spatial overlap of abnormalities across the different imaging techniques suggests widespread and consistent brain pathology in schizoaffective disorder. The abnormalities were mainly detected in areas that have commonly been reported to be abnormal in schizophrenia, and to some extent in bipolar disorder, which may explain the clinical and aetiological overlap in these disorders.
Corticospinal tract asymmetry and handedness in right- and left-handers by diffusion tensor tractography.

PubMed

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).
Diffusion tensor imaging of the sural nerve in normal controls☆

PubMed Central

Kim, Boklye; Srinivasan, Ashok; Sabb, Brian; Feldman, Eva L; Pop-Busui, Rodica

2016-01-01

Objective To develop a diffusion tensor imaging (DTI) protocol for assessing the sural nerve in healthy subjects. Methods Sural nerves in 25 controls were imaged using DTI at 3 T with 6, 15, and 32 gradient directions. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were computed from nerve regions of interest co-registered with T2-weighted images. Results Coronal images with 0.5(RL)×2.0(FH)×0.5(AP) mm3 resolution successfully localized the sural nerve. FA maps showed less variability with 32 directions (0.559±0.071) compared to 15(0.590±0.080) and 6(0.659±0.109). Conclusions Our DTI protocol was effective in imaging sural nerves in controls to establish normative FA/ADC, with potential to be used non-invasively in diseased nerves of patients. PMID:24908367
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.
Using Perturbation Theory to Compute the Morphological Similarity of Diffusion Tensors

PubMed Central

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
White matter changes in preclinical Alzheimer's disease: a magnetic resonance imaging-diffusion tensor imaging study on cognitively normal older people with positive amyloid β protein 42 levels.

PubMed

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.
Mid-callosal plane determination using preferred directions from diffusion tensor images

NASA Astrophysics Data System (ADS)

Costa, André L.; Rittner, Letícia; Lotufo, Roberto A.; Appenzeller, Simone

2015-03-01

The corpus callosum is the major brain structure responsible for inter{hemispheric communication between neurons. Many studies seek to relate corpus callosum attributes to patient characteristics, cerebral diseases and psychological disorders. Most of those studies rely on 2D analysis of the corpus callosum in the mid-sagittal plane. However, it is common to find conflicting results among studies, once many ignore methodological issues and define the mid-sagittal plane based on precary or invalid criteria with respect to the corpus callosum. In this work we propose a novel method to determine the mid-callosal plane using the corpus callosum internal preferred diffusion directions obtained from diffusion tensor images. This plane is analogous to the mid-sagittal plane, but intended to serve exclusively as the corpus callosum reference. Our method elucidates the great potential the directional information of the corpus callosum fibers have to indicate its own referential. Results from experiments with five image pairs from distinct subjects, obtained under the same conditions, demonstrate the method effectiveness to find the corpus callosum symmetric axis relative to the axial plane.
High-grade glioma diffusive modeling using statistical tissue information and diffusion tensors extracted from atlases.

PubMed

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
Information geometry and its application to theoretical statistics and diffusion tensor magnetic resonance imaging

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.
Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments.

PubMed

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.
Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments*

PubMed Central

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
Symmetric Positive 4th Order Tensors & Their Estimation from Diffusion Weighted MRI⋆

PubMed Central

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
Using tensor-based morphometry to detect structural brain abnormalities in rats with adolescent intermittent alcohol exposure

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.
T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model.

PubMed

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.
Quantitative analysis of diffusion tensor imaging data in serial assessment of Krabbe disease.

PubMed

Provenzale, James M; Escolar, Maria; Kurtzberg, Joanne

2005-12-01

Krabbe disease is a rare autosomal recessive pediatric white matter (WM) disorder that is due to deficiency of a specific enzyme, beta-galactocerebrosidase. This report reviews our experience with use of diffusion tensor imaging (DTI) in serial assessment of WM changes in Krabbe disease following stem cell transplantation. DTI appears to be a sensitive means to monitor effects of stem cell transplantation on WM development in Krabbe disease. The group of early transplantation infants was clearly distinguishable from the group of late transplantation infants based on anisotropy measurements. Good correlation also was seen between neurodevelopmental scores and anisotropy measurements. The work described here in Krabbe disease may serve as a model for application of DTI to other therapies in various WM disorders such as multiple sclerosis and dysmyelinating disorders of childhood.
[Application of diffusion tensor imaging fractography in minimally invasive surgery of brain tumors].

PubMed

Yang, Lei; Zhang, Mao-zhi; Zhang, Wei; Zhao, Yuan-li; Zhao, Ji-zong

2006-05-23

To investigate the effects and prospect of application of diffusion tensor imaging (DTI) fractography in minimally invasive surgery of brain tumors. DTI fractography was performed in 52 patients with malignant brain tumors. Based on the DTI fractography results, 34 of the 52 patients underwent operation under neuro-navigation, and 18 of the 52 patients underwent operation routine minimally invasive craniotomy and tumor resection without neuro-navigation. The rate of total tumor resection was 86.5% (45/52). The mortality was 1.9% (1/52). The disability rate was 11.5% (6/52). No case needed the second operation. DTI fractography has raised the minimally invasive neurosurgery to the level of protecting the nuclei and nerve tracts and guiding intra-operative management of infiltration of deep-seated tumors, especially when combined with neuro-navigation and interventional MRI.
White matter integrity in Asperger syndrome: a preliminary diffusion tensor magnetic resonance imaging study in adults.

PubMed

Bloemen, Oswald J N; Deeley, Quinton; Sundram, Fred; Daly, Eileen M; Barker, Gareth J; Jones, Derek K; van Amelsvoort, Therese A M J; Schmitz, Nicole; Robertson, Dene; Murphy, Kieran C; Murphy, Declan G M

2010-10-01

Autistic Spectrum Disorder (ASD), including Asperger syndrome and autism, is a highly genetic neurodevelopmental disorder. There is a consensus that ASD has a biological basis, and it has been proposed that it is a "connectivity" disorder. Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) allows measurement of the microstructural integrity of white matter (a proxy measure of "connectivity"). However, nobody has investigated the microstructural integrity of whole brain white matter in people with Asperger syndrome. We measured the fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) of white matter, using DT-MRI, in 13 adults with Asperger syndrome and 13 controls. The groups did not differ significantly in overall intelligence and age. FA, MD and RD were assessed using whole brain voxel-based techniques. Adults with Asperger syndrome had a significantly lower FA than controls in 13 clusters. These were largely bilateral and included white matter in the internal capsule, frontal, temporal, parietal and occipital lobes, cingulum and corpus callosum. Adults with Asperger syndrome have widespread significant differences from controls in white matter microstructural integrity.

White matter integrity in dementia with Lewy bodies: A Voxel-Based Analysis of Diffusion Tensor Imaging

PubMed Central

Nedelska, Zuzana; Schwarz, Christopher G.; Boeve, Bradley F.; Lowe, Val; Reid, Robert I.; Przybelski, Scott A.; Lesnick, Timothy G.; Gunter, Jeffrey L.; Senjem, Matthew L.; Ferman, Tanis J.; Smith, Glenn E.; Geda, Yonas E.; Knopman, David S.; Petersen, Ronald C.; Jack, Clifford R.; Kantarci, Kejal

2015-01-01

Many patients with dementia with Lewy bodies have overlapping Alzheimer's disease (AD)–related pathology, which may contribute to white matter (WM) diffusivity alterations on diffusion tensor imaging (DTI). Consecutive patients with DLB (n=30), age and sex matched AD patients (n=30), and cognitively normal controls (CN; n=60) were recruited. All subjects underwent DTI, 18F 2-fluoro-deoxy-d-glucose (FDG) and 11C Pittsburgh compound B (PiB) PET scans. DLB patients had reduced fractional anisotropy (FA) in the parieto-occipital WM but not elsewhere compared to CN, and elevated FA in parahippocampal WM compared to AD patients, which persisted after controlling for Aβ load in DLB. The pattern of WM FA alterations on DTI was consistent with the more diffuse posterior parietal and occipital glucose hypometabolism of FDG PET in the cortex. DLB is characterized by a loss of parieto-occipital WM integrity, independent of concomitant AD-related Aβ load. Cortical glucose hypometabolism accompanies WM FA alterations with a concordant pattern of gray and white matter involvement in the parieto-occipital lobes in DLB. PMID:25863527
Diffusion tensor eigenvector directional color imaging patterns in the evaluation of cerebral white matter tracts altered by tumor.

PubMed

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.
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.
Compromised Integrity of Central Visual Pathways in Patients With Macular Degeneration.

PubMed

Malania, Maka; Konrad, Julia; Jägle, Herbert; Werner, John S; Greenlee, Mark W

2017-06-01

Macular degeneration (MD) affects the central retina and leads to gradual loss of foveal vision. Although, photoreceptors are primarily affected in MD, the retinal nerve fiber layer (RNFL) and central visual pathways may also be altered subsequent to photoreceptor degeneration. Here we investigate whether retinal damage caused by MD alters microstructural properties of visual pathways using diffusion-weighted magnetic resonance imaging. Six MD patients and six healthy control subjects participated in the study. Retinal images were obtained by spectral-domain optical coherence tomography (SD-OCT). Diffusion tensor images (DTI) and high-resolution T1-weighted structural images were collected for each subject. We used diffusion-based tensor modeling and probabilistic fiber tractography to identify the optic tract (OT) and optic radiations (OR), as well as nonvisual pathways (corticospinal tract and anterior fibers of corpus callosum). Fractional anisotropy (FA) and axial and radial diffusivity values (AD, RD) were calculated along the nonvisual and visual pathways. Measurement of RNFL thickness reveals that the temporal circumpapillary retinal nerve fiber layer was significantly thinner in eyes with macular degeneration than normal. While we did not find significant differences in diffusion properties in nonvisual pathways, patients showed significant changes in diffusion scalars (FA, RD, and AD) both in OT and OR. The results indicate that the RNFL and the white matter of the visual pathways are significantly altered in MD patients. Damage to the photoreceptors in MD leads to atrophy of the ganglion cell axons and to corresponding changes in microstructural properties of central visual pathways.
A prospective microstructure imaging study in mixed-martial artists using geometric measures and diffusion tensor imaging: methods and findings

PubMed Central

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
A prospective microstructure imaging study in mixed-martial artists using geometric measures and diffusion tensor imaging: methods and findings.

PubMed

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.
Diffusion tensor imaging of hemispheric asymmetries in the developing brain.

PubMed

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.
Diffusive sensitivity to muscle architecture: a magnetic resonance diffusion tensor imaging study of the human calf.

PubMed

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.
Intensity ratio to improve black hole assessment in multiple sclerosis.

PubMed

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.
Detection of prostate cancer in peripheral zone: comparison of MR diffusion tensor imaging, quantitative dynamic contrast-enhanced MRI, and the two techniques combined at 3.0 T.

PubMed

Li, Chunmei; Chen, Min; Li, Saying; Zhao, Xuna; Zhang, Chen; Luo, Xiaojie; Zhou, Cheng

2014-03-01

Previous studies have shown that the diagnostic accuracy for prostate cancer improved with diffusion tensor imaging (DTI) or quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) only. However, the efficacy of combined DTI and quantitative DCE-MRI in detecting prostate cancer at 3.0 T is still indeterminate. To investigate the utility of diffusion tensor imaging (DTI), quantitative DCE-MRI, and the two techniques combined at 3.0 T in detecting prostate cancer of the peripheral zone (PZ). DTI and DCE-MRI of 33 patients was acquired prior to prostate biopsy. Regions of interest (ROIs) were drawn according to biopsy zones which were apex, mid-gland, and base on each side of the PZ. Apparent diffusion coefficient (ADC), fractional anisotropy (FA), volume transfer constant (K(trans)), and rate constant (kep) values of cancerous sextants and non-cancerous sextants in PZ were calculated. Logistic regression models were generated for DTI, DCE-MRI, and DTI + DCE-MRI. Receiver-operating characteristic (ROC) curves were used to compare the ability of these models to differentiate cancerous sextants from non-cancerous sextants of PZ. There were significant differences in the ADC, FA, K(trans), and kep values between cancerous sextants and non-cancerous sextants in PZ (P < 0.0001, P < 0.0001, P < 0.0001, and P < 0.0001, respectively). The area under curve (AUC) for DTI + DCE-MRI was significantly greater than that for either DTI (0.93 vs. 0.86, P = 0.0017) or DCE-MRI (0.93 vs. 0.84, P = 0.0034) alone. The combination of DTI and quantitative DCE-MRI has better diagnostic performance in detecting prostate cancer of the PZ than either technique alone.
Brain tissue segmentation based on DTI data

PubMed Central

Liu, Tianming; Li, Hai; Wong, Kelvin; Tarokh, Ashley; Guo, Lei; Wong, Stephen T.C.

2008-01-01

We present a method for automated brain tissue segmentation based on the multi-channel fusion of diffusion tensor imaging (DTI) data. The method is motivated by the evidence that independent tissue segmentation based on DTI parametric images provides complementary information of tissue contrast to the tissue segmentation based on structural MRI data. This has important applications in defining accurate tissue maps when fusing structural data with diffusion data. In the absence of structural data, tissue segmentation based on DTI data provides an alternative means to obtain brain tissue segmentation. Our approach to the tissue segmentation based on DTI data is to classify the brain into two compartments by utilizing the tissue contrast existing in a single channel. Specifically, because the apparent diffusion coefficient (ADC) values in the cerebrospinal fluid (CSF) are more than twice that of gray matter (GM) and white matter (WM), we use ADC images to distinguish CSF and non-CSF tissues. Additionally, fractional anisotropy (FA) images are used to separate WM from non-WM tissues, as highly directional white matter structures have much larger fractional anisotropy values. Moreover, other channels to separate tissue are explored, such as eigenvalues of the tensor, relative anisotropy (RA), and volume ratio (VR). We developed an approach based on the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm that combines these two-class maps to obtain a complete tissue segmentation map of CSF, GM, and WM. Evaluations are provided to demonstrate the performance of our approach. Experimental results of applying this approach to brain tissue segmentation and deformable registration of DTI data and spoiled gradient-echo (SPGR) data are also provided. PMID:17804258
Various diffusion magnetic resonance imaging techniques for pancreatic cancer

PubMed Central

Tang, Meng-Yue; Zhang, Xiao-Ming; Chen, Tian-Wu; Huang, Xiao-Hua

2015-01-01

Pancreatic cancer is one of the most common malignant tumors and remains a treatment-refractory cancer with a poor prognosis. Currently, the diagnosis of pancreatic neoplasm depends mainly on imaging and which methods are conducive to detecting small lesions. Compared to the other techniques, magnetic resonance imaging (MRI) has irreplaceable advantages and can provide valuable information unattainable with other noninvasive or minimally invasive imaging techniques. Advances in MR hardware and pulse sequence design have particularly improved the quality and robustness of MRI of the pancreas. Diffusion MR imaging serves as one of the common functional MRI techniques and is the only technique that can be used to reflect the diffusion movement of water molecules in vivo. It is generally known that diffusion properties depend on the characterization of intrinsic features of tissue microdynamics and microstructure. With the improvement of the diffusion models, diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique to the more complex. In this review, the various diffusion MRI techniques for pancreatic cancer are discussed, including conventional diffusion weighted imaging (DWI), multi-b DWI based on intra-voxel incoherent motion theory, diffusion tensor imaging and diffusion kurtosis imaging. The principles, main parameters, advantages and limitations of these techniques, as well as future directions for pancreatic diffusion imaging are also discussed. PMID:26753059
relationship between diffusion tensor imaging findings and cognitive outcomes following adult traumatic brain injury: A meta-analysis.

PubMed

Wallace, E J; Mathias, J L; Ward, L

2018-05-24

Cognitive impairments are common following a traumatic brain injury (TBI) and frequently result from white matter (WM) damage. This damage can be quantified using diffusion tensor imaging (DTI), which measures the directionality (fractional anisotropy: FA) and amount (mean diffusivity/apparent diffusion coefficient: MD/ADC) of water diffusion in WM, with high FA and low MD/ADC thought to indicate greater WM integrity. However, the relationship between DTI and cognitive outcomes is currently unclear. The data from 20 studies that examined the relationship between WM integrity (measured using DTI) and cognition (categorised into seven domains) following mild-severe adult TBI were meta-analysed. Overall, high FA and low MD/ADC in most brain regions was associated with better cognitive performance, with memory and attention most strongly related to DTI findings. Specifically, memory and/or attention were very strongly related to DTI findings in the corpus callosum, fornix, internal capsule, arcuate and uncinate fasciculi. However, most findings were based on single studies and therefore await replication. Larger-scale, longitudinal studies are now needed to determine the predictive utility of DTI. Copyright © 2018. Published by Elsevier Ltd.
Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm.

PubMed

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.
Potential long-term effects of MDMA on the basal ganglia-thalamocortical circuit: a proton MR spectroscopy and diffusion-tensor imaging study.

PubMed

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.
The role of diffusion tensor imaging and fractional anisotropy in the evaluation of patients with idiopathic normal pressure hydrocephalus: a literature review.

PubMed

Siasios, Ioannis; Kapsalaki, Eftychia Z; Fountas, Kostas N; Fotiadou, Aggeliki; Dorsch, Alexander; Vakharia, Kunal; Pollina, John; Dimopoulos, Vassilios

2016-09-01

OBJECTIVE Diffusion tensor imaging (DTI) for the assessment of fractional anisotropy (FA) and involving measurements of mean diffusivity (MD) and apparent diffusion coefficient (ADC) represents a novel, MRI-based, noninvasive technique that may delineate microstructural changes in cerebral white matter (WM). For example, DTI may be used for the diagnosis and differentiation of idiopathic normal pressure hydrocephalus (iNPH) from other neurodegenerative diseases with similar imaging findings and clinical symptoms and signs. The goal of the current study was to identify and analyze recently published series on the use of DTI as a diagnostic tool. Moreover, the authors also explored the utility of DTI in identifying patients with iNPH who could be managed by surgical intervention. METHODS The authors performed a literature search of the PubMed database by using any possible combinations of the following terms: "Alzheimer's disease," "brain," "cerebrospinal fluid," "CSF," "diffusion tensor imaging," "DTI," "hydrocephalus," "idiopathic," "magnetic resonance imaging," "normal pressure," "Parkinson's disease," and "shunting." Moreover, all reference lists from the retrieved articles were reviewed to identify any additional pertinent articles. RESULTS The literature search retrieved 19 studies in which DTI was used for the identification and differentiation of iNPH from other neurodegenerative diseases. The DTI protocols involved different approaches, such as region of interest (ROI) methods, tract-based spatial statistics, voxel-based analysis, and delta-ADC analysis. The most studied anatomical regions were the periventricular WM areas, such as the internal capsule (IC), the corticospinal tract (CST), and the corpus callosum (CC). Patients with iNPH had significantly higher MD in the periventricular WM areas of the CST and the CC than had healthy controls. In addition, FA and ADCs were significantly higher in the CST of iNPH patients than in any other patients with other neurodegenerative diseases. Gait abnormalities of iNPH patients were statistically significantly and negatively correlated with FA in the CST and the minor forceps. Fractional anisotropy had a sensitivity of 94% and a specificity of 80% for diagnosing iNPH. Furthermore, FA and MD values in the CST, the IC, the anterior thalamic region, the fornix, and the hippocampus regions could help differentiate iNPH from Alzheimer or Parkinson disease. Interestingly, CSF drainage or ventriculoperitoneal shunting significantly modified FA and ADCs in iNPH patients whose condition clinically responded to these maneuvers. CONCLUSIONS Measurements of FA and MD significantly contribute to the detection of axonal loss and gliosis in the periventricular WM areas in patients with iNPH. Diffusion tensor imaging may also represent a valuable noninvasive method for differentiating iNPH from other neurodegenerative diseases. Moreover, DTI can detect dynamic changes in the WM tracts after lumbar drainage or shunting procedures and could help identify iNPH patients who may benefit from surgical intervention.
White matter microstructure in transsexuals and controls investigated by diffusion tensor imaging.

PubMed

Kranz, Georg S; Hahn, Andreas; Kaufmann, Ulrike; Küblböck, Martin; Hummer, Allan; Ganger, Sebastian; Seiger, Rene; Winkler, Dietmar; Swaab, Dick F; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2014-11-12

Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects' sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development. Copyright © 2014 the authors 0270-6474/14/3415466-10$15.00/0.
In Silico Neuro-Oncology: Brownian Motion-Based Mathematical Treatment as a Potential Platform for Modeling the Infiltration of Glioma Cells into Normal Brain Tissue.

PubMed

Antonopoulos, Markos; Stamatakos, Georgios

2015-01-01

Intensive glioma tumor infiltration into the surrounding normal brain tissues is one of the most critical causes of glioma treatment failure. To quantitatively understand and mathematically simulate this phenomenon, several diffusion-based mathematical models have appeared in the literature. The majority of them ignore the anisotropic character of diffusion of glioma cells since availability of pertinent truly exploitable tomographic imaging data is limited. Aiming at enriching the anisotropy-enhanced glioma model weaponry so as to increase the potential of exploiting available tomographic imaging data, we propose a Brownian motion-based mathematical analysis that could serve as the basis for a simulation model estimating the infiltration of glioblastoma cells into the surrounding brain tissue. The analysis is based on clinical observations and exploits diffusion tensor imaging (DTI) data. Numerical simulations and suggestions for further elaboration are provided.
Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

PubMed Central

Tang, Xiaoying; Yoshida, Shoko; Hsu, John; Huisman, Thierry A. G. M.; Faria, Andreia V.; Oishi, Kenichi; Kutten, Kwame; Poretti, Andrea; Li, Yue; Miller, Michael I.; Mori, Susumu

2014-01-01

In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs). This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases. DTI images are modeled as high dimensional fields, with each voxel exhibiting a vector valued feature comprising of mean diffusivity (MD), fractional anisotropy (FA), and fiber angle. For each structure, the probability distribution of each element in the feature vector is modeled as a mixture of Gaussians, the parameters of which are estimated from the labeled atlases. The structure-specific feature vector is then used to parcellate the test image. For each atlas, a likelihood is iteratively computed based on the structure-specific vector feature. The likelihoods from multiple atlases are then fused. The updating and fusing of the likelihoods is achieved based on the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation problems. We first demonstrate the performance of the algorithm by examining the parcellation accuracy of 18 structures from 25 subjects with a varying degree of structural abnormality. Dice values ranging 0.8–0.9 were obtained. In addition, strong correlation was found between the volume size of the automated and the manual parcellation. Then, we present scan-rescan reproducibility based on another dataset of 16 DTI images – an average of 3.73%, 1.91%, and 1.79% for volume, mean FA, and mean MD respectively. Finally, the range of anatomical variability in the normal population was quantified for each structure. PMID:24809486
Evaluation of non-Gaussian diffusion in cardiac MRI.

PubMed

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.

Diffusion tensor imaging (DTI) findings in adult civilian, military, and sport-related mild traumatic brain injury (mTBI): a systematic critical review.

PubMed

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.
On the use of water phantom images to calibrate and correct eddy current induced artefacts in MR diffusion tensor imaging.

PubMed

Bastin, M E; Armitage, P A

2000-07-01

The accurate determination of absolute measures of diffusion anisotropy in vivo using single-shot, echo-planar imaging techniques requires the acquisition of a set of high signal-to-noise ratio, diffusion-weighted images that are free from eddy current induced image distortions. Such geometric distortions can be characterized and corrected in brain imaging data using magnification (M), translation (T), and shear (S) distortion parameters derived from separate water phantom calibration experiments. Here we examine the practicalities of using separate phantom calibration data to correct high b-value diffusion tensor imaging data by investigating the stability of these distortion parameters, and hence the eddy currents, with time. It is found that M, T, and S vary only slowly with time (i.e., on the order of weeks), so that calibration scans need not be performed after every patient examination. This not only minimises the scan time required to collect the calibration data, but also the computational time needed to characterize these eddy current induced distortions. Examples of how measurements of diffusion anisotropy are improved using this post-processing scheme are also presented.
The relationship between functional magnetic resonance imaging activation, diffusion tensor imaging, and training effects.

PubMed

Farrar, Danielle; Budson, Andrew E

2017-04-01

While the relationship between diffusion tensor imaging (DTI) measurements and training effects is explored by Voelker et al. (this issue), a cursory discussion of functional magnetic resonance imaging (fMRI) measurements categorizes increased activation with findings of greater white matter integrity. Evidence of the relationship between fMRI activation and white matter integrity is conflicting, as is the relationship between fMRI activation and training effects. An examination of the changes in fMRI activation in response to training is helpful, but the relationship between DTI and fMRI activation, particularly in the context of white matter changes, must be examined further before general conclusions can be drawn.
Identification of ghost artifact using texture analysis in pediatric spinal cord diffusion tensor images.

PubMed

Alizadeh, Mahdi; Conklin, Chris J; Middleton, Devon M; Shah, Pallav; Saksena, Sona; Krisa, Laura; Finsterbusch, Jürgen; Faro, Scott H; Mulcahey, M J; Mohamed, Feroze B

2018-04-01

Ghost artifacts are a major contributor to degradation of spinal cord diffusion tensor images. A multi-stage post-processing pipeline was designed, implemented and validated to automatically remove ghost artifacts arising from reduced field of view diffusion tensor imaging (DTI) of the pediatric spinal cord. A total of 12 pediatric subjects including 7 healthy subjects (mean age=11.34years) with no evidence of spinal cord injury or pathology and 5 patients (mean age=10.96years) with cervical spinal cord injury were studied. Ghost/true cords, labeled as region of interests (ROIs), in non-diffusion weighted b0 images were segmented automatically using mathematical morphological processing. Initially, 21 texture features were extracted from each segmented ROI including 5 first-order features based on the histogram of the image (mean, variance, skewness, kurtosis and entropy) and 16s-order feature vector elements, incorporating four statistical measures (contrast, correlation, homogeneity and energy) calculated from co-occurrence matrices in directions of 0°, 45°, 90° and 135°. Next, ten features with a high value of mutual information (MI) relative to the pre-defined target class and within the features were selected as final features which were input to a trained classifier (adaptive neuro-fuzzy interface system) to separate the true cord from the ghost cord. The implemented pipeline was successfully able to separate the ghost artifacts from true cord structures. The results obtained from the classifier showed a sensitivity of 91%, specificity of 79%, and accuracy of 84% in separating the true cord from ghost artifacts. The results show that the proposed method is promising for the automatic detection of ghost cords present in DTI images of the spinal cord. This step is crucial towards development of accurate, automatic DTI spinal cord post processing pipelines. Copyright © 2017 Elsevier Inc. All rights reserved.
Diffusion tensor imaging of cingulum bundle and corpus callosum in schizophrenia vs. bipolar disorder.

PubMed

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.
Tissue signature characterisation of diffusion tensor abnormalities in cerebral gliomas.

PubMed

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
White matter tractography by means of Turboprop diffusion tensor imaging.

PubMed

Arfanakis, Konstantinos; Gui, Minzhi; Lazar, Mariana

2005-12-01

White matter fiber-tractography by means of diffusion tensor imaging (DTI) is a noninvasive technique that provides estimates of the structural connectivity of the brain. However, conventional fiber-tracking methods using DTI are based on echo-planar image acquisitions (EPI), which suffer from image distortions and artifacts due to magnetic susceptibility variations and eddy currents. Thus, a large percentage of white matter fiber bundles that are mapped using EPI-based DTI data are distorted, and/or terminated early, while others are completely undetected. This severely limits the potential of fiber-tracking techniques. In contrast, Turboprop imaging is a multiple-shot gradient and spin-echo (GRASE) technique that provides images with significantly fewer susceptibility and eddy current-related artifacts than EPI. The purpose of this work was to evaluate the performance of fiber-tractography techniques when using data obtained with Turboprop-DTI. All fiber pathways that were mapped were found to be in agreement with the anatomy. There were no visible distortions in any of the traced fiber bundles, even when these were located in the vicinity of significant magnetic field inhomogeneities. Additionally, the Turboprop-DTI data used in this research were acquired in less than 19 min of scan time. Thus, Turboprop appears to be a promising DTI data acquisition technique for tracing white matter fibers.
Functional connectivity: integrating behavioral, diffusion tensor imaging, and functional magnetic resonance imaging data sets.

PubMed

Baird, Abigail A; Colvin, Mary K; Vanhorn, John D; Inati, Souheil; Gazzaniga, Michael S

2005-04-01

In the present study, we combined 2 types of magnetic resonance technology to explore individual differences on a task that required the recognition of objects presented from unusual viewpoints. This task was chosen based on previous work that has established the necessity of information transfer from the right parietal cortex to the left inferior cortex for its successful completion. We used reaction times (RTs) to localize regions of cortical activity in the superior parietal and inferior frontal regions (blood oxygen level-dependent [BOLD] response) that were more active with longer response times. These regions were then sampled, and their signal change used to predict individual differences in structural integrity of white matter in the corpus callosum (using diffusion tensor imaging). Results show that shorter RTs (and associated increases in BOLD response) are associated with increased organization in the splenium of the corpus callosum, whereas longer RTs are associated with increased organization in the genu.
Disrupted white matter integrity in heroin dependence: a controlled study utilizing diffusion tensor imaging.

PubMed

Liu, Haihong; Li, Lin; Hao, Yihui; Cao, Dong; Xu, Lin; Rohrbaugh, Robert; Xue, Zhimin; Hao, Wei; Shan, Baoci; Liu, Zhening

2008-01-01

Fractional anisotropy (FA) via diffusion tensor imaging (DTI) can quantify the white matter integrity. Exposure to addictive drugs, such as alcohol, cocaine, methamphetamine, marijuana, and nicotine has been shown to alter FA. White matter abnormalities have been shown, but it remains unclear whether the white matter FA is altered in heroin dependence. Utilizing DTI, we investigated the FA difference between heroin-dependent and control subjects by a voxel-based strategy. The FA values of the identified regions were calculated from the FA image of each subject and were correlated with clinical features including months of heroin use, age, education, and dose of methadone. Reduced FA among 16 heroin dependent subjects was located in the bilateral frontal sub-gyral regions, right precentral and left cingulate gyrus. FA in the right frontal sub-gyral was negatively correlated with duration of heroin use. The disrupted white matter integrity in right frontal white matter may occur in continuous heroin abuse.
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.
Diffusion Tensor Imaging of Normal-Appearing White Matter as Biomarker for Radiation-Induced Late Delayed Cognitive Decline

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
A prediction model for cognitive performance in health ageing using diffusion tensor imaging with graph theory.

PubMed

Yun, Ruijuan; Lin, Chung-Chih; Wu, Shuicai; Huang, Chu-Chung; Lin, Ching-Po; Chao, Yi-Ping

2013-01-01

In this study, we employed diffusion tensor imaging (DTI) to construct brain structural network and then derive the connection matrices from 96 healthy elderly subjects. The correlation analysis between these topological properties of network based on graph theory and the Cognitive Abilities Screening Instrument (CASI) index were processed to extract the significant network characteristics. These characteristics were then integrated to estimate the models by various machine-learning algorithms to predict user's cognitive performance. From the results, linear regression model and Gaussian processes model showed presented better abilities with lower mean absolute errors of 5.8120 and 6.25 to predict the cognitive performance respectively. Moreover, these extracted topological properties of brain structural network derived from DTI also could be regarded as the bio-signatures for further evaluation of brain degeneration in healthy aged and early diagnosis of mild cognitive impairment (MCI).
Clinical application of diffusion tensor magnetic resonance imaging in skeletal muscle

PubMed Central

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
Traumatic Brain Injury: Hope Through Research

MedlinePlus

... last decade to image milder TBI damage. For example, diffusion tensor imaging (DTI) can image white matter tracts, more sensitive tests like fluid-attenuated inversion recovery (FLAIR) can detect ...
Parallel changes in serum proteins and diffusion tensor imaging in methamphetamine-associated psychosis.

PubMed

Breen, Michael S; Uhlmann, Anne; Ozcan, Sureyya; Chan, Man; Pinto, Dalila; Bahn, Sabine; Stein, Dan J

2017-03-02

Methamphetamine-associated psychosis (MAP) involves widespread neurocognitive and molecular deficits, however accurate diagnosis remains challenging. Integrating relationships between biological markers, brain imaging and clinical parameters may provide an improved mechanistic understanding of MAP, that could in turn drive the development of better diagnostics and treatment approaches. We applied selected reaction monitoring (SRM)-based proteomics, profiling 43 proteins in serum previously implicated in the etiology of major psychiatric disorders, and integrated these data with diffusion tensor imaging (DTI) and psychometric measurements from patients diagnosed with MAP (N = 12), methamphetamine dependence without psychosis (MA; N = 14) and healthy controls (N = 16). Protein analysis identified changes in APOC2 and APOH, which differed significantly in MAP compared to MA and controls. DTI analysis indicated widespread increases in mean diffusivity and radial diffusivity delineating extensive loss of white matter integrity and axon demyelination in MAP. Upon integration, several co-linear relationships between serum proteins and DTI measures reported in healthy controls were disrupted in MA and MAP groups; these involved areas of the brain critical for memory and social emotional processing. These findings suggest that serum proteomics and DTI are sensitive measures for detecting pathophysiological changes in MAP and describe a potential diagnostic fingerprint of the disorder.
Interactive Volume Rendering of Diffusion Tensor Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hlawitschka, Mario; Weber, Gunther; Anwander, Alfred

As 3D volumetric images of the human body become an increasingly crucial source of information for the diagnosis and treatment of a broad variety of medical conditions, advanced techniques that allow clinicians to efficiently and clearly visualize volumetric images become increasingly important. Interaction has proven to be a key concept in analysis of medical images because static images of 3D data are prone to artifacts and misunderstanding of depth. Furthermore, fading out clinically irrelevant aspects of the image while preserving contextual anatomical landmarks helps medical doctors to focus on important parts of the images without becoming disoriented. Our goal wasmore » to develop a tool that unifies interactive manipulation and context preserving visualization of medical images with a special focus on diffusion tensor imaging (DTI) data. At each image voxel, DTI provides a 3 x 3 tensor whose entries represent the 3D statistical properties of water diffusion locally. Water motion that is preferential to specific spatial directions suggests structural organization of the underlying biological tissue; in particular, in the human brain, the naturally occuring diffusion of water in the axon portion of neurons is predominantly anisotropic along the longitudinal direction of the elongated, fiber-like axons [MMM+02]. This property has made DTI an emerging source of information about the structural integrity of axons and axonal connectivity between brain regions, both of which are thought to be disrupted in a broad range of medical disorders including multiple sclerosis, cerebrovascular disease, and autism [Mos02, FCI+01, JLH+99, BGKM+04, BJB+03].« less
Distortion-free diffusion tensor imaging for evaluation of lumbar nerve roots: Utility of direct coronal single-shot turbo spin-echo diffusion sequence.

PubMed

Sakai, Takayuki; Doi, Kunio; Yoneyama, Masami; Watanabe, Atsuya; Miyati, Tosiaki; Yanagawa, Noriyuki

2018-06-01

Diffusion tensor imaging (DTI) based on a single-shot echo planer imaging (EPI-DTI) is an established method that has been used for evaluation of lumbar nerve disorders in previous studies, but EPI-DTI has problems such as a long acquisition time, due to a lot of axial slices, and geometric distortion. To solve these problems, we attempted to apply DTI based on a single-shot turbo spin echo (TSE-DTI) with direct coronal acquisition. Our purpose in this study was to investigate whether TSE-DTI may be more useful for evaluation of lumbar nerve disorders than EPI-DTI. First, lumbar nerve roots of five healthy volunteers were evaluated for optimization of imaging parameters with TSE-DTI including b-values and the number of motion proving gradient (MPG) directions. Subsequently, optimized TSE-DTI was quantitatively compared with conventional EPI-DTI by using fractional anisotropy (FA) values and visual scores in subjective visual evaluation of tractography. Lumbar nerve roots of six patients, who had unilateral neurologic symptoms in one leg, were evaluated by the optimized TSE-DTI. TSE-DTI with b-value of 400 s/mm 2 and 32 diffusion-directions could reduce the image distortion compared with EPI-DTI, and showed that the average FA values on the symptomatic side for six patients were significantly lower than those on the non-symptomatic side (P < 0.05). Tractography with TSE-DTI might show damaged areas of lumbar nerve roots without severe image distortion. TSE-DTI might improve the reproducibility in measurements of FA values for quantification of a nerve disorder, and would become a useful tool for diagnosis of low back pain. Copyright © 2018 Elsevier Inc. All rights reserved.
Pixel-based meshfree modelling of skeletal muscles.

PubMed

Chen, Jiun-Shyan; Basava, Ramya Rao; Zhang, Yantao; Csapo, Robert; Malis, Vadim; Sinha, Usha; Hodgson, John; Sinha, Shantanu

2016-01-01

This paper introduces the meshfree Reproducing Kernel Particle Method (RKPM) for 3D image-based modeling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The material properties and muscle fiber direction obtained from Diffusion Tensor Imaging (DTI) are input at each pixel point. The reproducing kernel (RK) approximation allows a representation of material heterogeneity with smooth transition. A multiphase multichannel level set based segmentation framework is adopted for individual muscle segmentation using Magnetic Resonance Images (MRI) and DTI. The application of the proposed methods for modeling the human lower leg is demonstrated.
White matter microstructure on diffusion tensor imaging is associated with conventional magnetic resonance imaging findings and cognitive function in adolescents born preterm

PubMed Central

FELDMAN, HEIDI M; LEE, ELIANA S; LOE, IRENE M; YEOM, KRISTEN W; GRILL-SPECTOR, KALANIT; LUNA, BEATRIZ

2013-01-01

AIM Diffusion tensor imaging (DTI) was used to evaluate white matter architecture after preterm birth. The goals were (1) to compare white matter microstructure in two cohorts of preterm- and term-born children; and (2) within preterm groups, to determine if sex, gestational age, birthweight, white matter injury score from conventional magnetic resonance imaging (MRI), or IQ was associated with DTI measures. METHOD Participants (n=121; 66 females, 55 males) were aged 9 to 16 years. They comprised 58 preterm children (site 1, n=25; and site 2, n=33) born at less than 36 weeks’ gestation (mean 29.4wks; birthweight 1289g) and 63 term children (site 1, n=40; site 2, n=23) born at more than 37 weeks’ gestation. DTI was analyzed using tract-based spatial statistics. Diffusion measures were fractional anisotropy, axial, radial, and mean diffusivity. RESULTS In no region of the white matter skeleton was fractional anisotropy lower in the preterm group at either site. Within the preterm groups, fractional anisotropy was significantly associated with white matter injury score, but not sex, gestational age, or birthweight. At site 1, fractional anisotropy was associated with IQ. INTERPRETATION DTI contributes to understanding individual differences after preterm birth but may not differentiate a relatively high-functioning group of preterm children from a matched group of term-born children. PMID:22803787
Accelerating EPI distortion correction by utilizing a modern GPU-based parallel computation.

PubMed

Yang, Yao-Hao; Huang, Teng-Yi; Wang, Fu-Nien; Chuang, Tzu-Chao; Chen, Nan-Kuei

2013-04-01

The combination of phase demodulation and field mapping is a practical method to correct echo planar imaging (EPI) geometric distortion. However, since phase dispersion accumulates in each phase-encoding step, the calculation complexity of phase modulation is Ny-fold higher than conventional image reconstructions. Thus, correcting EPI images via phase demodulation is generally a time-consuming task. Parallel computing by employing general-purpose calculations on graphics processing units (GPU) can accelerate scientific computing if the algorithm is parallelized. This study proposes a method that incorporates the GPU-based technique into phase demodulation calculations to reduce computation time. The proposed parallel algorithm was applied to a PROPELLER-EPI diffusion tensor data set. The GPU-based phase demodulation method reduced the EPI distortion correctly, and accelerated the computation. The total reconstruction time of the 16-slice PROPELLER-EPI diffusion tensor images with matrix size of 128 × 128 was reduced from 1,754 seconds to 101 seconds by utilizing the parallelized 4-GPU program. GPU computing is a promising method to accelerate EPI geometric correction. The resulting reduction in computation time of phase demodulation should accelerate postprocessing for studies performed with EPI, and should effectuate the PROPELLER-EPI technique for clinical practice. Copyright © 2011 by the American Society of Neuroimaging.

Diffusion heterogeneity tensor MRI (?-Dti): mathematics and initial applications in spinal cord regeneration after trauma - biomed 2009.

PubMed

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.
Evaluation of diffusion kurtosis imaging in ex vivo hypomyelinated mouse brains.

PubMed

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.
Diffusion Tensor Imaging of Incentive Effects in Prospective Memory after Pediatric Traumatic Brain Injury

PubMed Central

Wilde, Elisabeth A.; Bigler, Erin D.; Chu, Zili; Yallampalli, Ragini; Oni, Margaret B.; Wu, Trevor C.; Ramos, Marco A.; Pedroza, Claudia; Vásquez, Ana C.; Hunter, Jill V.; Levin, Harvey S.

2011-01-01

Abstract Few studies exist investigating the brain-behavior relations of event-based prospective memory (EB-PM) impairments following traumatic brain injury (TBI). To address this, children with moderate-to-severe TBI performed an EB-PM test with two motivational enhancement conditions and underwent concurrent diffusion tensor imaging (DTI) at 3 months post-injury. Children with orthopedic injuries (OI; n = 37) or moderate-to-severe TBI (n = 40) were contrasted. Significant group differences were found for fractional anisotropy (FA) and apparent diffusion coefficient for orbitofrontal white matter (WM), cingulum bundles, and uncinate fasciculi. The FA of these WM structures in children with TBI significantly correlated with EB-PM performance in the high, but not the low motivation condition. Regression analyses within the TBI group indicated that the FA of the left cingulum bundle (p = 0.003), left orbitofrontal WM (p < 0.02), and left (p < 0.02) and right (p < 0.008) uncinate fasciculi significantly predicted EB-PM performance in the high motivation condition. We infer that the cingulum bundles, orbitofrontal WM, and uncinate fasciculi are important WM structures mediating motivation-based EB-PM responses following moderate-to-severe TBI in children. PMID:21250917
MRI-negative refractory partial epilepsy: role for diffusion tensor imaging in high field MRI.

PubMed

Chen, Qin; Lui, Su; Li, Chun-Xiao; Jiang, Li-Jun; Ou-Yang, Luo; Tang, He-Han; Shang, Hui-Fang; Huang, Xiao-Qi; Gong, Qi-Yong; Zhou, Dong

2008-07-01

Our aim is to use the high field MR scanner (3T) to verify whether diffusion tensor imaging (DTI) could help in locating the epileptogenic zone in patients with MRI-negative refractory partial epilepsy. Fifteen patients with refractory partial epilepsy who had normal conventional MRI, and 40 healthy volunteers were recruited for the study. DTI was performed on a 3T MR scanner, individual maps of mean diffusivity (MD) and fractional anisotropy (FA) were calculated, and Voxel-Based Analysis (VBA) was performed for individual comparison between patients and controls. Voxel-based analysis revealed significant MD increase in variant regions in 13 patients. The electroclinical seizure localization was concurred to seven patients. No patient exhibited regions of significant decreased MD. Regions of significant reduced FA were observed in five patients, with two of these concurring with electroclinical seizure localization. Two patients had regions of significant increase in FA, which were distinct from electroclinical seizure localization. Our study's results revealed that DTI is a responsive neuroradiologic technique that provides information about the epileptogenic areas in patients with MRI-negative refractory partial epilepsy. This technique may also helpful in pre-surgical evaluation.
Effects of insulin resistance on white matter microstructure in middle-aged and older adults

PubMed Central

Coutu, Jean-Philippe; Rosas, H. Diana; Salat, David H.

2014-01-01

Objective: To investigate the potential relationship between insulin resistance (IR) and white matter (WM) microstructure using diffusion tensor imaging in cognitively healthy middle-aged and older adults. Methods: Diffusion tensor imaging was acquired from 127 individuals (age range 41–86 years). IR was evaluated by the homeostasis model assessment of IR (HOMA-IR). Participants were divided into 2 groups based on HOMA-IR values: “high HOMA-IR” (≥2.5, n = 27) and “low HOMA-IR” (<2.5, n = 100). Cross-sectional voxel-based comparisons were performed using Tract-Based Spatial Statistics and anatomically defined regions of interest analysis. Results: The high HOMA-IR group demonstrated decreased axial diffusivity broadly throughout the cerebral WM in areas such as the corpus callosum, corona radiata, cerebral peduncle, posterior thalamic radiation, and right superior longitudinal fasciculus, and WM underlying the frontal, parietal, and temporal lobes, as well as decreased fractional anisotropy in the body and genu of corpus callosum and parts of the superior and anterior corona radiata, compared with the low HOMA-IR group, independent of age, WM signal abnormality volume, and antihypertensive medication status. These regions additionally demonstrated linear associations between diffusion measures and HOMA-IR across all subjects, with higher HOMA-IR values being correlated with lower axial diffusivity. Conclusions: In generally healthy adults, greater IR is associated with alterations in WM tissue integrity. These cross-sectional findings suggest that IR contributes to WM microstructural alterations in middle-aged and older adults. PMID:24771537
Parcellating the neuroanatomical basis of impaired decision-making in traumatic brain injury.

PubMed

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

PubMed Central

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
Diffusion Tensor Imaging Based Thalamic Segmentation in Deep Brain Stimulation for Chronic Pain Conditions

PubMed Central

Kim, Won; Chivukula, Srinivas; Hauptman, Jason; Pouratian, Nader

2016-01-01

Background/Aims Thalamic deep brain stimulation (DBS) for the treatment of medically refractory pain has largely been abandoned on account of its inconsistent and oftentimes poor efficacy. Our aim here was to use diffusion tensor imaging (DTI)-based segmentation to assess the internal thalamic nuclei of patients who have undergone thalamic DBS for intractable pain and retrospectively correlate lead position with clinical outcome. Methods DTI-based segmentation was performed on 5 patients who underwent sensory thalamus DBS for chronic pain. Postoperative computed tomography (CT) images obtained for electrode placement were fused with preoperative MRIs that had undergone DTI-based thalamic segmentation. Sensory thalamus maps of 4 patients were analyzed for lead positioning and interpatient variability. Results Four patients who experienced significant pain relief following DBS demonstrated contact positions within the DTI-determined sensory thalamus or in its vicinity, whereas one who did not respond to stimulation did not. Only four voxels (2%) within the sensory thalamus were mutually shared among patients; 108 voxels (58%) were uniquely represented. Conclusions DTI-based segmentation of the thalamus can be used to confirm thalamic lead placement relative to the sensory thalamus, and may serve as a useful tool to guide thalamic DBS electrode implantation in the future. PMID:27537848
Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation.

PubMed

Graña, M; Termenon, M; Savio, A; Gonzalez-Pinto, A; Echeveste, J; Pérez, J M; Besga, A

2011-09-20

The aim of this paper is to obtain discriminant features from two scalar measures of Diffusion Tensor Imaging (DTI) data, Fractional Anisotropy (FA) and Mean Diffusivity (MD), and to train and test classifiers able to discriminate Alzheimer's Disease (AD) patients from controls on the basis of features extracted from the FA or MD volumes. In this study, support vector machine (SVM) classifier was trained and tested on FA and MD data. Feature selection is done computing the Pearson's correlation between FA or MD values at voxel site across subjects and the indicative variable specifying the subject class. Voxel sites with high absolute correlation are selected for feature extraction. Results are obtained over an on-going study in Hospital de Santiago Apostol collecting anatomical T1-weighted MRI volumes and DTI data from healthy control subjects and AD patients. FA features and a linear SVM classifier achieve perfect accuracy, sensitivity and specificity in several cross-validation studies, supporting the usefulness of DTI-derived features as an image-marker for AD and to the feasibility of building Computer Aided Diagnosis systems for AD based on them. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
PROPELLER EPI: An MRI Technique Suitable for Diffusion Tensor Imaging at High Field Strength With Reduced Geometric Distortions

PubMed Central

Wang, Fu-Nien; Huang, Teng-Yi; Lin, Fa-Hsuan; Chuang, Tzu-Chao; Chen, Nan-Kuei; Chung, Hsiao-Wen; Chen, Cheng-Yu; Kwong, Kenneth K.

2013-01-01

A technique suitable for diffusion tensor imaging (DTI) at high field strengths is presented in this work. The method is based on a periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) k-space trajectory using EPI as the signal readout module, and hence is dubbed PROPELLER EPI. The implementation of PROPELLER EPI included a series of correction schemes to reduce possible errors associated with the intrinsically higher sensitivity of EPI to off-resonance effects. Experimental results on a 3.0 Tesla MR system showed that the PROPELLER EPI images exhibit substantially reduced geometric distortions compared with single-shot EPI, at a much lower RF specific absorption rate (SAR) than the original version of the PROPELLER fast spin-echo (FSE) technique. For DTI, the self-navigated phase-correction capability of the PROPELLER EPI sequence was shown to be effective for in vivo imaging. A higher signal-to-noise ratio (SNR) compared to single-shot EPI at an identical total scan time was achieved, which is advantageous for routine DTI applications in clinical practice. PMID:16206142
PROPELLER EPI: an MRI technique suitable for diffusion tensor imaging at high field strength with reduced geometric distortions.

PubMed

Wang, Fu-Nien; Huang, Teng-Yi; Lin, Fa-Hsuan; Chuang, Tzu-Chao; Chen, Nan-Kuei; Chung, Hsiao-Wen; Chen, Cheng-Yu; Kwong, Kenneth K

2005-11-01

A technique suitable for diffusion tensor imaging (DTI) at high field strengths is presented in this work. The method is based on a periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) k-space trajectory using EPI as the signal readout module, and hence is dubbed PROPELLER EPI. The implementation of PROPELLER EPI included a series of correction schemes to reduce possible errors associated with the intrinsically higher sensitivity of EPI to off-resonance effects. Experimental results on a 3.0 Tesla MR system showed that the PROPELLER EPI images exhibit substantially reduced geometric distortions compared with single-shot EPI, at a much lower RF specific absorption rate (SAR) than the original version of the PROPELLER fast spin-echo (FSE) technique. For DTI, the self-navigated phase-correction capability of the PROPELLER EPI sequence was shown to be effective for in vivo imaging. A higher signal-to-noise ratio (SNR) compared to single-shot EPI at an identical total scan time was achieved, which is advantageous for routine DTI applications in clinical practice. (c) 2005 Wiley-Liss, Inc.
Motion-induced phase error estimation and correction in 3D diffusion tensor imaging.

PubMed

Van, Anh T; Hernando, Diego; Sutton, Bradley P

2011-11-01

A multishot data acquisition strategy is one way to mitigate B0 distortion and T2∗ blurring for high-resolution diffusion-weighted magnetic resonance imaging experiments. However, different object motions that take place during different shots cause phase inconsistencies in the data, leading to significant image artifacts. This work proposes a maximum likelihood estimation and k-space correction of motion-induced phase errors in 3D multishot diffusion tensor imaging. The proposed error estimation is robust, unbiased, and approaches the Cramer-Rao lower bound. For rigid body motion, the proposed correction effectively removes motion-induced phase errors regardless of the k-space trajectory used and gives comparable performance to the more computationally expensive 3D iterative nonlinear phase error correction method. The method has been extended to handle multichannel data collected using phased-array coils. Simulation and in vivo data are shown to demonstrate the performance of the method.
A comparative study of the sensitivity of diffusion-related parameters obtained from diffusion tensor imaging, diffusional kurtosis imaging, q-space analysis and bi-exponential modelling in the early disease course (24 h) of hyperacute (6 h) ischemic stroke patients.

PubMed

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.
Diffusion Tensor Analysis by Two-Dimensional Pair Correlation of Fluorescence Fluctuations in Cells.

PubMed

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.
White matter changes and word finding failures with increasing age.

PubMed

Stamatakis, Emmanuel A; Shafto, Meredith A; Williams, Guy; Tam, Phyllis; Tyler, Lorraine K

2011-01-07

Increasing life expectancy necessitates the better understanding of the neurophysiological underpinnings of age-related cognitive changes. The majority of research examining structural-cognitive relationships in aging focuses on the role of age-related changes to grey matter integrity. In the current study, we examined the relationship between age-related changes in white matter and language production. More specifically, we concentrated on word-finding failures, which increase with age. We used Diffusion tensor MRI (a technique used to image, in vivo, the diffusion of water molecules in brain tissue) to relate white matter integrity to measures of successful and unsuccessful picture naming. Diffusion tensor images were used to calculate Fractional Anisotropy (FA) images. FA is considered to be a measure of white matter organization/integrity. FA images were related to measures of successful picture naming and to word finding failures using voxel-based linear regression analyses. Successful naming rates correlated positively with white matter integrity across a broad range of regions implicated in language production. However, word finding failure rates correlated negatively with a more restricted region in the posterior aspect of superior longitudinal fasciculus. The use of DTI-MRI provides evidence for the relationship between age-related white matter changes in specific language regions and word finding failures in old age.
White matter damage in primary progressive aphasias: a diffusion tensor tractography study.

PubMed

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.
Enhanced ICBM Diffusion Tensor Template of the Human Brain

PubMed Central

Zhang, Shengwei; Peng, Huiling; Dawe, Robert J.; Arfanakis, Konstantinos

2010-01-01

Development of a diffusion tensor (DT) template that is representative of the micro-architecture of the human brain is crucial for comparisons of neuronal structural integrity and brain connectivity across populations, as well as for the generation of a detailed white matter atlas. Furthermore, a DT template in ICBM space may simplify consolidation of information from DT, anatomical and functional MRI studies. The previously developed “IIT DT brain template” was produced in ICBM-152 space, based on a large number of subjects from a limited age-range, using data with minimal image artifacts, and non-linear registration. That template was characterized by higher image sharpness, provided the ability to distinguish smaller white matter fiber structures, and contained fewer image artifacts, than several previously published DT templates. However, low-dimensional registration was used in the development of that template, which led to a mismatch of DT information across subjects, eventually manifested as loss of local diffusion information and errors in the final tensors. Also, low-dimensional registration led to a mismatch of the anatomy in the IIT and ICBM-152 templates. In this work, a significantly improved DT brain template in ICBM-152 space was developed, using high-dimensional non-linear registration and the raw data collected for the purposes of the IIT template. The accuracy of inter-subject DT matching was significantly increased compared to that achieved for the development of the IIT template. Consequently, the new template contained DT information that was more representative of single-subject human brain data, and was characterized by higher image sharpness than the IIT template. Furthermore, a bootstrap approach demonstrated that the variance of tensor characteristics was lower in the new template. Additionally, compared to the IIT template, brain anatomy in the new template more accurately matched ICBM-152 space. Finally, spatial normalization of a number of DT datasets through registration to the new and existing IIT templates was improved when using the new template. PMID:20851772
Tractography of white matter based on diffusion tensor imaging in ischaemic stroke involving the corticospinal tract: a preliminary study

NASA Astrophysics Data System (ADS)

Zhong, Chongguang; Bai, Lijun; Cui, Fangyuan; Dai, Ruwei; Xue, Ting; Wang, Hu; Wei, Wenjuan; Liu, Zhenyu; You, Youbo; Zou, Yihuai; Tian, Jie

2012-03-01

Diffusion tensor MR imaging (DTI) provides information on diffusion anisotropy in vivo, which can be exhibited three-dimensional white matter tractography. Five healthy volunteers and five right-hand affected patients with early subacute ischaemic infarction involving the posterior limb of the internal capsule or corona radiate were recruited in this study. We used 3D white matter tractography to show the corticospinal tract in both volunteer group and stroke group. Then we compared parameters of the corticospinal tract in patients with that in normal subjects and assessed the relationships between the fiber number of the corticospinal tract in ipsilesional hemisphere and indicators of the patients' rehabilitation using Pearson correlation analysis. The fractional anisotropy (FA) values and apparent diffusion coefficient (ADC) values in the ipsilesional corticospinal tract may significantly reduce comparing with the volunteer group. In addition, the stroke patient with less fiber number of the ipsilesional corticospinal tract may bear more possibilities of better motor rehabilitation. The FA values, ADC values and fiber number of the corticospinal tract in the ipsilesional hemisphere might be helpful to the prognosis and prediction of clinical treatment in stroke patients.
Autism spectrum disorder: does neuroimaging support the DSM-5 proposal for a symptom dyad? A systematic review of functional magnetic resonance imaging and diffusion tensor imaging studies.

PubMed

Pina-Camacho, Laura; Villero, Sonia; Fraguas, David; Boada, Leticia; Janssen, Joost; Navas-Sánchez, Francisco J; Mayoral, Maria; Llorente, Cloe; Arango, Celso; Parellada, Mara

2012-07-01

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 abnormal function and structure of fronto-temporal and limbic networks with social and pragmatic language deficits, of temporo-parieto-occipital networks with syntactic-semantic language deficits, and of fronto-striato-cerebellar networks with repetitive behaviors and restricted interests in ASD patients. Therefore, this review partially supports the DSM-5 proposal for the ASD dyad.
Diffusion tensor imaging using multiple coils for mouse brain connectomics.

PubMed

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.

Analyses of Disruption of Cerebral White Matter Integrity in Schizophrenia with MR Diffusion Tensor Fiber Tracking Method

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.
Reduced fractional anisotropy on diffusion tensor magnetic resonance imaging after hypoxic-ischemic encephalopathy.

PubMed

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.
Motion Artifact Reduction in Pediatric Diffusion Tensor Imaging Using Fast Prospective Correction

PubMed Central

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.

PubMed

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.
Crossing Fibers Detection with an Analytical High Order Tensor Decomposition

PubMed Central

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
Stimulated echo diffusion tensor imaging and SPAIR T2-weighted imaging in Chronic Exertional Compartment Syndrome of the lower leg muscles

PubMed Central

Sigmund, Eric E.; Sui, Dabang; Ukpebor, Obehi; Baete, Steven; Fieremans, Els; Babb, James S.; Mechlin, Michael; Liu, Kecheng; Kwon, Jane; Mcgorty, KellyAnne; Hodnett, Phil; Bencardino, Jenny

2013-01-01

Purpose To evaluate the performance of diffusion tensor imaging (DTI) in the evaluation of chronic exertional compartment syndrome (CECS) as compared to T2-weighted imaging. Materials and Methods Using an IRB-approved HIPAA-compliant protocol, spectral adiabatic inversion recovery (SPAIR) T2-weighted imaging (T2w) and stimulated echo DTI were applied to 8 healthy volunteers and 14 suspected CECS patients before and after exertion. Longitudinal and transverse diffusion eigenvalues, mean diffusivity (MD), and fractional anisotropy (FA) were measured in 7 calf muscle compartments, which in patients were classified by their response on T2w: normal (<20% change), and CECS (>20% change). Mixed model analysis of variance compared subject groups and compartments in terms of response factors (post-/pre-exercise ratios) of DTI parameters. Results All diffusivities significantly increased (p<0.0001) and FA decreased (p=.0014) with exercise. Longitudinal diffusion responses were significantly smaller than transversal diffusion responses (p<0.0001). 19 of 98 patient compartments were classified as CECS on T2w. MD increased by 3.8±3.4% (volunteer), 7.4±4.2 % (normal), and 9.1±7.0% (CECS) with exercise. Conclusion DTI shows promise as an ancillary imaging method in the diagnosis and understanding of the pathophysiology in CECS. Future studies may explore its utility in predicting response to treatment. PMID:23440764
Preoperative Visualization of Cranial Nerves in Skull Base Tumor Surgery Using Diffusion Tensor Imaging Technology.

PubMed

Ma, Jun; Su, Shaobo; Yue, Shuyuan; Zhao, Yan; Li, Yonggang; Chen, Xiaochen; Ma, Hui

2016-01-01

To visualize cranial nerves (CNs) using diffusion tensor imaging (DTI) with special parameters. This study also involved the evaluation of preoperative estimates and intraoperative confirmation of the relationship between nerves and tumor by verifying the accuracy of visualization. 3T magnetic resonance imaging scans including 3D-FSPGR, FIESTA, and DTI were used to collect information from 18 patients with skull base tumor. DTI data were integrated into the 3D slicer for fiber tracking and overlapped anatomic images to determine course of nerves. 3D reconstruction of tumors was achieved to perform neighboring, encasing, and invading relationship between lesion and nerves. Optic pathway including the optic chiasm could be traced in cases of tuberculum sellae meningioma and hypophysoma (pituitary tumor). The oculomotor nerve, from the interpeduncular fossa out of the brain stem to supraorbital fissure, was clearly visible in parasellar meningioma cases. Meanwhile, cisternal parts of trigeminal nerve and abducens nerve, facial nerve were also imaged well in vestibular schwannomas and petroclival meningioma cases. The 3D-spatial relationship between CNs and skull base tumor estimated preoperatively by tumor modeling and tractography corresponded to the results determined during surgery. Supported by DTI and 3D slicer, preoperative 3D reconstruction of most CNs related to skull base tumor is feasible in pathological circumstances. We consider DTI Technology to be a useful tool for predicting the course and location of most CNs, and syntopy between them and skull base tumor.
Ultra-high field upper extremity peripheral nerve and non-contrast enhanced vascular imaging

PubMed Central

Raval, Shailesh B.; Britton, Cynthia A.; Zhao, Tiejun; Krishnamurthy, Narayanan; Santini, Tales; Gorantla, Vijay S.; Ibrahim, Tamer S.

2017-01-01

Objective The purpose of this study was to explore the efficacy of Ultra-high field [UHF] 7 Tesla [T] MRI as compared to 3T MRI in non-contrast enhanced [nCE] imaging of structural anatomy in the elbow, forearm, and hand [upper extremity]. Materials and method A wide range of sequences including T1 weighted [T1] volumetric interpolate breath-hold exam [VIBE], T2 weighted [T2] double-echo steady state [DESS], susceptibility weighted imaging [SWI], time-of-flight [TOF], diffusion tensor imaging [DTI], and diffusion spectrum imaging [DSI] were optimized and incorporated with a radiofrequency [RF] coil system composed of a transverse electromagnetic [TEM] transmit coil combined with an 8-channel receive-only array for 7T upper extremity [UE] imaging. In addition, Siemens optimized protocol/sequences were used on a 3T scanner and the resulting images from T1 VIBE and T2 DESS were compared to that obtained at 7T qualitatively and quantitatively [SWI was only qualitatively compared]. DSI studio was utilized to identify nerves based on analysis of diffusion weighted derived fractional anisotropy images. Images of forearm vasculature were extracted using a paint grow manual segmentation method based on MIPAV [Medical Image Processing, Analysis, and Visualization]. Results High resolution and high quality signal-to-noise ratio [SNR] and contrast-to-noise ratio [CNR]—images of the hand, forearm, and elbow were acquired with nearly homogeneous 7T excitation. Measured [performed on the T1 VIBE and T2 DESS sequences] SNR and CNR values were almost doubled at 7T vs. 3T. Cartilage, synovial fluid and tendon structures could be seen with higher clarity in the 7T T1 and T2 weighted images. SWI allowed high resolution and better quality imaging of large and medium sized arteries and veins, capillary networks and arteriovenous anastomoses at 7T when compared to 3T. 7T diffusion weighted sequence [not performed at 3T] demonstrates that the forearm nerves are clearly delineated by fiber tractography. The proper digital palmar arteries and superficial palmar arch could also be clearly visualized using TOF nCE 7T MRI. Conclusion Ultra-high resolution neurovascular imaging in upper extremities is possible at 7T without use of renal toxic intravenous contrast. 7T MRI can provide superior peripheral nerve [based on fiber anisotropy and diffusion coefficient parameters derived from diffusion tensor/spectrum imaging] and vascular [nCE MRA and vessel segmentation] imaging. PMID:28662061
Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography.

PubMed

Pierce, Theodore T; Calabrese, Evan; White, Leonard E; Chen, Steven D; Platt, Simon R; Provenzale, James M

2014-01-01

We set out to determine functional white matter (WM) connections passing through the canine corpus callosum; these WM connections would be useful for subsequent studies of canine brains that serve as models for human WM pathway disease. Based on prior studies, we anticipated that the anterior corpus callosum would send projections to the anterior cerebral cortex whereas progressively posterior segments would send projections to more posterior cortex. A postmortem canine brain was imaged using a 7-T MRI system producing 100-μm-isotropic-resolution diffusion-tensor imaging analyzed by tractography. Using regions of interest (ROIs) within cortical locations, which were confirmed by a Nissl stain that identified distinct cortical architecture, we successfully identified six important WM pathways. We also compared fractional anisotropy (FA), apparent diffusion coefficient (ADC), radial diffusivity, and axial diffusivity in tracts passing through the genu and splenium. Callosal fibers were organized on the basis of cortical destination (e.g., fibers from the genu project to the frontal cortex). Histologic results identified the motor cortex on the basis of cytoarchitectonic criteria that allowed placement of ROIs to discriminate between frontal and parietal lobes. We also identified cytoarchitecture typical of the orbital frontal, anterior frontal, and occipital regions and placed ROIs accordingly. FA, ADC, radial diffusivity, and axial diffusivity values were all higher in posterior corpus callosum fiber tracts. Using six cortical ROIs, we identified six major WM tracts that reflect major functional divisions of the cerebral hemispheres, and we derived quantitative values that can be used for study of canine models of human WM pathologic states.
Registration of High Angular Resolution Diffusion MRI Images Using 4th Order Tensors⋆

PubMed Central

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
Motor programme activating therapy influences adaptive brain functions in multiple sclerosis: clinical and MRI study.

PubMed

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.
Tensor distribution function

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.
Muscle changes detected with diffusion-tensor imaging after long-distance running.

PubMed

Froeling, Martijn; Oudeman, Jos; Strijkers, Gustav J; Maas, Mario; Drost, Maarten R; Nicolay, Klaas; Nederveen, Aart J

2015-02-01

To develop a protocol for diffusion-tensor imaging (DTI) of the complete upper legs and to demonstrate feasibility of detection of subclinical sports-related muscle changes in athletes after strenuous exercise, which remain undetected by using conventional T2-weighted magnetic resonance (MR) imaging with fat suppression. The research was approved by the institutional ethics committee review board, and the volunteers provided written consent before the study. Five male amateur long-distance runners underwent an MR examination (DTI, T1-weighted MR imaging, and T2-weighted MR imaging with fat suppression) of both upper legs 1 week before, 2 days after, and 3 weeks after they participated in a marathon. The tensor eigenvalues (λ1, λ2, and λ3), the mean diffusivity, and the fractional anisotropy (FA) were derived from the DTI data. Data per muscle from the three time-points were compared by using a two-way mixed-design analysis of variance with a Bonferroni posthoc test. The DTI protocol allowed imaging of both complete upper legs with adequate signal-to-noise ratio and within a 20-minute imaging time. After the marathon, T2-weighted MR imaging revealed grade 1 muscle strains in nine of the 180 investigated muscles. The three eigenvalues, mean diffusivity, and FA were significantly increased (P < .05) in the biceps femoris muscle 2 days after running. Mean diffusivity and eigenvalues λ1 and λ2 were significantly (P < .05) increased in the semitendinosus and gracilis muscles 2 days after the marathon. A feasible method for DTI measurements of the upper legs was developed that fully included frequently injured muscles, such as hamstrings, in one single imaging session. This study also revealed changes in DTI parameters that over time were not revealed by qualitative T2-weighted MR imaging with fat suppression. © RSNA, 2014.
Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema

PubMed Central

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
Language Dysfunction After Stroke and Damage to White Matter Tracts Evaluated Using Diffusion Tensor Imaging

PubMed Central

Breier, J.I.; Hasan, K.M.; Zhang, W.; Men, D.; Papanicolaou, A.C.

2011-01-01

BACKGROUND AND PURPOSE Knowledge of the anatomic basis of aphasia after stroke has both theoretic and clinical implications by informing models of cortical connectivity and providing data for diagnosis and prognosis. In this study we use diffusion tensor imaging to address the relationship between damage to specific white matter tracts and linguistic deficits after left hemisphere stroke. MATERIALS AND METHODS Twenty patients aged 38–77 years with a history of stroke in the left hemisphere underwent diffusion tensor imaging, structural MR imaging, and language testing. All of the patients were premorbidly right handed and underwent imaging and language testing at least 1 month after stroke. RESULTS Lower fractional anisotropy (FA) values in the superior longitudinal and arcuate fasciculi of the left hemisphere, an indication of greater damage to these tracts, were correlated with decreased ability to repeat spoken language. Comprehension deficits after stroke were associated with lower FA values in the arcuate fasciculus of the left hemisphere. The findings for repetition were independent of MR imaging ratings of the degree of damage to cortical areas of the left hemisphere involved in language function. There were no findings for homotopic tracts in the right hemisphere. CONCLUSION This study provides support for a specific role for damage to the superior longitudinal and arcuate fasciculi in the left hemisphere in patients with deficits in repetition of speech in aphasia after stroke. PMID:18039757
Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging

PubMed Central

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.

PubMed

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.
1H-MR spectroscopy and diffusion tensor imaging of normal-appearing temporal white matter in patients with nasopharyngeal carcinoma after irradiation: initial experience.

PubMed

Xiong, Wei Feng; Qiu, Shi Jun; Wang, Hong Zhuo; Lv, Xiao Fei

2013-01-01

To detect radiation-induced changes of temporal lobe normal-appearing white mater (NAWM) following radiation therapy (RT) for nasopharyngeal carcinoma (NPC). Seventy-five H(1)-MR spectroscopy and diffusion-tensor imaging (DTI) examinations were performed in 55 patients before and after receiving fractionated radiation therapy (total dose; 66-75GY). We divided the dataset into six groups, a pre-RT control group and five other groups based on time after completion of RT. N-acetylaspartic acid (NAA)/choline (Cho), NAA/creatine (Cr), Cho/Cr, mean diffusibility (MD), functional anisotropy (FA), radial diffusibility (λ(⊥)), and axial diffusibility (λ(||)) were calculated. NAA/Cho and NAA/Cr decreased and λ(⊥) increased significantly within 1 year after RT compared with pre-RT. After 1 year, NAA/Cho, NAA/Cr, and λ(⊥) were not significantly different from pre-RT. In all post-RT groups, FA decreased significantly. λ(||) decreased within 9 months after RT compared with pre-RT, but was not significantly different from pre-RT more than 9 months after RT. DTI and H(1)-MR spectroscopy can be used to detect early radiation-induced changes of temporal lobe NAWM following radiation therapy for NPC. Metabolic alterations and water diffusion characteristics of temporal lobe NAWM in patients with NPC after RT were dynamic and transient. Copyright © 2012 Wiley Periodicals, Inc.
Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm.

PubMed

Witwer, Brian P; Moftakhar, Roham; Hasan, Khader M; Deshmukh, Praveen; Haughton, Victor; Field, Aaron; Arfanakis, Konstantinos; Noyes, Jane; Moritz, Chad H; Meyerand, M Elizabeth; Rowley, Howard A; Alexander, Andrew L; Badie, Behnam

2002-09-01

Preserving vital cerebral function while maximizing tumor resection is a principal goal in surgical neurooncology. Although functional magnetic resonance imaging has been useful in the localization of eloquent cerebral cortex, this method does not provide information about the white matter tracts that may be involved in invasive, intrinsic brain tumors. Recently, diffusion-tensor (DT) imaging techniques have been used to map white matter tracts in the normal brain. The aim of this study was to demonstrate the role of DT imaging in preoperative mapping of white matter tracts in relation to cerebral neoplasms. Nine patients with brain malignancies (one pilocytic astrocytoma, five oligodendrogliomas, one low-grade oligoastrocytoma, one Grade 4 astrocytoma, and one metastatic adenocarcinoma) underwent DT imaging examinations prior to tumor excision. Anatomical information about white matter tract location, orientation, and projections was obtained in every patient. Depending on the tumor type and location, evidence of white matter tract edema (two patients), infiltration (two patients), displacement (five patients), and disruption (two patients) could be assessed with the aid of DT imaging in each case. Diffusion-tensor imaging allowed for visualization of white matter tracts and was found to be beneficial in the surgical planning for patients with intrinsic brain tumors. The authors' experience with DT imaging indicates that anatomically intact fibers may be present in abnormal-appearing areas of the brain. Whether resection of these involved fibers results in subtle postoperative neurological deficits requires further systematic study.
Feasibility of creating a high-resolution 3D diffusion tensor imaging based atlas of the human brainstem: A case study at 11.7T

PubMed Central

Aggarwal, Manisha; Zhang, Jiangyang; Pletnikova, Olga; Crain, Barbara; Troncoso, Juan; Mori, Susumu

2013-01-01

A three-dimensional stereotaxic atlas of the human brainstem based on high resolution ex vivo diffusion tensor imaging (DTI) is introduced. The atlas consists of high resolution (125–255 μm isotropic) three-dimensional DT images of the formalin-fixed brainstem acquired at 11.7T. The DTI data revealed microscopic neuroanatomical details, allowing three-dimensional visualization and reconstruction of fiber pathways including the decussation of the pyramidal tract fibers, and interdigitating fascicles of the corticospinal and transverse pontine fibers. Additionally, strong grey-white matter contrasts in the apparent diffusion coefficient (ADC) maps enabled precise delineation of grey matter nuclei in the brainstem, including the cranial nerve and the inferior olivary nuclei. Comparison with myelin-stained histology shows that at the level of resolution achieved in this study, the structural details resolved with DTI contrasts in the brainstem were comparable to anatomical delineation obtained with histological sectioning. Major neural structures delineated from DTI contrasts in the brainstem are segmented and three-dimensionally reconstructed. Further, the ex vivo DTI data are nonlinearly mapped to a widely-used in vivo human brain atlas, to construct a high-resolution atlas of the brainstem in the Montreal Neurological Institute (MNI) stereotaxic coordinate space. The results demonstrate the feasibility of developing a 3D DTI based atlas for detailed characterization of brainstem neuroanatomy with high resolution and contrasts, which will be a useful resource for research and clinical applications. PMID:23384518

APPROXIMATING SYMMETRIC POSITIVE SEMIDEFINITE TENSORS OF EVEN ORDER*

PubMed Central

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
Three-year changes in leisure activities are associated with concurrent changes in white matter microstructure and perceptual speed in individuals aged 80 years and older.

PubMed

Köhncke, Ylva; Laukka, Erika J; Brehmer, Yvonne; Kalpouzos, Grégoria; Li, Tie-Qiang; Fratiglioni, Laura; Bäckman, Lars; Lövdén, Martin

2016-05-01

Accumulating evidence suggests that engagement in leisure activities is associated with favorable trajectories of cognitive aging, but little is known about brain changes related to both activities and cognition. White matter microstructure shows experience-dependent plasticity and declines in aging. Therefore, we investigated the role of change in white matter microstructure in the activities-cognition link. We used repeated assessments of engagement, perceptual speed, and white matter microstructure (probed with diffusion tensor imaging) in a population-based sample of individuals over 80 years without dementia (n = 442, Mage = 85.1; n = 70 for diffusion tensor imaging; 2 occasions 3 years apart). Using multivariate latent change modeling, we observed positive correlations among changes in predominantly social activities, white matter microstructure, and perceptual speed. Interindividual differences in change in white matter microstructure statistically accounted for the association between change in leisure activities and change in perceptual speed. However, as analyses are based on observational data from 2 measurement occasions, causality remains unclear. Copyright © 2016 Elsevier Inc. All rights reserved.
Determination of multiple sclerosis plaque size with diffusion-tensor MR Imaging: comparison study with healthy volunteers.

PubMed

Kealey, Susan M; Kim, Youngjoo; Whiting, Wythe L; Madden, David J; Provenzale, James M

2005-08-01

To use diffusion-tensor magnetic resonance (MR) imaging to measure involvement of normal-appearing white matter (WM) immediately adjacent to multiple sclerosis (MS) plaques and thus redefine actual plaque size on diffusion-tensor images through comparison with T2-weighted images of equivalent areas in healthy volunteers. Informed consent was not required given the retrospective nature of the study on an anonymized database. The study complied with requirements of the Health Insurance Portability and Accountability Act. Twelve patients with MS (four men, eight women; mean age, 35 years) and 14 healthy volunteers (six men, eight women; mean age, 25 years) were studied. The authors obtained fractional anisotropy (FA) values in MS plaques and in the adjacent normal-appearing WM in patients with MS and in equivalent areas in healthy volunteers. They placed regions of interest (ROIs) around the periphery of plaques and defined the total ROIs (ie, plaques plus peripheral ROIs) as abnormal if their mean FA values were at least 2 standard deviations below those of equivalent ROIs within equivalent regions in healthy volunteers. The combined area of the plaque and the peripheral ROI was compared with the area of the plaque seen on T2-weighted MR images by means of a Student paired t test (P = .05). The mean plaque size on T2-weighted images was 72 mm2 +/- 21 (standard deviation). The mean plaque FA value was 0.285 +/- 0.088 (0.447 +/- 0.069 in healthy volunteers [P < .001]; mean percentage reduction in FA in MS plaques, 37%). The mean plaque size on FA maps was 91 mm2 +/- 35, a mean increase of 127% compared with the size of the original plaque on T2-weighted images (P = .03). A significant increase in plaque size was seen when normal-appearing WM was interrogated with diffusion-tensor MR imaging. This imaging technique may represent a more sensitive method of assessing disease burden and may have a future role in determining disease burden and activity.
DTI segmentation by statistical surface evolution.

PubMed

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.
Cerebral White Matter Integrity and Cognitive Aging: Contributions from Diffusion Tensor Imaging

PubMed Central

Madden, David J.; Bennett, Ilana J.; Song, Allen W.

2009-01-01

The integrity of cerebral white matter is critical for efficient cognitive functioning, but little is known regarding the role of white matter integrity in age-related differences in cognition. Diffusion tensor imaging (DTI) measures the directional displacement of molecular water and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner. This review considers DTI studies of aging and their implications for understanding adult age differences in cognitive performance. Decline in white matter integrity contributes to a disconnection among distributed neural systems, with a consistent effect on perceptual speed and executive functioning. The relation between white matter integrity and cognition varies across brain regions, with some evidence suggesting that age-related effects exhibit an anterior-posterior gradient. With continued improvements in spatial resolution and integration with functional brain imaging, DTI holds considerable promise, both for theories of cognitive aging and for translational application. PMID:19705281
Helical structure of the cardiac ventricular anatomy assessed by diffusion tensor magnetic resonance imaging with multiresolution tractography.

PubMed

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.
Exploratory analysis of diffusion tensor imaging in children with attention deficit hyperactivity disorder: evidence of abnormal white matter structure.

PubMed

Pastura, Giuseppe; Doering, Thomas; Gasparetto, Emerson Leandro; Mattos, Paulo; Araújo, Alexandra Prüfer

2016-06-01

Abnormalities in the white matter microstructure of the attentional system have been implicated in the aetiology of attention deficit hyperactivity disorder (ADHD). Diffusion tensor imaging (DTI) is a promising magnetic resonance imaging (MRI) technology that has increasingly been used in studies of white matter microstructure in the brain. The main objective of this work was to perform an exploratory analysis of white matter tracts in a sample of children with ADHD versus typically developing children (TDC). For this purpose, 13 drug-naive children with ADHD of both genders underwent MRI using DTI acquisition methodology and tract-based spatial statistics. The results were compared to those of a sample of 14 age- and gender-matched TDC. Lower fractional anisotropy was observed in the splenium of the corpus callosum, right superior longitudinal fasciculus, bilateral retrolenticular part of the internal capsule, bilateral inferior fronto-occipital fasciculus, left external capsule and posterior thalamic radiation (including right optic radiation). We conclude that white matter tracts in attentional and motor control systems exhibited signs of abnormal microstructure in this sample of drug-naive children with ADHD.
Diffusion tensor imaging reveals changes in the adult rat brain following long-term and passive moderate acoustic exposure.

PubMed

Abdoli, Sherwin; Ho, Leon C; Zhang, Jevin W; Dong, Celia M; Lau, Condon; Wu, Ed X

2016-12-01

This study investigated neuroanatomical changes following long-term acoustic exposure at moderate sound pressure level (SPL) under passive conditions, without coupled behavioral training. The authors utilized diffusion tensor imaging (DTI) to detect morphological changes in white matter. DTIs from adult rats (n = 8) exposed to continuous acoustic exposure at moderate SPL for 2 months were compared with DTIs from rats (n = 8) reared under standard acoustic conditions. Two distinct forms of DTI analysis were applied in a sequential manner. First, DTI images were analyzed using voxel-based statistics which revealed greater fractional anisotropy (FA) of the pyramidal tract and decreased FA of the tectospinal tract and trigeminothalamic tract of the exposed rats. Region of interest analysis confirmed (p < 0.05) that FA had increased in the pyramidal tract but did not show a statistically significant difference in the FA of the tectospinal or trigeminothalamic tract. The results of the authors show that long-term and passive acoustic exposure at moderate SPL increases the organization of white matter in the pyramidal tract.
Impaired functional but preserved structural connectivity in limbic white matter tracts in youth with conduct disorder or oppositional defiant disorder plus psychopathic traits.

PubMed

Finger, Elizabeth Carrie; Marsh, Abigail; Blair, Karina Simone; Majestic, Catherine; Evangelou, Iordanis; Gupta, Karan; Schneider, Marguerite Reid; Sims, Courtney; Pope, Kayla; Fowler, Katherine; Sinclair, Stephen; Tovar-Moll, Fernanda; Pine, Daniel; Blair, Robert James

2012-06-30

Youths with conduct disorder or oppositional defiant disorder and psychopathic traits (CD/ODD+PT) are at high risk of adult antisocial behavior and psychopathy. Neuroimaging studies demonstrate functional abnormalities in orbitofrontal cortex and the amygdala in both youths and adults with psychopathic traits. Diffusion tensor imaging in psychopathic adults demonstrates disrupted structural connectivity between these regions (uncinate fasiculus). The current study examined whether functional neural abnormalities present in youths with CD/ODD+PT are associated with similar white matter abnormalities. Youths with CD/ODD+PT and comparison participants completed 3.0 T diffusion tensor scans and functional magnetic resonance imaging scans. Diffusion tensor imaging did not reveal disruption in structural connections within the uncinate fasiculus or other white matter tracts in youths with CD/ODD+PT, despite the demonstration of disrupted amygdala-prefrontal functional connectivity in these youths. These results suggest that disrupted amygdala-frontal white matter connectivity as measured by fractional anisotropy is less sensitive than imaging measurements of functional perturbations in youths with psychopathic traits. If white matter tracts are intact in youths with this disorder, childhood may provide a critical window for intervention and treatment, before significant structural brain abnormalities solidify. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
High-resolution diffusion tensor imaging of the human kidneys using a free-breathing, multi-slice, targeted field of view approach

PubMed Central

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
High-resolution diffusion tensor imaging of the human kidneys using a free-breathing, multi-slice, targeted field of view approach.

PubMed

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.
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.
PSF mapping-based correction of eddy-current-induced distortions in diffusion-weighted echo-planar imaging.

PubMed

In, Myung-Ho; Posnansky, Oleg; Speck, Oliver

2016-05-01

To accurately correct diffusion-encoding direction-dependent eddy-current-induced geometric distortions in diffusion-weighted echo-planar imaging (DW-EPI) and to minimize the calibration time at 7 Tesla (T). A point spread function (PSF) mapping based eddy-current calibration method is newly presented to determine eddy-current-induced geometric distortions even including nonlinear eddy-current effects within the readout acquisition window. To evaluate the temporal stability of eddy-current maps, calibration was performed four times within 3 months. Furthermore, spatial variations of measured eddy-current maps versus their linear superposition were investigated to enable correction in DW-EPIs with arbitrary diffusion directions without direct calibration. For comparison, an image-based eddy-current correction method was additionally applied. Finally, this method was combined with a PSF-based susceptibility-induced distortion correction approach proposed previously to correct both susceptibility and eddy-current-induced distortions in DW-EPIs. Very fast eddy-current calibration in a three-dimensional volume is possible with the proposed method. The measured eddy-current maps are very stable over time and very similar maps can be obtained by linear superposition of principal-axes eddy-current maps. High resolution in vivo brain results demonstrate that the proposed method allows more efficient eddy-current correction than the image-based method. The combination of both PSF-based approaches allows distortion-free images, which permit reliable analysis in diffusion tensor imaging applications at 7T. © 2015 Wiley Periodicals, Inc.
No differences in brain microstructure between young KIBRA-C carriers and non-carriers.

PubMed

Hu, Li; Xu, Qunxing; Li, Jizhen; Wang, Feifei; Xu, Xinghua; Sun, Zhiyuan; Ma, Xiangxing; Liu, Yong; Wang, Qing; Wang, Dawei

2018-01-02

KIBRA rs17070145 polymorphism is associated with variations in memory function and the microstructure of related brain areas. Diffusion kurtosis imaging (DKI) as an extension of diffusion tensor imaging that can provide more information about changes in microstructure, based on the idea that water diffusion in biological tissues is heterogeneous due to structural hindrance and restriction. We used DKI to explore the relationship between KIBRA gene polymorphism and brain microstructure in young adults. We recruited 100 healthy young volunteers, including 53 TT carriers and 47 C allele carriers. No differences were detected between the TT homozygotes and C-allele carriers for any diffusion and kurtosis parameter. These results indicate KIBRA rs17070145 polymorphism likely has little or no effect on brain microstructure in young adults.
Voxel-based automated detection of focal cortical dysplasia lesions using diffusion tensor imaging and T2-weighted MRI data.

PubMed

Wang, Yanming; Zhou, Yawen; Wang, Huijuan; Cui, Jin; Nguchu, Benedictor Alexander; Zhang, Xufei; Qiu, Bensheng; Wang, Xiaoxiao; Zhu, Mingwang

2018-05-21

The aim of this study was to automatically detect focal cortical dysplasia (FCD) lesions in patients with extratemporal lobe epilepsy by relying on diffusion tensor imaging (DTI) and T2-weighted magnetic resonance imaging (MRI) data. We implemented an automated classifier using voxel-based multimodal features to identify gray and white matter abnormalities of FCD in patient cohorts. In addition to the commonly used T2-weighted image intensity feature, DTI-based features were also utilized. A Gaussian processes for machine learning (GPML) classifier was tested on 12 patients with FCD (8 with histologically confirmed FCD) scanned at 1.5 T and cross-validated using a leave-one-out strategy. Moreover, we compared the multimodal GPML paradigm's performance with that of single modal GPML and classical support vector machine (SVM). Our results demonstrated that the GPML performance on DTI-based features (mean AUC = 0.63) matches with the GPML performance on T2-weighted image intensity feature (mean AUC = 0.64). More promisingly, GPML yielded significantly improved performance (mean AUC = 0.76) when applying DTI-based features to multimodal paradigm. Based on the results, it can also be clearly stated that the proposed GPML strategy performed better and is robust to unbalanced dataset contrary to SVM that performed poorly (AUC = 0.69). Therefore, the GPML paradigm using multimodal MRI data containing DTI modality has promising result towards detection of the FCD lesions and provides an effective direction for future researches. Copyright © 2018 Elsevier Inc. All rights reserved.
The Diffusion Tensor Imaging Toolbox

PubMed Central

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
Stimulated echo diffusion tensor imaging and SPAIR T2 -weighted imaging in chronic exertional compartment syndrome of the lower leg muscles.

PubMed

Sigmund, Eric E; Sui, Dabang; Ukpebor, Obehi; Baete, Steven; Fieremans, Els; Babb, James S; Mechlin, Michael; Liu, Kecheng; Kwon, Jane; McGorty, KellyAnne; Hodnett, Philip A; Bencardino, Jenny

2013-11-01

To evaluate the performance of diffusion tensor imaging (DTI) in the evaluation of chronic exertional compartment syndrome (CECS) as compared to T2 -weighted (T2w) imaging. Using an Institutional Review Board (IRB)-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant protocol, spectral adiabatic inversion recovery (SPAIR) T2w imaging and stimulated echo DTI were applied to eight healthy volunteers and 14 suspected CECS patients before and after exertion. Longitudinal and transverse diffusion eigenvalues, mean diffusivity (MD), and fractional anisotropy (FA) were measured in seven calf muscle compartments, which in patients were classified by their response on T2w: normal (<20% change), and CECS (>20% change). Mixed model analysis of variance compared subject groups and compartments in terms of response factors (post/pre-exercise ratios) of DTI parameters. All diffusivities significantly increased (P < 0.0001) and FA decreased (P = 0.0014) with exercise. Longitudinal diffusion responses were significantly smaller than transversal diffusion responses (P < 0.0001). Nineteen of 98 patient compartments were classified as CECS on T2w. MD increased by 3.8 ± 3.4% (volunteer), 7.4 ± 4.2% (normal), and 9.1 ± 7.0% (CECS) with exercise. DTI shows promise as an ancillary imaging method in the diagnosis and understanding of the pathophysiology in CECS. Future studies may explore its utility in predicting response to treatment. Copyright © 2013 Wiley Periodicals, Inc.
A diffusion tensor imaging study of suicide attempters

PubMed Central

Thapa-Chhetry, Binod; Sublette, M. Elizabeth; Sullivan, Gregory M.; Oquendo, Maria A.; Mann, J. John; Parsey, Ramin V.

2014-01-01

Background Few studies have examined white matter abnormalities in suicide attempters using diffusion tensor imaging (DTI). This study sought to identify white matter regions altered in individuals with a prior suicide attempt. Methods DTI scans were acquired in 13 suicide attempters with major depressive disorder (MDD), 39 non-attempters with MDD, and 46 healthy participants (HP). Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) was determined in the brain using two methods: region of interest (ROI) and tract-based spatial statistics (TBSS). ROIs were limited a priori to white matter adjacent to the caudal anterior cingulate cortex, rostral anterior cingulate cortex, dorsomedial prefrontal cortex, and medial orbitofrontal cortex. Results Using the ROI approach, suicide attempters had lower FA than MDD non-attempters and HP in the dorsomedial prefrontal cortex. Uncorrected TBSS results confirmed a significant cluster within the right dorsomedial prefrontal cortex indicating lower FA in suicide attempters compared to non-attempters. There were no differences in ADC when comparing suicide attempters, non-attempters and HP groups using ROI or TBSS methods. Conclusions Low FA in the dorsomedial prefrontal cortex was associated with a suicide attempt history. Converging findings from other imaging modalities support this finding, making this region of potential interest in determining the diathesis for suicidal behavior. PMID:24462041
MRI assessment of the thigh musculature in dermatomyositis and healthy subjects using diffusion tensor imaging, intravoxel incoherent motion and dynamic DTI.

PubMed

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.
A Tractography Comparison between Turboprop and Spin-Echo Echo-Planar Diffusion Tensor Imaging

PubMed Central

Gui, Minzhi; Peng, Huiling; Carew, John D.; Lesniak, Maciej S.; Arfanakis, Konstantinos

2008-01-01

The development of accurate, non-invasive methods for mapping white matter fiber-tracts is of critical importance. However, fiber-tracking is typically performed on diffusion tensor imaging (DTI) data obtained with echo-planar-based imaging techniques (EPI), which suffer from susceptibility-related image artifacts, and image warping due to eddy-currents. Thus, a number of white matter fiber-bundles mapped using EPI-based DTI data are distorted and/or terminated early. This severely limits the clinical potential of fiber-tracking. In contrast, Turboprop-MRI provides images with significantly fewer susceptibility and eddy-current-related artifacts than EPI. The purpose of this work was to compare fiber-tracking results obtained from DTI data acquired with Turboprop-DTI and EPI-based DTI. It was shown that, in brain regions near magnetic field inhomogeneities, white matter fiber-bundles obtained with EPI-based DTI were distorted and/or partially detected, when magnetic susceptibility-induced distortions were not corrected. After correction, residual distortions were still present and several fiber-tracts remained partially detected. In contrast, when using Turboprop-DTI data, all traced fiber-tracts were in agreement with known anatomy. The inter-session reproducibility of tractography results was higher for Turboprop than EPI-based DTI data in regions near field inhomogeneities. Thus, Turboprop may be a more appropriate DTI data acquisition technique for tracing white matter fibers near regions with significant magnetic susceptibility differences, as well as in longitudinal studies of such fibers. However, the intra-session reproducibility of tractography results was higher for EPI-based than Turboprop DTI data. Thus, EPI-based DTI may be more advantageous for tracing fibers minimally affected by field inhomogeneities. PMID:18621131

A tractography comparison between turboprop and spin-echo echo-planar diffusion tensor imaging.

PubMed

Gui, Minzhi; Peng, Huiling; Carew, John D; Lesniak, Maciej S; Arfanakis, Konstantinos

2008-10-01

The development of accurate, non-invasive methods for mapping white matter fiber-tracts is of critical importance. However, fiber-tracking is typically performed on diffusion tensor imaging (DTI) data obtained with echo-planar-based imaging techniques (EPI), which suffer from susceptibility-related image artifacts, and image warping due to eddy-currents. Thus, a number of white matter fiber-bundles mapped using EPI-based DTI data are distorted and/or terminated early. This severely limits the clinical potential of fiber-tracking. In contrast, Turboprop-MRI provides images with significantly fewer susceptibility and eddy-current-related artifacts than EPI. The purpose of this work was to compare fiber-tracking results obtained from DTI data acquired with Turboprop-DTI and EPI-based DTI. It was shown that, in brain regions near magnetic field inhomogeneities, white matter fiber-bundles obtained with EPI-based DTI were distorted and/or partially detected, when magnetic susceptibility-induced distortions were not corrected. After correction, residual distortions were still present and several fiber-tracts remained partially detected. In contrast, when using Turboprop-DTI data, all traced fiber-tracts were in agreement with known anatomy. The inter-session reproducibility of tractography results was higher for Turboprop than EPI-based DTI data in regions near field inhomogeneities. Thus, Turboprop may be a more appropriate DTI data acquisition technique for tracing white matter fibers near regions with significant magnetic susceptibility differences, as well as in longitudinal studies of such fibers. However, the intra-session reproducibility of tractography results was higher for EPI-based than Turboprop DTI data. Thus, EPI-based DTI may be more advantageous for tracing fibers minimally affected by field inhomogeneities.
Dynamic and Inherent B0 Correction for DTI Using Stimulated Echo Spiral Imaging

PubMed Central

Avram, Alexandru V.; Guidon, Arnaud; Truong, Trong-Kha; Liu, Chunlei; Song, Allen W.

2013-01-01

Purpose To present a novel technique for high-resolution stimulated echo (STE) diffusion tensor imaging (DTI) with self-navigated interleaved spirals (SNAILS) readout trajectories that can inherently and dynamically correct for image artifacts due to spatial and temporal variations in the static magnetic field (B0) resulting from eddy currents, tissue susceptibilities, subject/physiological motion, and hardware instabilities. Methods The Hahn spin echo formed by the first two 90° radio-frequency pulses is balanced to consecutively acquire two additional images with different echo times (TE) and generate an inherent field map, while the diffusion-prepared STE signal remains unaffected. For every diffusion-encoding direction, an intrinsically registered field map is estimated dynamically and used to effectively and inherently correct for off-resonance artifacts in the reconstruction of the corresponding diffusion-weighted image (DWI). Results After correction with the dynamically acquired field maps, local blurring artifacts are specifically removed from individual STE DWIs and the estimated diffusion tensors have significantly improved spatial accuracy and larger fractional anisotropy. Conclusion Combined with the SNAILS acquisition scheme, our new method provides an integrated high-resolution short-TE DTI solution with inherent and dynamic correction for both motion-induced phase errors and off-resonance effects. PMID:23630029
Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study.

PubMed

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.
Ex Vivo Diffusion Tensor Imaging of Spinal Cord Injury in Rats of Varying Degrees of Severity

PubMed Central

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
Scientific Accomplishments for ARL Brain Structure-Function Couplings Research on Large-Scale Brain Networks from FY11-FY13 (DSI Final Report)

DTIC Science & Technology

2014-03-01

streamlines) from two types of diffusion weighted imaging scans, diffusion tensor imaging ( DTI ) and diffusion spectrum imaging (DSI). We examined...individuals. Importantly, the results also showed that this effect was greater for the DTI method than the DSI method. This suggested that DTI can better...compared to level surface walking. This project combines experimental EEG data and electromyography (EMG) data recorded from seven muscles of the leg
Higher-Order Motion-Compensation for In Vivo Cardiac Diffusion Tensor Imaging in Rats

PubMed Central

Welsh, Christopher L.; DiBella, Edward V. R.; Hsu, Edward W.

2015-01-01

Motion of the heart has complicated in vivo applications of cardiac diffusion MRI and diffusion tensor imaging (DTI), especially in small animals such as rats where ultra-high-performance gradient sets are currently not available. Even with velocity compensation via, for example, bipolar encoding pulses, the variable shot-to-shot residual motion-induced spin phase can still give rise to pronounced artifacts. This study presents diffusion-encoding schemes that are designed to compensate for higher-order motion components, including acceleration and jerk, which also have the desirable practical features of minimal TEs and high achievable b-values. The effectiveness of these schemes was verified numerically on a realistic beating heart phantom, and demonstrated empirically with in vivo cardiac diffusion MRI in rats. Compensation for acceleration, and lower motion components, was found to be both necessary and sufficient for obtaining diffusion-weighted images of acceptable quality and SNR, which yielded the first in vivo cardiac DTI demonstrated in the rat. These findings suggest that compensation for higher order motion, particularly acceleration, can be an effective alternative solution to high-performance gradient hardware for improving in vivo cardiac DTI. PMID:25775486
Diffusion Properties and 3D Architecture of Human Lower Leg Muscles Assessed with Ultra-High-Field-Strength Diffusion-Tensor MR Imaging and Tractography: Reproducibility and Sensitivity to Sex Difference and Intramuscular Variability.

PubMed

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.
Interrogating the origin and behavior of magnetic resonance diffusion tensor scalar parameters in the myocardium

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.
[Assessment of motor and sensory pathways of the brain using diffusion-tensor tractography in children with cerebral palsy].

PubMed

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.
Differences in integrity of white matter and changes with training in spelling impaired children: a diffusion tensor imaging study

PubMed Central

Gebauer, D.; Fink, A.; Filippini, N.; Johansen-Berg, H.; Reishofer, G.; Koschutnig, K.; Kargl, R.; Purgstaller, C.; Fazekas, F.; Enzinger, C.

2013-01-01

While the functional correlates of spelling impairment have been rarely investigated, to our knowledge no study exists regarding the structural characteristics of spelling impairment and potential changes with interventions. Using diffusion tensor imaging at 3.0 T, we here therefore sought to investigate (a) differences between children with poor spelling abilities (training group and waiting group) and controls, and (b) the effects of a morpheme- based spelling intervention in children with poor spelling abilities on DTI parameters. A baseline comparison of white matter indices revealed significant differences between controls and spelling-impaired children, mainly located in the right hemisphere (superior corona radiata (SCR), posterior limb of internal capsule, superior longitudinal fasciculus). After 5 weeks of training, spelling ability improved in the training group, along with increases in fractional anisotropy and decreases of radial diffusivity in the right hemisphere compared to controls. In addition, significantly higher decreases of mean diffusivity in the right SCR for the spelling-impaired training group compared to the waiting group were observed. Our results suggest that spelling impairment is associated with differences in white-matter integrity in the right hemisphere. We also provide first indications that white matter changes occur during successful training, but this needs to be more specifically addressed in future research. PMID:22198594
Differences in integrity of white matter and changes with training in spelling impaired children: a diffusion tensor imaging study.

PubMed

Gebauer, D; Fink, A; Filippini, N; Johansen-Berg, H; Reishofer, G; Koschutnig, K; Kargl, R; Purgstaller, C; Fazekas, F; Enzinger, C

2012-07-01

While the functional correlates of spelling impairment have been rarely investigated, to our knowledge no study exists regarding the structural characteristics of spelling impairment and potential changes with interventions. Using diffusion tensor imaging at 3.0 T, we here therefore sought to investigate (a) differences between children with poor spelling abilities (training group and waiting group) and controls, and (b) the effects of a morpheme-based spelling intervention in children with poor spelling abilities on DTI parameters. A baseline comparison of white matter indices revealed significant differences between controls and spelling-impaired children, mainly located in the right hemisphere (superior corona radiata (SCR), posterior limb of internal capsule, superior longitudinal fasciculus). After 5 weeks of training, spelling ability improved in the training group, along with increases in fractional anisotropy and decreases of radial diffusivity in the right hemisphere compared to controls. In addition, significantly higher decreases of mean diffusivity in the right SCR for the spelling-impaired training group compared to the waiting group were observed. Our results suggest that spelling impairment is associated with differences in white-matter integrity in the right hemisphere. We also provide first indications that white matter changes occur during successful training, but this needs to be more specifically addressed in future research.
Stimulated echo diffusion tensor imaging (STEAM-DTI) with varying diffusion times as a probe of breast tissue.

PubMed

Teruel, Jose R; Cho, Gene Y; Moccaldi Rt, Melanie; Goa, Pål E; Bathen, Tone F; Feiweier, Thorsten; Kim, Sungheon G; Moy, Linda; Sigmund, Eric E

2017-01-01

To explore the application of diffusion tensor imaging (DTI) for breast tissue and breast pathologies using a stimulated-echo acquisition mode (STEAM) with variable diffusion times. In this Health Insurance Portability and Accountability Act-compliant study, approved by the local institutional review board, eight patients and six healthy volunteers underwent an MRI examination at 3 Tesla including STEAM-DTI with several diffusion times ranging from 68.5 to 902.5 ms. A DTI model was fitted to the data for each diffusion time, and parametric maps of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for healthy fibroglandular tissue (FGT) and lesions. The median value of radial diffusivity for FGT was fitted to a linear decay to obtain an estimation of the surface-to-volume ratio, from which the radial diameter was calculated. For healthy FGT, radial diffusivity presented a linear decay with the square root of the diffusion time resulting in a range of estimated radial diameters from 202 to 496 µm, while axial diffusivity presented a nearly time-independent diffusion. Residual fat signal was reduced at longer diffusion times due to the shorter T1 of fat. Residual fat signal to the overall signal in the healthy volunteers' FGT was found to range from 2.39% to 2.55% (shortest mixing time), and from 0.40% to 0.51% (longest mixing time) for the b500 images. The use of variable diffusion times may provide an in vivo noninvasive tool to probe diffusion lengths in breast tissue and breast pathology, and might aid by improving fat suppression at longer diffusion times. 2 J. Magn. Reson. Imaging 2017;45:84-93. © 2016 International Society for Magnetic Resonance in Medicine.
White matter damage in primary progressive aphasias: a diffusion tensor tractography study

PubMed Central

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
Brain white matter fiber estimation and tractography using Q-ball imaging and Bayesian MODEL.

PubMed

Lu, Meng

2015-01-01

Diffusion tensor imaging allows for the non-invasive in vivo mapping of the brain tractography. However, fiber bundles have complex structures such as fiber crossings, fiber branchings and fibers with large curvatures that tensor imaging (DTI) cannot accurately handle. This study presents a novel brain white matter tractography method using Q-ball imaging as the data source instead of DTI, because QBI can provide accurate information about multiple fiber crossings and branchings in a single voxel using an orientation distribution function (ODF). The presented method also uses graph theory to construct the Bayesian model-based graph, so that the fiber tracking between two voxels can be represented as the shortest path in a graph. Our experiment showed that our new method can accurately handle brain white matter fiber crossings and branchings, and reconstruct brain tractograhpy both in phantom data and real brain data.
Through Diffusion Tensor Magnetic Resonance Imaging to Evaluate the Original Properties of Neural Pathways of Patients with Partial Seizures and Secondary Generalization by Individual Anatomic Reference Atlas

PubMed Central

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
[Effect of exercise load on apparent diffusion coefficient and fractional anisotropy of normal lumbar intervertebral discs in diffusion tensor imaging].

PubMed

Zhong, Xiu; Qiu, Shijun

2015-06-01

To investigate the effect of exercise load on apparent diffusion coefficient (ADC) and fractional anisotropy (FA) of normal lumbar intervertebral discs in magnetic resonance (MR) diffusion tensor imaging (DTI). Thirty healthy volunteers (24 males and 6 females, aged 19 to 25 years) underwent examinations with MR T2WI and DTI of the lumbar intervertebral discs before and after exercise load. Pfirrmann grading was evaluated with T2WI, and the B0 map, ADC map and FA map were reconstructed based on the DTI data to investigate the changes in ADC and FA after exercise. Of the 30 volunteers (150 intervertebral discs) receiving the examination, 27 with discs of Pfirrminn grade II were included for analysis. In these 27 volunteers, the average ADC and FA before exercise were (1.99 ± 0.18)×10⁻³ mm²/s and 0.155∓0.059, respectively. After exercise, ADC was lowered significantly to (1.93 ± 0.17)×10⁻³ mm²/s (P<0.05) and FA increased slightly to 0.1623 ± 0.017 (P>0.05). DTI allows quantitatively analysis of the changes in water molecular diffusion and anisotropy of the lumbar intervertebral discs after exercise load, which can cause a decreased ADC and a increased FA value, and the change of ADC is more sensitive to exercise load.
White Matter Microstructure of the Human Mirror Neuron System Is Related to Symptom Severity in Adults with Autism

ERIC Educational Resources Information Center

Fründt, Odette; Schulz, Robert; Schöttle, Daniel; Cheng, Bastian; Thomalla, Götz; Braaß, Hanna; Ganos, Christos; David, Nicole; Peiker, Ina; Engel, Andreas K.; Bäumer, Tobias; Münchau, Alexander

2018-01-01

Mirror neuron system (MNS) dysfunctions might underlie deficits in autism spectrum disorders (ASD). Diffusion tensor imaging based probabilistic tractography was conducted in 15 adult ASD patients and 13 matched, healthy controls. Fractional anisotropy (FA) was quantified to assess group differences in tract-related white matter microstructure of…
Comparison of diffusion tensor imaging tractography of language tracts and intraoperative subcortical stimulations.

PubMed

Leclercq, Delphine; Duffau, Hugues; Delmaire, Christine; Capelle, Laurent; Gatignol, Peggy; Ducros, Mathieu; Chiras, Jacques; Lehéricy, Stéphane

2010-03-01

Diffusion tensor (DT) imaging tractography is increasingly used to map fiber tracts in patients with surgical brain lesions to reduce the risk of postoperative functional deficit. There are few validation studies of DT imaging tractography in these patients. The aim of this study was to compare DT imaging tractography of language fiber tracts by using intraoperative subcortical electrical stimulations. The authors included 10 patients with low-grade gliomas or dysplasia located in language areas. The MR imaging examination included 3D T1-weighted images for anatomical coregistration, FLAIR, and DT images. Diffusion tensors and fiber tracts were calculated using in-house software. Four tracts were reconstructed in each patient including the arcuate fasciculus, the inferior occipitofrontal fasciculus, and 2 premotor fasciculi (the subcallosal medialis fiber tract and cortical fibers originating from the medial and lateral premotor areas). The authors compared fiber tracts reconstructed using DT imaging with those evidenced using intraoperative subcortical language mapping. Seventeen (81%) of 21 positive stimulations were concordant with DT imaging fiber bundles (located within 6 mm of a fiber tract). Four positive stimulations were not located in the vicinity of a DT imaging fiber tract. Stimulations of the arcuate fasciculus mostly induced articulatory and phonemic/syntactic disorders and less frequently semantic paraphasias. Stimulations of the inferior occipitofrontal fasciculus induced semantic paraphasias. Stimulations of the premotor-related fasciculi induced dysarthria and articulatory planning deficit. There was a good correspondence between positive stimulation sites and fiber tracts, suggesting that DT imaging fiber tracking is a reliable technique but not yet optimal to map language tracts in patients with brain lesions. Negative tractography does not rule out the persistence of a fiber tract, especially when invaded by the tumor. Stimulations of the different tracts induced variable language disorders that were specific to each fiber tract.
Brain Abnormalities in Congenital Fibrosis of the Extraocular Muscles Type 1: A Multimodal MRI Imaging Study.

PubMed

Miao, Wen; Man, Fengyuan; Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A; He, Huiguang; Jiao, Yonghong

2015-01-01

To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender-matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1.
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.

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.
Transverse Diffusivity of Cerebral Parenchyma Predicts Visual Tracking Performance in Relapsing-Remitting Multiple Sclerosis

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…
DTI and pathological changes in a rabbit model of radiation injury to the spinal cord after 125I radioactive seed implantation

PubMed Central

Cao, Xia; Fang, Le; Cui, Chuan-yu; Gao, Shi; Wang, Tian-wei

2018-01-01

Excessive radiation exposure may lead to edema of the spinal cord and deterioration of the nervous system. Magnetic resonance imaging can be used to judge and assess the extent of edema and to evaluate pathological changes and thus may be used for the evaluation of spinal cord injuries caused by radiation therapy. Radioactive 125I seeds to irradiate 90% of the spinal cord tissue at doses of 40–100 Gy (D90) were implanted in rabbits at T10 to induce radiation injury, and we evaluated their safety for use in the spinal cord. Diffusion tensor imaging showed that with increased D90, the apparent diffusion coefficient and fractional anisotropy values were increased. Moreover, pathological damage of neurons and microvessels in the gray matter and white matter was aggravated. At 2 months after implantation, obvious pathological injury was visible in the spinal cords of each group. Magnetic resonance diffusion tensor imaging revealed the radiation injury to the spinal cord, and we quantified the degree of spinal cord injury through apparent diffusion coefficient and fractional anisotropy. PMID:29623940
Preliminary diffusion tensor imaging studies in limb-girdle muscular dystrophies

NASA Astrophysics Data System (ADS)

Hidalgo-Tobon, S.; Hernandez-Salazar, G.; Vargas-Cañas, S.; Marrufo-Melendez, O.; Solis-Najera, S.; Taboada-Barajas, J.; Rodriguez, A. O.; Delgado-Hernandez, R.

2012-10-01

Limb-girdle muscular dystrophies (LGMD) are a group of autosomal dominantly or recessively inherited muscular dystrophies that also present with primary proximal (limb-girdle) muscle weakness. This type of dystrophy involves the shoulder and pelvic girdles, distinct phenotypic or clinical characteristics are recognized. Imaging experiments were conducted on a 1.5T GE scanner (General Electric Medical Systems. Milwaukee. USA), using a combination of two eight-channel coil array. Diffusion Tensor Imaging (DTI) data were acquired using a SE-EPI sequence, diffusion weighted gradients were applied along 30 non-collinear directions with a b-value=550 s/mm2. The connective tissue content does not appear to have a significant effect on the directionality of the diffusion, as assessed by fractional anisotropy. The fibers of the Sartorius muscle and gracilis showed decreased number of tracts, secondary to fatty infiltration and replacement of connective tissue and muscle mass loss characteristic of the underlying pathology. Our results demonstrated the utility of non-invasive MRI techniques to characterize the muscle pathology, through quantitative and qualitative methods such as the FA values and tractrography.
Surface-based reconstruction and diffusion MRI in the assessment of gray and white matter damage in multiple sclerosis

NASA Astrophysics Data System (ADS)

Caffini, Matteo; Bergsland, Niels; LaganÃ, Marcella; Tavazzi, Eleonora; Tortorella, Paola; Rovaris, Marco; Baselli, Giuseppe

2014-03-01

Despite advances in the application of nonconventional MRI techniques in furthering the understanding of multiple sclerosis pathogenic mechanisms, there are still many unanswered questions, such as the relationship between gray and white matter damage. We applied a combination of advanced surface-based reconstruction and diffusion tensor imaging techniques to address this issue. We found significant relationships between white matter tract integrity indices and corresponding cortical structures. Our results suggest a direct link between damage in white and gray matter and contribute to the notion of gray matter loss relating to clinical disability.
Assessment of MRI-Based Marker of Dopaminergic Integrity as a Biological Indicator of Gulf War Illness

DTIC Science & Technology

2015-10-01

October 2015 TYPE OF REPORT: Annual Report PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012...AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 11. SPONSOR...no funds have been used to date. 15. SUBJECT TERMS Gulf war illness; magnetic resonance imaging; dopamine ; diffusion tensor imaging 16. SECURITY
Diffusion properties of NAA in human corpus callosum as studied with diffusion tensor spectroscopy.

PubMed

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.
Fully Anisotropic Rotational Diffusion Tensor from Molecular Dynamics Simulations.

PubMed

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.
Structural Abnormalities in Early Tourette Syndrome Children: A Combined Voxel-Based Morphometry and Tract-Based Spatial Statistics Study

PubMed Central

Wang, Jieqiong; Gao, Peiyi; Yin, Guangheng; Zhang, Liping; Lv, Chuankai; Ji, Zhiying; Yu, Tong; Sabel, B. A.; He, Huiguang; Peng, Yun

2013-01-01

Tourette Syndrome (TS) is characterized with chronic motor and vocal tics beginning in childhood. Abnormality of both gray (GM) and white matter (WM) has been observed in cortico-striato-thalamo-cortical circuits and sensory-motor cortex of adult TS patient. It is not clear if these morphological changes are also present in TS children and if there are any microstructural changes of WM. To understand the developmental cause of such changes, we investigated volumetric changes of GM and WM using VBM and microstructural changes of WM using DTI, and correlated these changes with tic severity and duration. T1 images and Diffusion Tensor Images (DTI) from 21 TS children were compared with 20 age and gender matched health control children using a 1.5T Philips scanner. All of the 21 TS children met the DSM-IV-TR criteria. T1 images were analyzed using DARTEL-VBM in conjunction with statistical parametric mapping (SPM). Diffusion tensor imaging (DTI) analysis was performed using Tract-Based Spatial Statistics (TBSS). Brain volume changes were found in left superior temporal gyrus, left and right paracentral gyrus, right precuneous cortex, right pre- and post- central gyrus, left temporal occipital fusiform cortex, right frontal pole, and left lingual gyrus. Significant axial diffusivity (AD) and mean diffusivity (MD) increases were found in anterior thalamic radiation, right cingulum bundle projecting to the cingulate gurus and forceps minor. Decreases in white matter volume (WMV) in the right frontal pole were inversely related with tic severity (YGTSS), and increases in AD and MD were positively correlated with tic severity and duration, respectively. These changes in TS children can be interpreted as signs of neural plasticity in response to the experiential demand. Our findings may suggest that the morphological and microstructural measurements from structural MRI and DTI can potentially be used as a biomarker of the pathophysiologic pattern of early TS children. PMID:24098769
Structural abnormalities in early Tourette syndrome children: a combined voxel-based morphometry and tract-based spatial statistics study.

PubMed

Liu, Yue; Miao, Wen; Wang, Jieqiong; Gao, Peiyi; Yin, Guangheng; Zhang, Liping; Lv, Chuankai; Ji, Zhiying; Yu, Tong; Sabel, B A; He, Huiguang; Peng, Yun

2013-01-01

Tourette Syndrome (TS) is characterized with chronic motor and vocal tics beginning in childhood. Abnormality of both gray (GM) and white matter (WM) has been observed in cortico-striato-thalamo-cortical circuits and sensory-motor cortex of adult TS patient. It is not clear if these morphological changes are also present in TS children and if there are any microstructural changes of WM. To understand the developmental cause of such changes, we investigated volumetric changes of GM and WM using VBM and microstructural changes of WM using DTI, and correlated these changes with tic severity and duration. T1 images and Diffusion Tensor Images (DTI) from 21 TS children were compared with 20 age and gender matched health control children using a 1.5T Philips scanner. All of the 21 TS children met the DSM-IV-TR criteria. T1 images were analyzed using DARTEL-VBM in conjunction with statistical parametric mapping (SPM). Diffusion tensor imaging (DTI) analysis was performed using Tract-Based Spatial Statistics (TBSS). Brain volume changes were found in left superior temporal gyrus, left and right paracentral gyrus, right precuneous cortex, right pre- and post-central gyrus, left temporal occipital fusiform cortex, right frontal pole, and left lingual gyrus. Significant axial diffusivity (AD) and mean diffusivity (MD) increases were found in anterior thalamic radiation, right cingulum bundle projecting to the cingulate gurus and forceps minor. Decreases in white matter volume (WMV) in the right frontal pole were inversely related with tic severity (YGTSS), and increases in AD and MD were positively correlated with tic severity and duration, respectively. These changes in TS children can be interpreted as signs of neural plasticity in response to the experiential demand. Our findings may suggest that the morphological and microstructural measurements from structural MRI and DTI can potentially be used as a biomarker of the pathophysiologic pattern of early TS children.
Motor skill learning is associated with diffusion characteristics of white matter in individuals with chronic stroke.

PubMed

Borich, Michael R; Brown, Katlyn E; Boyd, Lara A

2014-07-01

Imaging advances allow investigation of white matter after stroke; a growing body of literature has shown links between diffusion-based measures of white matter microstructure and motor function. However, the relationship between these measures and motor skill learning has not been considered in individuals with stroke. The aim of this study was to investigate the relationships between posttraining white matter microstructural status, as indexed by diffusion tensor imaging within the ipsilesional posterior limb of the internal capsule (PLIC), and learning of a novel motor task in individuals with chronic stroke. A total of 13 participants with chronic stroke and 9 healthy controls practiced a visuomotor pursuit task across 5 sessions. Change in motor behavior associated with learning was indexed by comparing baseline performance with a delayed retention test. Fractional anisotropy (FA) indexed at the retention test was the primary diffusion tensor imaging-derived outcome measure. In individuals with chronic stroke, we discovered an association between posttraining ipsilesional PLIC FA and the magnitude of change associated with motor learning; hierarchical multiple linear regression analyses revealed that the combination of age, time poststroke, and ipsilesional PLIC FA posttraining was associated with motor learning-related change (R = 0.649; P = 0.02). Baseline motor performance was not related to posttraining ipsilesional PLIC FA. Diffusion characteristics of posttraining ipsilesional PLIC were linked to the magnitude of change in skilled motor behavior. These results imply that the microstructural properties of regional white matter indexed by diffusion behavior may be an important factor to consider when determining potential response to rehabilitation in persons with stroke. (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A59) for more insights from the authors.
In vivo High Angular Resolution Diffusion-Weighted Imaging of Mouse Brain at 16.4 Tesla

PubMed Central

Alomair, Othman I.; Brereton, Ian M.; Smith, Maree T.; Galloway, Graham J.; Kurniawan, Nyoman D.

2015-01-01

Magnetic Resonance Imaging (MRI) of the rodent brain at ultra-high magnetic fields (> 9.4 Tesla) offers a higher signal-to-noise ratio that can be exploited to reduce image acquisition time or provide higher spatial resolution. However, significant challenges are presented due to a combination of longer T 1 and shorter T 2/T2* relaxation times and increased sensitivity to magnetic susceptibility resulting in severe local-field inhomogeneity artefacts from air pockets and bone/brain interfaces. The Stejskal-Tanner spin echo diffusion-weighted imaging (DWI) sequence is often used in high-field rodent brain MRI due to its immunity to these artefacts. To accurately determine diffusion-tensor or fibre-orientation distribution, high angular resolution diffusion imaging (HARDI) with strong diffusion weighting (b >3000 s/mm2) and at least 30 diffusion-encoding directions are required. However, this results in long image acquisition times unsuitable for live animal imaging. In this study, we describe the optimization of HARDI acquisition parameters at 16.4T using a Stejskal-Tanner sequence with echo-planar imaging (EPI) readout. EPI segmentation and partial Fourier encoding acceleration were applied to reduce the echo time (TE), thereby minimizing signal decay and distortion artefacts while maintaining a reasonably short acquisition time. The final HARDI acquisition protocol was achieved with the following parameters: 4 shot EPI, b = 3000 s/mm2, 64 diffusion-encoding directions, 125×150 μm2 in-plane resolution, 0.6 mm slice thickness, and 2h acquisition time. This protocol was used to image a cohort of adult C57BL/6 male mice, whereby the quality of the acquired data was assessed and diffusion tensor imaging (DTI) derived parameters were measured. High-quality images with high spatial and angular resolution, low distortion and low variability in DTI-derived parameters were obtained, indicating that EPI-DWI is feasible at 16.4T to study animal models of white matter (WM) diseases. PMID:26110770
Structural abnormalities and altered regional brain activity in multiple sclerosis with simple spinal cord involvement.

PubMed

Yin, Ping; Liu, Yi; Xiong, Hua; Han, Yongliang; Sah, Shambhu Kumar; Zeng, Chun; Wang, Jingjie; Li, Yongmei

2018-02-01

To assess the changes of the structural and functional abnormalities in multiple sclerosis with simple spinal cord involvement (MS-SSCI) by using resting-state functional MRI (RS-fMRI), voxel based morphology (VBM) and diffusion tensor tractography. The amplitude of low-frequency fluctuation (ALFF) of 22 patients with MS-SSCI and 22 healthy controls (HCs) matched for age, gender and education were compared by using RS-fMRI. We also compared the volume, fractional anisotropy (FA) and apparent diffusion coefficient of the brain regions in baseline brain activity by using VBM and diffusion tensor imaging. The relationships between the expanded disability states scale (EDSS) scores, changed parameters of structure and function were further explored. (1) Compared with HCs, the ALFF of the bilateral hippocampus and right middle temporal gyrus in MS-SSCI decreased significantly. However, patients exhibited increased ALFF in the left middle frontal gyrus, left posterior cingulate gyrus and right middle occipital gyrus ( two-sample t-test, after AlphaSim correction, p < 0.01, voxel size > 40). The volume of right middle frontal gyrus reduced significantly (p < 0.01). The FA and ADC of right hippocampus, the FA of left hippocampus and right middle temporal gyrus were significantly different. (2) A significant correlation between EDSS scores and ALFF was noted only in the left posterior cingulate gyrus. Our results detected structural and functional abnormalities in MS-SSCI and functional parameters were associated with clinical abnormalities. Multimodal imaging plays an important role in detecting structural and functional abnormalities in MS-SSCI. Advances in knowledge: This is the first time to apply RS-fMRI, VBM and diffusion tensor tractography to study the structural and functional abnormalities in MS-SSCI, and to explore its correlation with EDSS score.
Bio-image warehouse system: concept and implementation of a diagnosis-based data warehouse for advanced imaging modalities in neuroradiology.

PubMed

Minati, L; Ghielmetti, F; Ciobanu, V; D'Incerti, L; Maccagnano, C; Bizzi, A; Bruzzone, M G

2007-03-01

Advanced neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), chemical shift spectroscopy imaging (CSI), diffusion tensor imaging (DTI), and perfusion-weighted imaging (PWI) create novel challenges in terms of data storage and management: huge amounts of raw data are generated, the results of analysis may depend on the software and settings that have been used, and most often intermediate files are inherently not compliant with the current DICOM (digital imaging and communication in medicine) standard, as they contain multidimensional complex and tensor arrays and various other types of data structures. A software architecture, referred to as Bio-Image Warehouse System (BIWS), which can be used alongside a radiology information system/picture archiving and communication system (RIS/PACS) system to store neuroimaging data for research purposes, is presented. The system architecture is conceived with the purpose of enabling to query by diagnosis according to a predefined two-layered classification taxonomy. The operational impact of the system and the time needed to get acquainted with the web-based interface and with the taxonomy are found to be limited. The development of modules enabling automated creation of statistical templates is proposed.
Diffusion MRI: Pitfalls, literature review and future directions of research in mild traumatic brain injury.

PubMed

Delouche, Aurélie; Attyé, Arnaud; Heck, Olivier; Grand, Sylvie; Kastler, Adrian; Lamalle, Laurent; Renard, Felix; Krainik, Alexandre

2016-01-01

Mild traumatic brain injury (mTBI) is a leading cause of disability in adults, many of whom report a distressing combination of physical, emotional and cognitive symptoms, collectively known as post-concussion syndrome, that persist after the injury. Significant developments in magnetic resonance diffusion imaging, involving voxel-based quantitative analysis through the measurement of fractional anisotropy or mean diffusivity, have enhanced our knowledge on the different stages of mTBI pathophysiology. Other diffusion imaging-derived techniques, including diffusion kurtosis imaging with multi-shell diffusion and high-order tractography models, have recently demonstrated their usefulness in mTBI. Our review starts by briefly outlining the physical basis of diffusion tensor imaging including the pitfalls for use in brain trauma, before discussing findings from diagnostic trials testing its usefulness in assessing brain structural changes in patients with mTBI. Use of different post-processing techniques for the diffusion imaging data, identified the corpus callosum as the most frequently injured structure in mTBI, particularly at sub-acute and chronic stages, and a crucial location for evaluating functional outcome. However, structural changes appear too subtle for identification using traditional diffusion biomarkers, thus disallowing expansion of these techniques into clinical practice. In this regard, more advanced diffusion techniques are promising in the assessment of this complex disease. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
* A 3D Tissue-Printing Approach for Validation of Diffusion Tensor Imaging in Skeletal Muscle.

PubMed

Berry, David B; You, Shangting; Warner, John; Frank, Lawrence R; Chen, Shaochen; Ward, Samuel R

2017-09-01

The ability to noninvasively assess skeletal muscle microstructure, which predicts function and disease, would be of significant clinical value. One method that holds this promise is diffusion tensor magnetic resonance imaging (DT-MRI), which is sensitive to the microscopic diffusion of water within tissues and has become ubiquitous in neuroimaging as a way of assessing neuronal structure and damage. However, its application to the assessment of changes in muscle microstructure associated with injury, pathology, or age remains poorly defined, because it is difficult to precisely control muscle microstructural features in vivo. However, recent advances in additive manufacturing technologies allow precision-engineered diffusion phantoms with histology informed skeletal muscle geometry to be manufactured. Therefore, the goal of this study was to develop skeletal muscle phantoms at relevant size scales to relate microstructural features to MRI-based diffusion measurements. A digital light projection based rapid 3D printing method was used to fabricate polyethylene glycol diacrylate based diffusion phantoms with (1) idealized muscle geometry (no geometry; fiber sizes of 30, 50, or 70 μm or fiber size of 50 μm with 40% of walls randomly deleted) or (2) histology-based geometry (normal and after 30-days of denervation) containing 20% or 50% phosphate-buffered saline (PBS). Mean absolute percent error (8%) of the printed phantoms indicated high conformity to templates when "fibers" were >50 μm. A multiple spin-echo echo planar imaging diffusion sequence, capable of acquiring diffusion weighted data at several echo times, was used in an attempt to combine relaxometry and diffusion techniques with the goal of separating intracellular and extracellular diffusion signals. When fiber size increased (30-70 μm) in the 20% PBS phantom, fractional anisotropy (FA) decreased (0.32-0.26) and mean diffusivity (MD) increased (0.44 × 10 -3 mm 2 /s-0.70 × 10 -3 mm 2 /s). Similarly, when fiber size increased from 30 to 70 μm in the 50% PBS diffusion phantoms, a small change in FA was observed (0.18-0.22), but MD increased from 0.86 × 10 -3 mm 2 /s to 1.79 × 10 -3 mm 2 /s. This study demonstrates a novel application of tissue engineering to understand complex diffusion signals in skeletal muscle. Through this work, we have also demonstrated the feasibility of 3D printing for skeletal muscle with relevant matrix geometries and physiologically relevant tissue characteristics.
Age Related Differences in Diffusion Tensor Indices and Fiber Architecture in the Medial and Lateral Gastrocnemius

PubMed Central

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
Age-related differences in diffusion tensor indices and fiber architecture in the medial and lateral gastrocnemius.

PubMed

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.
Determination of mouse skeletal muscle architecture using three-dimensional diffusion tensor imaging.

PubMed

Heemskerk, Anneriet M; Strijkers, Gustav J; Vilanova, Anna; Drost, Maarten R; Nicolay, Klaas

2005-06-01

Muscle architecture is the main determinant of the mechanical behavior of skeletal muscles. This study explored the feasibility of diffusion tensor imaging (DTI) and fiber tracking to noninvasively determine the in vivo three-dimensional (3D) architecture of skeletal muscle in mouse hind leg. In six mice, the hindlimb was imaged with a diffusion-weighted (DW) 3D fast spin-echo (FSE) sequence followed by the acquisition of an exercise-induced, T(2)-enhanced data set. The data showed the expected fiber organization, from which the physiological cross-sectional area (PCSA), fiber length, and pennation angle for the tibialis anterior (TA) were obtained. The values of these parameters ranged from 5.4-9.1 mm(2), 5.8-7.8 mm, and 21-24 degrees , respectively, which is in agreement with values obtained previously with the use of invasive methods. This study shows that 3D DT acquisition and fiber tracking is feasible for the skeletal muscle of mice, and thus enables the quantitative determination of muscle architecture.
High Efficiency, Low Distortion 3D Diffusion Tensor Imaging with Variable Density Spiral Fast Spin Echoes (3D DW VDS RARE)

PubMed Central

Frank, Lawrence R.; Jung, Youngkyoo; Inati, Souheil; Tyszka, J. Michael; Wong, Eric C.

2009-01-01

We present an acquisition and reconstruction method designed to acquire high resolution 3D fast spin echo diffusion tensor images while mitigating the major sources of artifacts in DTI - field distortions, eddy currents and motion. The resulting images, being 3D, are of high SNR, and being fast spin echoes, exhibit greatly reduced field distortions. This sequence utilizes variable density spiral acquisition gradients, which allow for the implementation of a self-navigation scheme by which both eddy current and motion artifacts are removed. The result is that high resolution 3D DTI images are produced without the need for eddy current compensating gradients or B0 field correction. In addition, a novel method for fast and accurate reconstruction of the non-Cartesian data is employed. Results are demonstrated in the brains of normal human volunteers. PMID:19778618

Diagnosis of Lumbar Foraminal Stenosis using Diffusion Tensor Imaging.

PubMed

Eguchi, Yawara; Ohtori, Seiji; Suzuki, Munetaka; Oikawa, Yasuhiro; Yamanaka, Hajime; Tamai, Hiroshi; Kobayashi, Tatsuya; Orita, Sumihisa; Yamauchi, Kazuyo; Suzuki, Miyako; Aoki, Yasuchika; Watanabe, Atsuya; Kanamoto, Hirohito; Takahashi, Kazuhisa

2016-02-01

Diagnosis of lumbar foraminal stenosis remains difficult. Here, we report on a case in which bilateral lumbar foraminal stenosis was difficult to diagnose, and in which diffusion tensor imaging (DTI) was useful. The patient was a 52-year-old woman with low back pain and pain in both legs that was dominant on the right. Right lumbosacral nerve compression due to a massive uterine myoma was apparent, but the leg pain continued after a myomectomy was performed. No abnormalities were observed during nerve conduction studies. Computed tomography and magnetic resonance imaging indicated bilateral L5 lumbar foraminal stenosis. DTI imaging was done. The extraforaminal values were decreased and tractography was interrupted in the foraminal region. Bilateral L5 vertebral foraminal stenosis was treated by transforaminal lumbar interbody fusion and the pain in both legs disappeared. The case indicates the value of DTI for diagnosing vertebral foraminal stenosis.
Fast and Analytical EAP Approximation from a 4th-Order Tensor.

PubMed

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

PubMed Central

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
The tensor distribution function.

PubMed

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.
Prediction of neurodevelopmental outcome after hypoxic-ischemic encephalopathy treated with hypothermia by diffusion tensor imaging analyzed using tract-based spatial statistics.

PubMed

Tusor, Nora; Wusthoff, Courtney; Smee, Natalie; Merchant, Nazakat; Arichi, Tomoki; Allsop, Joanna M; Cowan, Frances M; Azzopardi, Denis; Edwards, A David; Counsell, Serena J

2012-07-01

Objective biomarkers are needed to assess neuroprotective therapies after perinatal hypoxic-ischemic encephalopathy (HIE). We tested the hypothesis that, in infants who underwent therapeutic hypothermia after perinatal HIE, neurodevelopmental performance was predicted by fractional anisotropy (FA) values in the white matter (WM) on early diffusion tensor imaging (DTI) as assessed by means of tract-based spatial statistics (TBSS). We studied 43 term infants with HIE. Developmental assessments were carried out at a median (range) age of 24 (12-28) mo. As compared with infants with favorable outcomes, those with unfavorable outcomes had significantly lower FA values (P < 0.05) in the centrum semiovale, corpus callosum (CC), anterior and posterior limbs of the internal capsule, external capsules, fornix, cingulum, cerebral peduncles, optic radiations, and inferior longitudinal fasciculus. In a second analysis in 32 assessable infants, the Griffiths Mental Development Scales (Revised) (GMDS-R) showed a significant linear correlation (P < 0.05) between FA values and developmental quotient (DQ) and all its component subscale scores. DTI analyzed by TBSS provides a qualified biomarker that can be used to assess the efficacy of additional neuroprotective therapies after HIE.
Intrinsic disruption of white matter microarchitecture in first-episode, drug-naive major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging.

PubMed

Chen, Guangxiang; Guo, Yi; Zhu, Hongyan; Kuang, Weihong; Bi, Feng; Ai, Hua; Gu, Zhongwei; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

2017-06-02

Previous studies have demonstrated the influences of episodes and antidepressant drugs on white matter (WM) in patients with major depressive disorder (MDD). However, most diffusion tensor imaging (DTI) studies included highly heterogeneous individuals with different numbers of depressive episodes or medication status. To exclude the confounding effects of multiple episodes or medication, we conducted a quantitative voxel-based meta-analysis of fractional anisotropy (FA) in patients with first-episode, drug-naive MDD to identify the intrinsic WM alterations involved in the pathogenesis of MDD. The pooled meta-analysis revealed significant FA reductions in the body of the corpus callosum (CC), bilateral anterior limb of the internal capsule (ALIC), right inferior temporal gyrus (ITG) and right superior frontal gyrus (SFG) in MDD patients relative to healthy controls. Meta-regression analyses revealed that FA reduction in the right ALIC and right SFG was negatively correlated with symptom severity and duration of depression, respectively. Our findings provide robust evidence that the WM impairments in the interhemispheric connections and frontal-subcortical neuronal circuits may play an important role in MDD pathogenesis. Copyright © 2017. Published by Elsevier Inc.
FADTTSter: accelerating hypothesis testing with functional analysis of diffusion tensor tract statistics

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.
3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).
A Diffusion Tensor Imaging Study on the White Matter Skeleton in Individuals with Sports-Related Concussion

PubMed Central

Cubon, Valerie A.; Putukian, Margot; Boyer, Cynthia

2011-01-01

Abstract Recognizing and managing the effects of cerebral concussion is very challenging, given the discrete symptomatology. Most individuals with sports-related concussion will not score below 15 on the Glasgow Coma Scale, but will present with rapid onset of short-lived neurological impairment, demonstrating no structural changes on traditional magnetic resonance imaging (MRI) and computed tomography (CT) scans. The return-to-play decision is one of the most difficult responsibilities facing the physician, and so far this decision has been primarily based on neurological examination, symptom checklists, and neuropsychological (NP) testing. Diffusion tensor imaging (DTI) may be a more objective tool to assess the severity and recovery of function after concussion. We assessed white matter (WM) fiber tract integrity in varsity level college athletes with sports-related concussion without loss of consciousness, who experienced protracted symptoms for at least 1 month after injury. Evaluation of fractional anisotropy (FA) and mean diffusivity (MD) of the WM skeleton using tract-based spatial statistics (TBSS) revealed a large cluster of significantly increased MD for concussed subjects in several WM fiber tracts in the left hemisphere, including parts of the inferior/superior longitudinal and fronto-occipital fasciculi, the retrolenticular part of the internal capsule, and posterior thalamic and acoustic radiations. Qualitative comparison of average FA and MD suggests that with increasing level of injury severity (ranging from sports-related concussion to severe traumatic brain injury), MD might be more sensitive at detecting mild injury, whereas FA captures more severe injuries. In conclusion, the TBSS analysis used to evaluate diffuse axonal injury of the WM skeleton seems sensitive enough to detect structural changes in sports-related concussion. PMID:21083414
Relationship between suicidality and impulsivity in bipolar I disorder: a diffusion tensor imaging study

PubMed Central

Mahon, Katie; Burdick, Katherine E; Wu, Jinghui; Ardekani, Babak A; Szeszko, Philip R

2012-01-01

Background Impulsivity is characteristic of individuals with bipolar disorder and may be a contributing factor to the high rate of suicide in patients with this disorder. Although white matter abnormalities have been implicated in the pathophysiology of bipolar disorder, their relationship to impulsivity and suicidality in this disorder has not been well-investigated. Methods Diffusion tensor imaging scans were acquired in 14 bipolar disorder patients with a prior suicide attempt, 15 bipolar disorder patients with no prior suicide attempt, and 15 healthy volunteers. Bipolar disorder patients received clinical assessments including measures of impulsivity, depression, mania, and anxiety. Images were processed using the Tract-Based Spatial Statistics method in the FSL software package. Results Bipolar disorder patients with a prior suicide attempt had lower fractional anisotropy (FA) within the left orbital frontal white matter (p < 0.05, corrected) and higher overall impulsivity compared to patients without a previous suicide attempt. Among patients with a prior suicide attempt, FA in the orbital frontal white matter region correlated inversely with motor impulsivity. Conclusions Abnormal orbital frontal white matter may play a role in impulsive and suicidal behavior among patients with bipolar disorder. PMID:22329475
Abnormal cholesterol is associated with prefrontal white matter abnormalities among obese adults, a diffusion tensor imaging study

PubMed Central

Cohen, Jessica I.; Cazettes, Fanny; Convit, Antonio

2011-01-01

The brain is the most cholesterol-rich organ in the body. Although most of the cholesterol in the brain is produced endogenously, some studies suggest that systemic cholesterol may be able to enter the brain. We investigated whether abnormal cholesterol profiles correlated with diffusion-tensor-imaging-based estimates of white matter microstructural integrity of lean and overweight/obese (o/o) adults. Twenty-two lean and 39 obese adults underwent magnetic resonance imaging, kept a 3-day food diary, and had a standardized assessment of fasting blood lipids. The lean group ate less cholesterol rich food than o/o although both groups ate equivalent servings of food per day. Voxelwise correlational analyses controlling for age, diabetes, and white matter hyperintensities, resulted in two significant clusters of negative associations between abnormal cholesterol profile and fractional anisotropy, located in the left and right prefrontal lobes. When the groups were split, the lean subjects showed no associations, whereas the o/o group expanded the association to three significant clusters, still in the frontal lobes. These findings suggest that cholesterol profile abnormalities may explain some of the reductions in white matter microstructural integrity that are reported in obesity. PMID:22163070
Reproducibility Analysis of Diffusion Tensor Indices and Fiber Architecture of Human Calf Muscles in vivo at 1.5 Tesla in Neutral and Plantarflexed Ankle Positions at Rest

PubMed Central

Sinha, Shantanu; Sinha, Usha

2011-01-01

Purpose To investigate the reproducibility of diffusion tensor imaging (DTI) derived indices and fiber architecture of calf muscles at 1.5 Tesla, to establish an imaging based method to confirm ankle position, and to compare fiber architecture at different ankle positions. Materials and Methods Six subjects were imaged at 1.5T with the foot in neutral and plantarflexed positions. DTI indices were calculated in four muscle compartments (medial and lateral gastrocnemius (MG, LG), superficial and deep anterior tibialis (AT-S, AT-D). Two subjects were scanned on three days to calculate the coefficient of variability (CV) and the repeatability coefficient (RC). Results DTI indices were close to the values obtained in earlier 3T and 1.5 T studies. FA decreased significantly in the MG and increased significantly in the AT-S and AT-D compartments while fiber orientation with respect to the magnet Z-axis increased significantly in the MG and decreased significantly in the AT-S compartment with plantarflexion. The CV and RC for the DTI indices and fiber orientations were comparable to 3T studies. Fiber lengths and orientation angles in the MG matched corresponding measures from ultrasound studies. Conclusion DTI at 1.5 Tesla provides reproducible measures of diffusion indices and fiber architecture of calf muscle at different muscle lengths. PMID:21608064
Quantitative analysis of diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) for brain disorders

NASA Astrophysics Data System (ADS)

Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon

2013-07-01

This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.
Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

PubMed

Dyrba, Martin; Barkhof, Frederik; Fellgiebel, Andreas; Filippi, Massimo; Hausner, Lucrezia; Hauenstein, Karlheinz; Kirste, Thomas; Teipel, Stefan J

2015-01-01

Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI). We applied a Support Vector Machine (SVM) classifier to DTI and volumetric magnetic resonance imaging data from 35 amyloid-β42 negative MCI subjects (MCI-Aβ42-), 35 positive MCI subjects (MCI-Aβ42+), and 25 healthy controls (HC) retrieved from the European DTI Study on Dementia. The SVM was applied to DTI-derived fractional anisotropy, mean diffusivity (MD), and mode of anisotropy (MO) maps. For comparison, we studied classification based on gray matter (GM) and WM volume. We obtained accuracies of up to 68% for MO and 63% for GM volume when it came to distinguishing between MCI-Aβ42- and MCI-Aβ42+. When it came to separating MCI-Aβ42+ from HC we achieved an accuracy of up to 77% for MD and a significantly lower accuracy of 68% for GM volume. The accuracy of multimodal classification was not higher than the accuracy of the best single modality. Our results suggest that DTI data provide better prediction accuracy than GM volume in predementia AD. Copyright © 2015 by the American Society of Neuroimaging.
Correlation of dopaminergic terminal dysfunction and microstructural abnormalities of the basal ganglia and the olfactory tract in Parkinson's disease.

PubMed

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.
Investigating Architectural Issues in Neuromorphic Computing

DTIC Science & Technology

2009-06-01

An example of this is Diffusion Tensor Imaging ( DTI ), a variant of fMRI, which detects water diffusion. DTI is routinely applied at medical...model computed for a subfield positioned over a section of the silhouette dog’s hind leg . The illustrated angles roughly correspond to orientation
Serial proton MR spectroscopy and diffusion tensor imaging in infantile Balo's concentric sclerosis.

PubMed

Dreha-Kulaczewski, Steffi F; Helms, Gunther; Dechent, Peter; Hofer, Sabine; Gärtner, Jutta; Frahm, Jens

2009-02-01

Proton magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) yield different parameters for characterizing the evolution of a demyelinating white matter disease. The purpose was to elucidate biochemical and microstructural changes in Balo's concentric sclerosis lesions and to correlate the findings with the clinical course. Localized short-echo time MRS and DTI were performed over 6 years in a left occipital lesion of a female patient (age at onset 13.8 years) with Balo's concentric sclerosis. A right homonym hemianopsia persisted. Metabolite patterns were in line with initial active demyelination followed by gliosis and partial recovery of neuroaxonal metabolites. Fractional anisotropy and mean diffusivity of tissue water remained severely altered. Fiber tracking confirmed a disruption in the geniculo-calcarine tract as well as involvement of the corpus callosum. MRS and DTI depict complementary parameters, but DTI seems to correlate better with clinical symptoms.
Fast estimation of diffusion tensors under Rician noise by the EM algorithm.

PubMed

Liu, Jia; Gasbarra, Dario; Railavo, Juha

2016-01-15

Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a fast computational method for maximum likelihood estimation (MLE) of diffusivities under the Rician noise model based on the expectation maximization (EM) algorithm. By using data augmentation, we are able to transform a non-linear regression problem into the generalized linear modeling framework, reducing dramatically the computational cost. The Fisher-scoring method is used for achieving fast convergence of the tensor parameter. The new method is implemented and applied using both synthetic and real data in a wide range of b-amplitudes up to 14,000s/mm(2). Higher accuracy and precision of the Rician estimates are achieved compared with other log-normal based methods. In addition, we extend the maximum likelihood (ML) framework to the maximum a posteriori (MAP) estimation in DTI under the aforementioned scheme by specifying the priors. We will describe how close numerically are the estimators of model parameters obtained through MLE and MAP estimation. Copyright © 2015 Elsevier B.V. All rights reserved.
Multi-Shell Hybrid Diffusion Imaging (HYDI) at 7 Tesla in TgF344-AD Transgenic Alzheimer Rats.

PubMed

Daianu, Madelaine; Jacobs, Russell E; Weitz, Tara M; Town, Terrence C; Thompson, Paul M

2015-01-01

Diffusion weighted imaging (DWI) is widely used to study microstructural characteristics of the brain. Diffusion tensor imaging (DTI) and high-angular resolution imaging (HARDI) are frequently used in radiology and neuroscience research but can be limited in describing the signal behavior in composite nerve fiber structures. Here, we developed and assessed the benefit of a comprehensive diffusion encoding scheme, known as hybrid diffusion imaging (HYDI), composed of 300 DWI volumes acquired at 7-Tesla with diffusion weightings at b = 1000, 3000, 4000, 8000 and 12000 s/mm2 and applied it in transgenic Alzheimer rats (line TgF344-AD) that model the full clinico-pathological spectrum of the human disease. We studied and visualized the effects of the multiple concentric "shells" when computing three distinct anisotropy maps-fractional anisotropy (FA), generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA). We tested the added value of the multi-shell q-space sampling scheme, when reconstructing neural pathways using mathematical frameworks from DTI and q-ball imaging (QBI). We show a range of properties of HYDI, including lower apparent anisotropy when using high b-value shells in DTI-based reconstructions, and increases in apparent anisotropy in QBI-based reconstructions. Regardless of the reconstruction scheme, HYDI improves FA-, GFA- and NQA-aided tractography. HYDI may be valuable in human connectome projects and clinical research, as well as magnetic resonance research in experimental animals.
Multi-Shell Hybrid Diffusion Imaging (HYDI) at 7 Tesla in TgF344-AD Transgenic Alzheimer Rats

PubMed Central

Daianu, Madelaine; Jacobs, Russell E.; Weitz, Tara M.; Town, Terrence C.; Thompson, Paul M.

2015-01-01

Diffusion weighted imaging (DWI) is widely used to study microstructural characteristics of the brain. Diffusion tensor imaging (DTI) and high-angular resolution imaging (HARDI) are frequently used in radiology and neuroscience research but can be limited in describing the signal behavior in composite nerve fiber structures. Here, we developed and assessed the benefit of a comprehensive diffusion encoding scheme, known as hybrid diffusion imaging (HYDI), composed of 300 DWI volumes acquired at 7-Tesla with diffusion weightings at b = 1000, 3000, 4000, 8000 and 12000 s/mm2 and applied it in transgenic Alzheimer rats (line TgF344-AD) that model the full clinico-pathological spectrum of the human disease. We studied and visualized the effects of the multiple concentric “shells” when computing three distinct anisotropy maps–fractional anisotropy (FA), generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA). We tested the added value of the multi-shell q-space sampling scheme, when reconstructing neural pathways using mathematical frameworks from DTI and q-ball imaging (QBI). We show a range of properties of HYDI, including lower apparent anisotropy when using high b-value shells in DTI-based reconstructions, and increases in apparent anisotropy in QBI-based reconstructions. Regardless of the reconstruction scheme, HYDI improves FA-, GFA- and NQA-aided tractography. HYDI may be valuable in human connectome projects and clinical research, as well as magnetic resonance research in experimental animals. PMID:26683657

FY09 Annual Report to the Executive Agent

DTIC Science & Technology

2009-01-01

tensor imaging ( DTI ) after follow-up im- aging studies. This case report was published in Neuroimage, 2009 Aug; 47 Suppl 2:T152-3. Epub 2009 Feb 10 and...27(7), 2009. Diffusion Tensor Imaging Study Shows Blast Injury May Cause Brain Inflammation Researchers from the DCoE for PH/TBI used DTI to...similar to what occurs in the brain with infection or stroke. DTI in blast patients was different from the pattern seen for the traditional impact forms
Application of Diffusion Tensor Imaging Parameters to Detect Change in Longitudinal Studies in Cerebral Small Vessel Disease.

PubMed

Zeestraten, Eva Anna; Benjamin, Philip; Lambert, Christian; Lawrence, Andrew John; Williams, Owen Alan; Morris, Robin Guy; Barrick, Thomas Richard; Markus, Hugh Stephen

2016-01-01

Cerebral small vessel disease (SVD) is the major cause of vascular cognitive impairment, resulting in significant disability and reduced quality of life. Cognitive tests have been shown to be insensitive to change in longitudinal studies and, therefore, sensitive surrogate markers are needed to monitor disease progression and assess treatment effects in clinical trials. Diffusion tensor imaging (DTI) is thought to offer great potential in this regard. Sensitivity of the various parameters that can be derived from DTI is however unknown. We aimed to evaluate the differential sensitivity of DTI markers to detect SVD progression, and to estimate sample sizes required to assess therapeutic interventions aimed at halting decline based on DTI data. We investigated 99 patients with symptomatic SVD, defined as clinical lacunar syndrome with MRI confirmation of a corresponding infarct as well as confluent white matter hyperintensities over a 3 year follow-up period. We evaluated change in DTI histogram parameters using linear mixed effect models and calculated sample size estimates. Over a three-year follow-up period we observed a decline in fractional anisotropy and increase in diffusivity in white matter tissue and most parameters changed significantly. Mean diffusivity peak height was the most sensitive marker for SVD progression as it had the smallest sample size estimate. This suggests disease progression can be monitored sensitively using DTI histogram analysis and confirms DTI's potential as surrogate marker for SVD.
Test-Retest Reliability of Diffusion Tensor Imaging in Huntington's Disease.

PubMed

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.
Diffusion Tensor Imaging of Frontal White Matter and Executive Functioning in Cocaine-Exposed Children

PubMed Central

Warner, Tamara Duckworth; Behnke, Marylou; Eyler, Fonda Davis; Padgett, Kyle; Leonard, Christiana; Hou, Wei; Garvan, Cynthia Wilson; Schmalfuss, Ilona M.; Blackband, Stephen J.

2011-01-01

BACKGROUND Although animal studies have demonstrated frontal white matter and behavioral changes resulting from prenatal cocaine exposure, no human studies have associated neuropsychological deficits in attention and inhibition with brain structure. We used diffusion tensor imaging to investigate frontal white matter integrity and executive functioning in cocaine-exposed children. METHODS Six direction diffusion tensor images were acquired using a Siemens 3T scanner with a spin-echo echo-planar imaging pulse sequence on right-handed cocaine-exposed (n = 28) and sociodemographically similar non-exposed children (n = 25; mean age: 10.6 years) drawn from a prospective, longitudinal study. Average diffusion and fractional anisotropy were measured in the left and right frontal callosal and frontal projection fibers. Executive functioning was assessed using two well-validated neuropsychological tests (Stroop color-word test and Trail Making Test). RESULTS Cocaine-exposed children showed significantly higher average diffusion in the left frontal callosal and right frontal projection fibers. Cocaine-exposed children were also significantly slower on a visual-motor set-shifting task with a trend toward lower scores on a verbal inhibition task. Controlling for gender and intelligence, average diffusion in the left frontal callosal fibers was related to prenatal exposure to alcohol and marijuana and an interaction between cocaine and marijuana exposure. Performance on the visual-motor set-shifting task was related to prenatal cocaine exposure and an interaction between cocaine and tobacco exposure. Significant correlations were found between test performance and fractional anisotropy in areas of the frontal white matter. CONCLUSIONS Prenatal cocaine exposure, alone and in combination with exposure to other drugs, is associated with slightly poorer executive functioning and subtle microstructural changes suggesting less mature development of frontal white matter pathways. The relative contribution of postnatal environmental factors, including characteristics of the caregiving environment and stressors associated with poverty and out-of-home placement, on brain development and behavioral functioning in polydrug-exposed children awaits further research. PMID:17079574
Diffusion tensor imaging of frontal white matter and executive functioning in cocaine-exposed children.

PubMed

Warner, Tamara Duckworth; Behnke, Marylou; Eyler, Fonda Davis; Padgett, Kyle; Leonard, Christiana; Hou, Wei; Garvan, Cynthia Wilson; Schmalfuss, Ilona M; Blackband, Stephen J

2006-11-01

Although animal studies have demonstrated frontal white matter and behavioral changes resulting from prenatal cocaine exposure, no human studies have associated neuropsychological deficits in attention and inhibition with brain structure. We used diffusion tensor imaging to investigate frontal white matter integrity and executive functioning in cocaine-exposed children. Six direction diffusion tensor images were acquired using a Siemens 3T scanner with a spin-echo echo-planar imaging pulse sequence on right-handed cocaine-exposed (n = 28) and sociodemographically similar non-exposed children (n = 25; mean age: 10.6 years) drawn from a prospective, longitudinal study. Average diffusion and fractional anisotropy were measured in the left and right frontal callosal and frontal projection fibers. Executive functioning was assessed using two well-validated neuropsychological tests (Stroop color-word test and Trail Making Test). Cocaine-exposed children showed significantly higher average diffusion in the left frontal callosal and right frontal projection fibers. Cocaine-exposed children were also significantly slower on a visual-motor set-shifting task with a trend toward lower scores on a verbal inhibition task. Controlling for gender and intelligence, average diffusion in the left frontal callosal fibers was related to prenatal exposure to alcohol and marijuana and an interaction between cocaine and marijuana exposure. Performance on the visual-motor set-shifting task was related to prenatal cocaine exposure and an interaction between cocaine and tobacco exposure. Significant correlations were found between test performance and fractional anisotropy in areas of the frontal white matter. Prenatal cocaine exposure, alone and in combination with exposure to other drugs, is associated with slightly poorer executive functioning and subtle microstructural changes suggesting less mature development of frontal white matter pathways. The relative contribution of postnatal environmental factors, including characteristics of the caregiving environment and stressors associated with poverty and out-of-home placement, on brain development and behavioral functioning in polydrug-exposed children awaits further research.
The Plasticity of the Superior Longitudinal Fasciculus as a Function of Musical Expertise: A Diffusion Tensor Imaging Study

PubMed Central

Oechslin, Mathias S.; Imfeld, Adrian; Loenneker, Thomas; Meyer, Martin; Jäncke, Lutz

2009-01-01

Previous neuroimaging studies have demonstrated that musical expertise leads to functional alterations in language processing. We utilized diffusion tensor imaging (DTI) to investigate white matter plasticity in musicians with absolute pitch (AP), relative pitch and non-musicians. Using DTI, we analysed the fractional anisotropy (FA) of the superior longitudinal fasciculus (SLF), which is considered the most primary pathway for processing and production of speech and music. In association with different levels of musical expertise, we found that AP is characterized by a greater left than right asymmetry of FA in core fibres of the SLF. A voxel-based analysis revealed three clusters within the left hemisphere SLF that showed significant positive correlations with error rates only for AP-musicians in an AP-test, but not for musicians without AP. We therefore conclude that the SLF architecture in AP musicians is related to AP acuity. In order to reconcile our observations with general aspects of development of fibre bundles, we introduce the Pioneer Axon Thesis, a theoretical approach to formalize axonal arrangements of major white matter pathways. PMID:20161812
Axial and radial diffusivity in preterm infants who have diffuse white matter changes on magnetic resonance imaging at term-equivalent age.

PubMed

Counsell, Serena J; Shen, Yuji; Boardman, James P; Larkman, David J; Kapellou, Olga; Ward, Philip; Allsop, Joanna M; Cowan, Frances M; Hajnal, Joseph V; Edwards, A David; Rutherford, Mary A

2006-02-01

Diffuse excessive high signal intensity (DEHSI) is observed in the majority of preterm infants at term-equivalent age on conventional MRI, and diffusion-weighted imaging has shown that apparent diffusion coefficient values are elevated in the white matter (WM) in DEHSI. Our aim was to obtain diffusion tensor imaging on preterm infants at term-equivalent age and term control infants to test the hypothesis that radial diffusivity was significantly different in the WM in preterm infants with DEHSI compared with both preterm infants with normal-appearing WM on conventional MRI and term control infants. Diffusion tensor imaging was obtained on 38 preterm infants at term-equivalent age and 8 term control infants. Values for axial (lambda1) and radial [(lambda2 + lambda3)/2] diffusivity were calculated in regions of interest positioned in the central WM at the level of the centrum semiovale, frontal WM, posterior periventricular WM, occipital WM, anterior and posterior portions of the posterior limb of the internal capsule, and the genu and splenium of the corpus callosum. Radial diffusivity was elevated significantly in the posterior portion of the posterior limb of the internal capsule and the splenium of the corpus callosum, and both axial and radial diffusivity were elevated significantly in the WM at the level of the centrum semiovale, the frontal WM, the periventricular WM, and the occipital WM in preterm infants with DEHSI compared with preterm infants with normal-appearing WM and term control infants. There was no significant difference between term control infants and preterm infants with normal-appearing WM in any region studied. These findings suggest that DEHSI represents an oligodendrocyte and/or axonal abnormality that is widespread throughout the cerebral WM.
Mathematical abilities in dyslexic children: a diffusion tensor imaging study.

PubMed

Koerte, Inga K; Willems, Anna; Muehlmann, Marc; Moll, Kristina; Cornell, Sonia; Pixner, Silvia; Steffinger, Denise; Keeser, Daniel; Heinen, Florian; Kubicki, Marek; Shenton, Martha E; Ertl-Wagner, Birgit; Schulte-Körne, Gerd

2016-09-01

Dyslexia is characterized by a deficit in language processing which mainly affects word decoding and spelling skills. In addition, children with dyslexia also show problems in mathematics. However, for the latter, the underlying structural correlates have not been investigated. Sixteen children with dyslexia (mean age 9.8 years [0.39]) and 24 typically developing children (mean age 9.9 years [0.29]) group matched for age, gender, IQ, and handedness underwent 3 T MR diffusion tensor imaging as well as cognitive testing. Tract-Based Spatial Statistics were performed to correlate behavioral data with diffusion data. Children with dyslexia performed worse than controls in standardized verbal number tasks, such as arithmetic efficiency tests (addition, subtraction, multiplication, division). In contrast, the two groups did not differ in the nonverbal number line task. Arithmetic efficiency, representing the total score of the four arithmetic tasks, multiplication, and division, correlated with diffusion measures in widespread areas of the white matter, including bilateral superior and inferior longitudinal fasciculi in children with dyslexia compared to controls. Children with dyslexia demonstrated lower performance in verbal number tasks but performed similarly to controls in a nonverbal number task. Further, an association between verbal arithmetic efficiency and diffusion measures was demonstrated in widespread areas of the white matter suggesting compensatory mechanisms in children with dyslexia compared to controls. Taken together, poor fact retrieval in children with dyslexia is likely a consequence of deficits in the language system, which not only affects literacy skills but also impacts on arithmetic skills.
Persistent Microstructural Deficits of Internal Capsule in One-Year Abstinent Male Methamphetamine Users: a Longitudinal Diffusion Tensor Imaging Study.

PubMed

Zhuang, Wenxu; Tang, Yingying; Zhong, Na; Jiang, Haifeng; Du, Jiang; Wang, Jijun; Zhao, Min

2016-09-01

White matter (WM) alterations have been reported in methamphetamine (MA) users. However, knowledge about longitudinal changes in WM during abstinence from MA remains unknown. The present study aimed to examine how WM changes in long-term MA abstinent, in particular, whether the WM deficits would recover as the duration of abstinence extended. Twenty male MA dependent individuals and 19 healthy controls (HCs) were recruited and participated in both clinical assessments and diffusion tensor imaging (DTI) scans. The MA group underwent two DTI scans, a baseline scan with a duration of abstinence of 6.4 months and and a follow-up scan with a duration of abstinence of 13.0 months. Tract-Based Spatial Statistics was utilized to conduct baseline DTI analysis of MA group compared with HCs. The clusters with significant group differences of factional anisotropy (FA) were extracted as region of interests (ROIs). Mean values of DTI measurements (FA, mean diffusivity, axial diffusivity and radial diffusivity) were calculated within the ROIs in each subject's native space at baseline and follow-up. The MA group showed significant lower FA in the right internal capsule and superior corona radiate than HCs. The deficits did not recover when the duration of abstinence from MA reached 13 months. No significant correlations were found between FA and clinical measurements. Our results suggested persistent microstructure deficits of WM tracts surrounding the basal ganglia in MA dependent individuals.
Tri-linear interpolation-based cerebral white matter fiber imaging

PubMed Central

Jiang, Shan; Zhang, Pengfei; Han, Tong; Liu, Weihua; Liu, Meixia

2013-01-01

Diffusion tensor imaging is a unique method to visualize white matter fibers three-dimensionally, non-invasively and in vivo, and therefore it is an important tool for observing and researching neural regeneration. Different diffusion tensor imaging-based fiber tracking methods have been already investigated, but making the computing faster, fiber tracking longer and smoother and the details shown clearer are needed to be improved for clinical applications. This study proposed a new fiber tracking strategy based on tri-linear interpolation. We selected a patient with acute infarction of the right basal ganglia and designed experiments based on either the tri-linear interpolation algorithm or tensorline algorithm. Fiber tracking in the same regions of interest (genu of the corpus callosum) was performed separately. The validity of the tri-linear interpolation algorithm was verified by quantitative analysis, and its feasibility in clinical diagnosis was confirmed by the contrast between tracking results and the disease condition of the patient as well as the actual brain anatomy. Statistical results showed that the maximum length and average length of the white matter fibers tracked by the tri-linear interpolation algorithm were significantly longer. The tracking images of the fibers indicated that this method can obtain smoother tracked fibers, more obvious orientation and clearer details. Tracking fiber abnormalities are in good agreement with the actual condition of patients, and tracking displayed fibers that passed though the corpus callosum, which was consistent with the anatomical structures of the brain. Therefore, the tri-linear interpolation algorithm can achieve a clear, anatomically correct and reliable tracking result. PMID:25206524
FADTTS: functional analysis of diffusion tensor tract statistics.

PubMed

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.
Effects of image distortions originating from susceptibility variations and concomitant fields on diffusion MRI tractography results

PubMed Central

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
Differentiating between axonal damage and demyelination in healthy aging by combining diffusion-tensor imaging and diffusion-weighted spectroscopy in the human corpus callosum at 7 T.

PubMed

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.
Surface Based Analysis of Diffusion Orientation for Identifying Architectonic Domains in the In Vivo Human Cortex

PubMed Central

McNab, Jennifer A.; Polimeni, Jonathan R.; Wang, Ruopeng; Augustinack, Jean C.; Fujimoto, Kyoko; Player, Allison; Janssens, Thomas; Farivar, Reza; Folkerth, Rebecca D.; Vanduffel, Wim; Wald, Lawrence L.

2012-01-01

Diffusion tensor MRI is sensitive to the coherent structure of brain tissue and is commonly used to study large-scale white matter structure. Diffusion in grey matter is more isotropic, however, several groups have observed coherent patterns of diffusion anisotropy within the cerebral cortical grey matter. We extend the study of cortical diffusion anisotropy by relating it to the local coordinate system of the folded cerebral cortex. We use 1mm and sub-millimeter isotropic resolution diffusion imaging to perform a laminar analysis of the principal diffusion orientation, fractional anisotropy, mean diffusivity and partial volume effects. Data from 6 in vivo human subjects, a fixed human brain specimen and an anesthetized macaque were examined. Large regions of cortex show a radial diffusion orientation. In vivo human and macaque data displayed a sharp transition from radial to tangential diffusion orientation at the border between primary motor and somatosensory cortex, and some evidence of tangential diffusion in secondary somatosensory cortex and primary auditory cortex. Ex vivo diffusion imaging in a human tissue sample showed some tangential diffusion orientation in S1 but mostly radial diffusion orientations in both M1 and S1. PMID:23247190
Aging in deep gray matter and white matter revealed by diffusional kurtosis imaging.

PubMed

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.
Brain Abnormalities in Congenital Fibrosis of the Extraocular Muscles Type 1: A Multimodal MRI Imaging Study

PubMed Central

Wu, Shaoqin; Lv, Bin; Wang, Zhenchang; Xian, Junfang; Sabel, Bernhard A.; He, Huiguang; Jiao, Yonghong

2015-01-01

Purpose To explore the possible brain structural and functional alterations in congenital fibrosis of extraocular muscles type 1 (CFEOM1) patients using multimodal MRI imaging. Methods T1-weighted, diffusion tensor images and functional MRI data were obtained from 9 KIF21A positive patients and 19 age- and gender- matched healthy controls. Voxel based morphometry and tract based spatial statistics were applied to the T1-weighted and diffusion tensor images, respectively. Amplitude of low frequency fluctuations and regional homogeneity were used to process the functional MRI data. We then compared these multimodal characteristics between CFEOM1 patients and healthy controls. Results Compared with healthy controls, CFEOM1 patients demonstrated increased grey matter volume in bilateral frontal orbital cortex and in the right temporal pole. No diffusion indices changes were detected, indicating unaffected white matter microstructure. In addition, from resting state functional MRI data, trend of amplitude of low-frequency fluctuations increases were noted in the right inferior parietal lobe and in the right frontal cortex, and a trend of ReHo increase (p<0.001 uncorrected) in the left precentral gyrus, left orbital frontal cortex, temporal pole and cingulate gyrus. Conclusions CFEOM1 patients had structural and functional changes in grey matter, but the white matter was unaffected. These alterations in the brain may be due to the abnormality of extraocular muscles and their innervating nerves. Future studies should consider the possible correlations between brain morphological/functional findings and clinical data, especially pertaining to eye movements, to obtain more precise answers about the role of brain area changes and their functional consequence in CFEOM1. PMID:26186732
Fiber tracking of brain white matter based on graph theory.

PubMed

Lu, Meng

2015-01-01

Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.
A Unified Approach to Diffusion Direction Sensitive Slice Registration and 3-D DTI Reconstruction From Moving Fetal Brain Anatomy

PubMed Central

Fogtmann, Mads; Seshamani, Sharmishtaa; Kroenke, Christopher; Cheng, Xi; Chapman, Teresa; Wilm, Jakob; Rousseau, François

2014-01-01

This paper presents an approach to 3-D diffusion tensor image (DTI) reconstruction from multi-slice diffusion weighted (DW) magnetic resonance imaging acquisitions of the moving fetal brain. Motion scatters the slice measurements in the spatial and spherical diffusion domain with respect to the underlying anatomy. Previous image registration techniques have been described to estimate the between slice fetal head motion, allowing the reconstruction of 3-D a diffusion estimate on a regular grid using interpolation. We propose Approach to Unified Diffusion Sensitive Slice Alignment and Reconstruction (AUDiSSAR) that explicitly formulates a process for diffusion direction sensitive DW-slice-to-DTI-volume alignment. This also incorporates image resolution modeling to iteratively deconvolve the effects of the imaging point spread function using the multiple views provided by thick slices acquired in different anatomical planes. The algorithm is implemented using a multi-resolution iterative scheme and multiple real and synthetic data are used to evaluate the performance of the technique. An accuracy experiment using synthetically created motion data of an adult head and a experiment using synthetic motion added to sedated fetal monkey dataset show a significant improvement in motion-trajectory estimation compared to a state-of-the-art approaches. The performance of the method is then evaluated on challenging but clinically typical in utero fetal scans of four different human cases, showing improved rendition of cortical anatomy and extraction of white matter tracts. While the experimental work focuses on DTI reconstruction (second-order tensor model), the proposed reconstruction framework can employ any 5-D diffusion volume model that can be represented by the spatial parameterizations of an orientation distribution function. PMID:24108711
Toward Precision and Reproducibility of Diffusion Tensor Imaging: A Multicenter Diffusion Phantom and Traveling Volunteer Study.

PubMed

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.
Axial diffusivity of the corona radiata correlated with ventricular size in adult hydrocephalus.

PubMed

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.

Diffusion Tensor Imaging of Central Auditory Pathways in Patients with Sensorineural Hearing Loss: A Systematic Review.

PubMed

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.
Myofiber Architecture of the Human Atria as Revealed by Submillimeter Diffusion Tensor Imaging.

PubMed

Pashakhanloo, Farhad; Herzka, Daniel A; Ashikaga, Hiroshi; Mori, Susumu; Gai, Neville; Bluemke, David A; Trayanova, Natalia A; McVeigh, Elliot R

2016-04-01

Accurate knowledge of the human atrial fibrous structure is paramount in understanding the mechanisms of atrial electric function in health and disease. Thus far, such knowledge has been acquired from destructive sectioning, and there is a paucity of data about atrial fiber architecture variability in the human population. In this study, we have developed a customized 3-dimensional diffusion tensor magnetic resonance imaging sequence on a clinical scanner that makes it possible to image an entire intact human heart specimen ex vivo at submillimeter resolution. The data from 8 human atrial specimens obtained with this technique present complete maps of the fibrous organization of the human atria. The findings demonstrate that the main features of atrial anatomy are mostly preserved across subjects although the exact location and orientation of atrial bundles vary. Using the full tractography data, we were able to cluster, visualize, and characterize the distinct major bundles in the human atria. Furthermore, quantitative characterization of the fiber angles across the atrial wall revealed that the transmural fiber angle distribution is heterogeneous throughout different regions of the atria. The application of submillimeter diffusion tensor magnetic resonance imaging provides an unprecedented level of information on both human atrial structure, as well as its intersubject variability. The high resolution and fidelity of this data could enhance our understanding of structural contributions to atrial rhythm and pump disorders and lead to improvements in their targeted treatment. © 2016 American Heart Association, Inc.
Measurement tensors in diffusion MRI: generalizing the concept of diffusion encoding.

PubMed

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).
Harmonization of multi-site diffusion tensor imaging data.

PubMed

Fortin, Jean-Philippe; Parker, Drew; Tunç, Birkan; Watanabe, Takanori; Elliott, Mark A; Ruparel, Kosha; Roalf, David R; Satterthwaite, Theodore D; Gur, Ruben C; Gur, Raquel E; Schultz, Robert T; Verma, Ragini; Shinohara, Russell T

2017-11-01

Diffusion tensor imaging (DTI) is a well-established magnetic resonance imaging (MRI) technique used for studying microstructural changes in the white matter. As with many other imaging modalities, DTI images suffer from technical between-scanner variation that hinders comparisons of images across imaging sites, scanners and over time. Using fractional anisotropy (FA) and mean diffusivity (MD) maps of 205 healthy participants acquired on two different scanners, we show that the DTI measurements are highly site-specific, highlighting the need of correcting for site effects before performing downstream statistical analyses. We first show evidence that combining DTI data from multiple sites, without harmonization, may be counter-productive and negatively impacts the inference. Then, we propose and compare several harmonization approaches for DTI data, and show that ComBat, a popular batch-effect correction tool used in genomics, performs best at modeling and removing the unwanted inter-site variability in FA and MD maps. Using age as a biological phenotype of interest, we show that ComBat both preserves biological variability and removes the unwanted variation introduced by site. Finally, we assess the different harmonization methods in the presence of different levels of confounding between site and age, in addition to test robustness to small sample size studies. Copyright © 2017 Elsevier Inc. All rights reserved.
Flexible ex vivo phantoms for validation of diffusion tensor tractography on a clinical scanner.

PubMed

Watanabe, Makoto; Aoki, Shigeki; Masutani, Yoshitaka; Abe, Osamu; Hayashi, Naoto; Masumoto, Tomohiko; Mori, Harushi; Kabasawa, Hiroyuki; Ohtomo, Kuni

2006-11-01

The aim of this study was to develop ex vivo diffusion tensor (DT) flexible phantoms. Materials were bundles of textile threads of cotton, monofilament nylon, rayon, and polyester bunched with spiral wrapping bands and immersed in water. DT images were acquired on a 1.5-Tesla clinical magnetic resonance scanner using echo planar imaging sequences with 15 motion probing gradient directions. DT tractography with seeding and a line-tracking method was carried out by software originally developed on a PC-based workstation. We observed relatively high fractional anisotropy on the polyester phantom and were able to reconstruct tractography. Straight tracts along the bundle were displayed when it was arranged linearly. It was easy to bend arcuately or bifurcate at one end; and tracts followed the course of the bundle, whether it was curved or branched and had good agreement with direct visual observation. Tractography with the other fibers was unsuccessful. The polyester phantom revealed a diffusion anisotropic structure according to its shape and would be utilizable repeatedly under the same conditions, differently from living central neuronal system. It would be useful to validate DT sequences and to optimize an algorithm or parameters of DT tractography software. Additionally, the flexibility of the phantom would enable us to model human axonal projections.
Calibrated imaging reveals altered grey matter metabolism related to white matter microstructure and symptom severity in multiple sclerosis.

PubMed

Hubbard, Nicholas A; Turner, Monroe P; Ouyang, Minhui; Himes, Lyndahl; Thomas, Binu P; Hutchison, Joanna L; Faghihahmadabadi, Shawheen; Davis, Scott L; Strain, Jeremy F; Spence, Jeffrey; Krawczyk, Daniel C; Huang, Hao; Lu, Hanzhang; Hart, John; Frohman, Teresa C; Frohman, Elliot M; Okuda, Darin T; Rypma, Bart

2017-11-01

Multiple sclerosis (MS) involves damage to white matter microstructures. This damage has been related to grey matter function as measured by standard, physiologically-nonspecific neuroimaging indices (i.e., blood-oxygen-level dependent signal [BOLD]). Here, we used calibrated functional magnetic resonance imaging and diffusion tensor imaging to examine the extent to which specific, evoked grey matter physiological processes were associated with white matter diffusion in MS. Evoked changes in BOLD, cerebral blood flow (CBF), and oxygen metabolism (CMRO 2 ) were measured in visual cortex. Individual differences in the diffusion tensor measure, radial diffusivity, within occipital tracts were strongly associated with MS patients' BOLD and CMRO 2 . However, these relationships were in opposite directions, complicating the interpretation of the relationship between BOLD and white matter microstructural damage in MS. CMRO 2 was strongly associated with individual differences in patients' fatigue and neurological disability, suggesting that alterations to evoked oxygen metabolic processes may be taken as a marker for primary symptoms of MS. This work demonstrates the first application of calibrated and diffusion imaging together and details the first application of calibrated functional MRI in a neurological population. Results lend support for neuroenergetic hypotheses of MS pathophysiology and provide an initial demonstration of the utility of evoked oxygen metabolism signals for neurology research. Hum Brain Mapp 38:5375-5390, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
White matter microstructure in athletes with a history of concussion: Comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI).

PubMed

Churchill, Nathan W; Caverzasi, Eduardo; Graham, Simon J; Hutchison, Michael G; Schweizer, Tom A

2017-08-01

Sport concussion is associated with disturbances in brain function in the absence of gross anatomical lesions, and may have long-term health consequences. Diffusion-weighted magnetic resonance imaging (MRI) methods provide a powerful tool for investigating alterations in white matter microstructure reflecting the long-term effects of concussion. In a previous study, diffusion tensor imaging (DTI) showed that athletes with a history of concussion had elevated fractional anisotropy (FA) and reduced mean diffusivity (MD) parameters. To better understand these effects, this study compared DTI results to neurite orientation dispersion and density imaging (NODDI), which was used to estimate the intracellular volume fraction (V IC ) and orientation dispersion index (ODI). Sixty-eight (68) varsity athletes were recruited, including 37 without a history of concussion and 31 with concussion >6 months prior to imaging. Univariate analyses showed elevated FA and decreased MD for concussed athletes, along with increased V IC and reduced ODI, indicating greater neurite density and coherence of neurite orientation within white matter. Multivariate analyses also showed that for athletes with a history of concussion, white matter regions with increased FA had increased V IC and decreased ODI, with greater effects among athletes who were imaged a longer time since their last concussion. These findings enhance our understanding of the relationship between the biophysics of water diffusion and concussion neurobiology for young, healthy adults. Hum Brain Mapp 38:4201-4211, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.
Microstructural Integrity of the Corpus Callosum Linked with Neuropsychological Performance in Adolescents

ERIC Educational Resources Information Center

Fryer, Susanna L.; Frank, Lawrence R.; Spadoni, Andrea D.; Theilmann, Rebecca J.; Nagel, Bonnie J.; Schweinsburg, Alecia D.; Tapert, Susan F.

2008-01-01

Background: Diffusion tensor imaging (DTI) has revealed microstructural aspects of adolescent brain development, the cognitive correlates of which remain relatively uncharacterized. Methods: DTI was used to assess white matter microstructure in 18 typically developing adolescents (ages 16-18). Fractional anisotropy (FA) and mean diffusion (MD)…
High-Resolution Multi-Shot Spiral Diffusion Tensor Imaging with Inherent Correction of Motion-Induced Phase Errors

PubMed Central

Truong, Trong-Kha; Guidon, Arnaud

2014-01-01

Purpose To develop and compare three novel reconstruction methods designed to inherently correct for motion-induced phase errors in multi-shot spiral diffusion tensor imaging (DTI) without requiring a variable-density spiral trajectory or a navigator echo. Theory and Methods The first method simply averages magnitude images reconstructed with sensitivity encoding (SENSE) from each shot, whereas the second and third methods rely on SENSE to estimate the motion-induced phase error for each shot, and subsequently use either a direct phase subtraction or an iterative conjugate gradient (CG) algorithm, respectively, to correct for the resulting artifacts. Numerical simulations and in vivo experiments on healthy volunteers were performed to assess the performance of these methods. Results The first two methods suffer from a low signal-to-noise ratio (SNR) or from residual artifacts in the reconstructed diffusion-weighted images and fractional anisotropy maps. In contrast, the third method provides high-quality, high-resolution DTI results, revealing fine anatomical details such as a radial diffusion anisotropy in cortical gray matter. Conclusion The proposed SENSE+CG method can inherently and effectively correct for phase errors, signal loss, and aliasing artifacts caused by both rigid and nonrigid motion in multi-shot spiral DTI, without increasing the scan time or reducing the SNR. PMID:23450457
In vivo assessment of peripheral nerve regeneration by diffusion tensor imaging.

PubMed

Morisaki, Shinsuke; Kawai, Yuko; Umeda, Masahiro; Nishi, Mayumi; Oda, Ryo; Fujiwara, Hiroyoshi; Yamada, Kei; Higuchi, Toshihiro; Tanaka, Chuzo; Kawata, Mitsuhiro; Kubo, Toshikazu

2011-03-01

To evaluate the sensitivity of diffusion tensor imaging (DTI) in assessing peripheral nerve regeneration in vivo. We assessed the changes in the DTI parameters and histological analyses after nerve injury to examine degeneration and regeneration in the rat sciatic nerves. For magnetic resonance imaging (MRI), 16 rats were randomly divided into two groups: group P (permanently crushed; n = 7) and group T (temporally crushed; n = 9). Serial MRI of the right leg was performed before the operation, and then performed at the timepoints of 1, 2, 3, and 4 weeks after the crush injury. The changes in fractional anisotropy (FA), axial diffusivity (λ(∥)), and radial diffusivity (λ(⟂)) were quantified. For histological analyses, the number of axons and the myelinated axon areas were quantified. Decreased FA and increased λ(⟂) were observed in the degenerative phase, and increased FA and decreased λ(⟂) were observed in the regenerative phase. The changes in FA and λ(⟂) were strongly correlated with histological changes, including axonal and myelin regeneration. DTI parameters, especially λ(⟂) , can be good indicators for peripheral nerve regeneration and can be applied as noninvasive diagnostic tools for a variety of neurological diseases. Copyright © 2011 Wiley-Liss, Inc.
Experience-Related Structural Changes of Degenerated Occipital White Matter in Late-Blind Humans – A Diffusion Tensor Imaging Study

PubMed Central

Dietrich, Susanne; Hertrich, Ingo; Kumar, Vinod; Ackermann, Hermann

2015-01-01

Late-blind humans can learn to understand speech at ultra-fast syllable rates (ca. 20 syllables/s), a capability associated with hemodynamic activation of the central-visual system. Thus, the observed functional cross-modal recruitment of occipital cortex might facilitate ultra-fast speech processing in these individuals. To further elucidate the structural prerequisites of this skill, diffusion tensor imaging (DTI) was conducted in late-blind subjects differing in their capability of understanding ultra-fast speech. Fractional anisotropy (FA) was determined as a quantitative measure of the directionality of water diffusion, indicating fiber tract characteristics that might be influenced by blindness as well as the acquired perceptual skills. Analysis of the diffusion images revealed reduced FA in late-blind individuals relative to sighted controls at the level of the optic radiations at either side and the right-hemisphere dorsal thalamus (pulvinar). Moreover, late-blind subjects showed significant positive correlations between FA and the capacity of ultra-fast speech comprehension within right-hemisphere optic radiation and thalamus. Thus, experience-related structural alterations occurred in late-blind individuals within visual pathways that, presumably, are linked to higher order frontal language areas. PMID:25830371
Diffusion Tensor Imaging as a Biomarker to Differentiate Acute Disseminated Encephalomyelitis From Multiple Sclerosis at First Demyelination.

PubMed

Aung, Wint Yan; Massoumzadeh, Parinaz; Najmi, Safa; Salter, Amber; Heaps, Jodi; Benzinger, Tammie L S; Mar, Soe

2018-01-01

There are no clinical features or biomarkers that can reliably differentiate acute disseminated encephalomyelitis from multiple sclerosis at the first demyelination attack. Consequently, a final diagnosis is sometimes delayed by months and years of follow-up. Early treatment for multiple sclerosis is recommended to reduce long-term disability. Therefore, we intend to explore neuroimaging biomarkers that can reliably distinguish between the two diagnoses. We reviewed prospectively collected clinical, standard MRI and diffusion tensor imaging data from 12 pediatric patients who presented with acute demyelination with and without encephalopathy. Patients were followed for an average of 6.5 years to determine the accuracy of final diagnosis. Final diagnosis was determined using 2013 International Pediatric MS Study Group criteria. Control subjects consisted of four age-matched healthy individuals for each patient. The study population consisted of six patients with central nervous system demyelination with encephalopathy with a presumed diagnosis of acute disseminated encephalomyelitis and six without encephalopathy with a presumed diagnosis of multiple sclerosis or clinically isolated syndrome at high risk for multiple sclerosis. During follow-up, two patients with initial diagnosis of acute disseminated encephalomyelitis were later diagnosed with multiple sclerosis. Diffusion tensor imaging region of interest analysis of baseline scans showed differences between final diagnosis of multiple sclerosis and acute disseminated encephalomyelitis patients, whereby low fractional anisotropy and high radial diffusivity occurred in multiple sclerosis patients compared with acute disseminated encephalomyelitis patients and the age-matched controls. Fractional anisotropy and radial diffusivity measures may have the potential to serve as biomarkers for distinguishing acute disseminated encephalomyelitis from multiple sclerosis at the onset. Copyright © 2017 Elsevier Inc. All rights reserved.
Structural brain and neuropsychometric changes associated with pediatric bipolar disorder with psychosis.

PubMed

James, Anthony; Hough, Morgan; James, Susan; Burge, Linda; Winmill, Louise; Nijhawan, Sunita; Matthews, Paul M; Zarei, Mojtaba

2011-02-01

To identify neuropsychological and structural brain changes using a combination of high-resolution structural and diffusion tensor imaging in pediatric bipolar disorder (PBD) with psychosis (presence of delusions and or hallucinations). We recruited 15 patients and 20 euthymic age- and gender-matched healthy controls. All subjects underwent high-resolution structural and diffusion tensor imaging. Voxel-based morphometry (VBM), tract-based spatial statistics (TBSS), and probabilistic tractography were used to analyse magnetic resonance imaging data. The PBD subjects had normal overall intelligence with specific impairments in working memory, executive function, language function, and verbal memory. Reduced gray matter (GM) density was found in the left orbitofrontal cortex, left pars triangularis, right premotor cortex, occipital cortex, right occipital fusiform gyrus, and right crus of the cerebellum. TBSS analysis showed reduced fractional anisotropy (FA) in the anterior corpus callosum. Probabilistic tractography from this cluster showed that this region of the corpus callosum is connected with the prefrontal cortices, including those regions whose density is decreased in PBD. In addition, FA change was correlated with verbal memory and working memory, while more widespread reductions in GM density correlated with working memory, executive function, language function, and verbal memory. The findings suggest widespread cortical changes as well as specific involvement of interhemispheric prefrontal tracts in PBD, which may reflect delayed myelination in these tracts. © 2011 John Wiley and Sons A/S.
Detection of white matter injury in concussion using high-definition fiber tractography.

PubMed

Shin, Samuel S; Pathak, Sudhir; Presson, Nora; Bird, William; Wagener, Lauren; Schneider, Walter; Okonkwo, David O; Fernandez-Miranda, Juan C

2014-01-01

Over the last few decades, structural imaging techniques of the human brain have undergone significant strides. High resolution provided by recent developments in magnetic resonance imaging (MRI) allows improved detection of injured regions in patients with moderate-to-severe traumatic brain injury (TBI). In addition, diffusion imaging techniques such as diffusion tensor imaging (DTI) has gained much interest recently due to its possible utility in detecting structural integrity of white matter pathways in mild TBI (mTBI) cases. However, the results from recent DTI studies in mTBI patients remain equivocal. Also, there are important shortcomings for DTI such as limited resolution in areas of multiple crossings and false tract formation. The detection of white matter damage in concussion remains challenging, and development of imaging biomarkers for mTBI is still in great need. In this chapter, we discuss our experience with high-definition fiber tracking (HDFT), a diffusion spectrum imaging-based technique. We also discuss ongoing developments and specific advantages HDFT may offer concussion patients. © 2014 S. Karger AG, Basel.
Orthogonal Invariant Sets of the Diffusion Tensor and the Development of a Curvilinear Set Suitable for Low-Anisotropy Tissues

PubMed Central

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
A framework to analyze cerebral mean diffusivity using surface guided diffusion mapping in diffusion tensor imaging

PubMed Central

Kwon, Oh-Hun; Park, Hyunjin; Seo, Sang-Won; Na, Duk L.; Lee, Jong-Min

2015-01-01

The mean diffusivity (MD) value has been used to describe microstructural properties in Diffusion Tensor Imaging (DTI) in cortical gray matter (GM). Recently, researchers have applied a cortical surface generated from the T1-weighted volume. When the DTI data are analyzed using the cortical surface, it is important to assign an accurate MD value from the volume space to the vertex of the cortical surface, considering the anatomical correspondence between the DTI and the T1-weighted image. Previous studies usually sampled the MD value using the nearest-neighbor (NN) method or Linear method, even though there are geometric distortions in diffusion-weighted volumes. Here we introduce a Surface Guided Diffusion Mapping (SGDM) method to compensate for such geometric distortions. We compared our SGDM method with results using NN and Linear methods by investigating differences in the sampled MD value. We also projected the tissue classification results of non-diffusion-weighted volumes to the cortical midsurface. The CSF probability values provided by the SGDM method were lower than those produced by the NN and Linear methods. The MD values provided by the NN and Linear methods were significantly greater than those of the SGDM method in regions suffering from geometric distortion. These results indicate that the NN and Linear methods assigned the MD value in the CSF region to the cortical midsurface (GM region). Our results suggest that the SGDM method is an effective way to correct such mapping errors. PMID:26236180
Clinical feasibility of simultaneous multi-slice imaging with blipped-CAIPI for diffusion-weighted imaging and diffusion-tensor imaging of the brain.

PubMed

Yokota, Hajime; Sakai, Koji; Tazoe, Jun; Goto, Mariko; Imai, Hiroshi; Teramukai, Satoshi; Yamada, Kei

2017-12-01

Background Simultaneous multi-slice (SMS) imaging is starting to be used in clinical situation, although evidence of clinical feasibility is scanty. Purpose To prospectively assess the clinical feasibility of SMS diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI) with blipped-controlled aliasing in parallel imaging for brain lesions. Material and Methods The institutional review board approved this study. This study included 156 hyperintense lesions on DWI from 32 patients. A slice acceleration factor of 2 was applied for SMS scans, which allowed shortening of the scan time by 41.3%. The signal-to-noise ratio (SNR) was calculated for brain tissue of a selected slice. The contrast-to-noise ratio (CNR), apparent diffusion coefficient (ADC), and fractional anisotropy (FA) were calculated in 36 hyperintense lesions with a diameter of three pixels or more. Visual assessment was performed for all 156 lesions. Tractography of the corticospinal tract of 29 patients was evaluated. The number of tracts and averaged tract length were used for quantitative analysis, and visual assessment was evaluated by grading. Results The SMS scan showed no bias and acceptable 95% limits of agreement compared to conventional scans in SNR, CNR, and ADC on Bland-Altman analyses. Only FA of the lesions was higher in the SMS scan by 9% ( P = 0.016), whereas FA of the surrounding tissues was similar. Quantitative analysis of tractography showed similar values. Visual assessment of DWI hyperintense lesions and tractography also resulted in comparable evaluation. Conclusion SMS imaging was clinically feasible for imaging quality and quantitative values compared with conventional DWI and DTI.
Acute white matter changes following sport-related concussion: A serial diffusion tensor and diffusion kurtosis tensor imaging study.

PubMed

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.
The Role of Standardized and Study-specific Human Brain Diffusion Tensor Templates in Inter-subject Spatial Normalization

PubMed Central

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

Structural network efficiency is associated with cognitive impairment in small-vessel disease.

PubMed

Lawrence, Andrew J; Chung, Ai Wern; Morris, Robin G; Markus, Hugh S; Barrick, Thomas R

2014-07-22

To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. © 2014 American Academy of Neurology.
Structural network efficiency is associated with cognitive impairment in small-vessel disease

PubMed Central

Chung, Ai Wern; Morris, Robin G.; Markus, Hugh S.; Barrick, Thomas R.

2014-01-01

Objective: To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. Methods: A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Results: Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Conclusions: Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. PMID:24951477
Tensor-based Dictionary Learning for Spectral CT Reconstruction

PubMed Central

Zhang, Yanbo; Wang, Ge

2016-01-01

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628
Neuropsychological Correlates of Diffusion Tensor Imaging in Schizophrenia

PubMed Central

Nestor, Paul G.; Kubicki, Marek; Gurrera, Ronald J.; Niznikiewicz, Margaret; Frumin, Melissa; McCarley, Robert W.; Shenton, Martha E.

2009-01-01

Patients with schizophrenia (n = 41) and healthy comparison participants (n = 46) completed neuropsychological measures of intelligence, memory, and executive function. A subset of each group also completed magnetic resonance diffusion tensor imaging (DTI) studies (fractional anisotropy and cross-sectional area) of the uncinate fasciculus (UF) and cingulate bundle (CB). Patients with schizophrenia showed reduced levels of functioning across all neuropsychological measures. In addition, selective neuropsychological–DTI relationships emerged. Among patients but not controls, lower levels of declarative–episodic verbal memory correlated with reduced left UF, whereas executive function errors related to performance monitoring correlated with reduced left CB. The data suggested abnormal DTI patterns linking declarative–episodic verbal memory deficits to the left UF and executive function deficits to the left CB among patients with schizophrenia. PMID:15506830
Connectome imaging for mapping human brain pathways

PubMed Central

Shi, Y; Toga, A W

2017-01-01

With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project. Characterization of the microstructural environment in the human brain is discussed from the tensor model to the general fiber orientation distribution (FOD) models that can resolve crossing fibers in each voxel of the image. Using FOD-based tractography, we describe novel methods for fiber bundle reconstruction and graph-based connectivity analysis. Building upon these novel developments, there have already been successful applications of connectome imaging techniques in reconstructing challenging brain pathways. Examples including retinofugal and brainstem pathways will be reviewed. Finally, we discuss future directions in connectome imaging and its interaction with other aspects of brain imaging research. PMID:28461700
Diffusion tensor imaging of the optic tracts in multiple sclerosis: association with retinal thinning and visual disability.

PubMed

Dasenbrock, Hormuzdiyar H; Smith, Seth A; Ozturk, Arzu; Farrell, Sheena K; Calabresi, Peter A; Reich, Daniel S

2011-04-01

Visual disability is common in multiple sclerosis, but its relationship to abnormalities of the optic tracts remains unknown. Because they are only rarely affected by lesions, the optic tracts may represent a good model for assessing the imaging properties of normal-appearing white matter in multiple sclerosis. Whole-brain diffusion tensor imaging was performed on 34 individuals with multiple sclerosis and 26 healthy volunteers. The optic tracts were reconstructed by tractography, and tract-specific diffusion indices were quantified. In the multiple-sclerosis group, peripapillary retinal nerve-fiber-layer thickness and total macular volume were measured by optical coherence tomography, and visual acuity at 100%, 2.5%, and 1.25% contrast was examined. After adjusting for age and sex, optic-tract mean and perpendicular diffusivity were higher (P=.002) in multiple sclerosis. Lower optic-tract fractional anisotropy was correlated with retinal nerve-fiber-layer thinning (r=.51, P=.003) and total-macular-volume reduction (r=.59, P=.002). However, optic-tract diffusion indices were not specifically correlated with visual acuity or with their counterparts in the optic radiation. Optic-tract diffusion abnormalities are associated with retinal damage, suggesting that both may be related to optic-nerve injury, but do not appear to contribute strongly to visual disability in multiple sclerosis. Copyright © 2010 by the American Society of Neuroimaging.
Diffusion Tensor Imaging of the Optic Tracts in Multiple Sclerosis: Association with Retinal Thinning and Visual Disability

PubMed Central

Dasenbrock, Hormuzdiyar H.; Smith, Seth A.; Ozturk, Arzu; Farrell, Sheena K.; Calabresi, Peter A.; Reich, Daniel S.

2009-01-01

Background and purpose Visual disability is common in multiple sclerosis, but its relationship to abnormalities of the optic tracts remains unknown. Because they are only rarely affected by lesions, the optic tracts may represent a good model for assessing the imaging properties of normal-appearing white matter in multiple sclerosis. Methods Whole-brain diffusion tensor imaging was performed on 34 individuals with multiple sclerosis and 26 healthy volunteers. The optic tracts were reconstructed by tractography, and tract-specific diffusion indices were quantified. In the multiple-sclerosis group, peripapillary retinal nerve-fiber-layer thickness and total macular volume were measured by optical coherence tomography, and visual acuity at 100%, 2.5%, and 1.25% contrast was examined. Results After adjusting for age and sex, optic-tract mean and perpendicular diffusivity were higher (p=0.002) in multiple sclerosis. Lower optic-tract fractional anisotropy was correlated with retinal nerve-fiber-layer thinning (r=0.51, p=0.003) and total-macular-volume reduction (r=0.59, p=0.002). However, optic-tract diffusion indices were not specifically correlated with visual acuity or with their counterparts in the optic radiation. Conclusions Optic-tract diffusion abnormalities are associated with retinal damage, suggesting that both may be related to optic-nerve injury, but do not appear to contribute strongly to visual disability in multiple sclerosis. PMID:20331501
Multimodal Imaging Evidence for Axonal and Myelin Deterioration in Amnestic Mild Cognitive Impairment

PubMed Central

Gold, Brian T.; Jiang, Yang; Powell, David K.; Smith, Charles D.

2012-01-01

White matter (WM) microstructural declines have been demonstrated in Alzheimer’s disease and amnestic mild cognitive impairment (aMCI). However, the pattern of WM microstructural changes in aMCI after controlling for WM atrophy is unknown. Here, we address this issue through joint consideration of aMCI alterations in fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, as well as macrostructural volume in WM and gray matter compartments. Participants were 18 individuals with aMCI and 24 healthy seniors. Voxelwise analyses of diffusion tensor imaging data was carried out using tract-based spatial statistics (TBSS) and voxelwise analyses of high-resolution structural data was conducted using voxel based morphometry. After controlling for WM atrophy, the main pattern of TBSS findings indicated reduced fractional anisotropy with only small alterations in mean diffusivity/radial diffusivity/axial diffusivity. These WM microstructural declines bordered and/or were connected to gray matter structures showing volumetric declines. However, none of the potential relationships between WM integrity and volume in connected gray matter structures was significant, and adding fractional anisotropy information improved the classificatory accuracy of aMCI compared to the use of hippocampal atrophy alone. These results suggest that WM microstructural declines provide unique information not captured by atrophy measures that may aid the magnetic resonance imaging contribution to aMCI detection. PMID:22460327
Studying microstructure and microstructural changes in plant tissues by advanced diffusion magnetic resonance imaging techniques

PubMed Central

Morozov, Darya; Tal, Iris; Pisanty, Odelia; Shani, Eilon

2017-01-01

Abstract As sessile organisms, plants must respond to the environment by adjusting their growth and development. Most of the plant body is formed post-embryonically by continuous activity of apical and lateral meristems. The development of lateral adventitious roots is a complex process, and therefore the development of methods that can visualize, non-invasively, the plant microstructure and organ initiation that occur during growth and development is of paramount importance. In this study, relaxation-based and advanced diffusion magnetic resonance imaging (MRI) methods including diffusion tensor (DTI), q-space diffusion imaging (QSI), and double-pulsed-field-gradient (d-PFG) MRI, at 14.1 T, were used to characterize the hypocotyl microstructure and the microstructural changes that occurred during the development of lateral adventitious roots in tomato. Better contrast was observed in relaxation-based MRI using higher in-plane resolution but this also resulted in a significant reduction in the signal-to-noise ratio of the T2-weighted MR images. Diffusion MRI revealed that water diffusion is highly anisotropic in the vascular cylinder. QSI and d-PGSE MRI showed that in the vascular cylinder some of the cells have sizes in the range of 6–10 μm. The MR images captured cell reorganization during adventitious root formation in the periphery of the primary vascular bundles, adjacent to the xylem pole that broke through the cortex and epidermis layers. This study demonstrates that MRI and diffusion MRI methods allow the non-invasive study of microstructural features of plants, and enable microstructural changes associated with adventitious root formation to be followed. PMID:28398563
Examination of Cognitive Fatigue in Multiple Sclerosis using Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging

PubMed Central

Genova, Helen M.; Rajagopalan, Venkateswaran; DeLuca, John; Das, Abhijit; Binder, Allison; Arjunan, Aparna; Chiaravalloti, Nancy; Wylie, Glenn

2013-01-01

The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS), looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI) was used to examine where in the brain BOLD activity covaried with “state” fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI) was used to examine where in the brain white matter damage correlated with increased “trait” fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS) completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a “fatigue-network” in MS. PMID:24223850
Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging.

PubMed

Genova, Helen M; Rajagopalan, Venkateswaran; Deluca, John; Das, Abhijit; Binder, Allison; Arjunan, Aparna; Chiaravalloti, Nancy; Wylie, Glenn

2013-01-01

The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS), looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI) was used to examine where in the brain BOLD activity covaried with "state" fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI) was used to examine where in the brain white matter damage correlated with increased "trait" fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS) completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a "fatigue-network" in MS.
Diffusion tensor imaging and myelin composition analysis reveal abnormal myelination in corpus callosum of canine mucopolysaccharidosis I

PubMed Central

Provenzale, James M.; Nestrasil, Igor; Chen, Steven; Kan, Shih-hsin; Le, Steven Q.; Jens, Jacqueline K.; Snella, Elizabeth M.; Vondrak, Kristen N.; Yee, Jennifer K.; Vite, Charles H.; Elashoff, David; Duan, Lewei; Wang, Raymond Y.; Ellinwood, N. Matthew; Guzman, Miguel A.; Shapiro, Elsa G.; Dickson, Patricia I.

2015-01-01

Children with mucopolysaccharidosis I (MPS I) develop hyperintense white matter foci on T2-weighted brain magnetic resonance (MR) imaging that are associated clinically with cognitive impairment. We report here a diffusion tensor imaging (DTI) and tissue evaluation of white matter in a canine model of MPS I. We found that two DTI parameters, fractional anisotropy (a measure of white matter integrity) and radial diffusivity (which reflects degree of myelination) were abnormal in the corpus callosum of MPS I dogs compared to carrier controls. Tissue studies of the corpus callosum showed reduced expression of myelin-related genes and an abnormal composition of myelin in MPS I dogs. We treated MPS I dogs with recombinant alpha-l-iduronidase, which is the enzyme that is deficient in MPS I disease. The recombinant alpha-l-iduronidase was administered by intrathecal injection into the cisterna magna. Treated dogs showed partial correction of corpus callosum myelination. Our findings suggest that abnormal myelination occurs in the canine MPS I brain, that it may underlie clinically-relevant brain imaging findings in human MPS I patients, and that it may respond to treatment. PMID:26222335
The effect of sex and handedness on white matter anisotropy: a diffusion tensor magnetic resonance imaging study.

PubMed

Powell, J L; Parkes, L; Kemp, G J; Sluming, V; Barrick, T R; García-Fiñana, M

2012-04-05

Diffusion tensor magnetic resonance imaging provides a way of assessing the asymmetry of white matter (WM) connectivity, the degree of anisotropic diffusion within a given voxel being a marker of coherently bundled myelinated fibers. Voxel-based statistical analysis was performed on fractional anisotropy (FA) images of 42 right- and 40 left-handers, to assess differences in underlying WM anisotropy and FA asymmetry across the whole brain. Right-handers show greater anisotropy than left-handers in the uncinate fasciculus (UF) within the limbic lobe, and WM underlying prefrontal cortex, medial and inferior frontal gyri. Significantly greater leftward FA asymmetry in cerebellum posterior lobe is seen in left- than right-handers, and males show significantly greater rightward (right-greater-than-left) FA asymmetry in regions of middle occipital lobe, medial temporal gyrus, and a region of the superior longitudinal fasciculus underlying the supramarginal gyrus. Leftward (left-greater-than-right) anisotropy is found in regions of the arcuate fasciculus (AF), UF, and WM underlying pars triangularis in both handedness groups, with right-handers alone showing additional leftward FA asymmetry along the length of the superior temporal gyrus. Overall results indicate that although both handedness groups show anisotropy in similar WM regions, greater anisotropy is observed in right-handers compared with left-handers. The largest differences in FA asymmetry are found between males and females, suggesting a greater effect of sex than handedness on FA asymmetry. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.
Diffusion tensor imaging of the brainstem in children with achondroplasia

PubMed Central

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.

PubMed

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.
White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies.

PubMed

Vitolo, Enrico; Tatu, Mona Karina; Pignolo, Claudia; Cauda, Franco; Costa, Tommaso; Ando', Agata; Zennaro, Alessandro

2017-12-30

Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions. Copyright © 2017 Elsevier B.V. All rights reserved.
Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging.

PubMed

Handsfield, Geoffrey G; Bolsterlee, Bart; Inouye, Joshua M; Herbert, Robert D; Besier, Thor F; Fernandez, Justin W

2017-12-01

Determination of skeletal muscle architecture is important for accurately modeling muscle behavior. Current methods for 3D muscle architecture determination can be costly and time-consuming, making them prohibitive for clinical or modeling applications. Computational approaches such as Laplacian flow simulations can estimate muscle fascicle orientation based on muscle shape and aponeurosis location. The accuracy of this approach is unknown, however, since it has not been validated against other standards for muscle architecture determination. In this study, muscle architectures from the Laplacian approach were compared to those determined from diffusion tensor imaging in eight adult medial gastrocnemius muscles. The datasets were subdivided into training and validation sets, and computational fluid dynamics software was used to conduct Laplacian simulations. In training sets, inputs of muscle geometry, aponeurosis location, and geometric flow guides resulted in good agreement between methods. Application of the method to validation sets showed no significant differences in pennation angle (mean difference [Formula: see text] or fascicle length (mean difference 0.9 mm). Laplacian simulation was thus effective at predicting gastrocnemius muscle architectures in healthy volunteers using imaging-derived muscle shape and aponeurosis locations. This method may serve as a tool for determining muscle architecture in silico and as a complement to other approaches.
Alteration of diffusion-tensor MRI measures in brain regions involved in early stages of Parkinson's disease.

PubMed

Chen, Nan-Kuei; Chou, Ying-Hui; Sundman, Mark; Hickey, Patrick; Kasoff, Willard S; Bernstein, Adam; Trouard, Theodore P; Lin, Tanya; Rapcsak, Steven Z; Sherman, Scott J; Weingarten, Carol

2018-06-07

Many non-motor symptoms (e.g., hyposmia) appear years before the cardinal motor features of Parkinson's disease (PD). It is thus desirable to be able to use noninvasive brain imaging methods, such as magnetic resonance imaging (MRI), to detect brain abnormalities in early PD stages. Among the MRI modalities, diffusion tensor imaging (DTI) is suitable for detecting changes of brain tissue structure due to neurological diseases. The main purpose of this study was to investigate whether DTI signals measured from brain regions involved in early stages of PD differ from those of healthy controls. To answer this question, we analyzed whole-brain DTI data of 30 early-stage PD patients and 30 controls using improved ROI based analysis methods. Results showed that 1) the fractional anisotropy (FA) values in the olfactory tract (connected with the olfactory bulb: one of the first structures affected by PD) are lower in PD patients than healthy controls; 2) FA values are higher in PD patients than healthy controls in the following brain regions: corticospinal tract, cingulum (near hippocampus), and superior longitudinal fasciculus (temporal part). Experimental results suggest that the tissue property, measured by FA, in olfactory regions is structurally modulated by PD with a mechanism that is different from other brain regions.
Measuring Brain Connectivity: Diffusion Tensor Imaging Validates Resting State Temporal Correlations

PubMed Central

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D.; Hampson, Michelle; Skudlarska, Beata A.; Pearlson, Godfrey

2015-01-01

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions. PMID:18771736
Measuring brain connectivity: diffusion tensor imaging validates resting state temporal correlations.

PubMed

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D; Hampson, Michelle; Skudlarska, Beata A; Pearlson, Godfrey

2008-11-15

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions.

In vivo diffusion tensor imaging and ex vivo histologic characterization of white matter pathology in a post-status epilepticus model of temporal lobe epilepsy.

PubMed

van Eijsden, Pieter; Otte, Wim M; van der Hel, W Saskia; van Nieuwenhuizen, Onno; Dijkhuizen, Rick M; de Graaf, Robin A; Braun, Kees P J

2011-04-01

Although epilepsy is historically considered a disease of gray matter, recent diffusion tensor imaging (DTI) studies have shown white matter abnormalities in patients with epilepsy. The histopathologic correlate of these findings, and whether they are a cause or consequence of epilepsy, remains unclear. To characterize these changes and their underlying histopathology, DTI was performed in juvenile rats, 4 and 8 weeks after pilocarpine-induced status epilepticus (SE). In the medial corpus callosum (CC), mean diffusivity and axial diffusivity (MD and λ₁) as well as a myelin staining were significantly reduced at 4 weeks. Only the λ₁ decrease persisted at 8 weeks. In the fornix fimbriae (FF), λ₁ and myelin staining were decreased at both time points, whereas fractional anisotropy (FA) and MD were significantly reduced at 8 weeks only. We conclude that SE induces both transient and chronic white matter changes in the medial CC and FF that are to some degree related to myelin pathology. Wiley Periodicals, Inc. © 2011 International League Against Epilepsy.
Bound Pool Fractions Complement Diffusion Measures to Describe White Matter Micro and Macrostructure

PubMed Central

Stikov, Nikola; Perry, Lee M.; Mezer, Aviv; Rykhlevskaia, Elena; Wandell, Brian A.; Pauly, John M.; Dougherty, Robert F.

2010-01-01

Diffusion imaging and bound pool fraction (BPF) mapping are two quantitative magnetic resonance imaging techniques that measure microstructural features of the white matter of the brain. Diffusion imaging provides a quantitative measure of the diffusivity of water in tissue. BPF mapping is a quantitative magnetization transfer (qMT) technique that estimates the proportion of exchanging protons bound to macromolecules, such as those found in myelin, and is thus a more direct measure of myelin content than diffusion. In this work, we combine BPF estimates of macromolecular content with measurements of diffusivity within human white matter tracts. Within the white matter, the correlation between BPFs and diffusivity measures such as fractional anisotropy and radial diffusivity was modest, suggesting that diffusion tensor imaging and bound pool fractions are complementary techniques. We found that several major tracts have high BPF, suggesting a higher density of myelin in these tracts. We interpret these results in the context of a quantitative tissue model. PMID:20828622
Comparing fractional anisotropy in patients with childhood-onset schizophrenia, their healthy siblings, and normal volunteers through DTI.

PubMed

Moran, Marcel E; Luscher, Zoe I; McAdams, Harrison; Hsu, John T; Greenstein, Deanna; Clasen, Liv; Ludovici, Katharine; Lloyd, Jonae; Rapoport, Judith; Mori, Susumu; Gogtay, Nitin

2015-01-01

Diffusion tensor imaging is a neuroimaging method that quantifies white matter (WM) integrity and brain connectivity based on the diffusion of water in the brain. White matter has been hypothesized to be of great importance in the development of schizophrenia as part of the dysconnectivity model. Childhood-onset schizophrenia (COS), is a rare, severe form of the illness that resembles poor outcome adult-onset schizophrenia. We hypothesized that COS would be associated with WM abnormalities relative to a sample of controls. To evaluate WM integrity in this population 39 patients diagnosed with COS, 39 of their healthy (nonpsychotic) siblings, and 50 unrelated healthy volunteers were scanned using a diffusion tensor imaging (DTI) sequence during a 1.5 T MRI acquisition. Each DTI scan was processed via atlas-based analysis using a WM parcellation map, and diffeomorphic mapping that shapes a template atlas to each individual subject space. Fractional anisotropy (FA), a measure of WM integrity was averaged over each of the 46 regions of the atlas. Eleven WM regions were examined based on previous reports of WM growth abnormalities in COS. Of those regions, patients with COS, and their healthy siblings had significantly lower mean FA in the left and right cuneus as compared to the healthy volunteers (P < .005). Together, these findings represent the largest DTI study in COS to date, and provide evidence that WM integrity is significantly impaired in COS. Shared deficits in their healthy siblings might result from increased genetic risk. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center 2014.
Comparing Fractional Anisotropy in Patients With Childhood-Onset Schizophrenia, Their Healthy Siblings, and Normal Volunteers Through DTI

PubMed Central

Moran, Marcel E.; Luscher, Zoe I.; McAdams, Harrison; Hsu, John T.; Greenstein, Deanna; Clasen, Liv; Ludovici, Katharine; Lloyd, Jonae; Rapoport, Judith; Mori, Susumu; Gogtay, Nitin

2015-01-01

Background: Diffusion tensor imaging is a neuroimaging method that quantifies white matter (WM) integrity and brain connectivity based on the diffusion of water in the brain. White matter has been hypothesized to be of great importance in the development of schizophrenia as part of the dysconnectivity model. Childhood-onset schizophrenia (COS), is a rare, severe form of the illness that resembles poor outcome adult-onset schizophrenia. We hypothesized that COS would be associated with WM abnormalities relative to a sample of controls. Methods: To evaluate WM integrity in this population 39 patients diagnosed with COS, 39 of their healthy (nonpsychotic) siblings, and 50 unrelated healthy volunteers were scanned using a diffusion tensor imaging (DTI) sequence during a 1.5 T MRI acquisition. Each DTI scan was processed via atlas-based analysis using a WM parcellation map, and diffeomorphic mapping that shapes a template atlas to each individual subject space. Fractional anisotropy (FA), a measure of WM integrity was averaged over each of the 46 regions of the atlas. Eleven WM regions were examined based on previous reports of WM growth abnormalities in COS. Results: Of those regions, patients with COS, and their healthy siblings had significantly lower mean FA in the left and right cuneus as compared to the healthy volunteers (P < .005). Together, these findings represent the largest DTI study in COS to date, and provide evidence that WM integrity is significantly impaired in COS. Shared deficits in their healthy siblings might result from increased genetic risk. PMID:25217482
Application of Diffusion Tensor Imaging Parameters to Detect Change in Longitudinal Studies in Cerebral Small Vessel Disease

PubMed Central

Zeestraten, Eva Anna; Benjamin, Philip; Lambert, Christian; Lawrence, Andrew John; Williams, Owen Alan; Morris, Robin Guy; Barrick, Thomas Richard; Markus, Hugh Stephen

2016-01-01

Cerebral small vessel disease (SVD) is the major cause of vascular cognitive impairment, resulting in significant disability and reduced quality of life. Cognitive tests have been shown to be insensitive to change in longitudinal studies and, therefore, sensitive surrogate markers are needed to monitor disease progression and assess treatment effects in clinical trials. Diffusion tensor imaging (DTI) is thought to offer great potential in this regard. Sensitivity of the various parameters that can be derived from DTI is however unknown. We aimed to evaluate the differential sensitivity of DTI markers to detect SVD progression, and to estimate sample sizes required to assess therapeutic interventions aimed at halting decline based on DTI data. We investigated 99 patients with symptomatic SVD, defined as clinical lacunar syndrome with MRI confirmation of a corresponding infarct as well as confluent white matter hyperintensities over a 3 year follow-up period. We evaluated change in DTI histogram parameters using linear mixed effect models and calculated sample size estimates. Over a three-year follow-up period we observed a decline in fractional anisotropy and increase in diffusivity in white matter tissue and most parameters changed significantly. Mean diffusivity peak height was the most sensitive marker for SVD progression as it had the smallest sample size estimate. This suggests disease progression can be monitored sensitively using DTI histogram analysis and confirms DTI’s potential as surrogate marker for SVD. PMID:26808982
Linear associations between clinically assessed upper motor neuron disease and diffusion tensor imaging metrics in amyotrophic lateral sclerosis.

PubMed

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.
Alterations of white matter integrity in adults with major depressive disorder: a magnetic resonance imaging study

PubMed Central

Zou, Ke; Huang, Xiaoqi; Li, Tao; Gong, Qiyong; Li, Zhe; Ou-yang, Luo; Deng, Wei; Chen, Qin; Li, Chunxiao; Ding, Yi; Sun, Xueli

2008-01-01

Objective The purpose of our study was to investigate alterations of white matter integrity in adults with major depressive disorder (MDD) using magnetic resonance imaging (MRI). Methods We performed diffusion tensor imaging with a 3T MRI scanner on 45 patients with major depression and 45 healthy controls matched for age, sex and education. Using a voxel-based analysis, we measured the fractional anisotropy (FA), and we investigated the differences between the patient and control groups. We examined the correlations between the microstructure abnormalities of white matter and symptom severity, age of illness onset and cumulative illness duration, respectively. Results We found a significant decrease in FA in the left hemisphere, including the anterior limb of the internal capsule and the inferior parietal portion of the superior longitudinal fasciculus, in patients with MDD compared with healthy controls. Diffusion tensor imaging measures in the left anterior limb of the internal capsule were negatively related to the severity of depressive symptoms, even after we controlled for age and sex. Conclusion Our findings provide new evidence of microstructural changes of white matter in non–late-onset adult depression. Our results complement those observed in late-life depression and support the hypothesis that the disruption of cortical– subcortical circuit integrity may be involved in the etiology of major depressive disorder. PMID:18982175
Noninvasive Localization of Prostate Cancer via Diffusion Sensitive MRI

DTIC Science & Technology

2008-03-01

sequence, Haker et al and Roebuck et al using a line-scan diffusion sequence, and Vigneron et al using a fast spin-echo diffusion sequence (33,35-37...Mulkern RV, Haker S, Zhang J, Zou KH, Maier SE, Tempany CM. Detection of prostate cancer by integration of line-scan diffusion, T2-mapping and T2-weighted...36. Haker SJ, Szot Barnes A, Maier SE, Tempany CM, Mulkern RV. Diffusion Tensor Imaging for Prostate Cancer Detection: Preliminary Results from a
Pattern of structural brain changes in social anxiety disorder after cognitive behavioral group therapy: a longitudinal multimodal MRI study.

PubMed

Steiger, V R; Brühl, A B; Weidt, S; Delsignore, A; Rufer, M; Jäncke, L; Herwig, U; Hänggi, J

2017-08-01

Social anxiety disorder (SAD) is characterized by fears of social and performance situations. Cognitive behavioral group therapy (CBGT) has in general positive effects on symptoms, distress and avoidance in SAD. Prior studies found increased cortical volumes and decreased fractional anisotropy (FA) in SAD compared with healthy controls (HCs). Thirty-three participants diagnosed with SAD attended in a 10-week CBGT and were scanned before and after therapy. We applied three neuroimaging methods-surface-based morphometry, diffusion tensor imaging and network-based statistics-each with specific longitudinal processing protocols, to investigate CBGT-induced structural brain alterations of the gray and white matter (WM). Surface-based morphometry revealed a significant cortical volume reduction (pre- to post-treatment) in the left inferior parietal cortex, as well as a positive partial correlation between treatment success (indexed by reductions in Liebowitz Social Anxiety Scale) and reductions in cortical volume in bilateral dorsomedial prefrontal cortex. Diffusion tensor imaging analysis revealed a significant increase in FA in bilateral uncinate fasciculus and right inferior longitudinal fasciculus. Network-based statistics revealed a significant increase of structural connectivity in a frontolimbic network. No partial correlations with treatment success have been found in WM analyses. For, we believe, the first time, we present a distinctive pattern of longitudinal structural brain changes after CBGT measured with three established magnetic resonance imaging analyzing techniques. Our findings are in line with previous cross-sectional, unimodal SAD studies and extent them by highlighting anatomical brain alterations that point toward the level of HCs in parallel with a reduction in SAD symptomatology.
Mapping immune cell infiltration using restricted diffusion MRI.

PubMed

Yeh, Fang-Cheng; Liu, Li; Hitchens, T Kevin; Wu, Yijen L

2017-02-01

Diffusion MRI provides a noninvasive way to assess tissue microstructure. Based on diffusion MRI, we propose a model-free method called restricted diffusion imaging (RDI) to quantify restricted diffusion and correlate it with cellularity. An analytical relation between q-space signals and the density of restricted spins was derived to quantify restricted diffusion. A phantom study was conducted to investigate the performance of RDI, and RDI was applied to an animal study to assess immune cell infiltration in myocardial tissues with ischemia-reperfusion injury. Our phantom study showed a correlation coefficient of 0.998 between cell density and the restricted diffusion quantified by RDI. The animal study also showed that the high-value regions in RDI matched well with the macrophage infiltration areas in the H&E stained slides. In comparison with diffusion tensor imaging (DTI), RDI exhibited its outperformance to detect macrophage infiltration and delineate inflammatory myocardium. RDI can be used to reveal cell density and detect immune cell infiltration. RDI exhibits better specificity than the diffusivity measurement derived from DTI. Magn Reson Med 77:603-612, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Age-related decline in white matter integrity in a mouse model of tauopathy: an in vivo diffusion tensor magnetic resonance imaging study

PubMed Central

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
Eddy current-nulled convex optimized diffusion encoding (EN-CODE) for distortion-free diffusion tensor imaging with short echo times.

PubMed

Aliotta, Eric; Moulin, Kévin; Ennis, Daniel B

2018-02-01

To design and evaluate eddy current-nulled convex optimized diffusion encoding (EN-CODE) gradient waveforms for efficient diffusion tensor imaging (DTI) that is free of eddy current-induced image distortions. The EN-CODE framework was used to generate diffusion-encoding waveforms that are eddy current-compensated. The EN-CODE DTI waveform was compared with the existing eddy current-nulled twice refocused spin echo (TRSE) sequence as well as monopolar (MONO) and non-eddy current-compensated CODE in terms of echo time (TE) and image distortions. Comparisons were made in simulations, phantom experiments, and neuro imaging in 10 healthy volunteers. The EN-CODE sequence achieved eddy current compensation with a significantly shorter TE than TRSE (78 versus 96 ms) and a slightly shorter TE than MONO (78 versus 80 ms). Intravoxel signal variance was lower in phantoms with EN-CODE than with MONO (13.6 ± 11.6 versus 37.4 ± 25.8) and not different from TRSE (15.1 ± 11.6), indicating good robustness to eddy current-induced image distortions. Mean fractional anisotropy values in brain edges were also significantly lower with EN-CODE than with MONO (0.16 ± 0.01 versus 0.24 ± 0.02, P < 1 x 10 -5 ) and not different from TRSE (0.16 ± 0.01 versus 0.16 ± 0.01, P = nonsignificant). The EN-CODE sequence eliminated eddy current-induced image distortions in DTI with a TE comparable to MONO and substantially shorter than TRSE. Magn Reson Med 79:663-672, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Evaluation of optimized b-value sampling schemas for diffusion kurtosis imaging with an application to stroke patient data

PubMed Central

Yan, Xu; Zhou, Minxiong; Ying, Lingfang; Yin, Dazhi; Fan, Mingxia; Yang, Guang; Zhou, Yongdi; Song, Fan; Xu, Dongrong

2013-01-01

Diffusion kurtosis imaging (DKI) is a new method of magnetic resonance imaging (MRI) that provides non-Gaussian information that is not available in conventional diffusion tensor imaging (DTI). DKI requires data acquisition at multiple b-values for parameter estimation; this process is usually time-consuming. Therefore, fewer b-values are preferable to expedite acquisition. In this study, we carefully evaluated various acquisition schemas using different numbers and combinations of b-values. Acquisition schemas that sampled b-values that were distributed to two ends were optimized. Compared to conventional schemas using equally spaced b-values (ESB), optimized schemas require fewer b-values to minimize fitting errors in parameter estimation and may thus significantly reduce scanning time. Following a ranked list of optimized schemas resulted from the evaluation, we recommend the 3b schema based on its estimation accuracy and time efficiency, which needs data from only 3 b-values at 0, around 800 and around 2600 s/mm2, respectively. Analyses using voxel-based analysis (VBA) and region-of-interest (ROI) analysis with human DKI datasets support the use of the optimized 3b (0, 1000, 2500 s/mm2) DKI schema in practical clinical applications. PMID:23735303
Age-dependent association of thyroid function with brain morphology and microstructural organization: evidence from brain imaging.

PubMed

Chaker, Layal; Cremers, Lotte G M; Korevaar, Tim I M; de Groot, Marius; Dehghan, Abbas; Franco, Oscar H; Niessen, Wiro J; Ikram, M Arfan; Peeters, Robin P; Vernooij, Meike W

2018-01-01

Thyroid hormone (TH) is crucial during neurodevelopment, but high levels of TH have been linked to neurodegenerative disorders. No data on the association of thyroid function with brain imaging in the general population are available. We therefore investigated the association of thyroid-stimulating hormone and free thyroxine (FT4) with magnetic resonance imaging (MRI)-derived total intracranial volume, brain tissue volumes, and diffusion tensor imaging measures of white matter microstructure in 4683 dementia- and stroke-free participants (mean age 60.2, range 45.6-89.9 years). Higher FT4 levels were associated with larger total intracranial volumes (β = 6.73 mL, 95% confidence interval = 2.94-9.80). Higher FT4 levels were also associated with larger total brain and white matter volumes in younger individuals, but with smaller total brain and white matter volume in older individuals (p-interaction 0.02). There was a similar interaction by age for the association of FT4 with mean diffusivity on diffusion tensor imaging (p-interaction 0.026). These results are in line with differential effects of TH during neurodevelopmental and neurodegenerative processes and can improve the understanding of the role of thyroid function in neurodegenerative disorders. Copyright © 2017 Elsevier Inc. All rights reserved.
Three-Dimensional Printed Modeling of Diffuse Low-Grade Gliomas and Associated White Matter Tract Anatomy.

PubMed

Thawani, Jayesh P; Singh, Nickpreet; Pisapia, Jared M; Abdullah, Kalil G; Parker, Drew; Pukenas, Bryan A; Zager, Eric L; Verma, Ragini; Brem, Steven

2017-04-01

Diffuse low-grade gliomas (DLGGs) represent several pathological entities that infiltrate and invade cortical and subcortical structures in the brain. To describe methods for rapid prototyping of DLGGs and surgically relevant anatomy. Using high-definition imaging data and rapid prototyping technologies, we were able to generate 3 patient DLGGs to scale and represent the associated white matter tracts in 3 dimensions using advanced diffusion tensor imaging techniques. This report represents a novel application of 3-dimensional (3-D) printing in neurosurgery and a means to model individualized tumors in 3-D space with respect to subcortical white matter tract anatomy. Faculty and resident evaluations of this technology were favorable at our institution. Developing an understanding of the anatomic relationships existing within individuals is fundamental to successful neurosurgical therapy. Imaging-based rapid prototyping may improve on our ability to plan for and treat complex neuro-oncologic pathology. Copyright © 2017 by the Congress of Neurological Surgeons
Unique white matter microstructural patterns in ADHD presentations-a diffusion tensor imaging study.

PubMed

Svatkova, Alena; Nestrasil, Igor; Rudser, Kyle; Goldenring Fine, Jodene; Bledsoe, Jesse; Semrud-Clikeman, Margaret

2016-09-01

Attention-deficit/hyperactivity disorder predominantly inattentive (ADHD-PI) and combined (ADHD-C) presentations are likely distinct disorders that differ neuroanatomically, neurochemically, and neuropsychologically. However, to date, little is known about specific white matter (WM) regions differentiating ADHD presentations. This study examined differences in WM microstructure using diffusion tensor imaging (DTI) data from 20 ADHD-PI, 18 ADHD-C, and 27 typically developed children. Voxel-wise analysis of DTI measurements in major fiber bundles was carried out using tract-based spatial statistics (TBSS). Clusters showing diffusivity abnormalities were used as regions of interest for regression analysis between fractional anisotropy (FA) and neuropsychological outcomes. Compared to neurotypicals, ADHD-PI children showed higher FA in the anterior thalamic radiations (ATR), bilateral inferior longitudinal fasciculus (ILF), and in the left corticospinal tract (CST). In contrast, the ADHD-C group exhibited higher FA in the bilateral cingulum bundle (CB). In the ADHD-PI group, differences in FA in the left ILF and ATR were accompanied by axial diffusivity (AD) abnormalities. In addition, the ADHD-PI group exhibited atypical mean diffusivity in the forceps minor (FMi) and left ATR and AD differences in right CB compared to healthy subjects. Direct comparison between ADHD presentations demonstrated radial diffusivity differences in FMi. WM clusters with FA irregularities in ADHD were associated with neurobehavioral performance across groups. In conclusion, differences in WM microstructure in ADHD presentations strengthen the theory that ADHD-PI and ADHD-C are two distinct disorders. Regions with WM irregularity seen in both ADHD presentations might serve as predictors of executive and behavioral functioning across groups. Hum Brain Mapp 37:3323-3336, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Integrating histology and MRI in the first digital brain of common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Sun, Peizhen; Parvathaneni, Prasanna; Schilling, Kurt G.; Gao, Yurui; Janve, Vaibhav; Anderson, Adam; Landman, Bennett A.

2015-03-01

This effort is a continuation of development of a digital brain atlas of the common squirrel monkey, Saimiri sciureus, a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. Here, we present the integration of histology with multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. The central concept of this work is to use block face photography to establish an intermediate common space in coordinate system which preserves the high resolution in-plane resolution of histology while enabling 3-D correspondence with MRI. In vivo MRI acquisitions include high resolution T2 structural imaging (300 μm isotropic) and low resolution diffusion tensor imaging (600 um isotropic). Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging (both 300 μm isotropic). Cortical regions were manually annotated on the co-registered volumes based on published histological sections in-plane. We describe mapping of histology and MRI based data of the common squirrel monkey and construction of a viewing tool that enable online viewing of these datasets. The previously descried atlas MRI is used for its deformation to provide accurate conformation to the MRI, thus adding information at the histological level to the MRI volume. This paper presents the mapping of single 2D image slice in block face as a proof of concept and this can be extended to map the atlas space in 3D coordinate system as part of the future work and can be loaded to an XNAT system for further use.
Diffusion tensor imaging of the human calf: Variation of inter- and intramuscle-specific diffusion parameters.

PubMed

Schlaffke, Lara; Rehmann, Robert; Froeling, Martijn; Kley, Rudolf; Tegenthoff, Martin; Vorgerd, Matthias; Schmidt-Wilcke, Tobias

2017-10-01

To investigate to what extent inter- and intramuscular variations of diffusion parameters of human calf muscles can be explained by age, gender, muscle location, and body mass index (BMI) in a specific age group (20-35 years). Whole calf muscles of 18 healthy volunteers were evaluated. Magnetic resonance imaging (MRI) was performed using a 3T scanner and a 16-channel Torso XL coil. Diffusion-weighted images were acquired to perform fiber tractography and diffusion tensor imaging (DTI) analysis for each muscle of both legs. Fiber tractography was used to separate seven lower leg muscles. Associations between DTI parameters and confounds were evaluated. All muscles were additionally separated in seven identical segments along the z-axis to evaluate intramuscular differences in diffusion parameters. Fractional anisotropy (FA) and mean diffusivity (MD) were obtained for each muscle with low standard deviations (SDs) (SD FA : 0.01-0.02; SD MD : 0.07-0.14(10 -3 )). We found significant differences in FA values of the tibialis anterior muscle (AT) and extensor digitorum longus (EDL) muscles between men and women for whole muscle FA (two-sample t-tests; AT: P = 0.0014; EDL: P = 0.0004). We showed significant intramuscular differences in diffusion parameters between adjacent segments in most calf muscles (P < 0.001). Whereas muscle insertions showed higher (SD 0.03-0.06) than muscle bellies (SD 0.01-0.03), no relationships between FA or MD with age or BMI were found. Inter- and intramuscular variations in diffusion parameters of the calf were shown, which are not related to age or BMI in this age group. Differences between muscle belly and insertion should be considered when interpreting datasets not including whole muscles. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1137-1148. © 2017 International Society for Magnetic Resonance in Medicine.
Advanced Pediatric Brain Imaging Research and Training Program

DTIC Science & Technology

2013-10-01

diffusion tensor imaging and perfusion ( arterial spin labeling) MRI data and to relate measures of global and regional brain microstructural organization...AD_________________ Award Number: W81XWH-11-2-0198 TITLE: Advanced Pediatric Brain Imaging...September 2013 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Advanced Pediatric Brain Imaging Research and Training Program 5b. GRANT NUMBER W81XWH
Ultrasound backscatter tensor imaging (BTI): analysis of the spatial coherence of ultrasonic speckle in anisotropic soft tissues.

PubMed

Papadacci, Clement; Tanter, Mickael; Pernot, Mathieu; Fink, Mathias

2014-06-01

The assessment of fiber architecture is of major interest in the progression of myocardial disease. Recent techniques such as magnetic resonance diffusion tensor imaging (MR-DTI) or ultrasound elastic tensor imaging (ETI) can derive the fiber directions by measuring the anisotropy of water diffusion or tissue elasticity, but these techniques present severe limitations in a clinical setting. In this study, we propose a new technique, backscatter tensor imaging (BTI), which enables determination of the fiber directions in skeletal muscles and myocardial tissues, by measuring the spatial coherence of ultrasonic speckle. We compare the results to ultrasound ETI. Acquisitions were performed using a linear transducer array connected to an ultrasonic scanner mounted on a motorized rotation device with angles from 0° to 355° by 5° increments to image ex vivo bovine skeletal muscle and porcine left ventricular myocardial samples. At each angle, multiple plane waves were transmitted and the backscattered echoes recorded. The coherence factor was measured as the ratio of coherent intensity over incoherent intensity of backscattered echoes. In skeletal muscle, maximal/minimal coherence factor was found for the probe parallel/perpendicular to the fibers. In myocardium, the coherence was assessed across the entire myocardial thickness, and the position of maxima and minima varied transmurally because of the complex fibers distribution. In ETI, the shear wave speed variation with the probe angle was found to follow the coherence variation. Spatial coherence can thus reveal the anisotropy of the ultrasonic speckle in skeletal muscle and myocardium. BTI could be used on any type of ultrasonic scanner with rotating phased-array probes or 2-D matrix probes for noninvasive evaluation of myocardial fibers.

Ultrasound Backscatter Tensor Imaging (BTI): Analysis of the spatial coherence of ultrasonic speckle in anisotropic soft tissues

PubMed Central

Papadacci, Clement; Tanter, Mickael; Pernot, Mathieu; Fink, Mathias

2014-01-01

The assessment of fiber architecture is of major interest in the progression of myocardial disease. Recent techniques such as Magnetic Resonance (MR) Diffusion Tensor Imaging or Ultrasound Elastic Tensor Imaging (ETI) can derive the fiber directions by measuring the anisotropy of water diffusion or tissue elasticity, but these techniques present severe limitations in clinical setting. In this study, we propose a new technique, the Backscatter Tensor Imaging (BTI) which enables determining the fibers directions in skeletal muscles and myocardial tissues, by measuring the spatial coherence of ultrasonic speckle. We compare the results to ultrasound ETI. Acquisitions were performed using a linear transducer array connected to an ultrasonic scanner mounted on a motorized rotation device with angles from 0° to 355° by 5° increments to image ex vivo bovine skeletal muscle and porcine left ventricular myocardial samples. At each angle, multiple plane waves were transmitted and the backscattered echoes recorded. The coherence factor was measured as the ratio of coherent intensity over incoherent intensity of backscattered echoes. In skeletal muscle, maximal/minimal coherence factor was found for the probe parallel/perpendicular to the fibers. In myocardium, the coherence was assessed across the entire myocardial thickness, and the position of maxima and minima varied transmurally due to the complex fibers distribution. In ETI, the shear wave speed variation with the probe angle was found to follow the coherence variation. Spatial coherence can thus reveal the anisotropy of the ultrasonic speckle in skeletal muscle and myocardium. BTI could be used on any type of ultrasonic scanner with rotative phased-array probes or 2-D matrix probes for non-invasive evaluation of myocardial fibers. PMID:24859662
Epilepsy Surgery for Individuals with TSC

MedlinePlus

... tomography (PET), single-photon emission tomography (SPECT), magnetoencephalography (MEG), Diffusion Tensor Imaging (DTI), and functional MRI (fMRI). ... sclerosis: a comparison of high resolution EEG and MEG. Epilepsia 47:108-114 Jansen FE, Huffelen ACV, ...
Parameter Estimation in Atmospheric Data Sets

NASA Technical Reports Server (NTRS)

Wenig, Mark; Colarco, Peter

2004-01-01

In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .
Preliminary evidence of white matter abnormality in the uncinate fasciculus in generalized social anxiety disorder.

PubMed

Phan, K Luan; Orlichenko, Anton; Boyd, Erin; Angstadt, Mike; Coccaro, Emil F; Liberzon, Israel; Arfanakis, Konstantinos

2009-10-01

Individuals with generalized social anxiety disorder (GSAD) exhibit exaggerated amygdala reactivity to aversive social stimuli. These findings could be explained by microstructural abnormalities in white matter (WM) tracts that connect the amygdala and prefrontal cortex, which is known to modulate the amygdala's response to threat. The goal of this study was to investigate brain frontal WM abnormalities using diffusion tensor imaging (DTI) in patients with social anxiety disorder. A Turboprop DTI sequence was used to acquire diffusion tensor images in 30 patients with GSAD and 30 matched healthy control subjects. Fractional anisotropy, an index of axonal organization, within WM was quantified in individual subjects, and an automated voxel-based, whole-brain method was used to analyze group differences. Compared with healthy control subjects, patients had significantly lower fractional anisotropy localized to the right uncinate fasciculus WM near the orbitofrontal cortex. There were no areas of higher fractional anisotropy in patients than controls. These findings point to an abnormality in the uncinate fasciculus, the major WM tract connecting the frontal cortex to the amygdala and other limbic temporal regions, in GSAD, which could underlie the aberrant amygdala-prefrontal interactions resulting in dysfunctional social threat processing in this illness.
Value of Formalin Fixation for the Prolonged Preservation of Rodent Myocardial Microanatomical Organization: Evidence by MR Diffusion Tensor Imaging.

PubMed

Giannakidis, Archontis; Gullberg, Grant T; Pennell, Dudley J; Firmin, David N

2016-07-01

Previous ex vivo diffusion tensor imaging (DTI) studies on formalin-fixed myocardial tissue assumed that, after some initial changes in the first 48 hr since the start of fixation, DTI parameters remain stable over time. Prolonged preservation of cardiac tissue in formalin prior to imaging has been seen many times in the DTI literature as it is considered orderly. Our objective is to define the effects of the prolonged cardiac tissue exposure to formalin on tissue microanatomical organization, as this is assessed by DTI parameters. DTI experiments were conducted on eight excised rodent hearts that were fixed by immersion in formalin. The samples were randomly divided into two equinumerous groups corresponding to shorter (∼2 weeks) and more prolonged (∼6-8 weeks) durations of tissue exposure to formalin prior to imaging. We found that when the duration of cardiac tissue exposure to formalin before imaging increased, water diffusion became less restricted, helix angle (HA) histograms flattened out and exhibited heavier tails (even though the classic HA transmural variation was preserved), and a significant loss of inter-voxel primary diffusion orientation integrity was introduced. The prolonged preservation of cardiac tissue in formalin profoundly affected its microstructural organization, as this was assessed by DTI parameters. The accurate interpretation of diffusivity profiles necessitates awareness of the pitfalls of prolonged cardiac tissue exposure duration to formalin. The acquired knowledge works to the advantage of a proper experimental design of DTI studies of fixed hearts. Anat Rec, 299:878-887, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Test-retest reliability and repeatability of renal diffusion tensor MRI in healthy subjects.

PubMed

Cutajar, Marica; Clayden, Jonathan D; Clark, Christopher A; Gordon, Isky

2011-12-01

This study assessed test-retest reliability and repeatability of diffusion tensor imaging (DTI) in the kidneys. Seven healthy volunteers (age range, 19-31 years), were imaged three consecutive times on the same day (short-term reliability) and the same imaging protocol was repeated after a month (long-term reliability). Diffusion-weighted magnetic resonance imaging scans in the coronal-oblique projection of the kidney were acquired on a 1.5 T scanner using a multi-section echo-planar sequence; six contiguous slices each 5 mm thick, diffusion sensitisation along 20 non-collinear directions, TR=730 ms, TE=73 ms and 2 b-values (0 and 400 s mm(-2)). Volunteers were asked to hold their breath throughout each data acquisition (approx. 20 s). The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were obtained from maps generated using dedicated software MIStar (Apollo Medical Imaging, Melbourne, Australia). Statistical analyses of both short- and long-term repeats were carried out from which the within-subject coefficient of variation (wsCV) was calculated. The wsCV obtained for both the ADC and FA values were less than 10% in all the analyses carried out. In addition, paired (repeated measures) t-test was used to measure the variation between the diffusion parameters collected from the two scanning sessions a month apart. It showed no significant difference and the wsCV obtained after comparing the first and second scans were found to be smaller than 15% for both ADC and FA. Renal DTI produces reliable and repeatable results which make longitudinal investigation of patients viable. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Diffusion Tensor Imaging of Lumbar Nerve Roots: Comparison Between Fast Readout-Segmented and Selective-Excitation Acquisitions.

PubMed

Manoliu, Andrei; Ho, Michael; Nanz, Daniel; Piccirelli, Marco; Dappa, Evelyn; Klarhöfer, Markus; Del Grande, Filippo; Kuhn, Felix Pierre

2016-08-01

The aim of this study was to compare the quality of recently emerged advanced diffusion tensor imaging (DTI) techniques with conventional single-shot echo-planar imaging (EPI) in a functional assessment of lumbar nerve roots. The institutional review board approved the study including 12 healthy volunteers. Diffusion tensor imaging was performed at 3 T (MAGNETOM Skyra; Siemens Healthcare) with b-values of 0 and 700 s/mm and an isotropic spatial resolution for subsequent multiplanar reformatting. The nerve roots L2 to S1 were imaged in coronal orientation with readout-segmented EPI (rs-DTI) and selective-excitation EPI (sTX-DTI) with an acquisition time of 5 minutes each, and in axial orientation with single-shot EPI (ss-DTI) with an acquisition time of 12 minutes (scan parameters as in recent literature). Two independent readers qualitatively and quantitatively assessed image quality. The interobserver reliability ranged from "substantial" to "almost perfect" for all examined parameter and all 3 sequences (κ = 0.70-0.94). Overall image quality was rated higher, and artifact levels were scored lower for rs-DTI and sTX-DTI than for ss-DTI (P = 0.007-0.027), while fractional anisotropy and signal-to-noise ratio values were similar for all sequences (P ≥ 0.306 and P ≥ 0.100, respectively). Contrast-to-noise ratios were significantly higher for rs-DTI and ss-DTI than for sTX-DTI (P = 0.004-0.013). Despite shorter acquisition times, rs-DTI and sTX-DTI produced images of higher quality with smaller geometrical distortions than the current standard of reference, ss-DTI. Thus, DTI acquisitions in the coronal plane, requiring fewer slices for full coverage of exiting nerve roots, may allow for functional neurography in scan times suitable for routine clinical practice.
Gray Matter Atrophy Is Primarily Related to Demyelination of Lesions in Multiple Sclerosis: A Diffusion Tensor Imaging MRI Study.

PubMed

Tóth, Eszter; Szabó, Nikoletta; Csete, Gergõ; Király, András; Faragó, Péter; Spisák, Tamás; Bencsik, Krisztina; Vécsei, László; Kincses, Zsigmond T

2017-01-01

Objective: Cortical pathology, periventricular demyelination, and lesion formation in multiple sclerosis (MS) are related (Hypothesis 1). Factors in the cerebrospinal fluid close to these compartments could possibly drive the parallel processes. Alternatively, the cortical atrophy could be caused by remote axonal transection (Hypothesis 2). Since MRI can differentiate between demyelination and axon loss, we used this imaging modality to investigate the correlation between the pattern of diffusion parameter changes in the periventricular- and deep white matter and the gray matter atrophy. Methods: High-resolution T1-weighted, FLAIR, and diffusion MRI images were acquired in 52 RRMS patients and 50 healthy, age-matched controls. We used EDSS to estimate the clinical disability. We used Tract Based Spatial Statistics to compare diffusion parameters (fractional anisotropy, mean, axial, and radial diffusivity) between groups. We evaluated global brain, white, and gray matter atrophy with SIENAX. Averaged, standard diffusion parameters were calculated in four compartment: periventricular lesioned and normal appearing white matter, non-periventricular lesioned and normal appearing white matter. PLS regression was used to identify which diffusion parameter and in which compartment best predicts the brain atrophy and clinical disability. Results: In our diffusion tensor imaging study compared to controls we found extensive alterations of fractional anisotropy, mean and radial diffusivity and smaller changes of axial diffusivity (maximal p > 0.0002) in patients that suggested demyelination in the lesioned and in the normal appearing white matter. We found significant reduction in total brain, total white, and gray matter (patients: 718.764 ± 14.968, 323.237 ± 7.246, 395.527 ± 8.050 cm 3 , controls: 791.772 ± 22.692, 355.350 ± 10.929, 436.422 ± 12.011 cm 3 ; mean ± SE), ( p < 0.015; p < 0.0001; p < 0.009; respectively) of patients compared to controls. The PLS analysis revealed a combination of demyelination-like diffusion parameters (higher mean and radial diffusivity in patients) in the lesions and in the non-lesioned periventricular white matter, which best predicted the gray matter atrophy ( p < 0.001). Similarly, EDSS was best predicted by the radial diffusivity of the lesions and the non-lesioned periventricular white matter, but axial diffusivity of the periventricular lesions also contributed significantly ( p < 0.0001). Interpretation: Our investigation showed that gray matter atrophy and white matter demyelination are related in MS but white matter axonal loss does not significantly contribute to the gray matter pathology.
Brain tumor classification using the diffusion tensor image segmentation (D-SEG) technique.

PubMed

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.
Comparison of quality control software tools for diffusion tensor imaging.

PubMed

Liu, Bilan; Zhu, Tong; Zhong, Jianhui

2015-04-01

Image quality of diffusion tensor imaging (DTI) is critical for image interpretation, diagnostic accuracy and efficiency. However, DTI is susceptible to numerous detrimental artifacts that may impair the reliability and validity of the obtained data. Although many quality control (QC) software tools are being developed and are widely used and each has its different tradeoffs, there is still no general agreement on an image quality control routine for DTIs, and the practical impact of these tradeoffs is not well studied. An objective comparison that identifies the pros and cons of each of the QC tools will be helpful for the users to make the best choice among tools for specific DTI applications. This study aims to quantitatively compare the effectiveness of three popular QC tools including DTI studio (Johns Hopkins University), DTIprep (University of North Carolina at Chapel Hill, University of Iowa and University of Utah) and TORTOISE (National Institute of Health). Both synthetic and in vivo human brain data were used to quantify adverse effects of major DTI artifacts to tensor calculation as well as the effectiveness of different QC tools in identifying and correcting these artifacts. The technical basis of each tool was discussed, and the ways in which particular techniques affect the output of each of the tools were analyzed. The different functions and I/O formats that three QC tools provide for building a general DTI processing pipeline and integration with other popular image processing tools were also discussed. Copyright © 2015 Elsevier Inc. All rights reserved.
Microstructural effects of Ramadan fasting on the brain: a diffusion tensor imaging study.

PubMed

Bakan, Ayse Ahsen; Yıldız, Seyma; Alkan, Alpay; Yetis, Huseyin; Kurtcan, Serpil; Ilhan, Mahmut Muzaffer

2015-01-01

We aimed to examine whether the brain displays any microstructural changes after a three-week Ramadan fasting period using diffusion tenson imaging. This study included a study and a control group of 25 volunteers each. In the study group, we examined and compared apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values of the participants during (phase 1) and after (phase 2) a period of fasting. The control group included individuals who did not fast. ADC and FA values obtained in phase 1 and phase 2 were compared between the study and control groups. In the study group, ADC values of hypothalamus and, to a lesser extent, of insula were lower in phase 1 compared with phase 2 and the control group. The FA values of amygdala, middle temporal cortex, thalamus and, to a lesser extent, of medial prefrontal cortex were lower in phase 1 compared with phase 2 and the control group. Phase 2 ADC and FA values of the study group were not significantly different compared with the control group at any brain location. A three-week Ramadan fasting period can cause microstructural changes in the brain, and diffusion tensor imaging enables the visualization of these changes. The identification of brain locations where changes occurred in ADC and FA values during fasting can be helpful in diagnostic imaging and understanding the pathophysiology of eating disorders.
Microstructural effects of Ramadan fasting on the brain: a diffusion tensor imaging study

PubMed Central

Bakan, Ayse Ahsen; Yıldız, Seyma; Alkan, Alpay; Yetis, Huseyin; Kurtcan, Serpil; Ilhan, Mahmut Muzaffer

2015-01-01

PURPOSE We aimed to examine whether the brain displays any microstructural changes after a three-week Ramadan fasting period using diffusion tenson imaging. METHODS This study included a study and a control group of 25 volunteers each. In the study group, we examined and compared apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values of the participants during (phase 1) and after (phase 2) a period of fasting. The control group included individuals who did not fast. ADC and FA values obtained in phase 1 and phase 2 were compared between the study and control groups. RESULTS In the study group, ADC values of hypothalamus and, to a lesser extent, of insula were lower in phase 1 compared with phase 2 and the control group. The FA values of amygdala, middle temporal cortex, thalamus and, to a lesser extent, of medial prefrontal cortex were lower in phase 1 compared with phase 2 and the control group. Phase 2 ADC and FA values of the study group were not significantly different compared with the control group at any brain location. CONCLUSION A three-week Ramadan fasting period can cause microstructural changes in the brain, and diffusion tensor imaging enables the visualization of these changes. The identification of brain locations where changes occurred in ADC and FA values during fasting can be helpful in diagnostic imaging and understanding the pathophysiology of eating disorders. PMID:25835077
Impact of blood flow on diffusion coefficients of the human kidney: a time-resolved ECG-triggered diffusion-tensor imaging (DTI) study at 3T.

PubMed

Heusch, Philipp; Wittsack, Hans-Jörg; Kröpil, Patric; Blondin, Dirk; Quentin, Michael; Klasen, Janina; Pentang, Gael; Antoch, Gerald; Lanzman, Rotem S

2013-01-01

To evaluate the impact of renal blood flow on apparent diffusion coefficients (ADC) and fractional anisotropy (FA) using time-resolved electrocardiogram (ECG)-triggered diffusion-tensor imaging (DTI) of the human kidneys. DTI was performed in eight healthy volunteers (mean age 29.1 ± 3.2) using a single slice coronal echoplanar imaging (EPI) sequence (3 b-values: 0, 50, and 300 s/mm(2)) at the timepoint of minimum (20 msec after R wave) and maximum renal blood flow (200 msec after R wave) at 3T. Following 2D motion correction, region of interest (ROI)-based analysis of cortical and medullary ADC- and FA-values was performed. ADC-values of the renal cortex at maximum blood flow (2.6 ± 0.19 × 10(-3) mm(2)/s) were significantly higher than at minimum blood flow (2.2 ± 0.11 × 10(-3) mm(2)/s) (P < 0.001), while medullary ADC-values did not differ significantly (maximum blood flow: 2.2 ± 0.18 × 10(-3) mm(2)/s; minimum blood flow: 2.15 ± 0.14 × 10(-3) mm(2)/s). FA-values of the renal medulla were significantly greater at maximal blood (0.53 ± 0.05) than at minimal blood flow (0.47 ± 0.05) (P < 0.01). In contrast, cortical FA-values were comparable at different timepoints of the cardiac cycle. ADC-values in the renal cortex as well as FA-values in the renal medulla are influenced by renal blood flow. This impact has to be considered when interpreting renal ADC- and FA-values. Copyright © 2012 Wiley Periodicals, Inc.
Does the use of hormonal contraceptives cause microstructural changes in cerebral white matter? Preliminary results of a DTI and tractography study.

PubMed

De Bondt, Timo; Van Hecke, Wim; Veraart, Jelle; Leemans, Alexander; Sijbers, Jan; Sunaert, Stefan; Jacquemyn, Yves; Parizel, Paul M

2013-01-01

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

ERIC Educational Resources Information Center

Shukla, Dinesh K.; Keehn, Brandon; Smylie, Daren M.; Muller, Ralph-Axel

2011-01-01

Recent functional connectivity magnetic resonance imaging and diffusion tensor imaging (DTI) studies have suggested atypical functional connectivity and reduced integrity of long-distance white matter fibers in autism spectrum disorder (ASD). However, evidence for short-distance white matter fibers is still limited, despite some speculation of…
Approximating high angular resolution apparent diffusion coefficient profiles using spherical harmonics under BiGaussian assumption

NASA Astrophysics Data System (ADS)

Cao, Ning; Liang, Xuwei; Zhuang, Qi; Zhang, Jun

2009-02-01

Magnetic Resonance Imaging (MRI) techniques have achieved much importance in providing visual and quantitative information of human body. Diffusion MRI is the only non-invasive tool to obtain information of the neural fiber networks of the human brain. The traditional Diffusion Tensor Imaging (DTI) is only capable of characterizing Gaussian diffusion. High Angular Resolution Diffusion Imaging (HARDI) extends its ability to model more complex diffusion processes. Spherical harmonic series truncated to a certain degree is used in recent studies to describe the measured non-Gaussian Apparent Diffusion Coefficient (ADC) profile. In this study, we use the sampling theorem on band-limited spherical harmonics to choose a suitable degree to truncate the spherical harmonic series in the sense of Signal-to-Noise Ratio (SNR), and use Monte Carlo integration to compute the spherical harmonic transform of human brain data obtained from icosahedral schema.
Diffusion Weighted Callosal Integrity Reflects Interhemispheric Communication Efficiency in Multiple Sclerosis

ERIC Educational Resources Information Center

Warlop, Nele P.; Achten, Eric; Debruyne, Jan; Vingerhoets, Guy

2008-01-01

We aimed to investigate the relation between damage in the corpus callosum and the performance on an interhemispheric communication task in patients with multiple sclerosis (MS). Relative callosal lesion load defined as the ratio between callosal area and the total lesion load in the total corpus callosum, and the diffusion tensor imaging (DTI)…
Visual System Involvement in Patients with Newly Diagnosed Parkinson Disease.

PubMed

Arrigo, Alessandro; Calamuneri, Alessandro; Milardi, Demetrio; Mormina, Enricomaria; Rania, Laura; Postorino, Elisa; Marino, Silvia; Di Lorenzo, Giuseppe; Anastasi, Giuseppe Pio; Ghilardi, Maria Felice; Aragona, Pasquale; Quartarone, Angelo; Gaeta, Michele

2017-12-01

Purpose To assess intracranial visual system changes of newly diagnosed Parkinson disease in drug-naïve patients. Materials and Methods Twenty patients with newly diagnosed Parkinson disease and 20 age-matched control subjects were recruited. Magnetic resonance (MR) imaging (T1-weighted and diffusion-weighted imaging) was performed with a 3-T MR imager. White matter changes were assessed by exploring a white matter diffusion profile by means of diffusion-tensor imaging-based parameters and constrained spherical deconvolution-based connectivity analysis and by means of white matter voxel-based morphometry (VBM). Alterations in occipital gray matter were investigated by means of gray matter VBM. Morphologic analysis of the optic chiasm was based on manual measurement of regions of interest. Statistical testing included analysis of variance, t tests, and permutation tests. Results In the patients with Parkinson disease, significant alterations were found in optic radiation connectivity distribution, with decreased lateral geniculate nucleus V2 density (F, -8.28; P < .05), a significant increase in optic radiation mean diffusivity (F, 7.5; P = .014), and a significant reduction in white matter concentration. VBM analysis also showed a significant reduction in visual cortical volumes (P < .05). Moreover, the chiasmatic area and volume were significantly reduced (P < .05). Conclusion The findings show that visual system alterations can be detected in early stages of Parkinson disease and that the entire intracranial visual system can be involved. © RSNA, 2017 Online supplemental material is available for this article.
Advanced diffusion MRI and biomarkers in the central nervous system: a new approach.

PubMed

Martín Noguerol, T; Martínez Barbero, J P

The introduction of diffusion-weighted sequences has revolutionized the detection and characterization of central nervous system (CNS) disease. Nevertheless, the assessment of diffusion studies of the CNS is often limited to qualitative estimation. Moreover, the pathophysiological complexity of the different entities that affect the CNS cannot always be correctly explained through classical models. The development of new models for the analysis of diffusion sequences provides numerous parameters that enable a quantitative approach to both diagnosis and prognosis as well as to monitoring the response to treatment; these parameters can be considered potential biomarkers of health and disease. In this update, we review the physical bases underlying diffusion studies and diffusion tensor imaging, advanced models for their analysis (intravoxel coherent motion and kurtosis), and the biological significance of the parameters derived. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.
Three-dimensional high-resolution diffusion tensor imaging and tractography of the developing rabbit brain.

PubMed

D'Arceuil, Helen; Liu, Christina; Levitt, Pat; Thompson, Barbara; Kosofsky, Barry; de Crespigny, Alex

2008-01-01

Diffusion tensor imaging (DTI) is sensitive to structural ordering in brain tissue particularly in the white matter tracts. Diffusion anisotropy changes with disease and also with neural development. We used high-resolution DTI of fixed rabbit brains to study developmental changes in regional diffusion anisotropy and white matter fiber tract development. Imaging was performed on a 4.7-tesla Bruker Biospec Avance scanner using custom-built solenoid coils and DTI was performed at various postnatal ages. Trace apparent diffusion coefficient, fractional diffusion anisotropy maps and fiber tracts were generated and compared across the ages. The brain was highly anisotropic at birth and white matter anisotropy increased with age. Regional DTI tractography of the internal capsule showed refinement in regional tract architecture with maturation. Interestingly, brains with congenital deficiencies of the callosal commissure showed selectively strikingly different fiber architecture compared to age-matched brains. There was also some evidence of subcortical to cortical fiber connectivity. DTI tractography of the anterior and posterior limbs of the internal capsule showed reproducibly coherent fiber tracts corresponding to known corticospinal and corticobulbar tract anatomy. There was some minor interanimal tract variability, but there was remarkable similarity between the tracts in all animals. Therefore, ex vivo DTI tractography is a potentially powerful tool for neuroscience investigations and may also reveal effects (such as fiber tract pruning during development) which may be important targets for in vivo human studies. Copyright 2007 S. Karger AG, Basel.

Diffusion tensor spectroscopic imaging of the human brain in children and adults.

PubMed

Fotso, Kevin; Dager, Stephen R; Landow, Alec; Ackley, Elena; Myers, Orrin; Dixon, Mindy; Shaw, Dennis; Corrigan, Neva M; Posse, Stefan

2017-10-01

We developed diffusion tensor spectroscopic imaging (DTSI), based on proton-echo-planar-spectroscopic imaging (PEPSI), and evaluated the feasibility of mapping brain metabolite diffusion in adults and children. PRESS prelocalized DTSI at 3 Tesla (T) was performed using navigator-based correction of movement-related phase errors and cardiac gating with compensation for repetition time (TR) related variability in T 1 saturation. Mean diffusivity (MD) and fractional anisotropy (FA) of total N-acetyl-aspartate (tNAA), total creatine (tCr), and total choline (tCho) were measured in eight adults (17-60 years) and 10 children (3-24 months) using b max = 1734 s/mm 2 , 1 cc and 4.5 cc voxel sizes, with nominal scan times of 17 min and 8:24 min. Residual movement-related phase encoding ghosting (PEG) was used as a regressor across scans to correct overestimation of MD. After correction for PEG, metabolite slice-averaged MD estimated at 20% PEG were lower (P < 0.042) for adults (0.17/0.20/0.18 × 10 -3 mm 2 /s) than for children (0.26/0.27/0.24 × 10 -3 mm 2 /s). Extrapolated to 0% PEG, the MD estimates decreased further (0.09/0.11/0.11 × 10 -3 mm 2 /s versus 0.15/0.16/0.15 × 10 -3 mm 2 /s). Slice-averaged FA of tNAA (P = 0.049), tCr (P = 0.067), and tCho (P = 0.003) were higher in children. This high-speed DTSI approach with PEG regression allows for estimation of metabolite MD and FA with improved tolerance to movement. Our preliminary data suggesting age-related changes support DTSI as a sensitive technique for investigating intracellular markers of biological processes. Magn Reson Med 78:1246-1256, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Diffusion Tensor Imaging of Pedophilia.

PubMed

Cantor, James M; Lafaille, Sophie; Soh, Debra W; Moayedi, Massieh; Mikulis, David J; Girard, Todd A

2015-11-01

Pedophilia is a principal motivator of child molestation, incurring great emotional and financial burdens on victims and society. Even among pedophiles who never commit any offense,the condition requires lifelong suppression and control. Previous comparison using voxel-based morphometry (VBM)of MR images from a large sample of pedophiles and controls revealed group differences in white matter. The present study therefore sought to verify and characterize white matter involvement using diffusion tensor imaging (DTI), which better captures the microstructure of white matter than does VBM. Pedophilics ex offenders (n=24) were compared with healthy, age-matched controls with no criminal record and no indication of pedophilia (n=32). White matter microstructure was analyzed with Tract-Based Spatial Statistics, and the trajectories of implicated fiber bundles were identified by probabilistic tractography. Groups showed significant, highly focused differences in DTI parameters which related to participants’ genital responses to sexual depictions of children, but not to measures of psychopathy or to childhood histories of physical abuse, sexual abuse, or neglect. Some previously reported gray matter differences were suggested under highly liberal statistical conditions (p(uncorrected)<.005), but did not survive ordinary statistical correction (whole brain per voxel false discovery rate of 5%). These results confirm that pedophilia is characterized by neuroanatomical differences in white matter microstructure, over and above any neural characteristics attributable to psychopathy and childhood adversity, which show neuroanatomic footprints of their own. Although some gray matter structures were implicated previously, only few have emerged reliably.
Analytical performance bounds for multi-tensor diffusion-MRI.

PubMed

Ahmed Sid, Farid; Abed-Meraim, Karim; Harba, Rachid; Oulebsir-Boumghar, Fatima

2017-02-01

To examine the effects of MR acquisition parameters on brain white matter fiber orientation estimation and parameter of clinical interest in crossing fiber areas based on the Multi-Tensor Model (MTM). We compute the Cramér-Rao Bound (CRB) for the MTM and the parameter of clinical interest such as the Fractional Anisotropy (FA) and the dominant fiber orientations, assuming that the diffusion MRI data are recorded by a multi-coil, multi-shell acquisition system. Considering the sum-of-squares method for the reconstructed magnitude image, we introduce an approximate closed-form formula for Fisher Information Matrix that has the simplicity and easy interpretation advantages. In addition, we propose to generalize the FA and the mean diffusivity to the multi-tensor model. We show the application of the CRB to reduce the scan time while preserving a good estimation precision. We provide results showing how the increase of the number of acquisition coils compensates the decrease of the number of diffusion gradient directions. We analyze the impact of the b-value and the Signal-to-Noise Ratio (SNR). The analysis shows that the estimation error variance decreases with a quadratic rate with the SNR, and that the optimum b-values are not unique but depend on the target parameter, the context, and eventually the target cost function. In this study we highlight the importance of choosing the appropriate acquisition parameters especially when dealing with crossing fiber areas. We also provide a methodology for the optimal tuning of these parameters using the CRB. Copyright © 2016 Elsevier Inc. All rights reserved.
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.
Individual classification of Alzheimer's disease with diffusion magnetic resonance imaging.

PubMed

Schouten, Tijn M; Koini, Marisa; Vos, Frank de; Seiler, Stephan; Rooij, Mark de; Lechner, Anita; Schmidt, Reinhold; Heuvel, Martijn van den; Grond, Jeroen van der; Rombouts, Serge A R B

2017-05-15

Diffusion magnetic resonance imaging (MRI) is a powerful non-invasive method to study white matter integrity, and is sensitive to detect differences in Alzheimer's disease (AD) patients. Diffusion MRI may be able to contribute towards reliable diagnosis of AD. We used diffusion MRI to classify AD patients (N=77), and controls (N=173). We use different methods to extract information from the diffusion MRI data. First, we use the voxel-wise diffusion tensor measures that have been skeletonised using tract based spatial statistics. Second, we clustered the voxel-wise diffusion measures with independent component analysis (ICA), and extracted the mixing weights. Third, we determined structural connectivity between Harvard Oxford atlas regions with probabilistic tractography, as well as graph measures based on these structural connectivity graphs. Classification performance for voxel-wise measures ranged between an AUC of 0.888, and 0.902. The ICA-clustered measures ranged between an AUC of 0.893, and 0.920. The AUC for the structural connectivity graph was 0.900, while graph measures based upon this graph ranged between an AUC of 0.531, and 0.840. All measures combined with a sparse group lasso resulted in an AUC of 0.896. Overall, fractional anisotropy clustered into ICA components was the best performing measure. These findings may be useful for future incorporation of diffusion MRI into protocols for AD classification, or as a starting point for early detection of AD using diffusion MRI. Copyright © 2017 Elsevier Inc. All rights reserved.
Diffusion tensor analysis with invariant gradients and rotation tangents.

PubMed

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.
Diffusion tensor driven contour closing for cell microinjection targeting.

PubMed

Becattini, Gabriele; Mattos, Leonardo S; Caldwell, Darwin G

2010-01-01

This article introduces a novel approach to robust automatic detection of unstained living cells in bright-field (BF) microscope images with the goal of producing a target list for an automated microinjection system. The overall image analysis process is described and includes: preprocessing, ridge enhancement, image segmentation, shape analysis and injection point definition. The developed algorithm implements a new version of anisotropic contour completion (ACC) based on the partial differential equation (PDE) for heat diffusion which improves the cell segmentation process by elongating the edges only along their tangent direction. The developed ACC algorithm is equivalent to a dilation of the binary edge image with a continuous elliptic structural element that takes into account local orientation of the contours preventing extension towards normal direction. Experiments carried out on real images of 10 to 50 microm CHO-K1 adherent cells show a remarkable reliability in the algorithm along with up to 85% success for cell detection and injection point definition.
A 3D high resolution ex vivo white matter atlas of the common squirrel monkey (saimiri sciureus) based on diffusion tensor imaging

NASA Astrophysics Data System (ADS)

Gao, Yurui; Parvathaneni, Prasanna; Schilling, Kurt G.; Wang, Feng; Stepniewska, Iwona; Xu, Zhoubing; Choe, Ann S.; Ding, Zhaohua; Gore, John C.; Chen, Li min; Landman, Bennett A.; Anderson, Adam W.

2016-03-01

Modern magnetic resonance imaging (MRI) brain atlases are high quality 3-D volumes with specific structures labeled in the volume. Atlases are essential in providing a common space for interpretation of results across studies, for anatomical education, and providing quantitative image-based navigation. Extensive work has been devoted to atlas construction for humans, macaque, and several non-primate species (e.g., rat). One notable gap in the literature is the common squirrel monkey - for which the primary published atlases date from the 1960's. The common squirrel monkey has been used extensively as surrogate for humans in biomedical studies, given its anatomical neuro-system similarities and practical considerations. This work describes the continued development of a multi-modal MRI atlas for the common squirrel monkey, for which a structural imaging space and gray matter parcels have been previously constructed. This study adds white matter tracts to the atlas. The new atlas includes 49 white matter (WM) tracts, defined using diffusion tensor imaging (DTI) in three animals and combines these data to define the anatomical locations of these tracks in a standardized coordinate system compatible with previous development. An anatomist reviewed the resulting tracts and the inter-animal reproducibility (i.e., the Dice index of each WM parcel across animals in common space) was assessed. The Dice indices range from 0.05 to 0.80 due to differences of local registration quality and the variation of WM tract position across individuals. However, the combined WM labels from the 3 animals represent the general locations of WM parcels, adding basic connectivity information to the atlas.
A 3D high resolution ex vivo white matter atlas of the common squirrel monkey (Saimiri sciureus) based on diffusion tensor imaging

PubMed Central

Gao, Yurui; Parvathaneni, Prasanna; Schilling, Kurt G.; Wang, Feng; Stepniewska, Iwona; Xu, Zhoubing; Choe, Ann S.; Ding, Zhaohua; Gore, John C.; Chen, Li Min; Landman, Bennett A.; Anderson, Adam W.

2016-01-01

Modern magnetic resonance imaging (MRI) brain atlases are high quality 3-D volumes with specific structures labeled in the volume. Atlases are essential in providing a common space for interpretation of results across studies, for anatomical education, and providing quantitative image-based navigation. Extensive work has been devoted to atlas construction for humans, macaque, and several non-primate species (e.g., rat). One notable gap in the literature is the common squirrel monkey – for which the primary published atlases date from the 1960’s. The common squirrel monkey has been used extensively as surrogate for humans in biomedical studies, given its anatomical neuro-system similarities and practical considerations. This work describes the continued development of a multi-modal MRI atlas for the common squirrel monkey, for which a structural imaging space and gray matter parcels have been previously constructed. This study adds white matter tracts to the atlas. The new atlas includes 49 white matter (WM) tracts, defined using diffusion tensor imaging (DTI) in three animals and combines these data to define the anatomical locations of these tracks in a standardized coordinate system compatible with previous development. An anatomist reviewed the resulting tracts and the inter-animal reproducibility (i.e., the Dice index of each WM parcel across animals in common space) was assessed. The Dice indices range from 0.05 to 0.80 due to differences of local registration quality and the variation of WM tract position across individuals. However, the combined WM labels from the 3 animals represent the general locations of WM parcels, adding basic connectivity information to the atlas. PMID:27064328
A 3D high resolution ex vivo white matter atlas of the common squirrel monkey (Saimiri sciureus) based on diffusion tensor imaging.

PubMed

Gao, Yurui; Parvathaneni, Prasanna; Schilling, Kurt G; Wang, Feng; Stepniewska, Iwona; Xu, Zhoubing; Choe, Ann S; Ding, Zhaohua; Gore, John C; Chen, Li Min; Landman, Bennett A; Anderson, Adam W

2016-02-27

Modern magnetic resonance imaging (MRI) brain atlases are high quality 3-D volumes with specific structures labeled in the volume. Atlases are essential in providing a common space for interpretation of results across studies, for anatomical education, and providing quantitative image-based navigation. Extensive work has been devoted to atlas construction for humans, macaque, and several non-primate species (e.g., rat). One notable gap in the literature is the common squirrel monkey - for which the primary published atlases date from the 1960's. The common squirrel monkey has been used extensively as surrogate for humans in biomedical studies, given its anatomical neuro-system similarities and practical considerations. This work describes the continued development of a multi-modal MRI atlas for the common squirrel monkey, for which a structural imaging space and gray matter parcels have been previously constructed. This study adds white matter tracts to the atlas. The new atlas includes 49 white matter (WM) tracts, defined using diffusion tensor imaging (DTI) in three animals and combines these data to define the anatomical locations of these tracks in a standardized coordinate system compatible with previous development. An anatomist reviewed the resulting tracts and the inter-animal reproducibility (i.e., the Dice index of each WM parcel across animals in common space) was assessed. The Dice indices range from 0.05 to 0.80 due to differences of local registration quality and the variation of WM tract position across individuals. However, the combined WM labels from the 3 animals represent the general locations of WM parcels, adding basic connectivity information to the atlas.
Structural white matter changes in adolescents and young adults with maple syrup urine disease.

PubMed

Klee, D; Thimm, E; Wittsack, H J; Schubert, D; Primke, R; Pentang, G; Schaper, J; Mödder, U; Antoch, A; Wendel, U; Cohnen, M

2013-11-01

To get insight into the nature of magnetic resonance (MR) white matter abnormalities of patients with classic maple syrup urine disease (MSUD) under diet control. Ten patients with classic MSUD and one with a severe MSUD variant (mean age 21.5 ± 5.1 years) on diet and 11 age and sex-matched healthy subjects were enrolled. Apart from standard MR sequences, diffusion weighted images (DWI), diffusion tensor images (DTI), and magnetization transfer images (MT) were obtained and comparatively analyzed for apparent diffusion coefficient (ADC), tensor fractional anisotropy (FA) and MT maps in 11 regions of interest (ROI) within the white matter. In MSUD patients DWI, DTI and FA showed distinct signal changes in the cerebral hemispheres, the dorsal limb of internal capsule, the brain stem and the central cerebellum. Signal intensity was increased in DWI with a reduced ADC and decreased values for FA. MT did not reveal differences between patients and control subjects. Signal abnormalities in the white matter of adolescents and young adults under diet control may be interpreted as consequence of structural alterations like dysmyelination. The reduced ADC and FA in the white matter with preserved MT indicate a reduction in fiber tracks.
Longitudinal regression analysis of spatial-temporal growth patterns of geometrical diffusion measures in early postnatal brain development with diffusion tensor imaging

PubMed Central

Chen, Yasheng; An, Hongyu; Zhu, Hongtu; Jewells, Valerie; Armao, Diane; Shen, Dinggang; Gilmore, John H.; Lin, Weili

2011-01-01

Although diffusion tensor imaging (DTI) has provided substantial insights into early brain development, most DTI studies based on fractional anisotropy (FA) and mean diffusivity (MD) may not capitalize on the information derived from the three principal diffusivities (e.g. eigenvalues). In this study, we explored the spatial and temporal evolution of white matter structures during early brain development using two geometrical diffusion measures, namely, linear (Cl) and planar (Cp) diffusion anisotropies, from 71 longitudinal datasets acquired from 29 healthy, full-term pediatric subjects. The growth trajectories were estimated with generalized estimating equations (GEE) using linear fitting with logarithm of age (days). The presence of the white matter structures in Cl and Cp was observed in neonates, suggesting that both the cylindrical and fanning or crossing structures in various white matter regions may already have been formed at birth. Moreover, we found that both Cl and Cp evolved in a temporally nonlinear and spatially inhomogeneous manner. The growth velocities of Cl in central white matter were significantly higher when compared to peripheral, or more laterally located, white matter: central growth velocity Cl = 0.0465±0.0273/log(days), versus peripheral growth velocity Cl=0.0198±0.0127/log(days), p<10−6. In contrast, the growth velocities of Cp in central white matter were significantly lower than that in peripheral white matter: central growth velocity Cp= 0.0014±0.0058/log(days), versus peripheral growth velocity Cp = 0.0289±0.0101/log(days), p<10−6. Depending on the underlying white matter site which is analyzed, our findings suggest that ongoing physiologic and microstructural changes in the developing brain may exert different effects on the temporal evolution of these two geometrical diffusion measures. Thus, future studies utilizing DTI with correlative histological analysis in the study of early brain development are warranted. PMID:21784163
Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging.

PubMed

Truong, Trong-Kha; Song, Allen W; Chen, Nan-Kuei

2015-01-01

In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T2(∗) -weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed.
Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging

PubMed Central

Truong, Trong-Kha; Song, Allen W.; Chen, Nan-kuei

2015-01-01

In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T 2 ∗-weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed. PMID:26413505
Quantitative validation of a nonlinear histology-MRI coregistration method using Generalized Q-sampling Imaging in complex human cortical white matter

PubMed Central

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
Reduced white matter integrity and verbal fluency impairment in young adults with bipolar disorder: a diffusion tensor imaging study

PubMed Central

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
Individual white matter fractional anisotropy analysis on patients with MRI negative partial epilepsy.

PubMed

Duning, Thomas; Kellinghaus, Christoph; Mohammadi, Siawoosh; Schiffbauer, Hagen; Keller, Simon; Ringelstein, E Bernd; Knecht, Stefan; Deppe, Michael

2010-02-01

Conventional structural MRI fails to identify a cerebral lesion in 25% of patients with cryptogenic partial epilepsy (CPE). Diffusion tensor imaging is an MRI technique sensitive to microstructural abnormalities of cerebral white matter (WM) by quantification of fractional anisotropy (FA). The objectives of the present study were to identify focal FA abnormalities in patients with CPE who were deemed MRI negative during routine presurgical evaluation. Diffusion tensor imaging at 3 T was performed in 12 patients with CPE and normal conventional MRI and in 67 age matched healthy volunteers. WM integrity was compared between groups on the basis of automated voxel-wise statistics of FA maps using an analysis of covariance. Volumetric measurements from high resolution T1-weighted images were also performed. Significant FA reductions in WM regions encompassing diffuse areas of the brain were observed when all patients as a group were compared with controls. On an individual basis, voxel based analyses revealed widespread symmetrical FA reduction in CPE patients. Furthermore, asymmetrical temporal lobe FA reduction was consistently ipsilateral to the electroclinical focus. No significant correlations were found between FA alterations and clinical data. There were no differences in brain volumes of CPE patients compared with controls. Despite normal conventional MRI, WM integrity abnormalities in CPE patients extend far beyond the epileptogenic zone. Given that unilateral temporal lobe FA abnormalities were consistently observed ipsilateral to the seizure focus, analysis of temporal FA may provide an informative in vivo investigation into the localisation of the epileptogenic zone in MRI negative patients.
Cognitive functions, electroencephalographic and diffusion tensor imaging changes in children with active idiopathic epilepsy.

PubMed

A Yassine, Imane; M Eldeeb, Waleed; A Gad, Khaled; A Ashour, Yossri; A Yassine, Inas; O Hosny, Ahmed

2018-07-01

Neurocognitive impairment represents one of the most common comorbidities occurring in children with idiopathic epilepsy. Diagnosis of the idiopathic form of epilepsy requires the absence of any macrostructural abnormality in the conventional MRI. Though changes can be seen at the microstructural level imaged using advanced techniques such as the Diffusion Tensor Imaging (DTI). The aim of this work is to study the correlation between the microstructural white matter DTI findings, the electroencephalographic changes and the cognitive dysfunction in children with active idiopathic epilepsy. A comparative cross-sectional study, included 60 children with epilepsy based on the Stanford-Binet 5th Edition Scores was conducted. Patients were equally assigned to normal cognitive function or cognitive dysfunction groups. The history of the epileptic condition was gathered via personal interviews. All patients underwent brain Electroencephalography (EEG) and DTI, which was analyzed using FSL. The Fractional Anisotropy (FA) was significantly higher whereas the Mean Diffusivity (MD) was significantly lower in the normal cognitive function group than in the cognitive dysfunction group. This altered microstructure was related to the degree of the cognitive performance of the studied children with epilepsy. The microstructural alterations of the neural fibers in children with epilepsy and cognitive dysfunction were significantly related to the younger age of onset of epilepsy, the poor control of the clinical seizures, and the use of multiple antiepileptic medications. Children with epilepsy and normal cognitive functions differ in white matter integrity, measured using DTI, compared with children with cognitive dysfunction. These changes have important cognitive consequences. Copyright © 2018 Elsevier Inc. All rights reserved.
Changes in lumbosacral spinal nerve roots on diffusion tensor imaging in spinal stenosis.

PubMed

Hou, Zhong-Jun; Huang, Yong; Fan, Zi-Wen; Li, Xin-Chun; Cao, Bing-Yi

2015-11-01

Lumbosacral degenerative disc disease is a common cause of lower back and leg pain. Conventional T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) scans are commonly used to image spinal cord degeneration. However, these modalities are unable to image the entire lumbosacral spinal nerve roots. Thus, in the present study, we assessed the potential of diffusion tensor imaging (DTI) for quantitative assessment of compressed lumbosacral spinal nerve roots. Subjects were 20 young healthy volunteers and 31 patients with lumbosacral stenosis. T2WI showed that the residual dural sac area was less than two-thirds that of the corresponding normal area in patients from L3 to S1 stenosis. On T1WI and T2WI, 74 lumbosacral spinal nerve roots from 31 patients showed compression changes. DTI showed thinning and distortion in 36 lumbosacral spinal nerve roots (49%) and abruption in 17 lumbosacral spinal nerve roots (23%). Moreover, fractional anisotropy values were reduced in the lumbosacral spinal nerve roots of patients with lumbosacral stenosis. These findings suggest that DTI can objectively and quantitatively evaluate the severity of lumbosacral spinal nerve root compression.
Spatial Mapping of Structural and Connectional Imaging Data for the Developing Human Brain with Diffusion Tensor Imaging

PubMed Central

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao

2014-01-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302

DWI-based neural fingerprinting technology: a preliminary study on stroke analysis.

PubMed

Ye, Chenfei; Ma, Heather Ting; Wu, Jun; Yang, Pengfei; Chen, Xuhui; Yang, Zhengyi; Ma, Jingbo

2014-01-01

Stroke is a common neural disorder in neurology clinics. Magnetic resonance imaging (MRI) has become an important tool to assess the neural physiological changes under stroke, such as diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Quantitative analysis of MRI images would help medical doctors to localize the stroke area in the diagnosis in terms of structural information and physiological characterization. However, current quantitative approaches can only provide localization of the disorder rather than measure physiological variation of subtypes of ischemic stroke. In the current study, we hypothesize that each kind of neural disorder would have its unique physiological characteristics, which could be reflected by DWI images on different gradients. Based on this hypothesis, a DWI-based neural fingerprinting technology was proposed to classify subtypes of ischemic stroke. The neural fingerprint was constructed by the signal intensity of the region of interest (ROI) on the DWI images under different gradients. The fingerprint derived from the manually drawn ROI could classify the subtypes with accuracy 100%. However, the classification accuracy was worse when using semiautomatic and automatic method in ROI segmentation. The preliminary results showed promising potential of DWI-based neural fingerprinting technology in stroke subtype classification. Further studies will be carried out for enhancing the fingerprinting accuracy and its application in other clinical practices.
Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling.

PubMed

Ertas, Gokhan

2018-07-01

To assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors. Fifty tumors imaged using DTI on a 3 T MRI device were analyzed. Regions of interests focusing on the center of tumor foci and noncancerous tissue on the maps of mean diffusivity (MD) and fractional anisotropy (FA) were used to extract the minimum, the maximum and the mean measures. Measure ratio was computed by dividing tumor measure by noncancerous tissue measure. Logistic regression models were fitted for all possible pair combinations of the measures using 5-fold cross validation. Systematic differences are present for all MD measures and also for all FA measures in distinguishing the high risk tumors [GS ≥ 7(4 + 3)] from the low risk tumors [GS ≤ 7(3 + 4)] (P < 0.05). Smaller value for MD measures and larger value for FA measures indicate the high risk. The models enrolling the measures achieve good fits and good classification performances (R 2 adj  = 0.55-0.60, AUC = 0.88-0.91), however the models using the measure ratios perform better (R 2 adj  = 0.59-0.75, AUC = 0.88-0.95). The model that employs the ratios of minimum MD and maximum FA accomplishes the highest sensitivity, specificity and accuracy (Se = 77.8%, Sp = 96.9% and Acc = 90.0%). Joint evaluation of MD and FA diffusion tensor imaging measures is valuable to detect high GS risk group peripheral zone prostate tumors. However, use of the ratios of the measures improves the accuracy of the detections substantially. Logistic regression modelling provides a favorable solution for the joint evaluations easily adoptable in clinical practice. Copyright © 2018 Elsevier Inc. All rights reserved.
Diffusion tensor imaging can detect the early stages of cartilage damage: a comparison study.

PubMed

Ukai, Taku; Sato, Masato; Yamashita, Tomohiro; Imai, Yutaka; Mitani, Genya; Takagaki, Tomonori; Serigano, Kenji; Mochida, Joji

2015-02-21

In the present study, we measured damaged areas of cartilage with diffusion tensor (DT) imaging and T2 mapping, and investigated the extent to which cartilage damage could be determined using these techniques. Forty-one patients underwent arthroscopic knee surgery for osteoarthritis of the knee, a meniscus injury, or an anterior cruciate ligament injury. Preoperative magnetic resonance imaging of the knee was performed, including T2 mapping and diffusion tensor imaging. The presence of cartilage injury involving the medial and lateral femoral condyles and tibia plateau was assessed during surgery using the Outerbridge scale. The ADC, T2 values and fractional anisotropy of areas of cartilage injury were then retrospectively analysed. The ADC results identified significant differences between Outerbridge grades 0 and 2 (P = 0.041); 0 and 3 (P < 0.001); 1 and 2 (P = 0.045); 1 and 3 (P < 0.001); and 2 and 3 (P = 0.028). The FA results identified significant differences between grades 0 and 1 (P < 0.001); 0 and 2 (P < 0.001); and 0 and 3 (P < 0.001). T2 mapping identified significant differences between Outerbridge grades 0 and 2 (P = 0.032); 0 and 3 (P < 0.001); 1 and 3 (P < 0.001); and 2 and 3 (P < 0.001). Both the T2 mapping (R(2) = 0.7883) and the ADC (R(2) = 0.9184) correlated significantly with the Outerbridge grade. The FA (R(2) = 0.6616) correlated slightly with the Outerbridge grade. T2 mapping can be useful for detecting moderate or severe cartilage damage, and the ADC can be used to detect early stage cartilage damage. The FA can also distinguish normal from damaged cartilage.
Bilateral Brain Regions Associated with Naming in Older Adults

ERIC Educational Resources Information Center

Obler, Loraine K.; Rykhlevskaia, Elena; Schnyer, David; Clark-Cotton, Manuella R.; Spiro, Avron, III; Hyun, JungMoon; Kim, Dae-Shik; Goral, Mira; Albert, Martin L.

2010-01-01

To determine structural brain correlates of naming abilities in older adults, we tested 24 individuals aged 56-79 on two confrontation-naming tests (the Boston Naming Test (BNT) and the Action Naming Test (ANT)), then collected from these individuals structural Magnetic-Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI) data. Overall,…
A Tractography Study in Dyslexia: Neuroanatomic Correlates of Orthographic, Phonological and Speech Processing

ERIC Educational Resources Information Center

Vandermosten, Maaike; Boets, Bart; Poelmans, Hanne; Sunaert, Stefan; Wouters, Jan; Ghesquiere, Pol

2012-01-01

Diffusion tensor imaging tractography is a structural magnetic resonance imaging technique allowing reconstruction and assessment of the integrity of three dimensional white matter tracts, as indexed by their fractional anisotropy. It is assumed that the left arcuate fasciculus plays a crucial role for reading development, as it connects two…
Affinity learning with diffusion on tensor product graph.

PubMed

Yang, Xingwei; Prasad, Lakshman; Latecki, Longin Jan

2013-01-01

In many applications, we are given a finite set of data points sampled from a data manifold and represented as a graph with edge weights determined by pairwise similarities of the samples. Often the pairwise similarities (which are also called affinities) are unreliable due to noise or due to intrinsic difficulties in estimating similarity values of the samples. As observed in several recent approaches, more reliable similarities can be obtained if the original similarities are diffused in the context of other data points, where the context of each point is a set of points most similar to it. Compared to the existing methods, our approach differs in two main aspects. First, instead of diffusing the similarity information on the original graph, we propose to utilize the tensor product graph (TPG) obtained by the tensor product of the original graph with itself. Since TPG takes into account higher order information, it is not a surprise that we obtain more reliable similarities. However, it comes at the price of higher order computational complexity and storage requirement. The key contribution of the proposed approach is that the information propagation on TPG can be computed with the same computational complexity and the same amount of storage as the propagation on the original graph. We prove that a graph diffusion process on TPG is equivalent to a novel iterative algorithm on the original graph, which is guaranteed to converge. After its convergence we obtain new edge weights that can be interpreted as new, learned affinities. We stress that the affinities are learned in an unsupervised setting. We illustrate the benefits of the proposed approach for data manifolds composed of shapes, images, and image patches on two very different tasks of image retrieval and image segmentation. With learned affinities, we achieve the bull's eye retrieval score of 99.99 percent on the MPEG-7 shape dataset, which is much higher than the state-of-the-art algorithms. When the data- points are image patches, the NCut with the learned affinities not only significantly outperforms the NCut with the original affinities, but it also outperforms state-of-the-art image segmentation methods.
Deficits in Docosahexaenoic Acid Accrual during Adolescence Reduce Rat Forebrain White Matter Microstructural Integrity: An in vivo Diffusion Tensor Imaging Study.

PubMed

McNamara, Robert K; Schurdak, Jennifer D; Asch, Ruth H; Peters, Bart D; Lindquist, Diana M

2018-01-01

Neuropsychiatric disorders that frequently initially emerge during adolescence are associated with deficits in the omega-3 (n-3) fatty acid docosahexaenoic acid (DHA), elevated proinflammatory signaling, and regional reductions in white matter integrity (WMI). This study determined the effects of altering brain DHA accrual during adolescence on WMI in the rat brain by diffusion tensor imaging (DTI), and investigated the potential mediating role of proinflammatory signaling. During periadolescent development, male rats were fed a diet deficient in n-3 fatty acids (DEF, n = 20), a fish oil-fortified diet containing preformed DHA (FO, n = 20), or a control diet (CON, n = 20). In adulthood, DTI scans were performed and brain WMI was determined using voxelwise tract-based spatial statistics (TBSS). Postmortem fatty acid composition, peripheral (plasma IL-1β, IL-6, and C-reactive protein [CRP]) and central (IL-1β and CD11b mRNA) proinflammatory markers, and myelin basic protein (MBP) mRNA expression were determined. Compared with CON rats, forebrain DHA levels were lower in DEF rats and higher in FO rats. Compared with CON rats, DEF rats exhibited greater radial diffusivity (RD) and mean diffusivity in the right external capsule, and greater axial diffusivity in the corpus callosum genu and left external capsule. DEF rats also exhibited greater RD than FO rats in the right external capsule. Forebrain MBP expression did not differ between groups. Compared with CON rats, central (IL-1β and CD11b) and peripheral (IL-1β and IL-6) proinflammatory markers were not different in DEF rats, and DEF rats exhibited lower CRP levels. These findings demonstrate that deficits in adolescent DHA accrual negatively impact forebrain WMI, independently of elevated proinflammatory signaling. © 2017 S. Karger AG, Basel.
Diffusion anisotropy in fresh and fixed prostate tissue ex vivo.

PubMed

Bourne, Roger M; Bongers, Andre; Chatterjee, Aritrick; Sved, Paul; Watson, Geoffrey

2016-08-01

To investigate diffusion anisotropy in whole human prostate specimens Seven whole radical prostatectomy specimens were obtained with informed patient consent and institutional ethics approval. Diffusion tensor imaging was performed at 9.4 Tesla. Diffusion tensors were calculated from the native acquired data and after progressive downsampling Fractional anisotropy (FA) decreased as voxel volume increased, and differed widely between prostates. Fixation decreased mean FA by ∼0.05-0.08 at all voxel volumes but did not alter principle eigenvector orientation. In unfixed tissue high FA (> 0.6) was found only in voxels of volume <0.5 mm(3) , and then only in a small fraction of all voxels. At typical clinical voxel volumes (4-16 mm(3) ) less than 50% of voxels had FA > 0.25. FA decreased at longer diffusion times (Δ = 60 or 80 ms compared with 20 ms), but only by ∼0.02 at typical clinical voxel volume. Peripheral zone FA was significantly lower than transition zone FA in five of the seven prostates FA varies widely between prostates. The very small proportion of clinical size voxels with high FA suggests that in clinical DWI studies ADC based on three-direction measurements will be minimally affected by anisotropy. Magn Reson Med 76:626-634, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
Neurocognitive Effects of Radiotherapy

DTIC Science & Technology

2014-10-01

patients have completed a 4-5 hour neurocognitive testing assessment at baseline by Dr. Carol Armstrong. In addition , all patients have completed a 1...hour standard MRI as well as additional testing including diffuse tensor imaging (DTI), perfusion and diffusion. The majority of patients have...completed baseline and at least two additional time-points in regards to both neurocognitive testing and MRI. Eight patients have completed
Microstructures in striato-thalamo-orbitofrontal circuit in methamphetamine users.

PubMed

Li, Yadi; Dong, Haibo; Li, Feng; Wang, Gaoyan; Zhou, Wenhua; Yu, Rongbin; Zhang, Lingjun

2017-11-01

Background Striato-thalamo-orbitofrontal (STO) circuit plays a key role in the development of drug addiction. Few studies have investigated its microstructural abnormalities in methamphetamine (MA) users. Purpose To evaluate the microstructural changes and relevant clinical relevance of the STO circuit in MA users using diffusion tensor imaging (DTI). Material and Methods Twenty-eight MA users and 28 age-matched normal volunteers were enrolled. 3T magnetic resonance imaging (MRI) was employed to obtain structural T1-weighted (T1W) imaging and diffusion-tensor imaging (DTI) data. Freesurfer software was used for automated segmentation of the bilateral nucleus accumbens (NAc), thalami, and orbitofrontal cortex (OFC). Four DTI measures maps, fractional anisotropy (FA), mean diffusivity (MD), axial diffusion (AD), and radial diffusion (RD) were generated and non-linearly co-registered to structural space. Comparisons of DTI measures of the STO circuit were carried out between MA and controls using repeated measures analysis of variance. Correlation analyses were performed between STO circuit DTI measures and clinical characteristics. Results The MA group had significant FA reduction in the bilateral NAc, OFC, and right thalamus ( P < 0.05). Lower left OFC FA and right NAc FA/AD were associated with longer duration of MA use. Lower right OFC FA was associated with younger age at first MA use. Higher FA and lower MD/RD in the thalamus, as well as higher left OFC RD, were associated with increased psychiatric symptoms. Conclusion The STO circuit has reduced microstructural integrity in MA users. Microstructural changes in the thalamus may compensate for dysfunction in functionally connected cortices, which needs further investigation.
High Resolution Diffusion Tensor Imaging of Cortical-Subcortical White Matter Tracts in TBI

DTIC Science & Technology

2009-10-01

other words, CT perfusion is a change in CT intensity (or Hounsfield Unit , HU) over time following a bolus of iodine based contrast agent. Although...E-Mail: little@uic.edu 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT...estimates of the eigenvalues and decrease the signal-to-noise ratio, a background noise level of 125 (MR Units ) was applied prior to calculation of
Relationship between white matter integrity and serum cortisol levels in drug-naive patients with major depressive disorder: diffusion tensor imaging study using tract-based spatial statistics.

PubMed

Liu, Xiaodan; Watanabe, Keita; Kakeda, Shingo; Yoshimura, Reiji; Abe, Osamu; Ide, Satoru; Hayashi, Kenji; Katsuki, Asuka; Umene-Nakano, Wakako; Watanabe, Rieko; Ueda, Issei; Nakamura, Jun; Korogi, Yukunori

2016-06-01

Higher daytime cortisol levels because of a hyperactive hypothalamic-pituitary-adrenal axis have been reported in patients with major depressive disorder (MDD). The elevated glucocorticoids inhibit the proliferation of the oligodendrocytes that are responsible for myelinating the axons of white matter fibre tracts. To evaluate the relationship between white matter integrity and serum cortisol levels during a first depressive episode in drug-naive patients with MDD (MDD group) using a tract-based spatial statistics (TBSS) method. The MDD group (n = 29) and a healthy control group (n = 47) underwent diffusion tensor imaging (DTI) scans and an analysis was conducted using TBSS. Morning blood samples were obtained from both groups for cortisol measurement. Compared with the controls, the MDD group had significantly reduced fractional anisotropy values (P<0.05, family-wise error (FWE)-corrected) in the inferior fronto-occipital fasciculus, uncinate fasciculus and anterior thalamic radiation. The fractional anisotropy values of the inferior fronto-occipital fasciculus, uncinate fasciculus and anterior thalamic radiation had significantly negative correlations with the serum cortisol levels in the MDD group (P<0.05, FWE-corrected). Our findings indicate that the elevated cortisol levels in the MDD group may injure the white matter integrity in the frontal-subcortical and frontal-limbic circuits. © The Royal College of Psychiatrists 2016.
White matter abnormalities of microstructure and physiological noise in schizophrenia.

PubMed

Cheng, Hu; Newman, Sharlene D; Kent, Jerillyn S; Bolbecker, Amanda; Klaunig, Mallory J; O'Donnell, Brian F; Puce, Aina; Hetrick, William P

2015-12-01

White matter abnormalities in schizophrenia have been revealed by many imaging techniques and analysis methods. One of the findings by diffusion tensor imaging is a decrease in fractional anisotropy (FA), which is an indicator of white matter integrity. On the other hand, elevation of metabolic rate in white matter was observed from positron emission tomography (PET) studies. In this report, we aim to compare the two structural and functional effects on the same subjects. Our comparison is based on the hypothesis that signal fluctuation in white matter is associated with white matter functional activity. We examined the variance of the signal in resting state fMRI and found significant differences between individuals with schizophrenia and non-psychiatric controls specifically in white matter tissue. Controls showed higher temporal signal-to-noise ratios clustered in regions including temporal, frontal, and parietal lobes, cerebellum, corpus callosum, superior longitudinal fasciculus, and other major white matter tracts. These regions with higher temporal signal-to-noise ratio agree well with those showing higher metabolic activity reported by studies using PET. The results suggest that individuals with schizophrenia tend to have higher functional activity in white matter in certain brain regions relative to healthy controls. Despite some overlaps, the distinct regions for physiological noise are different from those for FA derived from diffusion tensor imaging, and therefore provide a unique angle to explore potential mechanisms to white matter abnormality.
Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis.

PubMed

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.
Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging.

PubMed

Lemkaddem, Alia; Daducci, Alessandro; Kunz, Nicolas; Lazeyras, François; Seeck, Margitta; Thiran, Jean-Philippe; Vulliémoz, Serge

2014-01-01

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities.
Differences in Supratentorial Damage of White Matter in Pediatric Survivors of Posterior Fossa Tumors With and Without Adjuvant Treatment as Detected by Magnetic Resonance Diffusion Tensor Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rueckriegel, Stefan Mark, E-mail: stefan.rueckriegel@charite.d; Driever, Pablo Hernaiz; Blankenburg, Friederike

2010-03-01

Purpose: To elucidate morphologic correlates of brain dysfunction in pediatric survivors of posterior fossa tumors by using magnetic resonance diffusion tensor imaging (DTI) to examine neuroaxonal integrity in white matter. Patients and Methods: Seventeen medulloblastoma (MB) patients who had received surgery and adjuvant treatment, 13 pilocytic astrocytoma (PA) patients who had been treated only with surgery, and age-matched healthy control subjects underwent magnetic resonance imaging on a 3-Tesla system. High-resolution conventional T1- and T2-weighted magnetic resonance imaging and DTI data sets were obtained. Fractional anisotropy (FA) maps were analyzed using tract-based spatial statistics, a part of the Functional MRI ofmore » the Brain Software Library. Results: Compared with control subjects, FA values of MB patients were significantly decreased in the cerebellar midline structures, in the frontal lobes, and in the callosal body. Fractional anisotropy values of the PA patients were not only decreased in cerebellar hemispheric structures as expected, but also in supratentorial parts of the brain, with a distribution similar to that in MB patients. However, the amount of significantly decreased FA was greater in MB than in PA patients, underscoring the aggravating neurotoxic effect of the adjuvant treatment. Conclusions: Neurotoxic mechanisms that are present in PA patients (e.g., internal hydrocephalus and damaged cerebellar structures affecting neuronal circuits) contribute significantly to the alteration of supratentorial white matter in pediatric posterior fossa tumor patients.« less
The Superior Frontal Transsulcal Approach to the Anterior Ventricular System: Exploring the Sulcal and Subcortical Anatomy Using Anatomic Dissections and Diffusion Tensor Imaging Tractography.

PubMed

Koutsarnakis, Christos; Liakos, Faidon; Kalyvas, Aristotelis V; Skandalakis, Georgios P; Komaitis, Spyros; Christidi, Fotini; Karavasilis, Efstratios; Liouta, Evangelia; Stranjalis, George

2017-10-01

To explore the superior frontal sulcus (SFS) morphology, trajectory of the applied surgical corridor, and white matter bundles that are traversed during the superior frontal transsulcal transventricular approach. Twenty normal, adult, formalin-fixed cerebral hemispheres and 2 cadaveric heads were included in the study. The topography, morphology, and dimensions of the SFS were recorded in all specimens. Fourteen hemispheres were investigated through the fiber dissection technique whereas the remaining 6 were explored using coronal cuts. The cadaveric heads were used to perform the superior frontal transsulcal transventricular approach. In addition, 2 healthy volunteers underwent diffusion tensor imaging and tractography reconstruction studies. The SFS was interrupted in 40% of the specimens studied and was always parallel to the interhemispheric fissure. The proximal 5 cm of the SFS (starting from the SFS precentral sulcus meeting point) were found to overlie the anterior ventricular system in all hemispheres. Five discrete white matter layers were identified en route to the anterior ventricular system (i.e., the arcuate fibers, the frontal aslant tract, the external capsule, internal capsule, and the callosal radiations). Diffusion tensor imaging studies confirmed the fiber tract architecture. When feasible, the superior frontal transsulcal transventricular approach offers a safe and effective corridor to the anterior part of the lateral ventricle because it minimizes brain retraction and transgression and offers a wide and straightforward working corridor. Meticulous preoperative planning coupled with a sound microneurosurgical technique are prerequisites to perform the approach successfully. Copyright © 2017 Elsevier Inc. All rights reserved.
Anisotropic diffusion of fluorescently labeled ATP in rat cardiomyocytes determined by raster image correlation spectroscopy

PubMed Central

Vendelin, Marko; Birkedal, Rikke

2008-01-01

A series of experimental data points to the existence of profound diffusion restrictions of ADP/ATP in rat cardiomyocytes. This assumption is required to explain the measurements of kinetics of respiration, sarcoplasmic reticulum loading with calcium, and kinetics of ATP-sensitive potassium channels. To be able to analyze and estimate the role of intracellular diffusion restrictions on bioenergetics, the intracellular diffusion coefficients of metabolites have to be determined. The aim of this work was to develop a practical method for determining diffusion coefficients in anisotropic medium and to estimate the overall diffusion coefficients of fluorescently labeled ATP in rat cardiomyocytes. For that, we have extended raster image correlation spectroscopy (RICS) protocols to be able to discriminate the anisotropy in the diffusion coefficient tensor. Using this extended protocol, we estimated diffusion coefficients of ATP labeled with the fluorescent conjugate Alexa Fluor 647 (Alexa-ATP). In the analysis, we assumed that the diffusion tensor can be described by two values: diffusion coefficient along the myofibril and that across it. The average diffusion coefficients found for Alexa-ATP were as follows: 83 ± 14 μm2/s in the longitudinal and 52 ± 16 μm2/s in the transverse directions (n = 8, mean ± SD). Those values are ∼2 (longitudinal) and ∼3.5 (transverse) times smaller than the diffusion coefficient value estimated for the surrounding solution. Such uneven reduction of average diffusion coefficient leads to anisotropic diffusion in rat cardiomyocytes. Although the source for such anisotropy is uncertain, we speculate that it may be induced by the ordered pattern of intracellular structures in rat cardiomyocytes. PMID:18815224
White matter microstructural alterations in clinically isolated syndrome and multiple sclerosis.

PubMed

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.
Diffusion tensor imaging of the inferior colliculus and brainstem auditory-evoked potentials in preterm infants.

PubMed

Reiman, Milla; Parkkola, Riitta; Johansson, Reijo; Jääskeläinen, Satu K; Kujari, Harry; Lehtonen, Liisa; Haataja, Leena; Lapinleimu, Helena

2009-08-01

Preterm and low-birth-weight infants have an increased risk of sensorineural hearing loss. Brainstem auditory-evoked potentials (BAEP) are an effective method to detect subtle deficits in impulse conduction in the auditory pathway. Abnormalities on diffusion tensor imaging (DTI) have been shown to be associated with perinatal white-matter injury and reduced fractional anisotropy (FA) has been reported in patients with sensorineural hearing loss. To evaluate the possibility of a correlation between BAEP and DTI of the inferior colliculus in preterm infants. DTI at term age and BAEP measurements were performed on all very-low-birth-weight or very preterm study infants (n=56). FA and apparent diffusion coefficient (ADC) of the inferior colliculus were measured from the DTI. Shorter BAEP wave I, III, and V latencies and I-III and I-V intervals and higher wave V amplitude correlated with higher FA of the inferior colliculus. The association between the DTI findings of the inferior colliculus and BAEP responses suggests that DTI can be used to assess the integrity of the auditory pathway in preterm infants.

White matter alterations in narcolepsy patients with cataplexy: tract-based spatial statistics.

PubMed

Park, Yun K; Kwon, Oh-Hun; Joo, Eun Yeon; Kim, Jae-Hun; Lee, Jong M; Kim, Sung T; Hong, Seung B

2016-04-01

Functional imaging studies and voxel-based morphometry analysis of brain magnetic resonance imaging showed abnormalities in the hypothalamus-thalamus-orbitofrontal pathway, demonstrating altered hypocretin pathway in narcolepsy. Those distinct morphometric changes account for problems in wake-sleep control, attention and memory. It also raised the necessity to evaluate white matter changes. To investigate brain white matter alterations in drug-naïve narcolepsy patients with cataplexy and to explore relationships between white matter changes and patient clinical characteristics, drug-naïve narcolepsy patients with cataplexy (n = 22) and healthy age- and gender-matched controls (n = 26) were studied. Fractional anisotropy and mean diffusivity images were obtained from whole-brain diffusion tensor imaging, and tract-based spatial statistics were used to localize white matter abnormalities. Compared with controls, patients showed significant decreases in fractional anisotropy of white matter of the bilateral anterior cingulate, fronto-orbital area, frontal lobe, anterior limb of the internal capsule and corpus callosum, as well as the left anterior and medial thalamus. Patients and controls showed no differences in mean diffusivity. Among patients, mean diffusivity values of white matter in the bilateral superior frontal gyri, bilateral fronto-orbital gyri and right superior parietal gyrus were positively correlated with depressive mood. This tract-based spatial statistics study demonstrated that drug-naïve patients with narcolepsy had reduced fractional anisotropy of white matter in multiple brain areas and significant relationship between increased mean diffusivity of white matter in frontal/cingulate and depression. It suggests the widespread disruption of white matter integrity and prevalent brain degeneration of frontal lobes according to a depressive symptom in narcolepsy. © 2015 European Sleep Research Society.
Perilesional and contralateral white matter evolution and integrity in patients with periventricular nodular heterotopia and epilepsy: a longitudinal diffusion tensor imaging study.

PubMed

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.
Introduction to Vector Field Visualization

NASA Technical Reports Server (NTRS)

Kao, David; Shen, Han-Wei

2010-01-01

Vector field visualization techniques are essential to help us understand the complex dynamics of flow fields. These can be found in a wide range of applications such as study of flows around an aircraft, the blood flow in our heart chambers, ocean circulation models, and severe weather predictions. The vector fields from these various applications can be visually depicted using a number of techniques such as particle traces and advecting textures. In this tutorial, we present several fundamental algorithms in flow visualization including particle integration, particle tracking in time-dependent flows, and seeding strategies. For flows near surfaces, a wide variety of synthetic texture-based algorithms have been developed to depict near-body flow features. The most common approach is based on the Line Integral Convolution (LIC) algorithm. There also exist extensions of LIC to support more flexible texture generations for 3D flow data. This tutorial reviews these algorithms. Tensor fields are found in several real-world applications and also require the aid of visualization to help users understand their data sets. Examples where one can find tensor fields include mechanics to see how material respond to external forces, civil engineering and geomechanics of roads and bridges, and the study of neural pathway via diffusion tensor imaging. This tutorial will provide an overview of the different tensor field visualization techniques, discuss basic tensor decompositions, and go into detail on glyph based methods, deformation based methods, and streamline based methods. Practical examples will be used when presenting the methods; and applications from some case studies will be used as part of the motivation.
Diffusion tensor imaging and diffusion tensor imaging-fibre tractograph depict the mechanisms of Broca-like and Wernicke-like conduction aphasia.

PubMed

Song, Xinjie; Dornbos, David; Lai, Zongli; Zhang, Yumei; Li, Tieshan; Chen, Hongyan; Yang, Zhonghua

2011-06-01

Conduction aphasia is usually considered a result of damage of the arcuate fasciculus, which is subjacent to the parietal portion of the supra-marginal gyrus and the upper part of the insula. It is important to stress that many features of conduction aphasia relate to a cortical deficit, more than a pure disconnection mechanism. In this study, we explore the mechanism of Broca-like and Wernicke-like conduction aphasia by using diffusion tensor imaging (DTI) and diffusion tensor imaging-fibre tractograph (DT-FT). We enrolled five Broca-like conduction aphasia cases, five Wernicke-like aphasia conduction cases and 10 healthy volunteers residing in Beijing and speaking Mandarin. All are right handed. We analyzed the arcuate fasciculus, Broca's areas and Wernicke's areas by DTI and measured fractional anisotrogy (FA). The results of left and right hemispheres were compared in both conduction aphasia cases and volunteers. Then the results of the conduction aphasia cases were compared with those of volunteers. The fibre construction of Broca's and Wernicke's areas was also compared by DTI-FT. The FA occupied by the identified connective pathways (Broca's area, Wernicke's area and the arcuate fasciculus) in the left hemisphere was larger than that in the right hemisphere in the control group (P<0.05). Among Broca-like conduction aphasia cases, the FA of the left Broca's area was smaller than that of the right mirror side (P<0.05), and the FA of the left anterior segment of the arcuate fasciculus was smaller than that of right mirror side (P<0.05). On the other hand, among Wernicke-like conduction aphasia patients, the FA of the left Wernicke's area was smaller than that of right mirror side (P<0.05), and the FA of left posterior segment of arcuate fasciculus was smaller than that of right mirror side (P<0.05). Conduction aphasia results from not only arcuate fasciculus destruction, but also from disruption of the associated cortical areas. Along different segments of the arcuate fasciculus, the characteristics of language disorders of conduction aphasia were different. A lesion involving Broca's area and the anterior segments of the arcuate fasciculus would lead to Broca-like conduction aphasia, whereas a lesion involved Wernicke's area and posterior segments of the arcuate fasciculus would lead to Wernicke-like conduction aphasia.
White matter pathology in ALS and lower motor neuron ALS variants: a diffusion tensor imaging study using tract-based spatial statistics.

PubMed

Prudlo, Johannes; Bißbort, Charlotte; Glass, Aenne; Grossmann, Annette; Hauenstein, Karlheinz; Benecke, Reiner; Teipel, Stefan J

2012-09-01

The aim of this work was to investigate white-matter microstructural changes within and outside the corticospinal tract in classical amyotrophic lateral sclerosis (ALS) and in lower motor neuron (LMN) ALS variants by means of diffusion tensor imaging (DTI). We investigated 22 ALS patients and 21 age-matched controls utilizing a whole-brain approach with a 1.5-T scanner for DTI. The patient group was comprised of 15 classical ALS- and seven LMN ALS-variant patients (progressive muscular atrophy, flail arm and flail leg syndrome). Disease severity was measured by the revised version of the functional rating scale. White matter fractional anisotropy (FA) was assessed using tract-based spatial statistics (TBSS) and a region of interest (ROI) approach. We found significant FA reductions in motor and extra-motor cerebral fiber tracts in classical ALS and in the LMN ALS-variant patients compared to controls. The voxel-based TBSS results were confirmed by the ROI findings. The white matter damage correlated with the disease severity in the patient group and was found in a similar distribution, but to a lesser extent, among the LMN ALS-variant subgroup. ALS and LMN ALS variants are multisystem degenerations. DTI shows the potential to determine an earlier diagnosis, particularly in LMN ALS variants. The statistically identical findings of white matter lesions in classical ALS and LMN variants as ascertained by DTI further underline that these variants should be regarded as part of the ALS spectrum.
Correlating subcortical interhemispheric connectivity and cortical hemispheric dominance in brain tumor patients: A repetitive navigated transcranial magnetic stimulation study.

PubMed

Sollmann, Nico; Ille, Sebastian; Tussis, Lorena; Maurer, Stefanie; Hauck, Theresa; Negwer, Chiara; Bauer, Jan S; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-02-01

The present study aims to investigate the relationship between transcallosal interhemispheric connectivity (IC) and hemispheric language lateralization by using a novel approach including repetitive navigated transcranial magnetic stimulation (rTMS), hemispheric dominance ratio (HDR) calculation, and rTMS-based diffusion tensor imaging fiber tracking (DTI FT). 31 patients with left-sided perisylvian brain lesions underwent diffusion tensor imaging (DTI) and rTMS language mapping. Cortical language-positive rTMS spots were used to calculate HDRs (HDR: quotient of the left-sided divided by right-sided naming error rates for corresponding left- and right-sided cortical regions) and to create regions of interest (ROIs) for DTI FT. Then, fibers connecting the rTMS-based ROIs of both hemispheres were tracked, and the correlation of IC to HDRs was calculated via Spearman's rank correlation coefficient (rs). Fibers connecting rTMS-based ROIs of both hemispheres were detected in 12 patients (38.7%). Within the patients in which IC was detected, the mean number of subcortical IC fibers ± standard deviation (SD) was 138.0 ± 346.5 (median: 7.5; range: 1-1,217 fibers). Regarding rs for the correlation of HDRs and fiber numbers of patients that showed IC, only moderate correlation was revealed. Our approach might be beneficial and technically feasible for further investigation of the relationship between IC and language lateralization. However, only moderate correlation was revealed in the present study. Copyright © 2015 Elsevier B.V. All rights reserved.
Diffusion tensor imaging of nigral degeneration in Parkinson's disease: A region-of-interest and voxel-based study at 3 T and systematic review with meta-analysis☆

PubMed Central

Schwarz, Stefan T.; Abaei, Maryam; Gontu, Vamsi; Morgan, Paul S.; Bajaj, Nin; Auer, Dorothee P.

2013-01-01

There is increasing interest in developing a reliable, affordable and accessible disease biomarker of Parkinson's disease (PD) to facilitate disease modifying PD-trials. Imaging biomarkers using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) can describe parameters such as fractional anisotropy (FA), mean diffusivity (MD) or apparent diffusion coefficient (ADC). These parameters, when measured in the substantia nigra (SN), have not only shown promising but also varying and controversial results. To clarify the potential diagnostic value of nigral DTI in PD and its dependency on selection of region-of-interest, we undertook a high resolution DTI study at 3 T. 59 subjects (32 PD patients, 27 age and sex matched healthy controls) were analysed using manual outlining of SN and substructures, and voxel-based analysis (VBA). We also performed a systematic literature review and meta-analysis to estimate the effect size (DES) of disease related nigral DTI changes. We found a regional increase in nigral mean diffusivity in PD (mean ± SD, PD 0.80 ± 0.10 vs. controls 0.73 ± 0.06 · 10− 3 mm2/s, p = 0.002), but no difference using a voxel based approach. No significant disease effect was seen using meta-analysis of nigral MD changes (10 studies, DES = + 0.26, p = 0.17, I2 = 30%). None of the nigral regional or voxel based analyses of this study showed altered fractional anisotropy. Meta-analysis of 11 studies on nigral FA changes revealed a significant PD induced FA decrease. There was, however, a very large variation in results (I2 = 86%) comparing all studies. After exclusion of five studies with unusual high values of nigral FA in the control group, an acceptable heterogeneity was reached, but there was non-significant disease effect (DES = − 0.5, p = 0.22, I2 = 28%). The small PD related nigral MD changes in conjunction with the negative findings on VBA and meta-analysis limit the usefulness of nigral MD measures as biomarker of Parkinson's disease. The negative results of nigral FA measurements at regional, sub-regional and voxel level in conjunction with the results of the meta-analysis of nigral FA changes question the stability and validity of this measure as a PD biomarker. PMID:24273730
Cerebrovascular risk factors and brain microstructural abnormalities on diffusion tensor images in HIV-infected individuals.

PubMed

Nakamoto, Beau K; Jahanshad, Neda; McMurtray, Aaron; Kallianpur, Kalpana J; Chow, Dominic C; Valcour, Victor G; Paul, Robert H; Marotz, Liron; Thompson, Paul M; Shikuma, Cecilia M

2012-08-01

HIV-associated neurocognitive disorder remains prevalent in HIV-infected individuals despite effective antiretroviral therapy. As these individuals age, comorbid cerebrovascular disease will likely impact cognitive function. Effective tools to study this impact are needed. This study used diffusion tensor imaging (DTI) to characterize brain microstructural changes in HIV-infected individuals with and without cerebrovascular risk factors. Diffusion-weighted MRIs were obtained in 22 HIV-infected subjects aged 50 years or older (mean age = 58 years, standard deviation = 6 years; 19 males, three females). Tensors were calculated to obtain fractional anisotropy (FA) and mean diffusivity (MD) maps. Statistical comparisons accounting for multiple comparisons were made between groups with and without cerebrovascular risk factors. Abnormal glucose metabolism (i.e., impaired fasting glucose, impaired glucose tolerance, or diabetes mellitus) was associated with significantly higher MD (false discovery rate (FDR) critical p value = 0.008) and lower FA (FDR critical p value = 0.002) in the caudate and lower FA in the hippocampus (FDR critical p value = 0.004). Pearson correlations were performed between DTI measures in the caudate and hippocampus and age- and education-adjusted composite scores of global cognitive function, memory, and psychomotor speed. There were no detectable correlations between the neuroimaging measures and measures of cognition. In summary, we demonstrate that brain microstructural abnormalities are associated with abnormal glucose metabolism in the caudate and hippocampus of HIV-infected individuals. Deep gray matter structures and the hippocampus may be vulnerable in subjects with comorbid abnormal glucose metabolism, but our results should be confirmed in further studies.
Diffusion tensor imaging of normal-appearing white matter in mild cognitive impairment and early Alzheimer disease: preliminary evidence of axonal degeneration in the temporal lobe.

PubMed

Huang, J; Friedland, R P; Auchus, A P

2007-01-01

Diffusion tensor imaging (DTI) is a sensitive technique for studying cerebral white matter. We used DTI to characterize microstructural white matter changes and their associations with cognitive dysfunction in Alzheimer disease (AD) and mild cognitive impairment (MCI). We studied elderly subjects with mild AD (n = 6), MCI (n = 11), or normal cognition (n = 8). A standardized clinical and neuropsychological evaluation was conducted on each subject. DTI images were acquired, and fractional anisotropy (FA), axial diffusivity (DA), and radial diffusivity (DR) of normal-appearing white matter (NAWM) in frontal, temporal, parietal, and occipital lobes were determined. These diffusion measurements were compared across the 3 groups, and significant differences were further examined for correlations with tests of cognitive function. Compared with normal controls, AD subjects demonstrated decreased FA and increased DR in the temporal, parietal, and frontal NAWM and decreased DA in temporal NAWM. MCI subjects also showed decreased FA and decreased DA in temporal NAWM, with decreased FA and increased DR in parietal NAWM. Diffusion measurements showed no differences in occipital NAWM. Across all subjects, temporal lobe FA and DR correlated with episodic memory, frontal FA and DR correlated with executive function, and parietal DR significantly correlated with visuospatial ability. We found evidence for functionally relevant microstructural changes in the NAWM of patients with AD and MCI. These changes were present in brain regions serving higher cortical functions, but not in regions serving primary functions, and are consistent with a hypothesized loss of axonal processes in the temporal lobe.
Characteristics of lesional and extra-lesional cortical grey matter in relapsing-remitting and secondary progressive multiple sclerosis: A magnetisation transfer and diffusion tensor imaging study.

PubMed

Yaldizli, Özgür; Pardini, Matteo; Sethi, Varun; Muhlert, Nils; Liu, Zheng; Tozer, Daniel J; Samson, Rebecca S; Wheeler-Kingshott, Claudia Am; Yousry, Tarek A; Miller, David H; Chard, Declan T

2016-02-01

In multiple sclerosis (MS), diffusion tensor and magnetisation transfer imaging are both abnormal in lesional and extra-lesional cortical grey matter, but differences between clinical subtypes and associations with clinical outcomes have only been partly assessed. To compare mean diffusivity, fractional anisotropy and magnetisation transfer ratio (MTR) in cortical grey matter lesions (detected using phase-sensitive inversion recovery (PSIR) imaging) and extra-lesional cortical grey matter, and assess associations with disability in relapse-onset MS. Seventy-two people with MS (46 relapsing-remitting (RR), 26 secondary progressive (SP)) and 36 healthy controls were included in this study. MTR, mean diffusivity and fractional anisotropy were measured in lesional and extra-lesional cortical grey matter. Mean fractional anisotropy was higher and MTR lower in lesional compared with extra-lesional cortical grey matter. In extra-lesional cortical grey matter mean fractional anisotropy and MTR were lower, and mean diffusivity was higher in the MS group compared with controls. Mean MTR was lower and mean diffusivity was higher in lesional and extra-lesional cortical grey matter in SPMS when compared with RRMS. These differences were independent of disease duration. In multivariate analyses, MTR in extra-lesional more so than lesional cortical grey matter was associated with disability. Magnetic resonance abnormalities in lesional and extra-lesional cortical grey matter are greater in SPMS than RRMS. Changes in extra-lesional compared with lesional cortical grey matter are more consistently associated with disability. © The Author(s), 2015.
White matter abnormalities in major depressive disorder with melancholic and atypical features: A diffusion tensor imaging study.

PubMed

Ota, Miho; Noda, Takamasa; Sato, Noriko; Hattori, Kotaro; Hori, Hiroaki; Sasayama, Daimei; Teraishi, Toshiya; Nagashima, Anna; Obu, Satoko; Higuchi, Teruhiko; Kunugi, Hiroshi

2015-06-01

The DSM-IV recognizes some subtypes of major depressive disorder (MDD). It is known that the effectiveness of antidepressants differs among the MDD subtypes, and thus the differentiation of the subtypes is important. However, little is known as to structural brain changes in MDD with atypical features (aMDD) in comparison with MDD with melancholic features (mMDD), which prompted us to examine possible differences in white matter integrity assessed with diffusion tensor imaging (DTI) between these two subtypes. Subjects were 21 patients with mMDD, 24 with aMDD, and 37 age- and sex-matched healthy volunteers whose DTI data were obtained by 1.5 tesla magnetic resonance imaging. We compared fractional anisotropy and mean diffusivity value derived from DTI data on a voxel-by-voxel basis among the two diagnostic groups and healthy subjects. There were significant decreases of fractional anisotropy and increases of mean diffusivity in patients with MDD compared with healthy subjects in the corpus callosum, inferior fronto-occipital fasciculus, and left superior longitudinal fasciculus. However, we detected no significant difference in any brain region between mMDD and aMDD. Our results suggest that patients with MDD had reduced white matter integrity in some regions; however, there was no major difference between aMDD and mMDD. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.
Evaluating Kurtosis-based Diffusion MRI Tissue Models for White Matter with Fiber Ball Imaging

PubMed Central

Jensen, Jens H.; McKinnon, Emilie T.; Glenn, G. Russell; Helpern, Joseph A.

2018-01-01

In order to quantify well-defined microstructural properties of brain tissue from diffusion MRI (dMRI) data, tissue models are typically employed that relate biological features, such as cell morphology and cell membrane permeability, to the diffusion dynamics. A variety of such models have been proposed for white matter, and their validation is a topic of active interest. In this paper, three different tissue models are tested by comparing their predictions for a specific microstructural parameter to the value measured independently with a recently proposed dMRI method known as fiber ball imaging (FBI). The three tissue models are all constructed with the diffusion and kurtosis tensors, and they are hence compatible with diffusional kurtosis imaging (DKI). Nevertheless, the models differ significantly in their details and predictions. For voxels with fractional anisotropies (FA) exceeding 0.5, all three are reasonably consistent with FBI. However, for lower FA values, one of these, called the white matter tract integrity (WMTI) model, is found to be in much better accord with FBI than the other two, suggesting that the WMTI model has a broader range of applicability. PMID:28085211
Characterization and correction of eddy-current artifacts in unipolar and bipolar diffusion sequences using magnetic field monitoring.

PubMed

Chan, Rachel W; von Deuster, Constantin; Giese, Daniel; Stoeck, Christian T; Harmer, Jack; Aitken, Andrew P; Atkinson, David; Kozerke, Sebastian

2014-07-01

Diffusion tensor imaging (DTI) of moving organs is gaining increasing attention but robust performance requires sequence modifications and dedicated correction methods to account for system imperfections. In this study, eddy currents in the "unipolar" Stejskal-Tanner and the velocity-compensated "bipolar" spin-echo diffusion sequences were investigated and corrected for using a magnetic field monitoring approach in combination with higher-order image reconstruction. From the field-camera measurements, increased levels of second-order eddy currents were quantified in the unipolar sequence relative to the bipolar diffusion sequence while zeroth and linear orders were found to be similar between both sequences. Second-order image reconstruction based on field-monitoring data resulted in reduced spatial misalignment artifacts and residual displacements of less than 0.43 mm and 0.29 mm (in the unipolar and bipolar sequences, respectively) after second-order eddy-current correction. Results demonstrate the need for second-order correction in unipolar encoding schemes but also show that bipolar sequences benefit from second-order reconstruction to correct for incomplete intrinsic cancellation of eddy-currents. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Local texture descriptors for the assessment of differences in diffusion magnetic resonance imaging of the brain.

PubMed

Thomsen, Felix Sebastian Leo; Delrieux, Claudio Augusto; de Luis-García, Rodrigo

2017-03-01

Descriptors extracted from magnetic resonance imaging (MRI) of the brain can be employed to locate and characterize a wide range of pathologies. Scalar measures are typically derived within a single-voxel unit, but neighborhood-based texture measures can also be applied. In this work, we propose a new set of descriptors to compute local texture characteristics from scalar measures of diffusion tensor imaging (DTI), such as mean and radial diffusivity, and fractional anisotropy. We employ weighted rotational invariant local operators, namely standard deviation, inter-quartile range, coefficient of variation, quartile coefficient of variation and skewness. Sensitivity and specificity of those texture descriptors were analyzed with tract-based spatial statistics of the white matter on a diffusion MRI group study of elderly healthy controls, patients with mild cognitive impairment (MCI), and mild or moderate Alzheimer's disease (AD). In addition, robustness against noise has been assessed with a realistic diffusion-weighted imaging phantom and the contamination of the local neighborhood with gray matter has been measured. The new texture operators showed an increased ability for finding formerly undetected differences between groups compared to conventional DTI methods. In particular, the coefficient of variation, quartile coefficient of variation, standard deviation and inter-quartile range of the mean and radial diffusivity detected significant differences even between previously not significantly discernible groups, such as MCI versus moderate AD and mild versus moderate AD. The analysis provided evidence of low contamination of the local neighborhood with gray matter and high robustness against noise. The local operators applied here enhance the identification and localization of areas of the brain where cognitive impairment takes place and thus indicate them as promising extensions in diffusion MRI group studies.
A Locally Adaptive Regularization Based on Anisotropic Diffusion for Deformable Image Registration of Sliding Organs

PubMed Central

Pace, Danielle F.; Aylward, Stephen R.; Niethammer, Marc

2014-01-01

We propose a deformable image registration algorithm that uses anisotropic smoothing for regularization to find correspondences between images of sliding organs. In particular, we apply the method for respiratory motion estimation in longitudinal thoracic and abdominal computed tomography scans. The algorithm uses locally adaptive diffusion tensors to determine the direction and magnitude with which to smooth the components of the displacement field that are normal and tangential to an expected sliding boundary. Validation was performed using synthetic, phantom, and 14 clinical datasets, including the publicly available DIR-Lab dataset. We show that motion discontinuities caused by sliding can be effectively recovered, unlike conventional regularizations that enforce globally smooth motion. In the clinical datasets, target registration error showed improved accuracy for lung landmarks compared to the diffusive regularization. We also present a generalization of our algorithm to other sliding geometries, including sliding tubes (e.g., needles sliding through tissue, or contrast agent flowing through a vessel). Potential clinical applications of this method include longitudinal change detection and radiotherapy for lung or abdominal tumours, especially those near the chest or abdominal wall. PMID:23899632
A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs.

PubMed

Pace, Danielle F; Aylward, Stephen R; Niethammer, Marc

2013-11-01

We propose a deformable image registration algorithm that uses anisotropic smoothing for regularization to find correspondences between images of sliding organs. In particular, we apply the method for respiratory motion estimation in longitudinal thoracic and abdominal computed tomography scans. The algorithm uses locally adaptive diffusion tensors to determine the direction and magnitude with which to smooth the components of the displacement field that are normal and tangential to an expected sliding boundary. Validation was performed using synthetic, phantom, and 14 clinical datasets, including the publicly available DIR-Lab dataset. We show that motion discontinuities caused by sliding can be effectively recovered, unlike conventional regularizations that enforce globally smooth motion. In the clinical datasets, target registration error showed improved accuracy for lung landmarks compared to the diffusive regularization. We also present a generalization of our algorithm to other sliding geometries, including sliding tubes (e.g., needles sliding through tissue, or contrast agent flowing through a vessel). Potential clinical applications of this method include longitudinal change detection and radiotherapy for lung or abdominal tumours, especially those near the chest or abdominal wall.
Combined Diffusion Tensor Imaging and Transverse Relaxometry in Early-Onset Bipolar Disorder

ERIC Educational Resources Information Center

Gonenc, Atilla; Frazier, Jean A.; Crowley, David J.; Moore, Constance M.

2010-01-01

Objective: Transverse relaxation time (T2) imaging provides the opportunity to examine membrane fluidity, which can affect a number of cellular functions. The objective of the present work was to examine T2 abnormalities in children with unmodified DSM-IV-TR bipolar disorder (BD) in bilateral cingulate-paracingulate (CPC) white matter. Method: A…
Strength of Default Mode Resting-State Connectivity Relates to White Matter Integrity in Children

ERIC Educational Resources Information Center

Gordon, Evan M.; Lee, Philip S.; Maisog, Jose M.; Foss-Feig, Jennifer; Billington, Michael E.; VanMeter, John; Vaidya, Chandan J.

2011-01-01

A default mode network of brain regions is known to demonstrate coordinated activity during the resting state. While the default mode network is well characterized in adults, few investigations have focused upon its development. We scanned 9-13-year-old children with diffusion tensor imaging and resting-state functional magnetic resonance imaging.…
Axonal disruption in white matter underlying cortical sulcus tau pathology in chronic traumatic encephalopathy.

PubMed

Holleran, Laurena; Kim, Joong Hee; Gangolli, Mihika; Stein, Thor; Alvarez, Victor; McKee, Ann; Brody, David L

2017-03-01

Chronic traumatic encephalopathy (CTE) is a progressive degenerative disorder associated with repetitive traumatic brain injury. One of the primary defining neuropathological lesions in CTE, based on the first consensus conference, is the accumulation of hyperphosphorylated tau in gray matter sulcal depths. Post-mortem CTE studies have also reported myelin loss, axonal injury and white matter degeneration. Currently, the diagnosis of CTE is restricted to post-mortem neuropathological analysis. We hypothesized that high spatial resolution advanced diffusion MRI might be useful for detecting white matter microstructural changes directly adjacent to gray matter tau pathology. To test this hypothesis, formalin-fixed post-mortem tissue blocks from the superior frontal cortex of ten individuals with an established diagnosis of CTE were obtained from the Veterans Affairs-Boston University-Concussion Legacy Foundation brain bank. Advanced diffusion MRI data was acquired using an 11.74 T MRI scanner at Washington University with 250 × 250 × 500 µm 3 spatial resolution. Diffusion tensor imaging, diffusion kurtosis imaging and generalized q-sampling imaging analyses were performed in a blinded fashion. Following MRI acquisition, tissue sections were tested for phosphorylated tau immunoreactivity in gray matter sulcal depths. Axonal disruption in underlying white matter was assessed using two-dimensional Fourier transform analysis of myelin black gold staining. A robust image co-registration method was applied to accurately quantify the relationship between diffusion MRI parameters and histopathology. We found that white matter underlying sulci with high levels of tau pathology had substantially impaired myelin black gold Fourier transform power coherence, indicating axonal microstructural disruption (r = -0.55, p = 0.0015). Using diffusion tensor MRI, we found that fractional anisotropy (FA) was modestly (r = 0.53) but significantly (p = 0.0012) correlated with axonal disruption, where lower FA was associated with greater axonal disruption in white matter directly adjacent to hyperphosphorylated tau positive sulci. In summary, our findings indicate that axonal disruption and tau pathology are closely associated, and high spatial resolution ex vivo diffusion MRI has the potential to detect microstructural alterations observed in CTE tissue. Future studies will be required to determine whether this approach can be applied to living people.
Artifact correction in diffusion MRI of non-human primate brains on a clinical 3T scanner.

PubMed

Zhang, Xiaodong; Kirsch, John E; Zhong, Xiaodong

2016-02-01

Smearing artifacts were observed and investigated in diffusion tensor imaging (DTI) studies of macaque monkeys on a clinical whole-body 3T scanner. Four adult macaques were utilized to evaluate DTI artifacts. DTI images were acquired with a single-shot echo-planar imaging (EPI) sequence using a parallel imaging technique. The smearing artifacts observed on the diffusion-weighted images and fractional anisotropy maps were caused by the incomplete fat suppression due to the irregular macaque frontal skull geometry and anatomy. The artifact can be reduced substantially using a novel three-dimensional (3D) shimming procedure. The smearing artifacts observed on diffusion weighted images and fractional anisotropy (FA) maps of macaque brains can be reduced substantially using a robust 3D shimming approach. The DTI protocol combined with the shimming procedure could be a robust approach to examine brain connectivity and white matter integrity of non-human primates using a conventional clinical setting. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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