scholarly journals Normal Development of Human Brain White Matter from Infancy to Early Adulthood: A Diffusion Tensor Imaging Study

2015 ◽  
Vol 37 (2) ◽  
pp. 182-194 ◽  
Author(s):  
Satoshi Uda ◽  
Mie Matsui ◽  
Chiaki Tanaka ◽  
Akiko Uematsu ◽  
Kayoko Miura ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Growth Rates ◽  
Right Hemisphere ◽  
Diffusion Tensor ◽  
Early Adulthood ◽  
Brain Regions ◽  
Hemispheric Differences ◽  
Healthy Humans ◽  
Brain White Matter

Diffusion tensor imaging (DTI), which measures the magnitude of anisotropy of water diffusion in white matter, has recently been used to visualize and quantify parameters of neural tracts connecting brain regions. In order to investigate the developmental changes and sex and hemispheric differences of neural fibers in normal white matter, we used DTI to examine 52 healthy humans ranging in age from 2 months to 25 years. We extracted the following tracts of interest (TOIs) using the region of interest method: the corpus callosum (CC), cingulum hippocampus (CGH), inferior longitudinal fasciculus (ILF), and superior longitudinal fasciculus (SLF). We measured fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD). Approximate values and changes in growth rates of all DTI parameters at each age were calculated and analyzed using LOESS (locally weighted scatterplot smoothing). We found that for all TOIs, FA increased with age, whereas ADC, AD and RD values decreased with age. The turning point of growth rates was at approximately 6 years. FA in the CC was greater than that in the SLF, ILF and CGH. Moreover, FA, ADC and AD of the splenium of the CC (sCC) were greater than in the genu of the CC (gCC), whereas the RD of the sCC was lower than the RD of the gCC. The FA of right-hemisphere TOIs was significantly greater than that of left-hemisphere TOIs. In infants, growth rates of both FA and RD were larger than those of AD. Our data show that developmental patterns differ by TOIs and myelination along with the development of white matter, which can be mainly expressed as an increase in FA together with a decrease in RD. These findings clarify the long-term normal developmental characteristics of white matter microstructure from infancy to early adulthood.

Diffusion tensor imaging in schizophrenia

2008 ◽  
Vol 23 (4) ◽  
pp. 255-273 ◽  
Author(s):  
Marinos Kyriakopoulos ◽  
Theodoros Bargiotas ◽  
Gareth J. Barker ◽  
Sophia Frangou
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Basic Principles ◽  
Future Directions ◽  
White Matter Abnormalities ◽  
Non Invasive ◽  
Brain White Matter ◽  
Diffusion Tensor Imaging Dti

AbstractDiffusion tensor imaging (DTI) is a magnetic resonance imaging technique that is increasingly being used for the non-invasive evaluation of brain white matter abnormalities. In this review, we discuss the basic principles of DTI, its roots and the contribution of European centres in its development, and we review the findings from DTI studies in schizophrenia. We searched EMBASE, PubMed, PsychInfo, and Medline from February 1998 to December 2006 using as keywords ‘schizophrenia’, ‘diffusion’, ‘tensor’, and ‘DTI’. Forty studies fulfilling the inclusion criteria of this review were included and systematically reviewed. White matter abnormalities in many diverse brain regions were identified in schizophrenia. Although the findings are not completely consistent, frontal and temporal white matter seems to be more commonly affected. Limitations and future directions of this method are discussed.

scholarly journals Retrospective analysis of hemispheric structural network change as a function of location and size of glioma

2020 ◽  
Author(s):  
Shawn D’Souza ◽  
Lisa Hirt ◽  
David R Ormond ◽  
John A Thompson
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Temporal Lobe ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Structural Network ◽  
Tumour Location ◽  
The Impact ◽  
Tractography Data ◽  
Diffusion Tensor Imaging Tractography

Abstract Gliomas are neoplasms that arise from glial cell origin and represent the largest fraction of primary malignant brain tumours (77%). These highly infiltrative malignant cell clusters modify brain structure and function through expansion, invasion and intratumoral modification. Depending on the growth rate of the tumour, location and degree of expansion, functional reorganization may not lead to overt changes in behaviour despite significant cerebral adaptation. Studies in simulated lesion models and in patients with stroke reveal both local and distal functional disturbances, using measures of anatomical brain networks. Investigations over the last two decades have sought to use diffusion tensor imaging tractography data in the context of intracranial tumours to improve surgical planning, intraoperative functional localization, and post-operative interpretation of functional change. In this study, we used diffusion tensor imaging tractography to assess the impact of tumour location on the white matter structural network. To better understand how various lobe localized gliomas impact the topology underlying efficiency of information transfer between brain regions, we identified the major alterations in brain network connectivity patterns between the ipsilesional versus contralesional hemispheres in patients with gliomas localized to the frontal, parietal or temporal lobe. Results were indicative of altered network efficiency and the role of specific brain regions unique to different lobe localized gliomas. This work draws attention to connections and brain regions which have shared structural susceptibility in frontal, parietal and temporal lobe glioma cases. This study also provides a preliminary anatomical basis for understanding which affected white matter pathways may contribute to preoperative patient symptomology.

scholarly journals White Matter Integrity Predicts Delay Discounting Behavior in 9- to 23-Year-Olds: A Diffusion Tensor Imaging Study

2009 ◽  
Vol 21 (7) ◽  
pp. 1406-1421 ◽  
Author(s):  
Elizabeth A. Olson ◽  
Paul F. Collins ◽  
Catalina J. Hooper ◽  
Ryan Muetzel ◽  
Kelvin O. Lim ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Delay Discounting ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Imaging Study ◽  
Temporal Lobes ◽  
Brain White Matter ◽  
Independent Effects ◽  
Age Range

Healthy participants (n = 79), ages 9–23, completed a delay discounting task assessing the extent to which the value of a monetary reward declines as the delay to its receipt increases. Diffusion tensor imaging (DTI) was used to evaluate how individual differences in delay discounting relate to variation in fractional anisotropy (FA) and mean diffusivity (MD) within whole-brain white matter using voxel-based regressions. Given that rapid prefrontal lobe development is occurring during this age range and that functional imaging studies have implicated the prefrontal cortex in discounting behavior, we hypothesized that differences in FA and MD would be associated with alterations in the discounting rate. The analyses revealed a number of clusters where less impulsive performance on the delay discounting task was associated with higher FA and lower MD. The clusters were located primarily in bilateral frontal and temporal lobes and were localized within white matter tracts, including portions of the inferior and superior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus, inferior fronto-occipital fasciculus, corticospinal tract, and splenium of the corpus callosum. FA increased and MD decreased with age in the majority of these regions. Some, but not all, of the discounting/DTI associations remained significant after controlling for age. Findings are discussed in terms of both developmental and age-independent effects of white matter organization on discounting behavior.

scholarly journals Quantitative diffusion tensor imaging analysis does not distinguish pediatric canines with mucopolysaccharidosis I from control canines

2017 ◽  
Vol 30 (5) ◽  
pp. 454-460
Author(s):  
Dana M Middleton ◽  
Jonathan Y Li ◽  
Steven D Chen ◽  
Leonard E White ◽  
Patricia I Dickson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Fractional Anisotropy ◽  
Imaging System ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Magnetic Resonance Imaging System ◽  
Radial Diffusivity ◽  
Mucopolysaccharidosis I ◽  
Diffusivity Measurements

Purpose We compared fractional anisotropy and radial diffusivity measurements between pediatric canines affected with mucopolysaccharidosis I and pediatric control canines. We hypothesized that lower fractional anisotropy and higher radial diffusivity values, consistent with dysmyelination, would be present in the mucopolysaccharidosis I cohort. Methods Six canine brains, three affected with mucopolysaccharidosis I and three unaffected, were euthanized at 7 weeks and imaged using a 7T small-animal magnetic resonance imaging system. Average fractional anisotropy and radial diffusivity values were calculated for four white-matter regions based on 100 regions of interest per region per specimen. A 95% confidence interval was calculated for each mean value. Results No difference was seen in fractional anisotropy or radial diffusivity values between mucopolysaccharidosis affected and unaffected brains in any region. In particular, the 95% confidence intervals for mucopolysaccharidosis affected and unaffected canines frequently overlapped for both fractional anisotropy and radial diffusivity measurements. In addition, in some brain regions a large range of fractional anisotropy and radial diffusivity values were seen within the same cohort. Conclusion The fractional anisotropy and radial diffusivity values of white matter did not differ between pediatric mucopolysaccharidosis affected canines and pediatric control canines. Possible explanations include: (a) a lack of white matter tissue differences between mucopolysaccharidosis affected and unaffected brains at early disease stages; (b) diffusion tensor imaging does not detect any existing differences; (c) inflammatory processes such as astrogliosis produce changes that offset the decreased fractional anisotropy values and increased radial diffusivity values that are expected in dysmyelination; and (d) our sample size was insufficient to detect differences. Further studies correlating diffusion tensor imaging findings to histology are warranted.

Diffusion tensor imaging (DTI) findings in schizophrenia: A review

2011 ◽  
Vol 26 (S2) ◽  
pp. 960-960
Author(s):  
J.L. Villegas Martínez ◽  
J.A. Blanco Garrote ◽  
F. Uribe Ladrón de Cegama ◽  
B. Arribas Simón ◽  
G. Cabús Piñol
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Cochrane Review ◽  
Brain Structures ◽  
Brain Regions ◽  
Parahippocampal Gyrus ◽  
First Episode ◽  
Chronic Patients ◽  
Brain White Matter ◽  
Diffusion Tensor Imaging Dti

IntroductionDiffusion tensor imaging (DTI) is a magnetic resonance imaging technique that have increasingly being used for the non-invasive evaluation of brain white matter (WM) abnormalities. Several studies suggest that the normal integration of cerebral function may be compromised in schizophrenia. Abnormalities in WM tracts may be directly relevant for the neuropathology of schizophrenia.ObjetivesThe purpose of this review was to discuss recent DTI findings in schizophrenia and a methodologic analysis.MethodsThe literature search was performed with the search engine PubMed of the U.S. National Library of Medicine. Search strategy used was based on the Cochrane review technique, limited to the period between 1998 (first report on DTI and schizophrenia) and May 2010. And limited to ‘Title/Abstract’. The reference lists of these studies were used to identify additional studies.ResultsThere is a striking amount of heterogeneity in findings, probably by methodologic problems. Brain regions such as the cingulate bundle, corpus callosum, and regions within frontal and temporal WM have a proportionally larger number of positive findings across the studies. In addition, WM tracts as The superior longitudinal fasciculus, fronto-occipital longitudinal fasciculi, uncinate fasciculi, frontal longitudinal fasciculus and the arcuate fasciculus have also positive findings in patients with schizophrenia. Other brain structures as the cerebellar peduncles, the fornix, the hippocampus and parahippocampal gyrus, the thalamic and optic radiations have been evaluated and shown positive findings. However, these findings are not present in all studies. DTI abnormalities in first-episode patients are less robust than in chronic patients.ConclusionsRecent DTI findings further support the hypothesis of structural dysconnectivity in schizophrenia.

Human Brain Diffusion Tensor Imaging Visualization With Virtual Reality

2010 ◽  
Author(s):  
Bin Chen ◽  
John Moreland
Keyword(s):  
Virtual Reality ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Biological Tissues ◽  
Head Tracking ◽  
Fiber Tractography ◽  
Brain White Matter ◽  
Diffusion Tensors ◽  
Visualization Techniques

Magnetic resonance diffusion tensor imaging (DTI) is sensitive to the anisotropic diffusion of water exerted by its macromolecular environment and has been shown useful in characterizing structures of ordered tissues such as the brain white matter, myocardium, and cartilage. The water diffusivity inside of biological tissues is characterized by the diffusion tensor, a rank-2 symmetrical 3×3 matrix, which consists of six independent variables. The diffusion tensor contains much information of diffusion anisotropy. However, it is difficult to perceive the characteristics of diffusion tensors by looking at the tensor elements even with the aid of traditional three dimensional visualization techniques. There is a need to fully explore the important characteristics of diffusion tensors in a straightforward and quantitative way. In this study, a virtual reality (VR) based MR DTI visualization with high resolution anatomical image segmentation and registration, ROI definition and neuronal white matter fiber tractography visualization and fMRI activation map integration is proposed. The VR application will utilize brain image visualization techniques including surface, volume, streamline and streamtube rendering, and use head tracking and wand for navigation and interaction, the application will allow the user to switch between different modalities and visualization techniques, as well making point and choose queries. The main purpose of the application is for basic research and clinical applications with quantitative and accurate measurements to depict the diffusivity or the degree of anisotropy derived from the diffusion tensor.

Diffusion Tensor Imaging and Fiber Tractography

2009 ◽  
pp. 229-246
Author(s):  
Evanthia E. Tripoliti ◽  
Dimitrios I. Fotiadis ◽  
Konstantia Veliou
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Cerebral White Matter ◽  
Tissue Microstructure ◽  
Diffusion Weighted Images ◽  
Fiber Tracts ◽  
Diffusion Weighted ◽  
Magnetic Resonance Imaging Mri

Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) modality which can significantly improve our understanding of the brain structures and neural connectivity. DTI measures are thought to be representative of brain tissue microstructure and are particularly useful for examining organized brain regions, such as white matter tract areas. DTI measures the water diffusion tensor using diffusion weighted pulse sequences which are sensitive to microscopic random water motion. The resulting diffusion weighted images (DWI) display and allow quantification of how water diffuses along axes or diffusion encoding directions. This can help to measure and quantify the tissue’s orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. In this chapter the authors discuss the theoretical aspects of DTI, the information that can be extracted from DTI data, and the use of the extracted information for the reconstruction of fiber tracts and the diagnosis of a disease. In addition, a review of known fiber tracking algorithms is presented.

scholarly journals Aberrant White Matter Networks Mediate Cognitive Impairment in Patients with Silent Lacunar Infarcts in Basal Ganglia Territory

2015 ◽  
Vol 35 (9) ◽  
pp. 1426-1434 ◽  
Author(s):  
Jinfu Tang ◽  
Suyu Zhong ◽  
Yaojing Chen ◽  
Kewei Chen ◽  
Junying Zhang ◽  
...  
Keyword(s):  
White Matter ◽  
Basal Ganglia ◽  
Cognitive Deficits ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Lacunar Infarcts ◽  
Healthy Elderly ◽  
Brain White Matter ◽  
Diffusion Tensor Imaging Tractography

Silent lacunar infarcts, which are present in over 20% of healthy elderly individuals, are associated with subtle deficits in cognitive functions. However, it remains largely unclear how these silent brain infarcts lead to cognitive deficits and even dementia. Here, we used diffusion tensor imaging tractography and graph theory to examine the topological organization of white matter networks in 27 patients with silent lacunar infarcts in the basal ganglia territory and 30 healthy controls. A whole-brain white matter network was constructed for each subject, where the graph nodes represented brain regions and the edges represented interregional white matter tracts. Compared with the controls, the patients exhibited a significant reduction in local efficiency and global efficiency. In addition, a total of eighteen brain regions showed significantly reduced nodal efficiency in patients. Intriguingly, nodal efficiency–behavior associations were significantly different between the two groups. The present findings provide new aspects into our understanding of silent infarcts that even small lesions in subcortical brain regions may affect large-scale cortical white matter network, as such may be the link between subcortical silent infarcts and the associated cognitive impairments. Our findings highlight the need for network-level neuroimaging assessment and more medical care for individuals with silent subcortical infarcts.

Influence of electroconvulsive therapy on white matter structure in a diffusion tensor imaging study

2019 ◽  
Vol 50 (5) ◽  
pp. 849-856 ◽  
Author(s):  
Jonathan Repple ◽  
Susanne Meinert ◽  
Irene Bollettini ◽  
Dominik Grotegerd ◽  
Ronny Redlich ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Prospective Study ◽  
Electroconvulsive Therapy ◽  
Inpatient Treatment ◽  
Right Hemisphere ◽  
Diffusion Tensor ◽  
Therapy Response ◽  
Seizure Duration ◽  
Depressed Patients

AbstractBackgroundElectroconvulsive therapy (ECT) is a fast-acting intervention for major depressive disorder. Previous studies indicated neurotrophic effects following ECT that might contribute to changes in white matter brain structure. We investigated the influence of ECT in a non-randomized prospective study focusing on white matter changes over time.MethodsTwenty-nine severely depressed patients receiving ECT in addition to inpatient treatment, 69 severely depressed patients with inpatient treatment (NON-ECT) and 52 healthy controls (HC) took part in a non-randomized prospective study. Participants were scanned twice, approximately 6 weeks apart, using diffusion tensor imaging, applying tract-based spatial statistics. Additional correlational analyses were conducted in the ECT subsample to investigate the effects of seizure duration and therapeutic response.ResultsMean diffusivity (MD) increased after ECT in the right hemisphere, which was an ECT-group-specific effect. Seizure duration was associated with decreased fractional anisotropy (FA) following ECT. Longitudinal changes in ECT were not associated with therapy response. However, within the ECT group only, baseline FA was positively and MD negatively associated with post-ECT symptomatology.ConclusionOur data suggest that ECT changes white matter integrity, possibly reflecting increased permeability of the blood–brain barrier, resulting in disturbed communication of fibers. Further, baseline diffusion metrics were associated with therapy response. Coherent fiber structure could be a prerequisite for a generalized seizure and inhibitory brain signaling necessary to successfully inhibit increased seizure activity.

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