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.

White Matter Alteration Following SWAT Explosive Breaching Training and the Moderating Effect of a Neck Collar Device: A DTI and NODDI Study

2021 ◽  
Author(s):  
Weihong Yuan ◽  
Jonathan Dudley ◽  
Alexis B Slutsky-Ganesh ◽  
James Leach ◽  
Pete Scheifele ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Moderating Effect ◽  
Significant Group ◽  
Blast Exposure ◽  
Diffusion Weighted ◽  
Weighted Data ◽  
The Right ◽  
The Impact

ABSTRACT Introduction Special Weapons and Tactics (SWAT) personnel who practice breaching with blast exposure are at risk for blast-related head trauma. We aimed to investigate the impact of low-level blast exposure on underlying white matter (WM) microstructure based on diffusion tensor imaging (DTI) and neurite orientation and density imaging (NODDI) in SWAT personnel before and after breacher training. Diffusion tensor imaging is an advanced MRI technique sensitive to underlying WM alterations. NODDI is a novel MRI technique emerged recently that acquires diffusion weighted data from multiple shells modeling for different compartments in the microstructural environment in the brain. We also aimed to evaluate the effect of a jugular vein compression collar device in mitigating the alteration of the diffusion properties in the WM as well as its role as a moderator on the association between the diffusion property changes and the blast exposure. Materials and Methods Twenty-one SWAT personnel (10 non-collar and 11 collar) completed the breacher training and underwent MRI at both baseline and after blast exposure. Diffusion weighted data were acquired with two shells (b = 1,000, 2,000 s/mm2) on 3T Phillips scanners. Diffusion tensor imaging metrices, including fractional anisotropy, mean, axial, and radial diffusivity, and NODDI metrics, including neurite density index (NDI), isotropic volume fraction (fiso), and orientation dispersion index, were calculated. Tract-based spatial statistics was used in the voxel-wise statistical analysis. Post hoc analyses were performed for the quantification of the pre- to post-blast exposure diffusion percentage change in the WM regions with significant group difference and for the assessment of the interaction of the relationship between blast exposure and diffusion alteration. Results The non-collar group exhibited significant pre- to post-blast increase in NDI (corrected P < .05) in the WM involving the right internal capsule, the right posterior corona radiation, the right posterior thalamic radiation, and the right sagittal stratum. A subset of these regions showed significantly greater alteration in NDI and fiso in the non-collar group when compared with those in the collar group (corrected P < .05). In addition, collar wearing exhibited a significant moderating effect for the alteration of fiso for its association with average peak pulse pressure. Conclusions Our data provided initial evidence of the impact of blast exposure on WM diffusion alteration based on both DTI and NODDI. The mitigating effect of WM diffusivity changes and the moderating effect of collar wearing suggest that the device may serve as a promising solution to protect WM against blast exposure.

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.

scholarly journals Regions of white matter abnormalities in the arcuate fasciculus in veterans with anger and aggression problems

2019 ◽  
Vol 225 (4) ◽  
pp. 1401-1411 ◽  
Author(s):  
Szabolcs David ◽  
Lieke Heesink ◽  
Elbert Geuze ◽  
Thomas Gladwin ◽  
Jack van Honk ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Military Veterans ◽  
Self Regulation ◽  
Brain Regions ◽  
Microstructural Properties ◽  
Uncinate Fasciculus ◽  
Arcuate Fasciculus ◽  
White Matter Connectivity ◽  
Diffusion Tensor Imaging Tractography

AbstractAggression after military deployment is a common occurrence in veterans. Neurobiological research has shown that aggression is associated with a dysfunction in a network connecting brain regions implicated in threat processing and emotion regulation. However, aggression may also be related to deficits in networks underlying communication and social cognition. The uncinate and arcuate fasciculi are integral to these networks, thus studying potential abnormalities in these white matter connections can further our understanding of anger and aggression problems in military veterans. Here, we use diffusion tensor imaging tractography to investigate white matter microstructural properties of the uncinate fasciculus and the arcuate fasciculus in veterans with and without anger and aggression problems. A control tract, the parahippocampal cingulum was also included in the analyses. More specifically, fractional anisotropy (FA) estimates are derived along the trajectory from all fiber pathways and compared between both groups. No between-group FA differences are observed for the uncinate fasciculus and the cingulum, however parts of the arcuate fasciculus show a significantly lower FA in the group of veterans with aggression and anger problems. Our data suggest that abnormalities in arcuate fasciculus white matter connectivity that are related to self-regulation may play an important role in the etiology of anger and aggression in military veterans.

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.

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