White Matter Fiber Tracts Based On Diffusion Tensor Imaging

2008 ◽  
Author(s):  
Qian Di ◽  
Tingting Wang ◽  
Li Yao ◽  
XiaoJie Zhao
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts

Postshunting corpus callosum swelling with depiction on tractography

2013 ◽  
Vol 11 (2) ◽  
pp. 178-180 ◽  
Author(s):  
Daniel T. Ginat ◽  
Sanjay P. Prabhu ◽  
Joseph R. Madsen
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Corpus Callosum ◽  
Posterior Margin ◽  
Diffusion Tensor ◽  
The Body ◽  
Transverse Orientation ◽  
Chronic Hydrocephalus ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts

Alterations in the appearance of the corpus callosum occasionally occur following successful ventricular decompression in patients with chronic hydrocephalus. There are certain features on imaging that suggest the diagnosis of what the authors propose be termed “postshunting corpus callosum swelling,” including diffuse high T2 signal predominantly affecting the body of the corpus callosum, with transverse orientation along the crossing white matter tracts and scalloping along the posterior margin of the structure. In this report, the authors demonstrate preservation of the corpus callosum white matter fiber tracts by using diffusion tensor imaging with tractography.

scholarly journals Diffusion tensor imaging correlates of hippocampal sclerosis and anterior temporal lobe T2 signal changes in pharmacoresistant epilepsy

2014 ◽  
Vol 01 (01) ◽  
pp. 001-007 ◽  
Author(s):  
Kevin Spitler ◽  
Francis Tirol ◽  
Itzhak Fried ◽  
Jerome Engel ◽  
Noriko Salamon
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Temporal Lobe ◽  
Diffusion Tensor ◽  
Hippocampal Sclerosis ◽  
Anterior Temporal Lobe ◽  
Pharmacoresistant Epilepsy ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
The Right

AbstractBackground and purpose Our goal was to determine fiber tract integrity in hippocampal sclerosis (HS) using diffusion tensor imaging (DTI) and to correlate white matter damage with other pathology in this disease.Methods Twenty-six patients and eight controls were studied with DTI tractography for 8 pairs of white matter fiber tracts and 2 commissural tracts. Fractional anisotropy (FA) of the fiber tracts was compared with controls. The FA of select fiber tracts was also compared with change in T2 signal in the anterior temporal lobe (ATC), and the performance on neuropsychological tests.Results In comparison with controls, subjects with left sided hippocampal sclerosis (L-HS) had 3 ipsilateral fiber tracts with decreased FA. The FA of fiber tracts was similar in right sided HS (R-HS) to controls. The ipsilateral inferior longitudinal fasciculus had a decrease in FA that correlated with the ATC (T2 signal change). The right superior longitudinal fasciculus had a decrease in FA proportional to lower performance on tests of memory and language.Conclusion The subjects with L-HS had more extensive structural abnormalities involving white matter tracts, both ipsilateral and contralateral. In contrast, subjects with R-HS had limited changes in white matter integrity. Pathology of white matter appears to be involved in deficits associated with HS, including ATC and cognitive performance.

scholarly journals A Longitudinal Diffusion Tensor Imaging Study Assessing White Matter Fiber Tracts after Sports-Related Concussion

2014 ◽  
Vol 31 (22) ◽  
pp. 1860-1871 ◽  
Author(s):  
Murali Murugavel ◽  
Valerie Cubon ◽  
Margot Putukian ◽  
Ruben Echemendia ◽  
Javier Cabrera ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
Longitudinal Diffusion ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
Diffusion Tensor Imaging Study

scholarly journals Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Node Degree ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
Structural Brain Network ◽  
Structural Networks

AbstractIn diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

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 Motor cortex gliomas induces microstructural changes of large fiber tracts revealed by TBSS

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xiangdong Wang ◽  
Chunyao Zhou ◽  
Lei Wang ◽  
Yinyan Wang ◽  
Tao Jiang
Keyword(s):  
White Matter ◽  
Motor Cortex ◽  
Diffusion Tensor ◽  
Early Stage ◽  
Mean Diffusivity ◽  
Cerebral White Matter ◽  
Control Group ◽  
Fiber Tracts ◽  
3.0 T ◽  
White Matter Fiber Tracts

Abstract Gliomas grow and invade along white matter fiber tracts. This study assessed the effects of motor cortex gliomas on the cerebral white matter fiber bundle skeleton. The motor cortex glioma group included 21 patients, and the control group comprised 14 healthy volunteers. Both groups underwent magnetic resonance imaging-based 3.0 T diffusion tensor imaging. We used tract-based spatial statistics to analyze the characteristics of white matter fiber bundles. The left and right motor cortex glioma groups were analyzed separately from the control group. Results were statistically corrected by the family-wise error rate. Compared with the controls, patients with left motor cortex gliomas exhibited significantly reduced fractional anisotropy and an increased radial diffusivity in the corpus callosum. The alterations in mean diffusivity (MD) and the axial diffusivity (AD) were widely distributed throughout the brain. Furthermore, atlas-based analysis showed elevated MD and AD in the contralateral superior fronto-occipital fasciculus. Motor cortex gliomas significantly affect white matter fiber microstructure proximal to the tumor. The range of affected white matter fibers may extend beyond the tumor-affected area. These changes are primarily related to early stage tumor invasion.

scholarly journals A Quantitative DTI Fiber Tract Analysis Suite

2005 ◽  
Author(s):  
Casey Goodlett ◽  
Isabelle Corouge ◽  
Matthieu Jomier ◽  
Guido Gerig
Keyword(s):  
Image Processing ◽  
Diffusion Tensor Imaging ◽  
User Interface ◽  
Quantitative Analysis ◽  
White Matter ◽  
Open Source ◽  
Diffusion Tensor ◽  
Fiber Tracts ◽  
Underlying Geometry ◽  
Diffusion Tensor Imaging Dti

Diffusion tensor imaging (DTI) allows a quantitative study of the underlying geometry and architecture of white matter. We have developed a suite of open source tools for quantitative analysis of DTI suitable for use in clinical research studies. We have leveraged open source tools for file IO, image processing, visualization, and user interface. The tools are designed to provide several interconnected modules to perform quantitative analysis of DTI data based on fiber tracts generated from tractography.

Abstract 221: Regional Vulnerability within White Matter tracts to White Matter Hyperintensities: a Diffusion Tensor Imaging Tractography Study

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Pauline Maillard ◽  
Sudha Seshadri ◽  
Alexa Beiser ◽  
Jayandra Himali ◽  
Charles DeCarli
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Cognitive Decline ◽  
White Matter Hyperintensities ◽  
Diffusion Tensor ◽  
Brain Mri ◽  
Fiber Tracts ◽  
Regional Vulnerability ◽  
Increased Risk ◽  
The Impact

Background: Characterizing the impact of cerebral white matter (WM) damage on age related cognitive decline is of growing interest. White matter hyperintensities (WMH) and reduced microstructural WM integrity, as expressed by diffusion tensor imaging (DTI), have been associated with increased risk of clinically cognitive decline in the elderly, but the regional vulnerability within certain WM tracts to WMH is not well understood. Characterizing the implication and interactions of microstructural integrity and WMH within specific WM tracts would further elucidate mechanisms of cognitive decline in normal aging. Methods: 410 cognitively normal individuals from the Offspring Framingham Heart Study, aged 72.5±7.5 ([54.2; 104.9]), received a comprehensive clinical evaluation and brain MRI including FLAIR and DTI sequences. WM tractography was performed from DTI using FSL tools, resulting in 27 fiber tracts maps for each subject. WMHs were detected on FLAIR scans using a standardized protocol and coregistered to the subject DTI space. The mean fractional anisotrophy (mFA) within each tract was computed. Superimposition of WMH masks onto fiber tracts maps was used to calculate the overlap ratio of WMH (WMHor) within each tract. For each tract, mFA was regressed against the age and tract size and resulting residuals related to WMHor using a linear regression model. Results: The highest rates of WMHor were found within the thalamic radiations (range: [0- 28%]) and the inferior longitudinal fasciculi ([0- 29%]). Lower mFA was independently associated with larger WMHor within almost all association and projection fibers (p values<0.05). Correcting for the overall WMH burden did not significantly alter the results. Discussion: Regional mean FA has been previously associated with the overall WMH burden. We extended this finding by showing that, independently of the overall WM injury, microstructural WM integrity was associated with WMH within specific fiber tracts. Further investigations are needed to detangle the impact of specific tract disruption from that of more generalized subtle WM injury on cognitive decline.

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