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.

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.

Diffusion tensor imaging in multiple sclerosis: a tool for monitoring changes in normal-appearing white matter

2004 ◽  
Vol 10 (2) ◽  
pp. 188-196 ◽  
Author(s):  
Emmanuelle Cassol ◽  
Jean-Philippe Ranjeva ◽  
Danielle Ibarrola ◽  
Claude Mékies ◽  
Claude Manelfe ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Lesion Load ◽  
Normal Appearing White Matter ◽  
Relapsing Remitting ◽  
One Year ◽  
Diffusion Tensor Imaging Dti

Our objectives were to determine the reproducibility of diffusion tensor imaging (DTI) in volunteers and to evaluate the ability of the method to monitor longitudinal changes occurring in the normal-appearing white matter (NAWM) of patients with multiple sclerosis (MS). DTI was performed three-mo nthly for one year in seven MS patients: three relapsing-remitting (RRMS), three secondary progressive (SPMS) and one relapsing SP. They were selected with a limited cerebral lesion load. Seven age- and sex-matched controls also underwent monthly examinations for three months. Diffusivity and anisotropy were quantified over the segmented whole supratentorial white matter, with the indices of trace (Tr) and fractional anisotropy (FA). Results obtained in volunteers show the reproducibility of the method. Patients had higher trace and lower anisotropy than matched controls (P B-0.0001). O ver the follow-up, both Tr and FA indicated a recovery after the acute phase in RRMS and a progressive shift towards abnormal values in SPMS. A lthough this result is not statistically significant, it suggests that DTI is sensitive to microscopic changes occurring in tissue of normal appearance in conventional images and could be useful for monitoring the course of the disease, even though it was unable to clearly distinguish between the various physiopathological processes involved.

scholarly journals Magnetic resonance diffusion tensor imaging in psychiatry: a narrative review of its potential role in diagnosis

2020 ◽  
Author(s):  
Piotr Podwalski ◽  
Krzysztof Szczygieł ◽  
Ernest Tyburski ◽  
Leszek Sagan ◽  
Błażej Misiak ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Magnetic Resonance ◽  
Potential Role ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Water Molecules ◽  
Mental Diseases ◽  
The Brain ◽  
Diffusion Tensor Imaging Dti

Abstract Diffusion tensor imaging (DTI) is an imaging technique that uses magnetic resonance. It measures the diffusion of water molecules in tissues, which can occur either without restriction (i.e., in an isotropic manner) or limited by some obstacles, such as cell membranes (i.e., in an anisotropic manner). Diffusion is most often measured in terms of, inter alia, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). DTI allows us to reconstruct, visualize, and evaluate certain qualities of white matter. To date, many studies have sought to associate various changes in the distribution of diffusion within the brain with mental diseases and disorders. A better understanding of white matter integrity disorders can help us recognize the causes of diseases, as well as help create objective methods of psychiatric diagnosis, identify biomarkers of mental illness, and improve pharmacotherapy. The aim of this work is to present the characteristics of DTI as well as current research on its use in schizophrenia, affective disorders, and other mental disorders.

scholarly journals Diffusion tensor imaging and tractwise fractional anisotropy statistics: quantitative analysis in white matter pathology

2007 ◽  
Vol 6 (1) ◽  
pp. 42 ◽  
Author(s):  
Hans-Peter Mueller ◽  
Alexander Unrath ◽  
Anne D Sperfeld ◽  
Albert C Ludolph ◽  
Axel Riecker ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Quantitative Analysis ◽  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
White Matter Pathology
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