Diffusion-Weighted and Diffusion Tensor Magnetic Resonance Brain Imaging: Principles and Applications

2003 ◽  
Vol 16 (2) ◽  
pp. 207-220 ◽  
Author(s):  
F. Pizzini ◽  
A. Beltramello ◽  
E. Piovan ◽  
F. Alessandrini
Keyword(s):  
White Matter ◽  
Magnetic Resonance ◽  
Brain Tissue ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Three Dimensional ◽  
Functional Studies ◽  
Fiber Tracts ◽  
Normal Appearing White Matter ◽  
Diffusion Weighted

Diffusion Weighted Imaging (DWI) is one of the most recent products of Magnetic Resonance (MR) technology evolution. DWI has been proposed as a noninvasive tool for evaluating structural and physiologic states in biologic tissues as hyperacute ischemic changes within brain tissue. Recently, its more complex and detailed evolution, Diffusion Tensor Imaging (DTI), has been introduced and its clinical applications are the evaluation of anatomical structures and pathologic processes in white matter. White matter quantitative maps that indicate the integrity of brain tissue, color map, and tractography that identifies macroscopic three-dimensional architecture of fiber tracts (e.g., projections and association pathways) can be obtained with DTI. Diffusion weighted imaging visualization techniques (ADC and Trace) are applied for the study of stroke, in the differential diagnosis of expansive lesions (e.g. epidermoid vs. arachnoid cyst) and in detecting traumatic and other lesions associated with restricted diffusion (e.g. MS plaques). On the other hand, DTI provides the identification of abnormalities in the otherwise normal appearing white matter with the understanding of the organization of the fibers, both in tumors and in other cortical or white matter diseases (including stroke, dementias, demyelinating-dismyelinating diseases, epilepsy, schizophrenia). Furthermore, in combination with functional MR, DTI might contribute to the comprehension of brain development, aging and connectivity, thus having a significant impact on brain functional studies.

Weekly diffusion-weighted imaging of normal-appearing white matter in MS

Neurology ◽  
2000 ◽  
Vol 55 (6) ◽  
pp. 882-884 ◽  
Author(s):  
M. A. Rocca ◽  
M. Cercignani ◽  
G. Iannucci ◽  
G. Comi ◽  
M. Filippi
Keyword(s):  
White Matter ◽  
Diffusion Weighted Imaging ◽  
Normal Appearing White Matter ◽  
Diffusion Weighted

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 Evaluation of white matter in patients with multiple sclerosis through diffusion tensor magnetic resonance imaging

2007 ◽  
Vol 65 (3a) ◽  
pp. 561-564 ◽  
Author(s):  
Rachel E. Maia de Andrade ◽  
Emerson L. Gasparetto ◽  
Luiz Celso Hygino Cruz Jr. ◽  
Fabiana Brito Ferreira ◽  
Roberto Cortês Domingues ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Magnetic Resonance ◽  
Mr Imaging ◽  
Diffusion Tensor ◽  
Statistical Treatment ◽  
Control Group ◽  
Normal Appearing White Matter ◽  
Significant Difference ◽  
Normal White Matter

OBJECTIVE: To study the white matter of patients with multiple sclerosis (MS) with diffusion tensor magnetic resonance (MR) imaging (DTI). METHOD: Forty patients with clinical-laboratorial diagnosis of relapsing-remitting MS and 40 age- and sex-matched controls, who underwent conventional and functional (DTI) MR imaging, were included in the study. The DTI sequences resulted in maps of fractional anisotropy (FA) and regions of interest were placed on the plaques, peri-plaque regions, normal-appearing white matter (NAWM) around the plaques, contralateral normal white matter (CNWM) and normal white matter of the controls (WMC). The FA values were compared and the statistical treatment was performed with the Mann-Whitney U test. RESULTS: The mean FA in plaques was 0.268, in peri-plaque regions 0.365, in NAWM 0.509, in CNWM 0.552 and in WMC 0.573. Statistical significant differences in FA values were observed in plaques, peri-plaque regions and in NAWM around the plaques when compared to the white matter in the control group. There was no significant difference between the FA values of the CNWM of patients with MS and normal white matter of controls. CONCLUSION: Patients with MS show difference in the FA values of the plaques, peri-plaques and NAWM around the plaques when compared to the normal white matter of controls. As a result, DTI may be considered more efficient than conventional MR imaging for the study of patients with MS.

DT MRI microstructural cortical lesion damage does not explain cognitive impairment in MS

2017 ◽  
Vol 23 (14) ◽  
pp. 1918-1928 ◽  
Author(s):  
Paolo Preziosa ◽  
Elisabetta Pagani ◽  
Maria E Morelli ◽  
Massimiliano Copetti ◽  
Vittorio Martinelli ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
White Matter ◽  
Diffusion Tensor ◽  
Gray Matter Volume ◽  
Three Dimensional ◽  
Mean Diffusivity ◽  
Cortical Lesion ◽  
Lesion Volume ◽  
Normal Appearing White Matter ◽  
Tissue Abnormalities

Objective: We combined double inversion recovery (DIR) and diffusion tensor (DT) magnetic resonance imaging (MRI) to quantify the severity of cortical lesion (CL) microstructural tissue abnormalities in a large cohort of relapse-onset multiple sclerosis (MS) patients and its contribution to cognitive dysfunction. Methods: DIR, DT, dual-echo, and three-dimensional (3D) T1-weighted scans were acquired from 149 MS patients and 40 controls. Cognitively impaired (CI) patients had ⩾2 abnormal neuropsychological tests. Diffusivity values in CLs, cortex, white matter (WM) lesions, and normal-appearing (NA) WM were assessed. Predictors of cognitive impairment were identified using a random forest analysis. Results: Compared to controls, MS patients had lower normalized brain volume (NBV), gray matter volume (GMV), WM volume, lower fractional anisotropy (FA), and higher mean diffusivity in cortex and normal-appearing white matter (NAWM). A total of 44 (29.5%) patients were CI. Compared to cognitively preserved (CP), CI patients had higher T2 WM lesion volume (LV), lower NBV and GMV, and more severe diffusivity abnormalities in WM lesions, cortex, and NAWM. CL measures did not differ between CI and CP patients. Cortex FA, age, disease duration, T2 WM LV, and GMV best predicted MS-related cognitive impairment (C-statistic = 0.88). Conclusion: “Diffuse” GM and NAWM damage and WM lesions, rather than intrinsic CL damage, contribute to cognitive impairment in MS.

Diffusion tensor imaging abnormalities in depressed multiple sclerosis patients

2009 ◽  
Vol 16 (2) ◽  
pp. 189-196 ◽  
Author(s):  
A. Feinstein ◽  
P. O'Connor ◽  
N. Akbar ◽  
L. Moradzadeh ◽  
CJM Scott ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Magnetic Resonance ◽  
Grey Matter ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Resonance Imaging ◽  
Normal Appearing White Matter

Depression is common in patients with multiple sclerosis, but to date no studies have explored diffusion tensor imaging indices associated with mood change. This study aimed to determine cerebral correlates of depression in multiple sclerosis patients using diffusion tensor imaging. Sixty-two subjects with multiple sclerosis were assessed for depression with the Beck Depression Inventory (BDI-II). All subjects underwent magnetic resonance imaging. Whole brain and regional volumes were calculated for lesions (hyper/hypointense) and normal-appearing white and grey matter. Fractional anisotropy and mean diffusivity were calculated for each brain region. Magnetic resonance imaging comparisons were undertaken between depressed (Beck Depression Inventory ≥19) and non-depressed subjects. Depressed subjects (n = 30) had a higher hypointense lesion volume in the right medial inferior frontal region, a smaller normal-appearing white matter volume in the left superior frontal region, and lower fractional anisotropy and higher mean diffusivity in the left anterior temporal normal-appearing white matter and normal-appearing grey matter regions, respectively. Depressed subjects also had higher mean diffusivity in right inferior frontal hyperintense lesions. Magnetic resonance imaging variables contributed to 43% of the depression variance. We conclude that the presence of more marked diffusion tensor imaging abnormalities in the normal-appearing white matter and normal-appearing grey matter of depressed subjects highlights the importance of more subtle measures of structural brain change in the pathogenesis of depression.

Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach

2011 ◽  
Vol 18 (6) ◽  
pp. 817-824 ◽  
Author(s):  
A Pichiecchio ◽  
E Tavazzi ◽  
G Poloni ◽  
M Ponzio ◽  
F Palesi ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Magnetic Resonance ◽  
Grey Matter ◽  
Diffusion Tensor ◽  
Healthy Controls ◽  
Voxel Based Morphometry ◽  
Resonance Imaging ◽  
Normal Appearing White Matter

Background: Several authors have used advanced magnetic resonance imaging (MRI) techniques to investigate whether patients with neuromyelitis optica (NMO) have occult damage in normal-appearing brain tissue, similarly to multiple sclerosis (MS). To date, the literature contains no data derived from the combined use of several advanced MRI techniques in the same NMO subjects. Objective: We set out to determine whether occult damage could be detected in the normal-appearing brain tissue of a small group of patients with NMO using a multiparametric MRI approach. Methods: Eight female patients affected by NMO (age range 44–58 years) and seven sex- and age-matched healthy controls were included. The techniques used on a 1.5 T MRI imaging scanner were magnetization transfer imaging, diffusion tensor imaging, tract-based spatial statistics, spectroscopy and voxel-based morphometry in order to analyse normal-appearing white matter and normal-appearing grey matter. Results: Structural and metabolic parameters showed no abnormalities in normal-appearing white matter of patients with NMO. Conversely, tract-based spatial statistics demonstrated a selective alteration of the optic pathways and the lateral geniculate nuclei. Diffusion tensor imaging values in the normal-appearing grey matter were found to be significantly different in the patients with NMO versus the healthy controls. Moreover, voxel-based morphometry analysis demonstrated a significant density and volume reduction of the sensorimotor cortex and the visual cortex. Conclusions: Our data disclosed occult structural damage in the brain of patients with NMO, predominantly involving regions connected with motor and visual systems. This damage seems to be the direct consequence of transsynaptic degeneration triggered by lesions of the optic nerve and spine.

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