scholarly journals Perivascular space fluid contributes to diffusion tensor imaging changes in white matter

2018 ◽  
Author(s):  
Farshid Sepehrband ◽  
Ryan P Cabeen ◽  
Jeiran Choupan ◽  
Giuseppe Barisano ◽  
Meng Law ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
Mean Diffusivity ◽  
Brain Parenchyma ◽  
Perivascular Space ◽  
List Type

AbstractDiffusion tensor imaging (DTI) has been extensively used to map changes in brain tissue related to neurological disorders. Among the most widespread DTI findings are increased mean diffusivity and decreased fractional anisotropy of white matter tissue in neurodegenerative diseases. Here we utilize multi-shell diffusion imaging to separate diffusion signal of the brain parenchyma from fluid within the white matter. We show that unincorporated anisotropic water in perivascular space (PVS) significantly, and systematically, biases DTI measures, casting new light on the biological validity of many previously reported findings. Despite the challenge this poses for interpreting these past findings, our results suggest that multi-shell diffusion MRI provides a new opportunity for incorporating the PVS contribution, ultimately strengthening the clinical and scientific value of diffusion MRI.HighlightsPerivascular space (PVS) fluid significantly contributes to diffusion tensor imaging metricsIncreased PVS fluid results in increased mean diffusivity and decreased fractional anisotropyPVS contribution to diffusion signal is overlooked and demands further investigation

scholarly journals Loss and Reorganisation of Superficial White Matter in Alzheimer's disease: A Diffusion MRI study

2021 ◽  
Author(s):  
Thomas Veale ◽  
Ian B Malone ◽  
Teresa Poole ◽  
Thomas D Parker ◽  
Catherine F Slattery ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Mri ◽  
Grey Matter ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Young Onset ◽  
Neurite Density

Pathological involvement of cerebral white matter in Alzheimer's disease has been shown using diffusion tensor imaging. Superficial white matter (SWM) changes have been relatively understudied despite their importance in cortico-cortical connections. Measuring SWM degeneration using diffusion tensor imaging is challenging due to its complex structure and proximity to the cortex. To overcome this we investigated diffusion MRI changes in young-onset Alzheimer's disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are due to degeneration (e.g. loss of myelinated fibres) and those due to reorganisation (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer's disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, the grey/white boundary, SWM (1mm below grey/white boundary) and SWM/deeper white matter (2mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants' diffusion metrics along the cortical profile. The SWM of young-onset Alzheimer's disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P<0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P<0.05). Young-onset Alzheimer's disease individuals had lower fractional anisotropy in the SWM of two regions (entorhinal and parahippocampus) (both P<0.05) and higher fractional anisotropy within the postcentral region (P<0.05). Mean diffusivity in SWM was higher in the young-onset Alzheimer's disease group in the parahippocampal region (P<0.05) and lower in three regions (postcentral, precentral and superior temporal) (all P<0.05). In the overlying grey matter, disease-related changes were largely consistent with SWM findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity SWM changes. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer's disease individuals (all P<0.001) but group differences reduced in magnitude and coverage when moving towards the SWM. These results show that microstructural changes occur within SWM and along the cortical profile in individuals with young-onset Alzheimer's disease. Lower neurite density and higher orientation dispersion suggests underlying SWM fibres undergo neurodegeneration and reorganisation, two effects previously indiscernible using standard diffusion tensor metrics in SWM.

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.

scholarly journals White matter differences between essential tremor and Parkinson disease

Neurology ◽  
2018 ◽  
Vol 92 (1) ◽  
pp. e30-e39 ◽  
Author(s):  
Meher R. Juttukonda ◽  
Giulia Franco ◽  
Dario J. Englot ◽  
Ya-Chen Lin ◽  
Kalen J. Petersen ◽  
...  
Keyword(s):  
White Matter ◽  
Parkinson Disease ◽  
Essential Tremor ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Superior Cerebellar Peduncle ◽  
Radial Diffusivity ◽  
Cerebellar Peduncles ◽  
Cerebellar Peduncle

ObjectiveTo assess white matter integrity in patients with essential tremor (ET) and Parkinson disease (PD) with moderate to severe motor impairment.MethodsSedated participants with ET (n = 57) or PD (n = 99) underwent diffusion tensor imaging (DTI) and fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity values were computed. White matter tracts were defined using 3 well-described atlases. To determine candidate white matter regions that differ between ET and PD groups, a bootstrapping analysis was applied using the least absolute shrinkage and selection operator. Linear regression was applied to assess magnitude and direction of differences in DTI metrics between ET and PD populations in the candidate regions.ResultsFractional anisotropy values that differentiate ET from PD localize primarily to thalamic and visual-related pathways, while diffusivity differences localized to the cerebellar peduncles. Patients with ET exhibited lower fractional anisotropy values than patients with PD in the lateral geniculate body (p < 0.01), sagittal stratum (p = 0.01), forceps major (p = 0.02), pontine crossing tract (p = 0.03), and retrolenticular internal capsule (p = 0.04). Patients with ET exhibited greater radial diffusivity values than patients with PD in the superior cerebellar peduncle (p < 0.01), middle cerebellar peduncle (p = 0.05), and inferior cerebellar peduncle (p = 0.05).ConclusionsRegionally, distinctive white matter microstructural values in patients with ET localize to the cerebellar peduncles and thalamo-cortical visual pathways. These findings complement recent functional imaging studies in ET but also extend our understanding of putative physiologic features that account for distinctions between ET and PD.

scholarly journals Discrimination of epileptogenic lesions and perilesional white matter using diffusion tensor magnetic resonance imaging

2018 ◽  
Vol 32 (1) ◽  
pp. 10-16
Author(s):  
Alexander Rau ◽  
Elias Kellner ◽  
Niels A Foit ◽  
Niklas Lützen ◽  
Dieter H Heiland ◽  
...  
Keyword(s):  
White Matter ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Focal Cortical Dysplasia ◽  
Mean Diffusivity ◽  
Area Under The Curve ◽  
P Value ◽  
Radial Diffusivity ◽  
Normal Appearing White Matter ◽  
Diffusion Parameters

The aim of this study was to evaluate whether ganglioglioma (GGL), dysembryoplastic neuroepithelial tumour (DNET) and FCD (focal cortical dysplasia) are distinguishable through diffusion tensor imaging. Additionally, it was investigated whether the diffusion measures differed in the perilesional (pNAWM) and in the contralateral normal appearing white matter (cNAWM). Six GGLs, eight DNETs and seven FCDs were included in this study. Quantitative diffusion measures, that is, axial, radial and mean diffusivity and fractional anisotropy, were determined in the lesion identified on isotropic T2 or FLAIR-weighted images and in pNAWM and cNAWM, respectively. DNET differed from FCD in mean diffusivity, and GGL from FCD in radial diffusivity. Both types of glioneuronal tumours were different from pNAWM in fractional anisotropy and radial diffusivity. For identifying the tumour edges, threshold values for tumour-free tissue were investigated with receiver operating characteristic analyses: tumour could be separated from pNAWM at a threshold ≤ 0.32 (fractional anisotropy) or ≥ 0.56 (radial diffusivity) *10–3 mm2/s (area under the curve 0.995 and 0.990 respectively). While diffusion parameters of FCDs differed from cNAWM (radial diffusivity (*10–3 mm/s2): 0.74 ± 0.19 vs. 0.43 ± 0.05; corrected p-value < 0.001), the pNAWM could not be differentiated from the FCD.

Diffusion tensor imaging of cerebral white matter in patients with myotonic dystrophy

2005 ◽  
Vol 46 (1) ◽  
pp. 104-109 ◽  
Author(s):  
H. Fukuda ◽  
J. Horiguchi ◽  
C. Ono ◽  
T. Ohshita ◽  
J. Takaba ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Myotonic Dystrophy ◽  
Normal Control ◽  
Diffusion Tensor ◽  
Age At Onset ◽  
Mean Diffusivity ◽  
Magnetic Resonance Images ◽  
Microstructural Changes ◽  
Control Subjects

Purpose: To determine whether myotonic dystrophy (MyD) patients have diffusion tensor abnormalities suggestive of microstructural changes in normal‐appearing white matter (NAWM). Material and Methods: Conventional and diffusion tensor magnetic resonance images of the brain were obtained in 19 MyD patients and 19 age‐matched normal control subjects. Fractional anisotropy (FA) and mean diffusivity (MD) values were calculated in white matter lesions (WMLs) and NAWM in MyD patients and in the white matter of normal control subjects. Differences between WML and NAWM values and between MyD patient and control subject values were analyzed statistically. Results: Significantly lower FA and higher MD values were found in all regions of interest in the NAWM of MyD patients than in the white matter of control subjects ( P<0.01), as well as significantly lower FA and higher MD values in WMLs than in NAWM of MyD patients ( P<0.05). There was no significant correlation of mean FA or MD values in NAWM with patient age, age at onset, or duration of illness ( P>0.1). Conclusion: Diffusion tensor imaging analysis suggests the presence of diffuse microstructural changes in NAWM of MyD patients that may play an important role in the development of disability.

scholarly journals Diffusion Tensor Imaging of the Kidneys: Influence of b-Value and Number of Encoding Directions on Image Quality and Diffusion Tensor Parameters

2013 ◽  
Vol 3 ◽  
pp. 53 ◽  
Author(s):  
Natalie C. Chuck ◽  
Günther Steidle ◽  
Iris Blume ◽  
Michael A. Fischer ◽  
Daniel Nanz ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Image Quality ◽  
Fractional Anisotropy ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Renal Medulla ◽  
Whole Body ◽  
Acquisition Time ◽  
Data Sets ◽  
B Values

Objectives: The purpose of this study was to evaluate to which degree investment of acquisition time in more encoding directions leads to better image quality (IQ) and what influence the number of encoding directions and the choice of b-values have on renal diffusion tensor imaging (DTI) parameters. Material and Methods: Eight healthy volunteers (32.3 y ± 5.1 y) consented to an examination in a 1.5T whole-body MR scanner. Coronal DTI data sets of the kidneys were acquired with systematic variation of b-values (50, 150, 300, 500, and 700 s/mm2) and number of diffusion-encoding directions (6, 15, and 32) using a respiratory-triggered echo-planar sequence (TR/TE 1500 ms/67 ms, matrix size 128 × 128). Additionally, two data sets with more than two b-values were acquired (0, 150, and 300 s/mm2 and all six b-values). Parametrical maps were calculated on a pixel-by-pixel basis. Image quality was determined with a reader score. Results: Best IQ was visually assessed for images acquired with 15 and 32 encoding directions, whereas images acquired with six directions had significantly lower IQ ratings. Image quality, fractional anisotropy, and mean diffusivity only varied insignificantly for b-values between 300 and 500 s/mm2. In the renal medulla fractional anisotropy (FA) values between 0.43 and 0.46 and mean diffusivity (MD) values between 1.8-2.1 × 10-3 mm2/s were observed. In the renal cortex, the corresponding ranges were 0.24-0.25 (FA) and 2.2-2.8 × 10-3 mm2/s (MD). Including b-values below 300 s/mm2, notably higher MD values were observed, while FA remained constant. Susceptibility artifacts were more prominent in FA maps than in MD maps. Conclusion: In DTI of the kidneys at 1.5T, the best compromise between acquisition time and resulting image quality seems the application of 15 encoding directions with b-values between 300 and 500 s/mm2. Including lower b-values allows for assessment of fast diffusing spin components.

scholarly journals Perivascular space fluid contributes to diffusion tensor imaging changes in white matter

NeuroImage ◽  
2019 ◽  
Vol 197 ◽  
pp. 243-254 ◽  
Author(s):  
Farshid Sepehrband ◽  
Ryan P. Cabeen ◽  
Jeiran Choupan ◽  
Giuseppe Barisano ◽  
Meng Law ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Perivascular Space
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