scholarly journals Disruption of neurite morphology parallels MS progression

2018 ◽  
Vol 5 (6) ◽  
pp. e502 ◽  
Author(s):  
Barbara Spanò ◽  
Giovanni Giulietti ◽  
Valerio Pisani ◽  
Manuela Morreale ◽  
Elisa Tuzzi ◽  
...  
Keyword(s):  
Brain Tissue ◽  
Disease Severity ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Compartment Model ◽  
Dispersion Index ◽  
Brain Areas ◽  
Neurite Density ◽  
Relapsing Remitting ◽  
Diffusion Tensor Imaging Dti

ObjectivesTo apply advanced diffusion MRI methods to the study of normal-appearing brain tissue in MS and examine their correlation with measures of clinical disability.MethodsA multi-compartment model of diffusion MRI called neurite orientation dispersion and density imaging (NODDI) was used to study 20 patients with relapsing-remitting MS (RRMS), 15 with secondary progressive MS (SPMS), and 20 healthy controls. Maps of NODDI were analyzed voxel-wise to assess the presence of abnormalities within the normal-appearing brain tissue and the association with disease severity. Standard diffusion tensor imaging (DTI) parameters were also computed for comparing the 2 techniques.ResultsPatients with MS showed reduced neurite density index (NDI) and increased orientation dispersion index (ODI) compared with controls in several brain areas (p < 0.05), with patients with SPMS having more widespread abnormalities. DTI indices were also sensitive to some changes. In addition, patients with SPMS showed reduced ODI in the thalamus and caudate nucleus. These abnormalities were associated with scores of disease severity (p < 0.05). The association with the MS functional composite score was higher in patients with SPMS compared with patients with RRMS.ConclusionsNODDI and DTI findings are largely overlapping. Nevertheless, NODDI helps interpret previous findings of increased anisotropy in the thalamus of patients with MS and are consistent with the degeneration of selective axon populations.

scholarly journals Scan–rescan and inter-vendor reproducibility of neurite orientation dispersion and density imaging metrics

2019 ◽  
Vol 62 (4) ◽  
pp. 483-494
Author(s):  
Christina Andica ◽  
Koji Kamagata ◽  
Takuya Hayashi ◽  
Akifumi Hagiwara ◽  
Wataru Uchida ◽  
...  
Keyword(s):  
Gray Matter ◽  
Healthy Subjects ◽  
Volume Fraction ◽  
Diffusion Tensor ◽  
Intraclass Correlation ◽  
Region Of Interest ◽  
Brain Regions ◽  
Automatic Extraction ◽  
Dispersion Index ◽  
Diffusion Tensor Imaging Dti

Abstract Purpose The reproducibility of neurite orientation dispersion and density imaging (NODDI) metrics in the human brain has not been explored across different magnetic resonance (MR) scanners from different vendors. This study aimed to evaluate the scan–rescan and inter-vendor reproducibility of NODDI metrics in white and gray matter of healthy subjects using two 3-T MR scanners from two vendors. Methods Ten healthy subjects (7 males; mean age 30 ± 7 years, range 23–37 years) were included in the study. Whole-brain diffusion-weighted imaging was performed with b-values of 1000 and 2000 s/mm2 using two 3-T MR scanners from two different vendors. Automatic extraction of the region of interest was performed to obtain NODDI metrics for whole and localized areas of white and gray matter. The coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were calculated to assess the scan–rescan and inter-vendor reproducibilities of NODDI metrics. Results The scan–rescan and inter-vendor reproducibility of NODDI metrics (intracellular volume fraction and orientation dispersion index) were comparable with those of diffusion tensor imaging (DTI) metrics. However, the inter-vendor reproducibilities of NODDI (CoV = 2.3–14%) were lower than the scan–rescan reproducibility (CoV: scanner A = 0.8–3.8%; scanner B = 0.8–2.6%). Compared with the finding of DTI metrics, the reproducibility of NODDI metrics was lower in white matter and higher in gray matter. Conclusion The lower inter-vendor reproducibility of NODDI in some brain regions indicates that data acquired from different MRI scanners should be carefully interpreted.

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 Loss of corticospinal tract integrity in early MS disease stages

2017 ◽  
Vol 4 (6) ◽  
pp. e399 ◽  
Author(s):  
Marc Pawlitzki ◽  
Jens Neumann ◽  
Jörn Kaufmann ◽  
Jan Heidel ◽  
Erhard Stadler ◽  
...  
Keyword(s):  
Corticospinal Tract ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Group Differences ◽  
Disability Score ◽  
Brain Volumes ◽  
Disability Status ◽  
Relapsing Remitting ◽  
Disease Stages ◽  
Diffusion Tensor Imaging Dti

Objective:We investigated corticospinal tract (CST) integrity in the absence of white matter (WM) lesions using diffusion tensor imaging (DTI) in early MS disease stages.Methods:Our study comprised 19 patients with clinically isolated syndrome (CIS), 11 patients with relapsing-remitting MS (RRMS), and 32 age- and sex-matched healthy controls, for whom MRI measures of CST integrity (fractional anisotropy [FA], mean diffusivity [MD]), T1- and T2-based lesion load, and brain volumes were available. The mean (SD) disease duration was 3.5 (2.1) months, and disability score was low (median Expanded Disability Status Scale 1.5) at the time of the study.Results:Patients with CIS and RRMS had significantly lower CST FA and higher CST MD values compared with controls. These findings were present, irrespective of whether WM lesions affected the CST. However, no group differences in the overall gray or WM volume were identified.Conclusions:In early MS disease stages, CST integrity is already affected in the absence of WM lesions or brain atrophy.

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 Dimensionality Reduction of Diffusion MRI Measures for Improved Tractometry of the Human Brain

2019 ◽  
Author(s):  
Maxime Chamberland ◽  
Erika P. Raven ◽  
Sila Genc ◽  
Kate Duffy ◽  
Maxime Descoteaux ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Angular Resolution ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
High Angular Resolution ◽  
Typically Developing ◽  
Typically Developing Children ◽  
Tissue Microstructure ◽  
Age Related ◽  
Diffusion Tensor Imaging Dti

AbstractVarious diffusion MRI measures have been proposed for characterising tissue microstructure over the last 15 years. Despite the growing number of experiments using different diffusion measures in assessments of white matter, there has been limited work on: 1) examining their covariance along specific pathways; and on 2) combining these different measures to study tissue microstructure. In this work, we first demonstrate redundancies in the amount of information captured by 10 diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) measures. Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in commonly-used DTI and HARDI measures profiled along 22 brain pathways extracted from typically developing children aged 8 - 18 years (n = 36). The first derived component captures properties related to hindrance and restriction in tissue microstructure, while the second component reflects characteristics related to tissue complexity and orientational dispersion. We demonstrate that the components generated by this approach preserve the biological relevance of the original measurements by showing age-related effects across developmentally sensitive pathways. Our results also suggest that HARDI measures are more sensitive at detecting age-related changes in tissue microstructure than DTI measures.

scholarly journals Non-Gaussian diffusion MRI of gray matter is associated with cognitive impairment in multiple sclerosis

2014 ◽  
Vol 21 (7) ◽  
pp. 935-944 ◽  
Author(s):  
M Bester ◽  
JH Jensen ◽  
JS Babb ◽  
A Tabesh ◽  
L Miles ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Gray Matter ◽  
Cognitive Deficits ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
Mean Diffusivity ◽  
Poor Performance ◽  
Relapsing Remitting ◽  
Non Gaussian ◽  
Diffusion Tensor Imaging Dti

Background: Non-Gaussian diffusion imaging by using diffusional kurtosis imaging (DKI) allows assessment of isotropic tissue as of gray matter (GM), an important limitation of diffusion tensor imaging (DTI). Objective: In this study, we describe DKI and DTI metrics of GM in multiple sclerosis (MS) patients and their association with cognitive deficits. Methods: Thirty-four patients with relapsing–remitting MS and 17 controls underwent MRI on a 3T scanner including a sequence for DKI with 30 diffusion directions and 3b values for each direction. Mean kurtosis (MK), mean diffusivity and fractional anisotropy (FA) of cortical and subcortical GM were measured using histogram analysis. Spearman rank correlations were used to characterize associations among imaging measures and clinical/neuropsychological scores. Results: In cortical GM, a significant decrease of MK (0.68 vs. 0.73; p < 0.001) and increase of FA (0.16 vs. 0.13; p < 0.001) was found in patients compared to controls. Decreased cortical MK was correlated with poor performance on the Delis-Kaplan Executive Function System test ( r = 0.66, p = 0.01). Conclusion: Mean kurtosis is sensitive to abnormality in GM of MS patients and can provide information that is complementary to that of conventional DTI-derived metrics. The association between MK and cognitive deficits suggests that DKI might serve as a clinically relevant biomarker for cortical injury.

scholarly journals Detection of Glioblastoma Subclinical Recurrence Using Serial Diffusion Tensor Imaging

Cancers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 568 ◽  
Author(s):  
Yan Jin ◽  
James W. Randall ◽  
Hesham Elhalawani ◽  
Karine A. Al Feghali ◽  
Andrew M. Elliott ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Group Analysis ◽  
Diffusion Maps ◽  
Mr Images ◽  
Neurite Density ◽  
Intracranial Recurrence ◽  
Diffusion Tensor Imaging Dti ◽  
Time Point

Glioblastoma is an aggressive brain tumor with a propensity for intracranial recurrence. We hypothesized that tumors can be visualized with diffusion tensor imaging (DTI) before they are detected on anatomical magnetic resonance (MR) images. We retrospectively analyzed serial MR images from 30 patients, including the DTI and T1-weighted images at recurrence, at 2 months and 4 months before recurrence, and at 1 month after radiation therapy. The diffusion maps and T1 images were deformably registered longitudinally. The recurrent tumor was manually segmented on the T1-weighted image and then applied to the diffusion maps at each time point to collect mean FA, diffusivities, and neurite density index (NDI) values, respectively. Group analysis of variance showed significant changes in FA (p = 0.01) and NDI (p = 0.0015) over time. Pairwise t tests also revealed that FA and NDI at 2 months before recurrence were 11.2% and 6.4% lower than those at 1 month after radiation therapy (p < 0.05), respectively. Changes in FA and NDI were observed 2 months before recurrence, suggesting that progressive microstructural changes and neurite density loss may be detectable before tumor detection in anatomical MR images. FA and NDI may serve as non-contrast MR-based biomarkers for detecting subclinical tumors.

scholarly journals Multimodal Neuroimaging Predictors of Gait Decline

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 767-767
Author(s):  
Lana Sargent ◽  
Qu Tian ◽  
Mike Nalls ◽  
Andrew Singleton ◽  
Stephanie Studenski ◽  
...  
Keyword(s):  
Gait Speed ◽  
Repeated Measures ◽  
Diffusion Tensor ◽  
Multimodal Neuroimaging ◽  
Brain Areas ◽  
Cross Sectional ◽  
Brain Volumes ◽  
Cognitively Normal ◽  
Diffusion Tensor Imaging Dti ◽  
Motor Areas

Abstract Prior studies suggesting associations between cortical brain areas and gait speed has been largely cross-sectional and limited to one modality neuroimaging. Using machine learning from 506 cognitively normal BLSA participants aged 55+ who had repeated measures of brain volumes, diffusion tensor imaging (DTI), and gait speed, we examined multimodal neuroimaging predictors of gait decline, accounting for demographics, body composition, and grip strength. Significant predictors of gait decline included changes in volumes and DTI measures of gray matter in selected frontal, parietal, temporal, and subcortical areas, as well as white matter changes in both fractional anisotropy and diffusivity of tracts connecting frontal areas to subcortical motor areas. This predictive model highlights the importance of atrophy and microstructural deterioration in selected frontal and subcortical motor areas in predicting gait speed decline.

scholarly journals [Re] Optimization of a free water elimination two-compartment model for diffusion tensor imaging

2017 ◽  
Author(s):  
Rafael Neto Henriques ◽  
Ariel Rokem ◽  
Eleftherios Garyfallidis ◽  
Samuel St-Jean ◽  
Eric Thomas Peterson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Free Water ◽  
Compartment Model ◽  
B Values ◽  
Brain White Matter ◽  
Diffusion Weighted ◽  
Two Compartment Model ◽  
Water Elimination

Typical diffusion-weighted imaging (DWI) is susceptible to partial volume effects: different types of tissue that reside in the same voxel are inextricably mixed. For instance, in regions near the cerebral ventricles or parenchyma, fractional anisotropy (FA) from diffusion tensor imaging (DTI) may be underestimated, due to partial volumes of cerebral spinal fluid (CSF). Free-water can be suppressed by adding parameters to diffusion MRI models. For example, the DTI model can be extended to separately take into account the contributions of tissue and CSF, by representing the tissue compartment with an anisotropic diffusion tensor and the CSF compartment as an isotropic free water diffusion coefficient. Recently, two procedures were proposed to fit this two-compartment model to diffusion-weighted data acquired for at least two different non-zero diffusion MRI b-values. In this work, the first open-source reference implementation of these procedures is provided. In addition to presenting some methodological improvements that increase model fitting robustness, the free water DTI procedures are re-evaluated using Monte-Carlo multicompartmental simulations. Analogous to previous studies, our results show that the free water elimination DTI model is able to remove confounding effects of fast diffusion for typical FA values of brain white matter. In addition, this study confirms that for a fixed scanning time the fwDTI fitting procedures have better performance when data is acquired for diffusion gradient direction evenly distributed along two b-values of 500 and 1500 s/mm2.

scholarly journals Apathy Is Correlated with Widespread Diffusion Tensor Imaging (DTI) Impairment in Amyotrophic Lateral Sclerosis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Cinzia Femiano ◽  
Francesca Trojsi ◽  
Giuseppina Caiazzo ◽  
Mattia Siciliano ◽  
Carla Passaniti ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Anterior Cingulate ◽  
Behavioral Impairment ◽  
Brain Areas ◽  
Significant Difference ◽  
Als Patients ◽  
Lateral Sclerosis ◽  
Diffusion Tensor Imaging Dti

Apathy is recognized as the most common behavioral change in several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), a multisystem neurodegenerative disorder. Particularly, apathy has been reported to be associated with poor ALS prognosis. However, the brain microstructural correlates of this behavioral symptom, reported as the most common in ALS, have not been completely elucidated. Using diffusion tensor imaging (DTI) and tract-based spatial statistics (TBSS), here we aimed to quantify the correlation between brain microstructural damage and apathy scores in the early stages of ALS. Twenty-one consecutive ALS patients, in King’s clinical stage 1 or 2, and 19 age- and sex-matched healthy controls (HCs) underwent magnetic resonance imaging and neuropsychological examination. Between-group comparisons did not show any significant difference on cognitive and behavioral variables. When compared to HCs, ALS patients exhibited a decreased fractional anisotropy (FA) [p<.05, threshold-free cluster enhancement (TFCE) corrected] in the corpus callosum and in bilateral anterior cingulate cortices. Self-rated Apathy Evaluation Scale (AES) scores and self-rated apathy T-scores of the Frontal Systems Behavior (FrSBe) scale were found inversely correlated to FA measures (p<.05, TFCE corrected) in widespread white matter (WM) areas, including several associative fiber tracts in the frontal, temporal, and parietal lobes. These results point towards an early microstructural degeneration of brain areas biologically involved in cognition and behavior regulation in ALS. Moreover, the significant correlations between apathy and DTI measures in several brain areas may suggest that subtle WM changes may be associated with mild behavioral symptoms in ALS even in the absence of overt cognitive and behavioral impairment.

Sign in / Sign up

Export Citation Format

Share Document