Relevant bibliographies by topics / Neurite orientation dispersion and density imaging

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Academic literature on the topic 'Neurite orientation dispersion and density imaging'

Author: Grafiati
Published: 5 June 2025
Last updated: 25 June 2025

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Journal articles on the topic "Neurite orientation dispersion and density imaging"

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Sato, Kanako, Aurelien Kerever, Koji Kamagata, et al. "Understanding microstructure of the brain by comparison of neurite orientation dispersion and density imaging (NODDI) with transparent mouse brain." Acta Radiologica Open 6, no. 4 (2017): 205846011770381. http://dx.doi.org/10.1177/2058460117703816.

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Background Neurite orientation dispersion and density imaging (NODDI) is a diffusion magnetic resonance imaging (MRI) technique with the potential to visualize the microstructure of the brain. Revolutionary histological methods to render the mouse brain transparent have recently been developed, but verification of NODDI by these methods has not been reported. Purpose To confirm the concordance of NODDI with histology in terms of density and orientation dispersion of neurites of the brain. Material and Methods Whole brain diffusion MRI of a thy-1 yellow fluorescent protein mouse was acquired with a 7-T MRI scanner, after which transparent brain sections were created from the same mouse. NODDI parameters calculated from the MR images, including the intracellular volume fraction (Vic) and the orientation dispersion index (ODI), were compared with histological findings. Neurite density, Vic, and ODI were compared between areas of the anterior commissure and the hippocampus containing crossing fibers (crossing areas) and parallel fibers (parallel areas), and the correlation between fiber density and Vic was assessed. Results The ODI was significantly higher in the crossing area compared to the parallel area in both the anterior commissure and the hippocampus ( P = 0.0247, P = 0.00022, respectively). Neurite density showed a similar tendency, but was significantly different only in the hippocampus ( P = 7.91E−07). There was no significant correlation between neurite density and Vic. Conclusion NODDI was verified by histology for quantification of the orientation dispersion of neurites. These results indicate that the ODI is a suitable index for understanding the microstructure of the brain in vivo.
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Shibata, Yasushi, and Sumire Ishiyama. "Neurite Damage in Patients with Migraine." Neurology International 16, no. 2 (2024): 299–311. http://dx.doi.org/10.3390/neurolint16020021.

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We examined neurite orientation dispersion and density imaging in patients with migraine. We found that patients with medication overuse headache exhibited lower orientation dispersion than those without. Moreover, orientation dispersion in the body of the corpus callosum was statistically negatively correlated with migraine attack frequencies. These findings indicate that neurite dispersion is damaged in patients with chronic migraine. Our study results indicate the orientation preference of neurite damage in migraine.
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Wang, Dan, Kai Shang, Zheng Sun, and Yue-Hua Li. "Experimental Imaging Study of Encephalomalacia Fluid-Attenuated Inversion Recovery (FLAIR) Hyperintense Lesions in Posttraumatic Epilepsy." Neural Plasticity 2021 (October 31, 2021): 1–10. http://dx.doi.org/10.1155/2021/2678379.

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This study introduced new MRI techniques such as neurite orientation dispersion and density imaging (NODDI); NODDI applies a three-compartment tissue model to multishell DWI data that allows the examination of both the intra- and extracellular properties of white matter tissue. This, in turn, enables us to distinguish the two key aspects of axonal pathology—the packing density of axons in the white matter and the spatial organization of axons (orientation dispersion (OD)). NODDI is used to detect possible abnormalities of posttraumatic encephalomalacia fluid-attenuated inversion recovery (FLAIR) hyperintense lesions in neurite density and dispersion. Methods. 26 epilepsy patients associated with FLAIR hyperintensity around the trauma encephalomalacia region were in the epilepsy group. 18 posttraumatic patients with a FLAIR hyperintense encephalomalacia region were in the nonepilepsy group. Neurite density and dispersion affection in FLAIR hyperintense lesions around encephalomalacia were measured by NODDI using intracellular volume fraction (ICVF), and we compare these findings with conventional diffusion MRI parameters, namely, fractional anisotropy (FA) and apparent diffusion coefficient (ADC). Differences were compared between the epilepsy and nonepilepsy groups, as well as in the FLAIR hyperintense part and in the FLAIR hypointense part to try to find neurite density and dispersion differences in these parts. Results. ICVF of FLAIR hyperintense lesions in the epilepsy group was significantly higher than that in the nonepilepsy group ( P < 0.001 ). ICVF reveals more information of FLAIR(+) and FLAIR(-) parts of encephalomalacia than OD and FA and ADC. Conclusion. The FLAIR hyperintense part around encephalomalacia in the epilepsy group showed higher ICVF, indicating that this part may have more neurite density and dispersion and may be contributing to epilepsy. NODDI indicated high neurite density with the intensity of myelin in the FLAIR hyperintense lesion. Therefore, NODDI likely shows that neurite density may be a more sensitive marker of pathology than FA.
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Collorone, Sara, Ferran Prados, Baris Kanber, et al. "Brain microstructural and metabolic alterations detected in vivo at onset of the first demyelinating event." Brain 144, no. 5 (2021): 1409–21. http://dx.doi.org/10.1093/brain/awab043.

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Abstract In early multiple sclerosis, a clearer understanding of normal-brain tissue microstructural and metabolic abnormalities will provide valuable insights into its pathophysiology. We used multi-parametric quantitative MRI to detect alterations in brain tissues of patients with their first demyelinating episode. We acquired neurite orientation dispersion and density imaging [to investigate morphology of neurites (dendrites and axons)] and 23Na MRI (to estimate total sodium concentration, a reflection of underlying changes in metabolic function). In this cross-sectional study, we enrolled 42 patients diagnosed with clinically isolated syndrome or multiple sclerosis within 3 months of their first demyelinating event and 16 healthy controls. Physical and cognitive scales were assessed. At 3 T, we acquired brain and spinal cord structural scans, and neurite orientation dispersion and density imaging. Thirty-two patients and 13 healthy controls also underwent brain 23Na MRI. We measured neurite density and orientation dispersion indices and total sodium concentration in brain normal-appearing white matter, white matter lesions, and grey matter. We used linear regression models (adjusting for brain parenchymal fraction and lesion load) and Spearman correlation tests (significance level P ≤ 0.01). Patients showed higher orientation dispersion index in normal-appearing white matter, including the corpus callosum, where they also showed lower neurite density index and higher total sodium concentration, compared with healthy controls. In grey matter, compared with healthy controls, patients demonstrated: lower orientation dispersion index in frontal, parietal and temporal cortices; lower neurite density index in parietal, temporal and occipital cortices; and higher total sodium concentration in limbic and frontal cortices. Brain volumes did not differ between patients and controls. In patients, higher orientation dispersion index in corpus callosum was associated with worse performance on timed walk test (P = 0.009, B = 0.01, 99% confidence interval = 0.0001 to 0.02), independent of brain and lesion volumes. Higher total sodium concentration in left frontal middle gyrus was associated with higher disability on Expanded Disability Status Scale (rs = 0.5, P = 0.005). Increased axonal dispersion was found in normal-appearing white matter, particularly corpus callosum, where there was also axonal degeneration and total sodium accumulation. The association between increased axonal dispersion in the corpus callosum and worse walking performance implies that morphological and metabolic alterations in this structure could mechanistically contribute to disability in multiple sclerosis. As brain volumes were neither altered nor related to disability in patients, our findings suggest that these two advanced MRI techniques are more sensitive at detecting clinically relevant pathology in early multiple sclerosis.
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Rasgado-Toledo, Jalil, Apurva Shah, Madhura Ingalhalikar, and Eduardo A. Garza-Villarreal. "Neurite orientation dispersion and density imaging in cocaine use disorder." Progress in Neuro-Psychopharmacology and Biological Psychiatry 113 (March 2022): 110474. http://dx.doi.org/10.1016/j.pnpbp.2021.110474.

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Wang, Nian, Jieying Zhang, Gary Cofer, et al. "Neurite orientation dispersion and density imaging of mouse brain microstructure." Brain Structure and Function 224, no. 5 (2019): 1797–813. http://dx.doi.org/10.1007/s00429-019-01877-x.

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Alotaibi, Abdulmajeed, Anna Podlasek, Amjad AlTokhis, Ali Aldhebaib, Rob A. Dineen, and Cris S. Constantinescu. "Investigating Microstructural Changes in White Matter in Multiple Sclerosis: A Systematic Review and Meta-Analysis of Neurite Orientation Dispersion and Density Imaging." Brain Sciences 11, no. 9 (2021): 1151. http://dx.doi.org/10.3390/brainsci11091151.

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Multiple sclerosis (MS) is characterised by widespread damage of the central nervous system that includes alterations in normal-appearing white matter (NAWM) and demyelinating white matter (WM) lesions. Neurite orientation dispersion and density imaging (NODDI) has been proposed to provide a precise characterisation of WM microstructures. NODDI maps can be calculated for the Neurite Density Index (NDI) and Orientation Dispersion Index (ODI), which estimate orientation dispersion and neurite density. Although NODDI has not been widely applied in MS, this technique is promising in investigating the complexity of MS pathology, as it is more specific than diffusion tensor imaging (DTI) in capturing microstructural alterations. We conducted a meta-analysis of studies using NODDI metrics to assess brain microstructural changes and neuroaxonal pathology in WM lesions and NAWM in patients with MS. Three reviewers conducted a literature search of four electronic databases. We performed a random-effect meta-analysis and the extent of between-study heterogeneity was assessed with the I2 statistic. Funnel plots and Egger’s tests were used to assess publication bias. We identified seven studies analysing 374 participants (202 MS and 172 controls). The NDI in WM lesions and NAWM were significantly reduced compared to healthy WM and the standardised mean difference of each was −3.08 (95%CI −4.22 to (−1.95), p ≤ 0.00001, I2 = 88%) and −0.70 (95%CI −0.99 to (−0.40), p ≤ 0.00001, I2 = 35%), respectively. There was no statistically significant difference of the ODI in MS WM lesions and NAWM compared to healthy controls. This systematic review and meta-analysis confirmed that the NDI is significantly reduced in MS lesions and NAWM than in WM from healthy participants, corresponding to reduced intracellular signal fraction, which may reflect underlying damage or loss of neurites.
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Broad, Rebecca, Matthew Gabel, Nicholas Dowell, et al. "CORRELATION ANALYSIS OF NEURITE ORIENTATION DISPERSION & DENSITY IMAGING IN MND." Journal of Neurology, Neurosurgery & Psychiatry 87, no. 12 (2016): e1.83-e1. http://dx.doi.org/10.1136/jnnp-2016-315106.173.

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Collorone, Sara, Niamh Cawley, Francesco Grussu, et al. "Reduced neurite density in the brain and cervical spinal cord in relapsing–remitting multiple sclerosis: A NODDI study." Multiple Sclerosis Journal 26, no. 13 (2019): 1647–57. http://dx.doi.org/10.1177/1352458519885107.

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Background: Multiple sclerosis (MS) affects both brain and spinal cord. However, studies of the neuraxis with advanced magnetic resonance imaging (MRI) are rare because of long acquisition times. We investigated neurodegeneration in MS brain and cervical spinal cord using neurite orientation dispersion and density imaging (NODDI). Objective: The aim of this study was to investigate possible alterations, and their clinical relevance, in neurite morphology along the brain and cervical spinal cord of relapsing–remitting MS (RRMS) patients. Methods: In total, 28 RRMS patients and 20 healthy controls (HCs) underwent brain and spinal cord NODDI at 3T. Physical and cognitive disability was assessed. Individual maps of orientation dispersion index (ODI) and neurite density index (NDI) in brain and spinal cord were obtained. We examined differences in NODDI measures between groups and the relationships between NODDI metrics and clinical scores using linear regression models adjusted for age, sex and brain tissue volumes or cord cross-sectional area (CSA). Results: Patients showed lower NDI in the brain normal-appearing white matter (WM) and spinal cord WM than HCs. In patients, a lower NDI in the spinal cord WM was associated with higher disability. Conclusion: Reduced neurite density occurs in the neuraxis but, especially when affecting the spinal cord, it may represent a mechanism of disability in MS.
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Mitchell, Trina, Derek B. Archer, Winston T. Chu, et al. "Neurite orientation dispersion and density imaging (NODDI) and free‐water imaging in Parkinsonism." Human Brain Mapping 40, no. 17 (2019): 5094–107. http://dx.doi.org/10.1002/hbm.24760.

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Dissertations / Theses on the topic "Neurite orientation dispersion and density imaging"

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Fukutomi, Hikaru. "Neurite imaging reveals microstructural variations in human cerebral cortical gray matter." Kyoto University, 2020. http://hdl.handle.net/2433/253174.

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Wu, Ming Lun, and 吳銘倫. "Cloud-based Data Analysis for Neurite Orientation Dispersion and Density Imaging." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/268xwp.

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Zhang, Zannan. "Using neurite orientation dispersion and density imaging and tracts constrained by underlying anatomy to differentiate between subjects along the Alzheimer's disease continuum." Thesis, 2019. https://hdl.handle.net/2144/36734.

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OBJECTIVE: To assess the involvement of the white matter of the brain in the pathology of Alzheimer’s disease. Using Neurite Orientation Density and Dispersion Imaging (NODDI) and the probabilistic white matter parcellation tool Tracula as a means for understanding whether alterations in the white matter underlie changes in perceived cognitive abilities across the spectrum from health aging to Alzheimer’s disease. METHOD: Data were obtained from 28 participants in the Health Outreach Program for the Elderly (HOPE) at the Boston University Alzheimer’s Disease Center (BU ADC) Clinical Core Registry. MRI scans included an MPRAGE T1 scan, multi-b shell diffusion scan and a High Angular Resolution Diffusion Imaging scan (HARDI). Scans were processed with Freesurfer v6.0 and the NODDI Python2.7 toolkit. The resulting data included the orientation dispersion index (ODI) and Fractional Anisotropy (FA) values for cortical and subcortical regions in the DKT atlas space as well as specific Tracts Constrained by Underlying Anatomy (TRACULA) measurements for 18 specific established white matter tracts. Statistical models using measures of pathway integrity (FA and ODI data) were used to assess relationships with Informant Cognitive Change Index (ICCI), self-described Cognitive Change Index (CCI), and Clinical Dementia Rating (CDR) values. RESULTS: Measures of white matter integrity within several tracts predicted ICCI and CDR well in statistical models. FA and ODI values of the bilateral superior longitudinal fasciculi, inferior longitudinal fasciculi, and the cingulum bundle tracts were all related to ICCI and CDR. None of the known tracts’ FA or ODI values were related to CCI. CONCLUSIONS: Measures of white matter pathway integrity were predictive of ICCI and CDR scores but not CCI. These finding support the notion that self-report of cognitive abilities may be compromised by alterations in insight and reinforce the need for informed study partners and clinical ratings to evaluate potential MCI and AD.
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Ting, Yi-Cen, and 丁怡岑. "Microstructural Characterization in the Peritumoral Area of Glioma Patients and in the Corpus Callosum of Normal Subjects Using Neurite Orientation Dispersion and Density Imaging (NODDI)." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/hj8ra4.

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碩士<br>國立陽明大學<br>腦科學研究所<br>107<br>Diffusion magnetic resonance imaging (dMRI) is a technique for the non-invasive characterization of the microstructure in biological tissues since it is sensitive for the diffusion processes of hydrogen molecules. dMRI is a promising candidate for in vivo quantification of neurite morphology in white matter. Over the past two decades, conventional dMRI method usually focused on Diffusion Tensor Imaging (DTI). DTI was widely used to assess the organization of tissue in white matter, providing some indices to describe changes in biology. The model of DTI describes the diffusive water molecules relevant to free diffusion or hindered anisotropic diffusion homogeneous within each voxel based on the assumption of Gaussian distribution. However, DTI was obtained at single b-value and lacked of specificity for describing tissues in this assumption. Additionally, several advanced dMRI techniques, especially multi-compartment models, have been proposed with complicated assumption for estimating neuron morphology. Neurite Orientation Dispersion and Density Imaging (NODDI) is a clinically feasible technique for estimating the microstructural complexity in central neuron system imaging, post by Zhang et al. in 2012. NODDI is a multi-compartment tissue model based on dMRI, combining a three-compartment tissue model: restricted compartment for non-Gaussian anisotropic diffusion (referring to the space bounded by the membrane of neurites), hindered compartment for Gaussian anisotropic diffusion (referring to the space around the neurites) and isotropic compartment for Gaussian diffusion (referring to the CSF space) in each voxel. Using three compartments, NODDI map not only axons in the white matter but also dendrites in gray matter in each voxel. Compared to DTI indices, NODDI may provide greater specificity to morphology and pathology, e.g. neurite density and orientation dispersion. The aims of this work are to explore the promising indices of diffusion models in characterizing the microstructural complexity in the peritumoral area of gliomas and to show the clinical feasibility and potential capability of NODDI studies. The first chapter gave an overview of dMRI and explained the models of NODDI as well as DTI (Chapter 1). In the chapters 2~5, we investigated the different preprocessing interference on NODDI and DTI as verified by topography of corpus callosum for optimization (Chapter 2), and then we differentiated different types of gliomas and characterized the infiltration in peritumoral area by NODDI and DTI using the optimized preprocessing method (Chapter 3); furthermore, we in-vivo evaluated the simplified NODDI imaging protocol and constructed the semi-automatic regions of interest (ROI) delineation for peritumoral areas (Chapter 4 and 5). Finally, the last chapter gave a conclusion of this thesis (Chapter 6).
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