neurite density
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2022 ◽  
Vol 15 ◽  
Author(s):  
Yash Patel ◽  
Nadine Parker ◽  
Giovanni A. Salum ◽  
Zdenka Pausova ◽  
Tomáš Paus

General psychopathology and cognition are likely to have a bidirectional influence on each other. Yet, the relationship between brain structure, psychopathology, and cognition remains unclear. This brief report investigates the association between structural properties of the cerebral cortex [surface area, cortical thickness, intracortical myelination indexed by the T1w/T2w ratio, and neurite density assessed by restriction spectrum imaging (RSI)] with general psychopathology and cognition in a sample of children from the Adolescent Brain Cognitive Development (ABCD) study. Higher levels of psychopathology and lower levels of cognitive ability were associated with a smaller cortical surface area. Inter-regionally—across the cerebral cortex—the strength of association between an area and psychopathology is strongly correlated with the strength of association between an area and cognition. Taken together, structural deviations particularly observed in the cortical surface area influence both psychopathology and cognition.


2022 ◽  
Author(s):  
Vanessa Vieites ◽  
Yvonne Ralph ◽  
Bethany Reeb-Sutherland ◽  
Anthony Steven Dick ◽  
Aaron T. Mattfeld ◽  
...  

The current study examined the relations between hippocampal structure (e.g., volume and neurite density) and performance on a trace eye blink conditioning (EBC) task in young children. Our first aim assessed whether individual differences in hippocampal volume were associated with trace EBC performance, using both percent Conditioned Responses (% CR) and CR onset latency or the average latency (ms) at which the child started their blink, as measures of hippocampal-dependent associative learning. Our second aim evaluated whether individual differences in hippocampal neurite density were associated with EBC performance using the same outcome measures. Typically developing 4- to 6-year-olds (N = 31; 14 girls; Mage = 5.67; SDage = 0.89) completed T1 and diffusion-weighted MRI scans and a 15-minute trace eyeblink conditioning task outside of the scanner. % CR and CR onset latency were computed across all tone-puff and tone-alone trials. While hippocampal volume was not associated with any of our EBC measures, greater hippocampal neurite density bilaterally, was associated with later CR onset. In other words, children with greater left and right hippocampal neurite density blinked closer to the US (i.e., air puff) than children with less hippocampal neurite density, indicating that structural changes in the hippocampus assisted in the accurate timing of conditioned responses.


2021 ◽  
Author(s):  
Eman Nishat ◽  
Sonja Stojanovski ◽  
Shannon E Scratch ◽  
Stephanie H Ameis ◽  
Anne L Wheeler

AbstractAs maturation of the brain continues throughout development, there is a risk of interference from concussions which are common in childhood. A concussion can cause widespread disruption to axons and inflammation in the brain and may influence emerging cognitive abilities. Females are more likely to experience persistent problems after a concussion, yet the sex-specific impact of concussions on brain microstructure in childhood is not well understood.In children from a large population sample, this study (1) investigated differences in white matter and cortical microstructure between children with and without a history of concussion, and (2) examined relationships between altered brain microstructure and cognitive performance.Neurite density measures from diffusion weighted magnetic resonance imaging were examined in 9-to 10-year-old children in the Adolescent Brain Cognitive Development Study with (n = 336) and without (n = 7368) a history of concussion. (1) Multivariate regression models were used to investigate the relationships between concussion history, sex, and age in the deep white matter, superficial white matter, subcortical structures, and cortex. (2) Principal component analysis was performed on neurite density, and components were examined in relation to performance on the Flanker Inhibitory Control and Attention Task and the Pattern Comparison Processing Speed Task to investigate the relationship between altered neurite density and cognitive performance.Neurite density in all tissue types demonstrated robust positive relationships with age reflecting maturation of brain microstructure. (1) Comparisons between children with and without a history of concussion revealed higher neurite density in deep and superficial white matter in females with concussion. No group differences were observed in subcortical or cortical neurite density. (2) Higher neurite density in superficial white matter beneath the frontal and temporal cortices was associated with lower scores on the processing speed test in females with concussion, and higher scores on the processing speed test in males with concussion.These findings suggest that concussion in childhood leads to premature white matter maturation in females and that this may be associated with slower processing speed. These sex-specific effects on the developing brain may contribute to the enhanced vulnerability to persistent symptoms after concussion in females.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dan Wang ◽  
Kai Shang ◽  
Zheng Sun ◽  
Yue-Hua Li

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.


2021 ◽  
Vol 12 ◽  
Author(s):  
Angela Radetz ◽  
Kalina Mladenova ◽  
Dumitru Ciolac ◽  
Gabriel Gonzalez-Escamilla ◽  
Vinzenz Fleischer ◽  
...  

Motor skills are frequently impaired in multiple sclerosis (MS) patients following grey and white matter damage with cortical excitability abnormalities. We applied advanced diffusion imaging with 3T magnetic resonance tomography for neurite orientation dispersion and density imaging (NODDI), as well as diffusion tensor imaging (DTI) in 50 MS patients and 49 age-matched healthy controls to quantify microstructural integrity of the motor system. To assess excitability, we determined resting motor thresholds using non-invasive transcranial magnetic stimulation. As measures of cognitive-motor performance, we conducted neuropsychological assessments including the Nine-Hole Peg Test, Trail Making Test part A and B (TMT-A and TMT-B) and the Symbol Digit Modalities Test (SDMT). Patients were evaluated clinically including assessments with the Expanded Disability Status Scale. A hierarchical regression model revealed that lower neurite density index (NDI) in primary motor cortex, suggestive for axonal loss in the grey matter, predicted higher motor thresholds, i.e. reduced excitability in MS patients (p = .009, adjusted r² = 0.117). Furthermore, lower NDI was indicative of decreased cognitive-motor performance (p = .007, adjusted r² = .142 for TMT-A; p = .009, adjusted r² = .129 for TMT-B; p = .006, adjusted r² = .142 for SDMT). Motor WM tracts of patients were characterized by overlapping clusters of lowered NDI (p &lt;.05, Cohen’s d = 0.367) and DTI-based fractional anisotropy (FA) (p &lt;.05, Cohen’s d = 0.300), with NDI exclusively detecting a higher amount of abnormally appearing voxels. Further, orientation dispersion index of motor tracts was increased in patients compared to controls, suggesting a decreased fiber coherence (p &lt;.05, Cohen’s d = 0.232). This study establishes a link between microstructural characteristics and excitability of neural tissue, as well as cognitive-motor performance in multiple sclerosis. We further demonstrate that the NODDI parameters neurite density index and orientation dispersion index detect a larger amount of abnormally appearing voxels in patients compared to healthy controls, as opposed to the classical DTI parameter FA. Our work outlines the potential for microstructure imaging using advanced biophysical models to forecast excitability alterations in neuroinflammation.


2021 ◽  
Vol 11 (9) ◽  
pp. 1151
Author(s):  
Abdulmajeed Alotaibi ◽  
Anna Podlasek ◽  
Amjad AlTokhis ◽  
Ali Aldhebaib ◽  
Rob A. Dineen ◽  
...  

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.


2021 ◽  
Author(s):  
Meng Cao ◽  
Yuyang Luo ◽  
Ziyan Wu ◽  
Kai Wu ◽  
Xiaobo Li

Traumatic brain injury is a major public health concern. A significant proportion of individuals experience post-traumatic brain injury behavioral impairments, especially in attention and inhibitory control domains. Traditional diffusion-weighted MRI techniques, such as diffusion tensor imaging, have provided tools to assess white matter structural disruptions reflecting the long-term brain tissue alterations associated with traumatic brain injury. The recently developed neurite orientation dispersion and density imaging is a more advanced diffusion-weighted MRI modality, which provides more refined characterization of brain tissue microstructures by assessing the neurite orientation dispersion and neurite density properties. In this study, we investigated the morphometrical and microstructural alterations at chronic brain injury stage and their relationships with the functional outcomes. Neurite orientation dispersion and density imaging data from 44 young adults with chronic traumatic brain injury (ranging from 18 - 27 years of age; 23 males/21 females) who had no prior-traumatic brain injury history of attention deficits and/or hyperactivity and 45 group-matched normal controls (23 males /22 females) were collected. Maps of fractional anisotropy, neurite orientation dispersion index, and neurite density index were calculated. Vertex-wise and voxel-wise analyses were conducted for gray matter and white matter, respectively. Post-hoc region of interest-based analyses were also performed. Compared to the controls, the group of traumatic brain injury showed significantly increased orientation dispersion index in various gray matter regions and significantly decreased orientation dispersion index in several white matter regions. Brain-behavioral association analyses indicated that the reduced neurite density index of left precentral gyrus and the reduced orientation dispersion index of left superior longitudinal fasciculus were significantly associated with elevated hyperactive/impulsive symptoms in the patients with traumatic brain injury. These findings suggest that traumatic brain injury-induced chronic neurite orientation dispersion alterations of left superior longitudinal fasciculus and left precentral may significantly contribute to post-traumatic brain injury hyperactive/impulsive behaviors in young adults with traumatic brain injury.


2021 ◽  
Author(s):  
Katherine E. Lawrence ◽  
Zvart Abaryan ◽  
Emily Laltoo ◽  
Leanna M. Hernandez ◽  
Michael Gandal ◽  
...  

AbstractSex differences in white matter microstructure have been robustly demonstrated in the adult brain using both conventional and advanced diffusion-weighted magnetic resonance imaging (dMRI) approaches. However, the effect of sex on white matter microstructure prior to adulthood remains poorly understood, with previous developmental work focusing on conventional microstructure metrics and yielding mixed results. Here we thoroughly and rigorously characterized sex differences in white matter microstructure among over 6,000 children from the Adolescent Brain Cognitive Development (ABCD) Study who were between 9 and 10 years old. Microstructure was quantified using both the conventional model - diffusion tensor imaging (DTI) - and an advanced model, restriction spectrum imaging (RSI). DTI metrics included fractional anisotropy (FA) and mean, axial, and radial diffusivity (MD, AD, RD). RSI metrics included normalized isotropic, directional, and total intracellular diffusion (N0, ND, NT). We found significant and replicable sex differences in DTI or RSI microstructure metrics in every white matter region examined across the brain. The impact of sex on FA was regionally specific. Across white matter regions, boys exhibited greater MD, AD, and RD than girls, on average. Girls displayed increased N0, ND, and NT compared to boys, on average, suggesting greater cell and neurite density in girls. Together, these robust and replicable findings provide an important foundation for understanding sex differences in health and disease.


2021 ◽  
Author(s):  
Andrada Ianus ◽  
Joana Carvalho ◽  
Francisca F Fernandes ◽  
Renata Cruz ◽  
Cristina Chavarrias ◽  
...  

Diffusion MRI (dMRI) provides unique insights into the neural tissue milieu by probing interaction of diffusing molecules and tissue microstructure. Most dMRI techniques focus on white matter tissues (WM) due to the relatively simpler modelling of diffusion in the more organized tracts; however, interest is growing in gray matter characterisations. The Soma and Neurite Density MRI (SANDI) methodology harnesses a model incorporating water diffusion in spherical objects (assumed to be associated with cell bodies) and in impermeable 'sticks' (representing neurites), which potentially enables the characterisation of cellular and neurite densities. Recognising the importance of rodents in animal models of development, aging, plasticity, and disease, we here sought to develop SANDI for preclinical imaging and provide a validation of the methodology by comparing its metrics with the Allen mouse brain atlas. SANDI was implemented on a 9.4T scanner equipped with a cryogenic coil, and experiments were carried out on N=6 mice. Pixelwise, ROI-based, and atlas comparisons were performed, and results were also compared to more standard Diffusion Kurtosis MRI (DKI) metrics. We further investigated effects of different pre-processing pipelines, specifically the comparison of magnitude and real-valued data, as well as different acceleration factors. Our findings reveal excellent reproducibility of the SANDI parameters, including the sphere and stick fraction as well as sphere size. More strikingly, we find a very good rank correlation between SANDI-driven soma fraction and Allen brain atlas contrast (which represents the cellular density in the mouse brain). Although some DKI parameters (FA, MD) correlated with some SANDI parameters in some ROIs, they did not correlate nearly as well as SANDI parameters with the Allen atlas, suggesting a much more specific nature of the SANDI parameters. We conclude that SANDI is a viable preclinical MRI technique that can greatly contribute to research on brain tissue microstructure.


2021 ◽  
pp. 1-11
Author(s):  
Rafael Romero-Garcia ◽  
John Suckling ◽  
Mallory Owen ◽  
Moataz Assem ◽  
Rohitashwa Sinha ◽  
...  

OBJECTIVE The aim of this study was to test brain tumor interactions with brain networks, thereby identifying protective features and risk factors for memory recovery after resection. METHODS Seventeen patients with diffuse nonenhancing glioma (ages 22–56 years) underwent longitudinal MRI before and after surgery, and during a 12-month recovery period (47 MRI scans in total after exclusion). After each scanning session, a battery of memory tests was performed using a tablet-based screening tool, including free verbal memory, overall verbal memory, episodic memory, orientation, forward digit span, and backward digit span. Using structural MRI and neurite orientation dispersion and density imaging (NODDI) derived from diffusion-weighted images, the authors estimated lesion overlap and neurite density, respectively, with brain networks derived from normative data in healthy participants (somatomotor, dorsal attention, ventral attention, frontoparietal, and default mode network [DMN]). Linear mixed-effect models (LMMs) that regressed out the effect of age, gender, tumor grade, type of treatment, total lesion volume, and total neurite density were used to test the potential longitudinal associations between imaging markers and memory recovery. RESULTS Memory recovery was not significantly associated with either the tumor location based on traditional lobe classification or the type of treatment received by patients (i.e., surgery alone or surgery with adjuvant chemoradiotherapy). Nonlocal effects of tumors were evident on neurite density, which was reduced not only within the tumor but also beyond the tumor boundary. In contrast, high preoperative neurite density outside the tumor but within the DMN was associated with better memory recovery (LMM, p value after false discovery rate correction [Pfdr] < 10−3). Furthermore, postoperative and follow-up neurite density within the DMN and frontoparietal network were also associated with memory recovery (LMM, Pfdr = 0.014 and Pfdr = 0.001, respectively). Preoperative tumor and postoperative lesion overlap with the DMN showed a significant negative association with memory recovery (LMM, Pfdr = 0.002 and Pfdr < 10−4, respectively). CONCLUSIONS Imaging biomarkers of cognitive recovery and decline can be identified using NODDI and resting-state networks. Brain tumors and their corresponding treatment affecting brain networks that are fundamental for memory functioning such as the DMN can have a major impact on patients’ memory recovery.


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