Neurite Orientation Dispersion And Density Imaging Research Articles

Association of lower heart rate variability with neuroimaging markers for dementia‐related pathology: The Multi‐Ethnic Study of Atherosclerosis (MESA)

AbstractBackgroundLower heart rate variability (HRV), indicating worse cardiac autonomic function, is associated with cardiovascular risk factors for dementia. We hypothesized that lower HRV would be associated with neuroimaging biomarkers for dementia‐related pathology independent of cardiovascular risk factors.MethodDuring MESA Exam 6 (2016‐19), 256 white and African‐American Wake Forest site participants completed 3T brain MRI, and 159 further completed Aβ‐PET imaging. HRV was calculated as standard deviation of normal‐to‐normal intervals (SDNN) and root mean square of successive differences (RMSSD) from 10‐second electrocardiogram at Exam 1 (2000‐02) and Exam 5 (2010‐12). We related continuous (log2‐normalized) HRV to neuroimaging parameters including mean temporal lobe cortical thickness, neurite orientation dispersion and density imaging (NODDI) free water in gray (gmFW) and white matter (wmFW), and presence of cerebral microbleeds (CMBs), lacunes, and Aβ positivity (Pittsburgh Compound B SUVR ≥1.21) using multivariable linear and logistic regression, and examined race and sex interactions. To account for potential non‐linearity, we also considered the association of lowest quartile HRV to neuroimaging markers. Regression coefficients (β [95% CI]; standard deviation units) and odds ratios (OR [95% CI]) are adjusted for age, race, sex, education, systolic blood pressure, body mass index, smoking, hypertension medication use, diabetes, and APOE genotype.ResultIn 254 participants (Exam 6 age 72.2±6.9 years; 58.7% female; 47.2% white) with HRV measurements, lower continuous Exam 1 SDNN (β = ‐0.23 [‐0.39, ‐0.07]) and RMSSD (β = ‐0.19 [‐0.33, ‐0.05]) were associated with higher wmFW. Interactions showed that CMBs were associated with lowest quartile Exam 1 SDNN (OR = 3.76 [1.15, 12.25]) and Exam 5 RMSSD (OR = 3.36 [1.07, 10.54]) in males only (sex interaction P<0.001), and with Exam 1 SDNN (OR = 2.58 [1.04, 6.45]) in African‐Americans only (race interaction P = 0.039). Lower HRV was not associated with cortical thickness or presence of lacunes. In 152 participants with Aβ‐PET, no associations with Aβ deposition were found.ConclusionLower HRV from up to 16 years prior may be associated with increased neuroinflammation as measured by free water in older adults. Associations between HRV and cerebral small vessel disease markers may differ by sex or race.

Age effects on white matter microstructure in individuals of self‐identified Indian ancestry from the UK Biobank

AbstractBackgroundThe incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increase in age. Given the lack of ethnic diversity in most brain research to date, it is valuable to study cohorts with diverse genetic and environmental backgrounds, to identify predictors of health and disease that can be generalized to other ethnic groups than the commonly studied populations of European ancestry. To address this gap in the literature, we modeled factors that affect aging patterns in the brain’s white matter in individuals with Indian ancestry using advanced diffusion‐weighted MRI (dMRI).MethodCross‐sectional dMRI data from 123 individuals (males, n=78; females, n=45) of self‐reported Indian ancestry (born in India: 44%; mean age: 60.1±8.3 SD, range: 45‐80) from the UK Biobank were analyzed using diffusion tensor imaging (DTI), the tensor distribution function (TDF), neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator MRI (MAPMRI). Main effects of age, sex, and age‐by‐sex interaction were investigated to characterize trajectories in whole‐brain white matter averages and the corpus callosum (CC), parcellated using the JHU‐ICBM atlas, covarying for years of education, waist/hip ratio, population structure (Figure 1) and the Townsend index. Normative lifespan charts were created to visualize white matter aging trajectories for the major diffusivity metrics.ResultNormative centile curves (Figures 2‐3) show, with increasing age, declining white matter integrity, increased diffusivity, lower white matter density and diffusion restriction at the whole‐brain level and CC (Table 1; Figure 4). There was no detectable effect of sex, nor age‐by‐sex interaction, across whole‐brain metrics. In the CC, a steeper aging trajectory, evidenced by more pronounced white matter changes, was observed in males relative to females (Table 1; Figure 5).ConclusionUsing advanced dMRI modeling, we report diffuse white matter changes with respect to age in a subsample of UK Biobank individuals of self‐reported Indian ancestry. Future studies should include larger sample sizes, comparisons with Indian ancestry individuals residing in India, consider vascular factors, and examine genotype interactions (e.g., with apolipoprotein E genotype), to further characterize risk factors and better understand brain aging in diverse populations with varied genetic and environmental backgrounds.

Effect of APOE4 and APOE2 genotype on white matter microstructure

AbstractBackgroundThe apolipoprotein E4 (APOE4) genotype is a major risk factor for late‐onset Alzheimer’s disease (AD). APOE2, on the other hand, has a protective effect. While there is evidence supporting an association between APOE genotype and white matter (WM) microstructure, findings have been inconsistent. Studies assessing AD risk in WM microstructure have largely used diffusion tensor imaging (DTI), but more recent diffusion MRI models may offer additional sensitivity to microstructural properties. Here, we characterized the effects of APOE4 and APOE2 genotypes on WM microstructure in a large, population‐based sample of adults from the UK Biobank.MethodDiffusion MRI data from 17,896 UK Biobank participants (age range: 45‐80 years; Fig 1a) were analyzed. Ten diffusion measures were derived from 4 models: 1) DTI, 2) the tensor distribution function (TDF), 3) mean apparent propagator MRI (MAPMRI), and 4) neurite orientation dispersion and density imaging (NODDI). Each measure was averaged across voxels within 25 WM regions (Fig 1c). Linear regressions were used to compare regional measures between individuals with an E3E3 genotype and E4 (E3E4+E4E4) or E2 (E2E3+E2E2) carriers, adjusting for age, sex, age‐by‐sex interaction, education, parents with dementia, and the first four genetic ancestry principal components. E4 or E2 carrier‐by‐age interactions were also tested, covarying for APOE genotype. FDR (q=0.05) was used to correct for multiple comparisons across 25 regions.ResultCompared to E3E3 carriers, E4 carriers showed widespread, yet subtle WM differences (Fig 2). The largest effects were detected with signal‐based model measures that reflect increased mean diffusivity (higher DTI‐MD, higher MSD, lower TDF‐FA). Significant E4‐by‐age interactions were detected with NODDI‐ISOVF, with E4 carriers showing a greater age‐related increase in ISOVF (Fig 3). Compared to E3E3 carriers, E2 carriers showed higher NODDI‐ICVF throughout the WM; differences were not detected with other measures. No significant E2‐by‐age interactions were detected (Fig 4).ConclusionAPOE4 carriers showed microstructural WM differences in measures reflecting less restricted diffusion, which could indicate neuronal loss or inflammation, particularly in posterior WM. Age‐dependent APOE4 effects were only detected with multi‐compartment diffusion measures. Greater neuronal density in APOE2 carriers may suggest a protective effect in WM, which was also detectable only with a multi‐compartment model.

Cardiometabolic disorders are associated with reduced cerebral perfusion and white matter microstructure

AbstractBackgroundCardiometabolic disorders (hypertension and diabetes) often co‐occur and are considered key modifiable risk factors for Alzheimer’s disease and related disorders; yet, the extent to which they each affect brain structure and function is unclear. We examined their associations with neuroimaging biomarkers of white matter microstructure, cerebral perfusion, and cognitive function in a diverse cohort of older adults.MethodParticipants aged 50‐85 years enrolled in Wake Forest Alzheimer’s Disease Research Center’s Clinical Core between 2016‐2020 received clinical evaluation, oral glucose tolerance testing (OGTT), neuroimaging, cognitive testing, and adjudication for mild cognitive impairment (MCI) and dementia. 3T brain MRI included T1 (for gray/white matter segmentation, regional volumes/thicknesses); FLAIR for white matter hyperintensity volume (WMHv); arterial spin labeling for cerebral blood flow (CBF); diffusion tensor imaging (DTI) for fractional anisotropy (FA); and neurite orientation dispersion and density imaging (NODDI) for Free Water. Hypertension (HTN) was staged using seated blood pressure (BP) and medications. Hyperglycemia was staged using OGTT 120 minute glucose levels (OGTT120), hemoglobin A1c, and fasting glucose as available. Cardiometabolic status was categorized (HTN only, hyperglycemia only, hyperglycemia+HTN, neither). Multivariable linear regression modeled associations with neuroimaging measures adjusted for age, gender, and race.ResultMRI was available on 478 participants (35% MCI and 10% dementia) with mean age of 70±8 years, 74% with HTN, 61% with hyperglycemia (4% with non‐insulin treated diabetes), and 15% African‐Americans. The combination of hyperglycemia+HTN was associated with significantly higher NODDI Free Water and WMHv, lower FA, and lower gray matter perfusion, compared to neither factor (Table). Continuous levels of systolic BP and OGTT120 broadly correlated with WM microstructure, WMHv, and gray matter CBF (Figure). In adjusted models, systolic BP remained significantly associated with higher NODDI Free Water and WMHv, and CBF in gray and white matter. OGTT120 and WMHv remained significant in adjusted models. Cardiometabolic factors were not associated with gray matter macrostructure (e.g. volumes, temporal lobe cortical thickness) or cognitive status in this sample.ConclusionIn this deeply phenotyped and racially diverse sample, individual cardiometabolic factors and the co‐occurrence of disorders was associated with reduced cerebral gray matter perfusion and reduced white matter microstructure.

Associations of plasma neurofilament light protein levels with cognitive functions and brain structure parameters

AbstractBackgroundNeurofilament light (NfL) protein level is considered a non‐specific marker of neurodegeneration. NfL levels have been associated with established, non‐blood based neurodegenerative markers, including cognitive performance and reduced brain volume. However, most studies were small (N<300), and compared levels in patients (MCI, Alzheimer’s disease) with those in healthy controls. We investigated to what extent NfL levels are associated with cognitive performance and MRI measures of brain volume and microstructure, in a large non‐demented population‐based sample.MethodThe analyses were based on 4,578 participants (30‐95 years) of the Rhineland Study, a community‐based cohort study in Bonn, Germany. Plasma NfL levels were measured on the SIMOA platform. We assessed cognitive performance with tests for memory, processing speed, executive function and crystallized intelligence and an eye movement (EM) test battery. 3,206 persons underwent structural and diffusion weighted MR imaging. Imaging outcomes included volumetric measures (total brain, grey matter, white matter, hippocampus); diffusion tensor measures (fractional anisotropy; mean, radial, and axial diffusivity); and neurite orientation dispersion and density imaging (NODDI) measures. We used multivariable regression models to assess the relation between NfL levels and cognitive performance and MRI measures with adjustment for possible confounders.ResultAcross all participants, we found only negligibly small associations between NfL levels and cognitive performance, brain volumetric and diffusion tensor measures. However, age‐stratified analyses revealed that in age 40‐49 and from age 60 onwards higher NfL levels were associated with lower orientation dispersion index (ODI). In the 70‐ to 79‐year‐olds, higher NfL levels were additionally associated with higher prosaccade accuracy, higher mean, axial and radial diffusivity, higher extracellular and lower intracellular volume fraction and a lower neurite density index. In the 80+‐year‐olds, NfL levels were negatively associated with hippocampal and white matter volume and positively associated with fractional anisotropy and radial diffusivity.ConclusionHigher NfL levels were associated with smaller hippocampal volume and diffusion tensor and NODDI measures in older subjects. In younger persons (up to age 70 years), NfL levels were only associated with ODI. This suggests that NfL level is a sensitive marker of subtle changes in brain microstructure, especially in old age.

Not all voxels are created equal: Reducing estimation bias in regional NODDI metrics using tissue-weighted means

Neurite orientation dispersion and density imaging (NODDI) estimates microstructural properties of brain tissue relating to the organisation and processing capacity of neurites, which are essential elements for neuronal communication. Descriptive statistics of NODDI tissue metrics are commonly analyzed in regions-of-interest (ROI) to identify brain-phenotype associations. Here, the conventional method to calculate the ROI mean weights all voxels equally. However, this produces biased estimates in the presence of CSF partial volume. This study introduces the tissue-weighted mean, which calculates the mean NODDI metric across the tissue within an ROI, utilising the tissue fraction estimate from NODDI to reduce estimation bias. We demonstrate the proposed mean in a study of white matter abnormalities in young onset Alzheimer's disease (YOAD). Results show the conventional mean induces significant bias that correlates with CSF partial volume, primarily affecting periventricular regions and more so in YOAD subjects than in healthy controls. Due to the differential extent of bias between healthy controls and YOAD subjects, the conventional mean under- or over-estimated the effect size for group differences in many ROIs. This demonstrates the importance of using the correct estimation procedure when inferring group differences in studies where the extent of CSF partial volume differs between groups. These findings are robust across different acquisition and processing conditions. Bias persists in ROIs at higher image resolution, as demonstrated using data obtained from the third phase of the Alzheimer's disease neuroimaging initiative (ADNI); and when performing ROI analysis in template space. This suggests that conventional ROI means of NODDI metrics are biased estimates under most contemporary experimental conditions, the correction of which requires the proposed tissue-weighted mean. The tissue-weighted mean produces accurate estimates of ROI means and group differences when ROIs contain voxels with CSF partial volume. In addition to NODDI, the technique can be applied to other multi-compartment models that account for CSF partial volume, such as the free water elimination method. We expect the technique to help generate new insights into normal and abnormal variation in tissue microstructure of regions typically confounded by CSF partial volume, such as those in individuals with larger ventricles due to atrophy associated with neurodegenerative disease.

Microstructural Tissue Changes in a Rat Model of Mild Traumatic Brain Injury.

Our study investigates the potential of diffusion MRI (dMRI), including diffusion tensor imaging (DTI), fixel-based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI), to detect microstructural tissue abnormalities in rats after mild traumatic brain injury (mTBI). The brains of sham-operated and mTBI rats 35 days after lateral fluid percussion injury were imaged ex vivo in a 11.7-T scanner. Voxel-based analyses of DTI-, fixel- and NODDI-based metrics detected extensive tissue changes in directly affected brain areas close to the primary injury, and more importantly, also in distal areas connected to primary injury and indirectly affected by the secondary injury mechanisms. Histology revealed ongoing axonal abnormalities and inflammation, 35 days after the injury, in the brain areas highlighted in the group analyses. Fractional anisotropy (FA), fiber density (FD) and fiber density and fiber bundle cross-section (FDC) showed similar pattern of significant areas throughout the brain; however, FA showed more significant voxels in gray matter areas, while FD and FDC in white matter areas, and orientation dispersion index (ODI) in areas most damage based on histology. Region-of-interest (ROI)-based analyses on dMRI maps and histology in selected brain regions revealed that the changes in MRI parameters could be attributed to both alterations in myelinated fiber bundles and increased cellularity. This study demonstrates that the combination of dMRI methods can provide a more complete insight into the microstructural alterations in white and gray matter after mTBI, which may aid diagnosis and prognosis following a mild brain injury.

Assessment of Isocitrate Dehydrogenase 1 Genotype and Cell Proliferation in Gliomas Using Multiple Diffusion Magnetic Resonance Imaging.

Objectives: To compare the efficacy of parameters from multiple diffusion magnetic resonance imaging (dMRI) for prediction of isocitrate dehydrogenase 1 (IDH1) genotype and assessment of cell proliferation in gliomas.Methods: Ninety-one patients with glioma underwent diffusion weighted imaging (DWI), multi-b-value DWI, and diffusion kurtosis imaging (DKI)/neurite orientation dispersion and density imaging (NODDI) on 3.0T MRI. Each parameter was compared between IDH1-mutant and IDH1 wild-type groups by Mann–Whitney U test in lower-grade gliomas (LrGGs) and glioblastomas (GBMs), respectively. Further, performance of each parameter was compared for glioma grading under the same IDH1 genotype. Spearman correlation coefficient between Ki-67 labeling index (LI) and each parameter was calculated.Results: The diagnostic performance was better achieved with apparent diffusion coefficient (ADC), slow ADC (D), fast ADC (D∗), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), mean kurtosis (MK), and intracellular volume fraction (ICVF) for distinguishing IDH1 genotypes in LrGGs, with statistically insignificant AUC values from 0.750 to 0.817. In GBMs, no difference between the two groups was found. For IDH1-mutant group, all parameters, except for fractional anisotropy (FA) and D∗, significantly discriminated LrGGs from GBMs (P < 0.05). However, for IDH1 wild-type group, only ADC statistically discriminated the two (P = 0.048). In addition, MK has maximal correlation coefficient (r = 0.567, P < 0.001) with Ki-67 LI.Conclusion: dMRI-derived parameters are promising biomarkers for predicting IDH1 genotype in LrGGs, and MK has shown great potential in assessing glioma cell proliferation.

In vivo detection of damage in multiple sclerosis cortex and cortical lesions using NODDI

ObjectiveTo characterise in vivo the microstructural abnormalities of multiple sclerosis (MS) normal-appearing (NA) cortex and cortical lesions (CLs) and their relations with clinical phenotypes and disability using neurite orientation dispersion...

Brain structural abnormalities in the preclinical stage of Machado-Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3): evaluation by MRI morphometry, diffusion tensor imaging and neurite orientation dispersion and density imaging.

To investigate whether neurite orientation dispersion and density imaging (NODDI) could provide the added value for detecting brain microstructural alterations in the preclinical stage of Machado-Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3) compared with MRI morphometry and diffusion tensor imaging (DTI). Twenty preclinical MJD/SCA3 patients and 21 healthy controls were enrolled. Three b values DWI and 3D T1-weighted images were acquired at 3.0T. Tract-based spatial statistics (TBSS) approach was used to investigate the white matter (WM) alterations in the DTI metrics and NODDI metrics. Gray matter-based spatial statistics (GBSS) approach was used to investigate the grey matter (GM) alterations in the NODDI metrics. Voxel-based morphometry (VBM) approach was performed on the 3D T1-weighted images. The relationship between the cytosine-adenine-guanine (CAG) repeat length and brain microstructural alterations of preclinical MJD/SCA3 was identified. Compared with healthy controls, the preclinical MJD/SCA3 patients showed decreased FA and NDI as well as increased MD, AD, and RD in the WM of cerebellum and brainstem (corrected P < 0.05), and decreased NDI in the GM of cerebellar vermis (corrected P < 0.05). The CAG repeat length in preclinical MJD/SCA3 patients was negatively correlated with the reduced FA and NDI of the infratentorial WM and the reduced NDI of the cerebellum, and positively with the increased MD and RD of the infratentorial WM. NOODI can provide novel quantitative microstructural changes in MJD/SCA3 carriers, expanding our understanding of the gray and white matter (axons and dendrites) degeneration in this frequent ataxia syndrome.

Quantification of normal-appearing white matter damage in early relapse-onset multiple sclerosis through neurite orientation dispersion and density imaging

Background Neurodegeneration is a major contributor of neurological disability in multiple sclerosis (MS). The possibility to fully characterize normal appearing white matter (NAWM) damage could provide the missing information needed to clarify the mechanisms beyond disability accumulation.Objective In the present study we aimed to characterize the presence and extent of NAWM damage and its correlation with clinical disability.Methods We applied Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) in a cohort of 27 early relapse-onset MS patients (disease duration < 5 years) compared to a population of 26 age- and sex-matched healthy controls (HCs). All patients underwent a neurological examination, including the Expanded Disability Status Scale (EDSS).Results MS patients showed lower fractional anisotropy (FA) and higher mean diffusivity (MD) values in the main WM bundles, such as the corticospinal tract, corpus callosum, superior and middle cerebellar peduncles, posterior thalamic radiation (which includes optic radiation), cingulum and external capsule. All brain areas with reduced FA/increased MD also displayed a reduction in neurite density index (NDI). However, comparing individual voxels of the WM skeleton between MS and HCs, a higher number of NDI significant voxels was disclosed compared to FA/MD (56.4% vs 11.2%/41.2%). No significant correlations were observed between DTI/NODDI metrics and EDSS.Conclusions Our findings suggest that NDI may allow for a better characterization and understanding of the microstructural changes in the NAWM since the early relapsing-remitting MS phases. Future longitudinal studies including a larger cohort of patients with different clinical phenotypes may clarify the association between NODDI metrics and disability progression.

Neurite orientation dispersion and density imaging in cocaine use disorder

Cocaine use disorder (CUD) is characterized by a compulsive search for cocaine. Several studies have shown that cocaine users exhibit cognitive deficits, including lack of inhibition and decision-making as well as brain volume and diffusion-based white-matter alterations in a wide variety of brain regions. However, the non-specificity of standard volumetric and diffusion-tensor methods to detect structural micropathology may lead to wrong conclusions. To better understand microstructural pathology in CUD, we analyzed 60 CUD participants (3 female) and 43 non-CUD controls (HC; 2 female) retrospectively from our cross-sectional Mexican SUD neuroimaging dataset (SUDMEX-CONN), using multi-shell diffusion-weighted imaging and the neurite orientation dispersion and density imaging (NODDI) analysis, which aims to more accurately model microstructural pathology. We used Viso values of NODDI that employ a three-compartment model in white (WM) and gray-matter (GM). These values were also correlated with clinical measures, including psychiatric severity status, impulsive behavior and pattern of cocaine and tobacco use in the CUD group. We found higher whole-brain microstructural pathology in WM and GM in CUD patients than controls. ROI analysis revealed higher Viso-NODDI values in superior longitudinal fasciculus, cingulum, hippocampus cingulum, forceps minor and Uncinate fasciculus, as well as in frontal and parieto-temporal GM structures. We also found correlations between significant ROI and impulsivity, onset age of cocaine use and weekly dosage with Viso-NODDI. However, we did not find correlations with psychopathology measures. Overall, although their clinical relevance remains questionable, microstructural pathology seems to be present in CUD both in gray and white matter.

Compartmental models for diffusion weighted MRI reveal widespread brain changes in HIV-infected patients.

Diffusion tensor imaging (DTI) has been used to explore changes in the brain of subjects with human immunodeficiency virus (HIV) infection. However, DTI notoriously suffers from low specificity. Neurite orientation dispersion and density imaging (NODDI) is a compartmental model able to provide specific microstructural information with additional sensitivity/specificity. In this study we use both the NODDI and the DTI models to evaluate microstructural differences between 35 HIV-positive patients and 20 healthy controls. Diffusion-weighted imaging was acquired using three b-values (0, 1000 and 2500 s/mm2). Both DTI and NODDI models were fitted to the data, obtaining estimates for fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), neurite density index (NDI) and orientation dispersion index (ODI), after which we performed group comparisons using Tract-based spatial statistics (TBSS). While significant group effects were found in in FA, MD, RD, AD and NDI, NDI analysis uncovered a much wider involvement of brain tissue in HIV infection as compared to DTI. In region-of interest (ROI)-based analysis, NDI estimates from the right corticospinal tract produced excellent performance in discriminating the two groups (AUC = 0.974, sensitivity = 90%; specificity =97%).

Experimental Imaging Study of Encephalomalacia Fluid-Attenuated Inversion Recovery (FLAIR) Hyperintense Lesions in Posttraumatic Epilepsy.

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.

White matter and nigral alterations in multiple system atrophy-parkinsonian type

Multiple system atrophy (MSA) is classified into two main types: parkinsonian and cerebellar ataxia with oligodendrogliopathy. We examined microstructural alterations in the white matter and the substantia nigra pars compacta (SNc) of patients with MSA of parkinsonian type (MSA-P) using multishell diffusion magnetic resonance imaging (dMRI) and myelin sensitive imaging techniques. Age- and sex-matched patients with MSA-P (n = 21, n = 10 first and second cohorts, respectively), Parkinson’s disease patients (n = 19, 17), and healthy controls (n = 20, 24) were enrolled. Magnetization transfer saturation imaging (MT-sat) and dMRI were obtained using 3-T MRI. Measurements obtained from diffusion tensor imaging (DTI), free-water elimination DTI, neurite orientation dispersion and density imaging (NODDI), and MT-sat were compared between groups. Tract-based spatial statistics analysis revealed differences in diffuse white matter alterations in the free-water fractional volume, myelin volume fraction, and intracellular volume fraction between the patients with MSA-P and healthy controls, whereas free-water and MT-sat differences were limited to the middle cerebellar peduncle in comparison with those with Parkinson’s disease. Region-of-interest analysis of white matter and SNc revealed significant differences in the middle and inferior cerebellar peduncle, pontine crossing tract, corticospinal tract, and SNc between the MSA-P and healthy controls and/or Parkinson’s disease patients. Our results shed light on alterations to brain microstructure in MSA.

Single-shell NODDI using dictionary-learner-estimated isotropic volume fraction.

Neurite orientation dispersion and density imaging (NODDI) enables the assessment of intracellular, extracellular, and free water signals from multi-shell diffusion MRI data. It is an insightful approach to characterize brain tissue microstructure. Single-shell reconstruction for NODDI parameters has been discouraged in previous studies caused by failure when fitting, especially for the neurite density index (NDI). Here, we investigated the possibility of creating robust NODDI parameter maps with single-shell data, using the isotropic volume fraction (fISO ) as a prior. Prior estimation was made independent of the NODDI model constraint using a dictionary learning approach. First, we used a stochastic sparse dictionary-based network (DictNet), which is trained with data obtained from in vivo and simulated diffusion MRI data, to predict fISO . In single-shell cases, the mean diffusivity and raw T2 signal with no diffusion weighting (S0 ) was incorporated in the dictionary for the fISO estimation. Then, the NODDI framework was used with the known fISO to estimate the NDI and orientation dispersion index (ODI). The fISO estimated using our model was compared with other fISO estimators in the simulation. Further, using both synthetic data simulation and human data collected on a 3 T scanner (both high-quality HCP and clinical dataset), we compared the performance of our dictionary-based learning prior NODDI (DLpN) with the original NODDI for both single-shell and multi-shell data. Our results suggest that DLpN-derived NDI and ODI parameters for single-shell protocols are comparable with original multi-shell NODDI, and the protocol with b= 2000 s/mm2 performs the best (error ~ 5% in white and gray matter). This may allow NODDI evaluation of studies on single-shell data by multi-shell scanning of two subjects for DictNet fISO training.

Linking Microstructural Integrity and Motor Cortex Excitability in Multiple Sclerosis.

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 <.05, Cohen’s d = 0.367) and DTI-based fractional anisotropy (FA) (p <.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 <.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.

Pain differences in neurite orientation dispersion and density imaging measures among community-dwelling older adults.

Neurite orientation dispersion and density imaging (NODDI) is a technique providing more detailed information on the microstructural bases of white matter. Given the previously reported white matter contributions to chronic pain, the present study aims to investigate pain-specific differences in NODDI measures across white matter tracts in a sample of community-dwelling older adults with (n=29) and without (n=18) chronic musculoskeletal pain. We further aimed to investigate associations between NODDI measures and clinical and experimental pain measures. As part of the Nepal study, a subset of older adults (>60years old), underwent multiple laboratory sessions providing self-reported and experimental pain measures and a diffusion weighted neuroimaging sequence. Older adults with chronic musculoskeletal pain had a lower neurite density with less geometric complexity across a number of white matter tracts compared to older pain-free controls (corrected p's<0.05). Lower neurite density was associated with greater self-reported pain intensity and anatomical pain sites, as well as greater experimental pain sensitivity (p's<0.05). There were also significant pain-by-sex differences in neurite density and geometric complexity across multiple white matter tracts mainly around the hippocampus (corrected p's<0.05). Finally, there were no pain differences with respect to extra-cellular water diffusion (corrected p's>0.05). Our study demonstrates less geometric complexity in neurite density and architecture in chronic musculoskeletal pain, partly in a sex-dependent manner. An increased understanding of neurobiological mechanisms such as those measured by NODDI may contribute to the potential targeting of interventions in our older population suffering from chronic pain.

NODDI microstructural abnormalities in normal-appearing gray matter and white matter contribute to cognitive impairment in multiple sclerosis

Heterogeneous processes contribute to multiple sclerosis (MS)-related cognitive impairment. Using neurite orientation dispersion and density imaging (NODDI), we explored the associations between microarchitecture abnormalities of focal lesions and normal-appearing (NA) tissues and cognitive impairment in patients with MS (PwMS).

NODDI discloses early changes in the normal appearing white matter in paediatric multiple sclerosis

Paediatric-onset multiple sclerosis (PedMS) is characterized by high degree of brain inflammation and rapid accumulation of white and grey matter damage. Abnormalities in the normal appearing white matter (NAWM) and their clinical relevance in PedMS were investigated by Neurite Orientation Dispersion and Density Imaging (NODDI).