Neurite Orientation Dispersion And Density Imaging Metrics Research Articles

Neurite orientation dispersion and density imaging reveals abnormal white matter and glymphatic function in active young boxers

AbstractThe neurological effects and underlying pathophysiological mechanisms of sports‐related concussion (SRC) in active young boxers remain poorly understood. This study aims to investigate the impairment of white matter microstructure and assess changes in glymphatic function following SRC by utilizing neurite orientation dispersion and density imaging (NODDI) on young boxers who have sustained SRC. A total of 60 young participants were recruited, including 30 boxers diagnosed with SRC and 30 healthy individuals engaging in regular exercise. The assessment of whole‐brain white matter damage was conducted using diffusion metrics, while the evaluation of glymphatic function was performed through diffusion tensor imaging (DTI) analysis along the perivascular space (DTI‐ALPS) index. A two‐sample t‐test was utilized to examine group differences in DTI and NODDI metrics. Spearman correlation and generalized linear mixed models were employed to investigate the relationship between clinical assessments of SRC and NODDI measurements. Significant alterations were observed in DTI and NODDI metrics among young boxers with SRC. Additionally, the DTI‐ALPS index in the SRC group exhibited a significantly higher value than that of the control group (left side: 1.58 vs. 1.48, PFDR = 0.009; right side: 1.61 vs. 1.51, PFDR = 0.02). Moreover, it was observed that the DTI‐ALPS index correlated with poorer cognitive test results among boxers in this study population. Repetitive SRC in active young boxers is associated with diffuse white matter injury and glymphatic dysfunction, highlighting the detrimental impact on brain health. These findings highlight the importance of long‐term monitoring of the neurological health of boxers.

Influences of amyloid-β and tau on white matter neurite alterations in dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer’s disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models. We evaluated the associations of tau and amyloid-β with DTI and NODDI parameters and examined the correlations of AD-related white matter injury with Clinical Dementia Rating (CDR). Structural equation models (SEM) explored relationships among age, APOE ε4, amyloid-β, tau, and white matter injury. The DLB spectrum group exhibited widespread white matter abnormalities, including reduced fractional anisotropy, increased mean diffusivity, and decreased neurite density index. Tau was significantly associated with limbic and temporal white matter injury, which was, in turn, associated with worse CDR. SEM revealed that amyloid-β exerted indirect effects on white matter injury through tau. We observed widespread disruptions in white matter tracts in DLB that were not attributed to AD pathologies, likely due to α-synuclein-related injury. However, a fraction of the white matter injury could be attributed to AD pathology. Our findings underscore the impact of AD pathology on white matter integrity in DLB and highlight the utility of NODDI in elucidating the biological basis of white matter injury in DLB.

White Matter Alterations in Military Service Members With Remote Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is the signature injury experienced by military service members and is associated with poor neuropsychiatric outcomes. Yet, there is a lack of reliable clinical tools for mTBI diagnosis and prognosis. To examine the white matter microstructure and neuropsychiatric outcomes of service members with a remote history of mTBI (ie, mTBI that occurred over 2 years ago) using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). This case-control study examined 98 male service members enrolled in a study at the National Intrepid Center of Excellence. Eligible participants were active duty status or able to enroll in the Defense Enrollment Eligibility Reporting system, ages 18 to 60 years, and had a remote history of mTBI; controls were matched by age. Remote history of mTBI. White matter microstructure was assessed using a region-of-interest approach of skeletonized diffusion images, including DTI (fractional anisotropy, mean diffusivity, radial diffusivity and axial diffusivity) and NODDI (orientation dispersion index [ODI], isotropic volume fraction, intra-cellular volume fraction). Neuropsychiatric outcomes associated with posttraumatic stress disorder (PTSD) and postconcussion syndrome were assessed. A total of 65 male patients with a remote history of mTBI (mean [SD] age, 40.5 [5.0] years) and 33 age-matched male controls (mean [SD] age, 38.9 [5.6] years) were included in analysis. Compared with the control cohort, the 65 service members with mTBI presented with significantly more severe PTSD-like symptoms (mean [SD] PTSD CheckList-Civilian [PCL-C] version scores: control, 19.0 [3.8] vs mTBI, 41.2 [11.6]; P < .001). DTI and NODDI metrics were altered in the mTBI group compared with the control, including intra-cellular volume fraction of the right cortico-spinal tract (β = -0.029, Cohen d = 0.66; P < .001), ODI of the left posterior thalamic radiation (β = -0.006, Cohen d = 0.55; P < .001), and ODI of the left uncinate fasciculus (β = 0.013, Cohen d = 0.61; P < .001). In service members with mTBI, fractional anisotropy of the left uncinate fasciculus was associated with postconcussion syndrome (β = 5.4 × 10-3; P = .003), isotropic volume fraction of the genu of the corpus callosum with PCL-C (β = 4.3 × 10-4; P = .01), and ODI of the left fornix and stria terminalis with PCL-C avoidance scores (β = 1.2 × 10-3; P = .02). In this case-control study of military-related mTBI, the results suggest that advanced magnetic resonance imaging techniques using NODDI can reveal white matter microstructural alterations associated with neuropsychiatric symptoms in the chronic phase of mTBI. Diffusion trends observed throughout widespread white matter regions-of-interest may reflect mechanisms of neurodegeneration as well as postinjury tissue scarring and reorganization.

Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study.

Multi-shell diffusion Magnetic Resonance Imaging (dMRI) data has been widely used to characterise white matter microstructure in several neurodegenerative diseases. The lack of standardised dMRI protocols often implies the acquisition of redundant measurements, resulting in prolonged acquisition times. In this study, we investigate the impact of the number of gradient directions on Diffusion Tensor Imaging (DTI) and on Neurite Orientation Dispersion and Density Imaging (NODDI) metrics. Data from 124 healthy controls collected in three different longitudinal studies were included. Using an in-house algorithm, we reduced the number of gradient directions in each data shell. We estimated DTI and NODDI measures on six white matter bundles clinically relevant for neurodegenerative diseases. Fractional Anisotropy (FA) measures on bundles where data were sampled at the 30% rate, showed a median L1 distance of up to 3.92% and a 95% CI of (1.74, 8.97)% when compared to those obtained at reference sampling. Mean Diffusivity (MD) reached up to 4.31% and a 95% CI of (1.60, 16.98)% on the same premises. At a sampling rate of 50%, we obtained a median of 3.90% and a 95% CI of (1.99, 16.65)% in FA, and 5.49% with a 95% CI of (2.14, 21.68)% in MD. The Intra-Cellular volume fraction (ICvf) median L1 distance was up to 2.83% with a 95% CI of (1.98, 4.82)% at a 30% sampling rate and 3.95% with a 95% CI of (2.39, 7.81)% at a 50% sampling rate. The volume difference of the reconstructed white matter at reference and 50% sampling reached a maximum of (2.09 ± 0.81)%. In conclusion, DTI and NODDI measures reported at reference sampling were comparable to those obtained when the number of dMRI volumes was reduced by up to 30%. Close to reference DTI and NODDI metrics were estimated with a significant reduction in acquisition time using three shells, respectively with: 4 directions at a b value of 700 s/mm2, 14 at 1000 s/mm2, and 32 at 2000 s/mm2. The study revealed aspects that can be important for large-scale clinical studies on bundle-specific diffusion MRI.

Neurite orientation dispersion and density imaging quantifies microstructural impairment in the thalamus and its connectivity in amyotrophic lateral sclerosis.

To evaluate microstructural impairment in the thalamus and thalamocortical connectivity using neurite orientation dispersion and density imaging (NODDI) in amyotrophic lateral sclerosis (ALS). This study included 47 healthy controls and 43 ALS patients, whose structural and diffusion-weighted data were collected. We used state-of-the-art parallel transport tractography to identify thalamocortical pathways in individual spaces. Thalamus was then parcellated into six subregions based on its connectivity pattern with the priori defined cortical (i.e., prefrontal/motor/somatosensory/temporal/posterior-parietal/occipital) regions. For each of the thalamic and cortical subregions and thalamo-cortical tracts, we compared the following NODDI metrics between groups: orientation dispersion index (ODI), neurite density index (NDI), and isotropic volume fraction (ISO). We also used these metrics to conduct receiver operating characteristic curve (ROC) analyses and Spearman correlation. In ALS patients, we found decreased ODI and increased ISO in the thalamic subregion connecting the left motor cortex and other extramotor (e.g., somatosensory and occipital) cortex (Bonferroni-corrected p < 0.05). NDI decreased in the bilateral thalamo-motor and thalamo-somatosensory tracts and in the right thalamo-posterior-parietal and thalamo-occipital tracts (Bonferroni-corrected p < 0.05). NDI reduction in the bilateral thalamo-motor tract (p = 0.017 and 0.009) and left thalamo-somatosensory tract (p = 0.029) was correlated with disease severity. In thalamo-cortical tracts, NDI yielded a higher effect size during between-group comparisons and a greater area under ROC (p < 0.05) compared with conventional diffusion tensor imaging metrics. Microstructural impairment in the thalamus and thalamocortical connectivity is the hallmark of ALS. NODDI improved the detection of disrupted thalamo-cortical connectivity in ALS.

Combined assessment of progressive apraxia of speech brain microstructure by diffusion tensor imaging tractography and multishell neurite orientation dispersion and density imaging.

Progressive apraxia of speech (PAOS) is characterized by difficulties with motor speech programming and planning. PAOS targets gray matter (GM) and white matter (WM) microstructure that can be assessed using diffusion tensor imaging (DTI) and multishell applications, such as neurite orientation dispersion and density imaging (NODDI). In this study, we aimed to apply DTI and NODDI to add further insight into PAOS tissue microstructure. Twenty-two PAOS patients and 26 age- and sex-matched controls, recruited by the Neurodegenerative Research Group (NRG) at Mayo Clinic, underwent diffusion MRI on 3T MRI. Brain maps of fractional anisotropy (FA) and mean diffusivity (MD) from DTI and intracellular volume fraction (ICVF) and isotropic volume fraction (IsoVF) from NODDI were generated. Global WM and GM, and specific WM tracts were identified using tractography and lobar GM regions. Global WM differences between PAOS and controls were greatest for ICVF, and global GM differences were greatest for MD and IsoVF. Abnormalities in key WM tracts involved in PAOS, including the body of the corpus callosum and frontal aslant tract, were identified with FA, MD, and ICVF, with excellent differentiation of PAOS from controls (area under the receiver operating characteristic curves >.90). MD and ICVF identified abnormalities in arcuate fasciculus, thalamic radiations, and corticostriatal tracts. Significant correlations were identified between an index of articulatory errors and DTI and NODDI metrics from the arcuate fasciculus, frontal aslant tract, and inferior longitudinal fasciculus. DTI and NODDI represent different aspects of brain tissue microstructure, increasing the number of potential biomarkers for PAOS.

Neurite-based white matter alterations in MAPT mutation carriers: A multi-shell diffusion MRI study in the ALLFTD consortium

We assessed white matter (WM) integrity in MAPT mutation carriers (16 asymptomatic, 5 symptomatic) compared to 31 non-carrier family controls using diffusion tensor imaging (DTI) (fractional anisotropy; FA, mean diffusivity; MD) and neurite orientation dispersion and density imaging (NODDI) (neurite density index; NDI, orientation and dispersion index; ODI). Linear mixed-effects models accounting for age and family relatedness revealed alterations across DTI and NODDI metrics in all mutation carriers and in symptomatic carriers, with the most significant differences involving fronto-temporal WM tracts. Asymptomatic carriers showed higher entorhinal MD and lower cingulum FA and patterns of higher ODI mostly involving temporal areas and long association and projections fibers. Regression models between estimated time to or time from disease and DTI and NODDI metrics in key regions (amygdala, cingulum, entorhinal, inferior temporal, uncinate fasciculus) in all carriers showed increasing abnormalities with estimated time to or time from disease onset, with FA and NDI showing the strongest relationships. Neurite-based metrics, particularly ODI, appear to be particularly sensitive to early WM involvement in asymptomatic carriers.

Medial temporal lobe gray matter microstructure alterations provide improved sensitivity to detect neurodegeneration associated with Alzheimer’s disease biomarkers

AbstractBackgroundDespite the strengths conventional structural imaging measures to detect atrophy, cross‐sectional relationships between neurodegeneration and Alzheimer’s disease (AD) biomarkers in early stages is limited. Neurite orientation dispersion and density imaging (NODDI) measures microstructural alterations that are unique from conventional structural metrics. Alterations in microstructure have been detected in individuals with AD compared to cognitively normal individuals, but there is sparse data regarding the relationship between these metrics and AD biomarkers. Here we sought to characterize how NODDI metrics in the medial temporal lobe (MTL) are associated with plasma AD biomarkers.MethodOne‐hundred and sixty‐seven cognitively normal (CN) individuals, 47 individuals with mild cognitive impairment, and 16 individuals with AD underwent diffusion and T1w imaging. T1w images were segmented using the ASHS‐T1 protocol to form anterior and posterior MTL ROIs. Multi‐shell DTI data were collected in 113 non‐collinear directions with 1.5mm isotropic voxels, were pre‐processed using a custom pipeline, and fit with voxel‐wise NODDI models. ANTs was used to linearly register NODDI and T1w images to allow transformation of MTL ROIs to diffusion space. Stepwise‐regression models examined relationships between anterior and posterior MTL NODDI metrics with plasma biomarkers in CN and impaired (MCI/AD) groups after accounting for MTL volume.ResultNODDI metrics of intracellular volume fraction (icVf) and orientation dispersion index (ODI) were decreased, and isometric volume fraction (isoVf) was increased in cognitively impaired compared to CN. Amyloid positivity was associated with decreased ODI and increased isoVf in cognitively impaired individuals. While posterior MTL volume predicted plasma p‐Tau‐181, inclusion of NODDI metrics subsumed this effect (F‐change&gt;7.54, p&lt;0.0067), and reduced ODI was the best predictor of plasma pTau‐181 within cognitively impaired individuals, while isoVf best predicted pTau‐181 across all individuals. Posterior MTL volume did not predict plasma GFAP, but inclusion of ODI and icVf both significantly predicted plasma GFAP in both CN and impaired individuals (F‐change&gt;12.68, p&lt;.001). Anterior MTL icVf predicted both pTau‐181 and GFAP.ConclusionMicrostructural alterations measured by NODDI appear more closely linked to AD‐related molecular measures and, thus, may provide a more sensitive cross‐sectional measure of neurodegeneration of the MTL compared to conventional macrostructural metrics.

Medial temporal lobe gray matter microstructure alterations provide improved sensitivity to detect neurodegeneration associated with Alzheimer’s disease biomarkers

AbstractBackgroundDespite the strengths conventional structural imaging measures to detect atrophy, cross‐sectional relationships between neurodegeneration and Alzheimer’s disease (AD) biomarkers in early stages is limited. Neurite orientation dispersion and density imaging (NODDI) measures microstructural alterations that are unique from conventional structural metrics. Alterations in microstructure have been detected in individuals with AD compared to cognitively normal individuals, but there is sparse data regarding the relationship between these metrics and AD biomarkers. Here we sought to characterize how NODDI metrics in the medial temporal lobe (MTL) are associated with plasma AD biomarkers.MethodOne‐hundred and sixty‐seven cognitively normal (CN) individuals, 47 individuals with mild cognitive impairment, and 16 individuals with AD underwent diffusion and T1w imaging. T1w images were segmented using the ASHS‐T1 protocol to form anterior and posterior MTL ROIs. Multi‐shell DTI data were collected in 113 non‐collinear directions with 1.5mm isotropic voxels, were pre‐processed using a custom pipeline, and fit with voxel‐wise NODDI models. ANTs was used to linearly register NODDI and T1w images to allow transformation of MTL ROIs to diffusion space. Stepwise‐regression models examined relationships between anterior and posterior MTL NODDI metrics with plasma biomarkers in CN and impaired (MCI/AD) groups after accounting for MTL volume.ResultNODDI metrics of intracellular volume fraction (icVf) and orientation dispersion index (ODI) were decreased, and isometric volume fraction (isoVf) was increased in cognitively impaired compared to CN. Amyloid positivity was associated with decreased ODI and increased isoVf in cognitively impaired individuals. While posterior MTL volume predicted plasma p‐Tau‐181, inclusion of NODDI metrics subsumed this effect (F‐change&gt;7.54, p&lt;0.0067), and reduced ODI was the best predictor of plasma pTau‐181 within cognitively impaired individuals, while isoVf best predicted pTau‐181 across all individuals. Posterior MTL volume did not predict plasma GFAP, but inclusion of ODI and icVf both significantly predicted plasma GFAP in both CN and impaired individuals (F‐change&gt;12.68, p&lt;.001). Anterior MTL icVf predicted both pTau‐181 and GFAP.ConclusionMicrostructural alterations measured by NODDI appear more closely linked to AD‐related molecular measures and, thus, may provide a more sensitive cross‐sectional measure of neurodegeneration of the MTL compared to conventional macrostructural metrics.

Associations between accelerometer‐based physical activity and brain white matter microstructure: Findings from the population‐based Rhineland Study

AbstractBackgroundWhite matter (WM) integrity declines with age and is affected by neurodegenerative diseases. Physical activity promotes neuronal health in animals, and is associated with WM microstructure metrics in humans. However, previous diffusion tensor imaging (DTI) studies were limited by small sample sizes and subjective questionnaire‐based physical activity assessments. Moreover, recently introduced neurite orientation dispersion and density imaging (NODDI) may offer complementary insights. Therefore, we examined the association between accelerometer‐based physical activity and DTI and NODDI measures of WM microstructure in a large population‐based cohort.MethodWe analyzed data of 2,455 participants (57.9% women, mean age: 54.7 years) with valid physical activity and MRI measurements from the Rhineland Study, a prospective cohort study in Bonn, Germany. We recorded physical activity using accelerometers and derived metabolic equivalent (MET)‐hours, step counts and time spent performing sedentary, light‐intensity and moderate‐to‐vigorous (MVPA) activities. DTI (fractional anisotropy (FA), mean diffusivity) and NODDI (orientation dispersion index, neurite density index) measures were obtained from 3T MR images using the microstructure diffusion toolbox. The association of physical activity with WM microstructure was assessed using multivariate polynomial regression, while adjusting for age, sex, education, body mass index and smoking status.ResultPhysical activity was associated with several global and tract‐specific DTI and NODDI measures. Effects were strongest at low physical activity quantities and weakened at higher levels. While higher MET‐hours, step counts and light and moderate‐to‐vigorous intensity activities were related to greater global FA, sedentary time was associated with reduced FA. We observed the strongest tract‐specific effects for moderate‐to‐vigorous intensity activities on the corpus callosum and corona radiata (standardized effects: MVPA on FA corpus callosum, ßlin = 0.0009 [95% CI: 0.0001; 0.0018] and ßqu = ‐0.0006 [95% CI: ‐0.0011; ‐0.0001]; MVPA on FA corona radiata, ßlin = 0.0011 [95% CI: 0.0001; 0.0021] and ßqu = ‐0.0009 [95% CI: ‐0.0014; ‐0.0003]). We obtained similar results for NODDI measures.ConclusionOur findings suggest that WM microstructure and particularly tracts connecting motor regions profit from physical activity. Sedentary individuals may benefit more from additional physical activity than already active individuals. NODDI metrics provide valuable complementary insights into the effects of physical activity on WM microstructure.

Locus coeruleus microstructural integrity is linked to plasma GFAP concentration and Aβ42/40 ratio in cognitively unimpaired individuals: a 7T MRI study

AbstractBackgroundRecent autopsy and in vivo MRI studies supported structural integrity of the brainstem locus coeruleus (LC) as a potential indicator of initial AD‐related pathological processes. Importantly, in the earliest stages of the disease, these changes to the neuronal density of the LC are associated with changes to the somatic morphology and dendritic atrophy. Here, we aimed to examine whether LC microstructural integrity, assessed in vivo with advanced diffusion‐weighted magnetic resonance imaging (dMRI), is related to plasma AD biomarkers in a sample of cognitively unimpaired individuals.MethodFifty‐seven cognitively unimpaired participants (mean age = 59.3±14.7y; 28 females) (Table 1) underwent a dMRI scanning session using a multi‐shell, high angular resolution acquisition protocol in a 7T scanner. LC microstructure was evaluated by applying the Neurite Orientation Dispersion and Density Imaging (NODDI) biophysical model on the dMRI data, yielding two metrics of microstructural integrity: Neurite Density Index (NDI) and Orientation Dispersion Index (ODI). Additionally, blood samples were analyzed to assess AD plasma biomarkers, including Aβ42/40 ratio, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), and tau phosphorylated at threonine 181 (pTau181) or threonine 231 (pTau231).ResultHigher age was associated with lower LC ODI (t = ‐2.77, p = 0.008) but not LC NDI values (t = 0.44, p = 0.658). Multiple linear regressions adjusted for age, sex, and estimated Total Intracranial Volume (eTIV) showed that lower NDI in the LC was associated with higher plasma GFAP levels (t = ‐2.08, p = .04, Figure 1). In addition, we found a negative association between ODI within the LC and Aβ42/40 (t = ‐2.79, p = .007, Figure 2). No significant relationships were found between LC NDI/ODI values and plasma NfL or pTau biomarkers.ConclusionConsistent with animal studies, these findings suggest that microstructural changes in the LC are associated with astroglial activation in the earliest stages of the disease. Associations with Aβ42/40 were unexpected but might reflect loss of white matter compartments or changes in lipid density. In future analyses, we will further examine the biological interpretation of the NODDI metrics in subcortical regions, in particular in the context of AD‐related processes.

Evidence of Ongoing Cerebral Microstructural Reorganization in Children With Persisting Symptoms Following Mild Traumatic Brain Injury: A NODDI DTI Analysis.

Approximately 300-550 children per 100,000 sustain a mild traumatic brain injury (mTBI) each year, of whom ∼25-30% have long-term cognitive problems. Following mTBI, free water (FW) accumulation occurs in white matter (WM) tracts. Diffusion tensor imaging (DTI) can be used to investigate structural integrity following mTBI. Compared with conventional DTI, neurite orientation dispersion and density imaging (NODDI) orientation dispersion index (ODI) and fraction of isolated free water (FISO) metrics may allow a more advanced insight into microstructural damage following pediatric mTBI. In this longitudinal study, we used NODDI to explore whole-brain and tract-specific differences in ODI and FISO in children with persistent symptoms after mTBI (n = 80) and in children displaying clinical recovery (n = 32) at 1 and 2-3 months post-mTBI compared with healthy controls (HCs) (n = 21). Two-way repeated measures analysis of variance (ANOVA) and voxelwise two-sample t tests were conducted to compare whole-brain and tract-specific diffusion across groups. All results were corrected at positive false discovery rate (pFDR) <0.05. We also examined the association between NODDI metrics and clinical outcomes, using logistical regression to investigate the value of NODDI metrics in predicting future recovery from mTBI. Whole-brain ODI was significantly increased in symptomatic participants compared with HCs at both 1 and 2 months post-injury, where the uncinate fasciculus (UF) and inferior fronto-occipital fasciculus (IFOF) were particularly implicated. Using region of interest (ROI) analysis in significant WM, bilateral IFOF and UF voxels, symptomatic participants had the highest ODI in all ROIs. ODI was lower in asymptomatic participants, and HCs had the lowest ODI in all ROIs. No changes in FISO were found across groups or over time. WM ODI was moderately correlated with a higher youth-reported post-concussion symptom inventory (PCSI) score. With 87% predictive power, ODI (1 month post-injury) and clinical predictors (age, sex, PCSI score, attention scores) were a more sensitive predictor of recovery at 2-3 months post-injury than fractional anisotropy (FA) and clinical predictors, or clinical predictors alone. FISO could not predict recovery at 2-3 months post-injury. Therefore, we found that ODI was significantly increased in symptomatic children following mTBI compared with HCs at 1 month post-injury, and progressively decreased over time alongside clinical recovery. We found no significant differences in FISO between groups or over time. WM ODI at 1 month was a more sensitive predictor of clinical recovery at 2-3 months post-injury than FA, FISO, or clinical measures alone. Our results show evidence of ongoing microstructural reorganization or neuroinflammation between 1 and 2-3 months post-injury, further supporting delayed return to play in children who remain symptomatic. We recommend future research examining the clinical utility of NODDI following mTBI to predict recovery or persistence of post-concussion symptoms and thereby inform management of mTBI.

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

BackgroundAlzheimer’s disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical.MethodsParticipants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination).ResultsUsing internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone.ConclusionUsing a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.

Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging.

Core symptoms of autism-spectrum disorder (ASD) have been associated with prefrontal cortex abnormalities. However, the mechanisms behind the observation remain incomplete, partially due to the challenges of modeling complex gray matter (GM) structures. This study aimed to identify GM microstructural alterations in adults with ASD using neurite orientation dispersion and density imaging (NODDI) and voxel-wise GM-based spatial statistics (GBSS) to reduce the partial volume effects from the white matter and cerebrospinal fluid. A total of 48 right-handed participants were included, of which 22 had ASD (17 men; mean age, 34.42 ± 8.27 years) and 26 were typically developing (TD) individuals (14 men; mean age, 32.57 ± 9.62 years). The metrics of NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) were compared between groups using GBSS. Diffusion tensor imaging (DTI) metrics and surface-based cortical thickness were also compared. The associations between magnetic resonance imaging-based measures and ASD-related scores, including ASD-spectrum quotient, empathizing quotient, and systemizing quotient were also assessed in the region of interest (ROI) analysis. After controlling for age, sex, and intracranial volume, GBSS demonstrated significantly lower NDI in the ASD group than in the TD group in the left prefrontal cortex (caudal middle frontal, lateral orbitofrontal, pars orbitalis, pars triangularis, rostral middle frontal, and superior frontal region). In the ROI analysis of individuals with ASD, a significantly positive correlation was observed between the NDI in the left rostral middle frontal, superior frontal, and left frontal pole and empathizing quotient score. No significant between-group differences were observed in all DTI metrics, other NODDI (i.e., ODI and ISOVF) metrics, and cortical thickness. GBSS analysis was used to demonstrate the ability of NODDI metrics to detect GM microstructural alterations in adults with ASD, while no changes were detected using DTI and cortical thickness evaluation. Specifically, we observed a reduced neurite density index in the left prefrontal cortices associated with reduced empathic abilities.

Comparison of different neurite density metrics with brain asymmetry evaluation

The standard diffusion MRI model with intra- and extra-axonal water pools offers a set of microstructural parameters describing brain white matter architecture. However, non-linearities in the standard model and diffusion data contamination by noise and imaging artefacts make estimation of diffusion metrics challenging. In order to develop reliable diffusion approaches and to avoid computational model degeneracy, additional theoretical assumptions allowing stable numerical implementations are required. Advanced diffusion approaches allow for estimation of intra-axonal water fraction (AWF), describing a key structural characteristic of brain tissue. AWF can be interpreted as an indirect measure or proxy of neurite density and has a potential as useful clinical biomarker. Established diffusion approaches such as white matter tract integrity, neurite orientation dispersion and density imaging (NODDI), and spherical mean technique provide estimates of AWF within their respective theoretical frameworks. In the present study, we estimated AWF metrics using different diffusion approaches and compared measures of brain asymmetry between the different metrics in a sub-sample of 182 subjects from the UK Biobank. Multivariate decomposition by mean of linked independent component analysis revealed that the various AWF proxies derived from the different diffusion approaches reflect partly non-overlapping variance of independent components, with distinct anatomical distributions and sensitivity to age. Further, voxel-wise analysis revealed age-related differences in AWF-based brain asymmetry, indicating less apparent left-right hemisphere difference with higher age. Finally, we demonstrated that NODDI metrics suffer from a quite strong dependence on used numerical algorithms and post-processing pipeline. The analysis based on AWF metrics strongly depends on the used diffusion approach and leads to poorly reproducible results.

Corticospinal fibers with different origins impair in amyotrophic lateral sclerosis: A neurite orientation dispersion and density imaging study.

To investigate microstructural impairments of corticospinal tracts (CSTs) with different origins in amyotrophic lateral sclerosis (ALS) using neurite orientation dispersion and density imaging (NODDI). Diffusion-weighted imaging data acquired from 39 patients with ALS and 50 controls were used to estimate NODDI and diffusion tensor imaging (DTI) models. Fine maps of CST subfibers originating from the primary motor area (M1), premotor cortex, primary sensory area, and supplementary motor area (SMA) were segmented. NODDI metrics (neurite density index [NDI] and orientation dispersion index [ODI]) and DTI metrics (fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) were computed. The patients with ALS showed microstructural impairments (reflected by NDI, ODI, and FA reductions and MD, AD, and RD increases) in CST subfibers, especially in M1 fibers, which correlated with disease severity. Compared with other diffusion metrics, NDI yielded a higher effect size and detected the greatest extent of CST subfibers damage. Logistic regression analyses based on NDI in M1 subfiber yielded the best diagnostic performance compared with other subfibers and the whole CST. Microstructural impairment of CST subfibers (especially those originating from M1) is the key feature of ALS. The combination of NODDI and CST subfibers analysis may improve diagnosing performance for ALS.

Dystonia is Associated with Macro and Microstructural Abnormalities of the Cerebellum: Analysis of Volumetric and Diffusion-Weighted MRI Data in the UK Biobank (P11-11.004)

<h3>Objective:</h3> To determine whether subjects with dystonia in the UK Biobank exhibit MRI-based cerebellar pathology. <h3>Background:</h3> Dystonia is a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal movements and/or postures. Although classically considered a basal-ganglia disorder, neuroimaging studies of dystonia have revealed physiologic, structural, and functional changes in both the (1) pallido-thalamic and (2) cerebello-thalamic networks. Diffusion-weighted-MRI (DWI) analyses of both networks in dystonia have revealed differences in non-specific Diffusion-Tensor metrics such as Fractional Anisotropy. However newer DWI models, such as Neurite Orientation Dispersion and Density Imaging (NODDI), assess more specific and biologically relevant white-matter properties. <h3>Design/Methods:</h3> Using the UK Biobank, 23 subjects with isolated dystonia and diffusion-MRI data were identified, along with 69 control subjects without neurologic (ICD10 G-coded) diagnoses, matched (1:3) on age, sex, imaging site, and medical comorbidities relevant to white-matter integrity (hypertension, hyperlipidemia, and diabetes). Two DTI metrics (mean diffusivity and fractional anisotropy) and three NODDI metrics (intracellular volume fraction, isotropic volume fraction, and orientation dispersion) were extracted from each of four tracts (inferior, middle, and superior cerebellar peduncles, and superior thalamic radiations). Volumetric data consisted of cerebellar (15 regions), basal ganglia (3 regions), and whole-brain grey and white-matter volumes. <h3>Results:</h3> After correcting for multiple-comparisons (40 volumetric and 35 diffusion-related) using the Benjamini-Hochberg procedure (FDR = 0.05), intracellular-volume-fraction (ICVF) of the middle- and superior-cerebellar peduncles was significantly lower in subjects with dystonia, suggesting reduced axon density; volumetric analysis showed significantly reduced volumes of the motor cerebellum (lobules VI and VIII). There were no differences in basal ganglia, cortical, or whole-brain volumes. <h3>Conclusions:</h3> These findings support the hypothesis that abnormalities of cerebellar networks contribute to the pathogenesis of dystonia. <b>Disclosure:</b> Dr. Mason has nothing to disclose. Miss Haddad has nothing to disclose. The institution of Neda Jahanshad has received research support from Biogen Inc.

Hemispheric lateralization of white matter microstructure in children and its potential role in sensory processing dysfunction.

Diffusion tensor imaging (DTI) studies have demonstrated white matter microstructural differences between the left and right hemispheres of the brain. However, the basis of these hemispheric asymmetries is not yet understood in terms of the biophysical properties of white matter microstructure, especially in children. There are reports of altered hemispheric white matter lateralization in ASD; however, this has not been studied in other related neurodevelopmental disorders such as sensory processing disorder (SPD). Firstly, we postulate that biophysical compartment modeling of diffusion MRI (dMRI), such as Neurite Orientation Dispersion and Density Imaging (NODDI), can elucidate the hemispheric microstructural asymmetries observed from DTI in children with neurodevelopmental concerns. Secondly, we hypothesize that sensory over-responsivity (SOR), a common type of SPD, will show altered hemispheric lateralization relative to children without SOR. Eighty-seven children (29 females, 58 males), ages 8-12 years, presenting at a community-based neurodevelopmental clinic were enrolled, 48 with SOR and 39 without. Participants were evaluated using the Sensory Processing 3 Dimensions (SP3D). Whole brain 3 T multi-shell multiband dMRI (b = 0, 1,000, 2,500 s/mm2) was performed. Tract Based Spatial Statistics were used to extract DTI and NODDI metrics from 20 bilateral tracts of the Johns Hopkins University White-Matter Tractography Atlas and the lateralization Index (LI) was calculated for each left-right tract pair. With DTI metrics, 12 of 20 tracts were left lateralized for fractional anisotropy and 17/20 tracts were right lateralized for axial diffusivity. These hemispheric asymmetries could be explained by NODDI metrics, including neurite density index (18/20 tracts left lateralized), orientation dispersion index (15/20 tracts left lateralized) and free water fraction (16/20 tracts lateralized). Children with SOR served as a test case of the utility of studying LI in neurodevelopmental disorders. Our data demonstrated increased lateralization in several tracts for both DTI and NODDI metrics in children with SOR, which were distinct for males versus females, when compared to children without SOR. Biophysical properties from NODDI can explain the hemispheric lateralization of white matter microstructure in children. As a patient-specific ratio, the lateralization index can eliminate scanner-related and inter-individual sources of variability and thus potentially serve as a clinically useful imaging biomarker for neurodevelopmental disorders.

Neurite Orientation Dispersion and Density Imaging in Multiple Sclerosis: A Systematic Review.

Diffusion-weighted imaging has been applied to investigate alterations in multiple sclerosis (MS). In the last years, advanced diffusion models were used to identify subtle changes and early lesions in MS. Among these models, neurite orientation dispersion and density imaging (NODDI) is an emerging approach, quantifying specific neurite morphology in both grey (GM) and white matter (WM) tissue and increasing the specificity of diffusion imaging. In this systematic review, we summarized the NODDI findings in MS. A search was conducted on PubMed, Scopus, and Embase, which yielded a total number of 24 eligible studies. Compared to healthy tissue, these studies identified consistent alterations in NODDI metrics involving WM (neurite density index), and GM lesions (neurite density index), or normal-appearing WM tissue (isotropic volume fraction and neurite density index). Despite some limitations, we pointed out the potential of NODDI in MS to unravel microstructural alterations. These results might pave the way to a deeper understanding of the pathophysiological mechanism of MS. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.

Altered isotropic volume fraction in gray matter after sleep deprivation and its association with visuospatial memory: A neurite orientation dispersion and density imaging study.

Diffusion magnetic resonance imaging (dMRI) studies have revealed microstructural abnormalities in white matter resulting from sleep deprivation (SD). This study aimed to adopt neurite orientation dispersion and density imaging (NODDI) to investigate the effect of SD on gray matter (GM) microstructural properties and its association to visuospatial memory (VSM). Twenty-four healthy women underwent two sessions of dMRI scanning and visuospatial ability assessment by Complex Figure Test (CFT), once during rested wakefulness (RW) and once after 24 h of SD. We calculated NODDI metrics, including intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISO). Differences in NODDI-related metrics between RW and SD were determined using a voxel-wise paired t-test. We identified an association between NODDI metrics and CFT results using Spearman's correlation coefficient. Sleep deprivation worsened subjects' performance in the delayed-CFT trial. We observed no significant difference in ICVF and ODI between RW and SD. After SD, subjects showed decreases in ISO, primarily in the prefrontal cortex and temporal lobe, while exhibiting ISO increases in the anterior and posterior cerebellar lobe and cerebellar vermis. Furthermore, ISO change in the left superior, middle and inferior frontal gyrus was significantly correlated with completion time change in delayed-CFT trial performance. Our results suggested that SD hardly affected the density and spatial organization of neurites in GM, but the extra-neurite water molecule diffusion process was affected (perhaps resulting from neuroinflammation), which contributed to VSM dysfunction.