Neurite Orientation Dispersion Research Articles

Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort.

We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N=299), mild cognitive impairment (MCI; N=192), or dementia (DEM; N=65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). Plasma biomarkers differed across diagnostic groups (DEM>MCI>CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. Plasma biomarkers differ across diagnostic groups (DEM>MCI>CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.

Probing white matter microstructure in youth with chronic pain and its relation to catastrophizing using neurite orientation dispersion and density imaging.

Chronic pain is common in young people and can have a major life impact. Despite the burden of chronic pain, mechanisms underlying chronic pain development and persistence are still poorly understood. Specifically, white matter (WM) connectivity has remained largely unexplored in pediatric chronic pain. Using diffusion-weighted imaging, this study examined WM microstructure in adolescents (age M = 15.8 years, SD = 2.8 years) with chronic pain (n = 44) compared with healthy controls (n = 24). Neurite orientation dispersion and density imaging modeling was applied, and voxel-based whole-white-matter analyses were used to obtain an overview of potential alterations in youth with chronic pain and tract-specific profile analyses to evaluate microstructural profiles of tracts of interest more closely. Our main findings are that (1) youth with chronic pain showed widespread elevated orientation dispersion compared with controls in several tracts, indicative of less coherence; (2) signs of neurite density tract-profile alterations were observed in several tracts of interest, with mainly higher density levels in patients; and (3) several WM microstructural alterations were associated with pain catastrophizing in the patient group. Implicated tracts include both those connecting cortical and limbic structures (uncinate fasciculus, cingulum, anterior thalamic radiation), which were associated with pain catastrophizing, as well as sensorimotor tracts (corticospinal tract). By identifying alterations in the biologically informative WM microstructural metrics orientation dispersion and neurite density, our findings provide important and novel mechanistic insights for understanding the pathophysiology underlying chronic pain. Taken together, the data support alterations in fiber organization as a meaningful characteristic, contributing process to the chronic pain state.

Assessing brain microstructural changes in chronic kidney disease: a diffusion imaging study using multiple models

ObjectivesTo explore the effectiveness of diffusion quantitative parameters derived from advanced diffusion models in detecting brain microstructural changes in patients with chronic kidney disease (CKD).MethodsThe study comprised 44 CKD patients (eGFR<59 mL/min/1.73 m2) and 35 age-and sex-matched healthy controls. All patients underwent diffusion spectrum imaging (DSI) and conventional magnetic resonance imaging. Reconstructed to obtain diffusion MRI models, including diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI) and Mean Apparent Propagator (MAP)-MRI, were processed to obtain multi-parameter maps. The Tract-Based Spatial Statistics (TBSS) analysis was utilized for detecting microstructural differences and Pearson correlation analysis assessed the relationship between renal metabolism markers and diffusion parameters in the brain regions of CKD patients. Receiver operating characteristic (ROC) curve analysis assessed the diagnostic performance of diffusion models, with AUC comparisons made using DeLong’s method.ResultsSignificant differences were noted in DTI, NODDI, and MAP-MRI parameters between CKD patients and controls (p < 0.05). DTI indicated a decrease in Fractional Anisotropy(FA) and an increase in Mean and Radial Diffusivity (MD and RD) in CKD patients. NODDI indicated decreased Intracellular and increased Extracellular Volume Fractions (ICVF and ECVF). MAP-MRI identified extensive microstructural changes, with elevated Mean Squared Displacement (MSD) and Q-space Inverse Variance (QIV) values, and reduced Non-Gaussianity (NG), Axial Non-Gaussianity (NGAx), Radial Non-Gaussianity (NGRad), Return-to-Origin Probability (RTOP), Return-to-Axis Probability (RTAP), and Return-to-Plane Probability (RTPP). There was a moderate correlation between serum uric acid (SUA) and diffusion parameters in six brain regions (p < 0.05). ROC analysis showed the AUC values of DTI_FA ranged from 0.70 to 0.793. MAP_NGAx in the Retrolenticular part of the internal capsule R reported a high AUC value of 0.843 (p < 0.05), which was not significantly different from other diffusion parameters (p > 0.05).ConclusionThe advanced diffusion models (DTI, NODDI, and MAP-MRI) are promising for detecting brain microstructural changes in CKD patients, offering significant insights into CKD-affected brain areas.

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.

White Matter Hyperintensities and Microstructural Alterations in Contact Sport Athletes from Adolescence to Early Midlife.

Studies have demonstrated associations between cumulative concussion and repetitive head impact exposure (RHI) via contact sports with white matter (WM) alterations later in life. The course of WM changes associated with exposure earlier in the lifespan are unclear. This study investigated alterations in white matter (WM hyperintensity [WMH] volume and microstructural changes) associated with concussion and RHI exposure from adolescence to early midlife, as well as the interaction between exposure and age-cohort (i.e., adolescent/young adult compared to early midlife athlete cohorts) on WM outcomes. Participating football players included an adolescent/young adulthood cohort (n=82; Mage=18.41.7) and an early midlife cohort (37 former collegiate players approximately 15-years removed from sport; Mage=37.71.4). Years of football participation and number of prior concussions were exposures of interest. White matter outcomes included log-transformed manually segmented total WMH volume and neurite orientation dispersion and density imaging metrics of microstructure/organization (isotropic volume fraction[Viso], intra-cellular volume fraction[Vic], and orientation dispersion[OD]). Regression models were fit to test effects of concussion history, years of football participation, and age-cohort by years of football participation with WM outcomes. Spearman's correlations assessed associations between significant WM metrics and measures of cognitive and psychological function. A significant age-cohort by years of participation effect was observed for whole brain white matter OD, B=-0.002, SE=0.001, p=0.001. The interaction was driven by a negative association between years of participation and OD within the younger cohort, B=-0.001, SE=0.0004, p=0.008, whereas a positive association between participation and OD in the early midlife cohort, B=0.001, SE=0.0003, p=0.039, was observed. Follow-up ROI analyses showed significant interaction effects for OD in the body of the corpus callosum, genu of the corpus callosum, cingulum, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, posterior thalamic radiation (ps<0.05). Greater concussion history was significantly associated with greater Viso in the early midlife cohort, B=0.001, SE= 0.0002, p=0.010. Years of participation and concussion history were not associated with WMH volume, ps>0.05. Performance on a measure of executive function was significantly associated with years of participation, =.34, p=.04, and a trend was observed for OD, =.28, p=.09 in the early midlife cohort only. The global characterization of white matter changes associated with years of football participation were broadly similar and stable from adolescence through early midlife (i.e., microstructural alterations, but not macroscopic lesions). An inverse association between years of participation and orientation dispersion across age-cohorts may represent a process of initial recovery/reorganization proximal to sport, followed by later reduction of white matter coherence.

Neuronal microstructural changes in the human brain are associated with neurocognitive aging.

Gray matter (GM) alterations play a role in aging-related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.

Multimodal 7T imaging reveals enhanced functional coupling between salience and frontoparietal networks in young adult tobacco cigarette smokers.

Tobacco cigarette smoking is associated with disrupted brain network dynamics in resting brain networks including the Salience (SN) and Fronto parietal (FPN). Unified multimodal methods [Resting state connectivity analysis, Diffusion Tensor Imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and cortical thickness analysis] were employed to test the hypothesis that the impact of cigarette smoking on the balance among these networks is due to alterations in white matter connectivity, microstructural architecture, functional connectivity and cortical thickness (CT) and that these metrics define fundamental differences between people who smoke and nonsmokers. Multimodal analyses of previously collected 7 Tesla MRI data via the Human Connectome Project were performed on 22 people who smoke (average number of daily cigarettes was 10 ± 5) and 22 age- and sex-matched nonsmoking controls. First, functional connectivity analysis was used to examine SN-FPN-DMN interactions between people who smoke and nonsmokers. The anatomy of these networks was then assessed using DTI and CT analyses while microstructural architecture of WM was analyzed using the NODDI toolbox. Seed-based connectivity analysis revealed significantly enhanced within network [p = 0.001 FDR corrected] and between network functional coupling of the salience and R-frontoparietal networks in people who smoke [p = 0.004 FDR corrected]. The network connectivity was lateralized to the right hemisphere. Whole brain diffusion analysis revealed no significant differences between people who smoke and nonsmokers in Fractional Anisotropy, Mean diffusivity and in neurite orienting and density. There were also no significant differences in CT in the hubs of these networks. Our results demonstrate that tobacco cigarette smoking is associated with enhanced functional connectivity, but anatomy is largely intact in young adults. Whether this enhanced connectivity is pre-existing, transient or permanent is not known. The observed enhanced connectivity in resting state networks may contribute to the maintenance of smoking frequency.

Assessment of white matter microstructure integrity in subacute postconcussive vestibular dysfunction using NODDI

Abstract Vestibular symptoms, such as dizziness and balance impairment, are frequently reported following mild traumatic brain injury (mTBI) and are associated with a protracted recovery, yet the underlying neuroanatomical substrates remain unclear. The present study utilized advanced diffusion MRI (dMRI) techniques including both conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to investigate microstructural white matter integrity in individuals with postconcussive vestibular dysfunction (PCVD) within the subacute injury period (median of 35 days from injury; IQR of 23). Study participants included 23 individuals with subacute PCVD and 37 healthy control subjects who underwent imaging and comprehensive clinical vestibular testing. Between-group voxelwise analysis of differences in white matter revealed areas of higher intra-neurite volume fraction (VIn) and isotropic volume fraction (VIso) within PCVD subjects compared to controls, which involved overlapping regions within the left hemisphere of the brain. Affected areas of higher VIn and VIso included the superior longitudinal fasciculus (SLF) and superior and posterior corona radiata (SCR and PCR, respectively). We examined the relationship between clinical vestibular measures and diffusion metrics including DTI (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD] and axial diffusivity [AD]) and NODDI (intraneurite volume fraction [VIn], isotropic volume fraction [VIso], dispersion anisotropy [DA], orientation dispersion indexTotal/Primary/Secondary [ODIT/P/S]) within 32 regions-of-interest. Clinical vestibular measures included self-reported measures including the Dizziness Handicap Inventory, Visual Vertigo Analog Scale, and Vestibular/Ocular-Motor Screening, as well as objective vestibular testing using the sensory organization test. Significant correlations were found with clinical measures across all diffusion maps (except DA), within various ROIs, including SLF, SCR, and PCR. These results implicate several important association bundles that may potentiate sensory processing dysfunction related to PCVD. Whether these neuroanatomical differences found within the subacute phase of PCVD are in response to injury or represent preexisting structural variations that increase vulnerability to sensory processing dysfunction is unclear and remains an active area of study.

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.

101 Glymphatic System Impairment Associated With Neurocognitive Dysfunction and Alzheimers Biomarkers in Moyamoya Disease

INTRODUCTION: Glymphatic system alterations have been proved to be associated with cognitive dysfunction in Alzheimer’s Disease (AD). The glymphatic pathway has not been elucidated in moyamoya disease (MMD), which was recognized as a chronic hypoperfusion model for AD. METHODS: We prospectively recruited 30 MMD patients and 30 matched healthy controls (HC) from October 2022 to March 2023. Participants underwent neurocognition evaluation, and multimodal magnetic resonance imaging (MRI). AD-related serum biomarkers, as well as correlations among these variables were examined. The glymphatic function was assessed by diffusion tensor image analysis along perivascular space (DTI-ALPS). Whole-brain (white matter and grey matter) volumes were calculated by using 3D T1-weighted MRI. Microstructural changes of white matter (intracellular volume fraction, Vic; orientation dispersion index, OD) were evaluated by neurite orientation dispersion and density imaging (NODDI). RESULTS: Serum Alzheimer’s biomarkers (ApoE, Aβ40, Aβ42, and tau) were significantly elevated and associated with neurocognitive dysfunction in MMD. Lower periventricular ALPS-index was identified in patients with MMD (P &lt; 0.001). The decreased ALPS-index correlated with declined neurocognitive performance of intelligence quotient, attention, and memory, increased levels of serum ApoE, Aβ40, Aβ42, as well as higher periventricular white matter volume and lower periventricular grey matter volume (P &lt; 0.001). Moreover, MMD patients had significantly lower Vic in the white matter and a lower OD in the cortex than HC. CONCLUSIONS: We firstly demonstrated the impaired glymphatic system as assessed by lower ALPS-index in patients with MMD. Glymphatic impairment was associated with AD-related biomarkers and cognitive dysfunction in MMD. These findings suggested that glymphatic disorder may interact with MMD-related pathophysiological processes.

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.

Early Infant Prefrontal Cortical Microstructure Predicts Present and Future Emotionality

BACKGROUNDHigh levels of infant negative emotionality (NE) and low positive emotionality (PE) predict future emotional and behavioral problems. The prefrontal cortex (PFC) supports emotional regulation, with each PFC subregion specializing in specific emotional processes. Neurite Orientation Dispersion and Density Imaging (NODDI) estimates microstructural integrity and myelination via the neurite density index (NDI) and dispersion via the orientation dispersion index (ODI), with potential to more accurately evaluate microstructural alterations in the developing brain. Yet, no study has used these indices to examine associations between PFC microstructure and concurrent or developing infant emotionality. METHODSWe modeled PFC subregional NDI and ODI at 3 months with caregiver-reported infant NE and PE at 3 months (n=61) and at 9 months (n=50), using multivariable and subsequent bivariate regression models. RESULTSThe most robust statistically-significant findings were positive associations among 3-month rACC ODI and cACC NDI and concurrent NE, and 3-month lOFC ODI and prospective NE; and a negative association between 3-month dlPFC ODI and concurrent PE. Multivariate models also revealed that other PFC subregional microstructure measures, and infant and caregiver sociodemographic and clinical factors, predicted infant 3- and 9-month NE and PE. CONCLUSIONSGreater NDI and ODI, reflecting greater microstructural complexity, in PFC regions supporting salience perception (rACC), decision-making (lOFC), action selection (cACC), and attentional processes (dlPFC) might result in greater integration of these subregions with other neural networks, greater attention to salient negative external cues, thus higher NE and/or lower PE. These findings provide potential infant cortical markers of future psychopathology risk.

Quantifying Apathy in Late-Life Depression: Unraveling Neurobehavioral Links through Daily Activity Patterns and Brain Connectivity Analysis

Better understanding apathy in late-life depression (LLD) would help predicting poor prognosis of the disease such as dementia. Actimetry provides an objective and ecological measure of apathy from patients' daily motor activity. We aimed to determine if patterns of motor activity were associated with apathy and brain connectivity in networks underlying goal-directed behaviors. Resting-state functional MRI and diffusion MRI were collected from 38 non-demented LLD subjects. Apathy was evaluated using the diagnostic criteria for apathy, the apathy evaluation scale (AES) and the apathy motivation index (AMI). Functional principal components (fPC) of motor activity were derived from actimetry recordings of 72 hours. Associations between fPC and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPC were identified via the threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry. We found two fPC associated with apathy: mean diurnal activity, negatively associated with AES, and an early chronotype, negatively associated with AMI. Mean diurnal activity was associated with increased connectivity in the default-mode, the cingulo-opercular and the frontoparietal networks, while chronotype was associated with a more heterogenous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs. Our findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in LLD, associated with modified functional connectivity of brain networks underlying goal-directed behaviors.

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.

A framework for optimizing the acquisition protocol multishell diffusion-weighted imaging for multimodel assessment.

Complementary aspects of tissue microstructure can be studied with diffusion-weighted imaging (DWI). However, there is no consensus on how to design a diffusion acquisition protocol for multiple models within a clinically feasible time. The purpose of this study is to provide a flexible framework that is able to optimize the shell acquisition protocol given a set of DWI models. Eleven healthy subjects underwent an extensive DWI acquisition protocol, including 15 candidate shells, ranging from 10 to 3500 s/mm2. The proposed framework aims to determine the optimized acquisition scheme (OAS) with a data-driven procedure minimizing the squared error of model-estimated parameters. We tested the proposed method over five heterogeneous DWI models exploiting both low and high b-values (i.e., diffusion tensor imaging [DTI], free water, intra-voxel incoherent motion [IVIM], diffusion kurtosis imaging [DKI], and neurite orientation dispersion and density imaging [NODDI]). A voxel-level and region of interest (ROI)-level analysis was conducted over the white matter and in 48 fiber bundles, respectively. Results showed that acquiring data for the five abovementioned models via OAS requires 14 min, compared with 35 min for the joint recommended acquisition protocol. The parameters derived from the reference acquisition scheme and the OAS are comparable in terms of estimated values, noise, and tissue contrast. Furthermore, the power analysis showed that the OAS retains the potential sensitivity to group-level differences in the parameters of interest, with the exception of the free water model. Overall, there is a linear correspondence (R2= 0.91) between OAS and reference-derived parameters. In conclusion, the proposed framework optimizes the shell acquisition scheme for a given set of DWI models (i.e., DTI, free water, IVIM, DKI, and NODDI), combining low and high b-values while saving acquisition time.

Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease

Background and purposeA substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD. MethodsThirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5). ResultsStatistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = −0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language. ConclusionThis cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.

Quantifying blood-brain barrier permeability in patients with ischemic stroke using non-contrast MRI

Increased blood-brain barrier permeability (BBBP) after ischemic stroke predisposes patients to hemorrhagic conversion. While altered BBBP can impact patient recovery, it is not routinely assessed during the workup of acute ischemic stroke (AIS). We study the effectiveness of the non-contrast MRI sequences diffusion-prepared pseudocontinuous arterial spin labeling (DP-pCASL) and Neurite Orientation Dispersion and Density Imaging (NODDI) in assessing BBBP and correlating to tissue microstructure after ischemic insult. Twelve patients with AIS were prospectively enrolled to undergo our multimodal MR imaging, which generated the DP-pCASL-derived cerebral blood flow (CBF), arterial transit time (ATT), and water exchange rate (kw) and the NODDI-derived b0, mean diffusivity (MD), orientation dispersion index (ODI), intracellular volume fraction (ICVF), and isotropic volume fraction (ISO) parametric maps. The mean age of the patients was 70.2 ± 14.8 with an average NIHSS of 13.0 (7.3–19.8). MR imaging was performed on average at 53.7 (27.8–93.3) hours from stroke symptom onset. The water exchange rate (kw) of the infarcted area and its contralateral territory were 89.7 min−1 (66.7–121.9) and 89.9 min−1 (65.9–106.0) respectively (p = 0.887). Multivariable linear regression analysis showed that b0, ODI, ISO and mechanical thrombectomy were significant predictors of kw. DP-pCASL and NODDI are promising non-contrast sequences for the routine assessment of BBBP.

High-performance presurgical differentiation of glioblastoma and metastasis by means of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics.

To evaluate the performance of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics in distinguishing between glioblastoma (Gb) and solitary brain metastasis (SBM). In this retrospective study, NODDI images were curated from 109 patients with Gb (n = 57) or SBM (n = 52). Automatically segmented multiple volumes of interest (VOIs) encompassed the main tumor regions, including necrosis, solid tumor, and peritumoral edema. Radiomics features were extracted for each main tumor region, using three NODDI parameter maps. Radiomics models were developed based on these three NODDI parameter maps and their amalgamation to differentiate between Gb and SBM. Additionally, radiomics models were constructed based on morphological magnetic resonance imaging (MRI) and diffusion imaging (diffusion-weighted imaging [DWI]; diffusion tensor imaging [DTI]) for performance comparison. The validation dataset results revealed that the performance of a single NODDI parameter map model was inferior to that of the combined NODDI model. In the necrotic regions, the combined NODDI radiomics model exhibited less than ideal discriminative capabilities (area under the receiver operating characteristic curve [AUC] = 0.701). For peritumoral edema regions, the combined NODDI radiomics model achieved a moderate level of discrimination (AUC = 0.820). Within the solid tumor regions, the combined NODDI radiomics model demonstrated superior performance (AUC = 0.904), surpassing the models of other VOIs. The comparison results demonstrated that the NODDI model was better than the DWI and DTI models, while those of the morphological MRI and NODDI models were similar. The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM. The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM, and radiomics features can be incorporated into the multidimensional phenotypic features that describe tumor heterogeneity. • The neurite orientation dispersion and density imaging (NODDI) radiomics model showed promising performance for preoperative discrimination between glioblastoma and solitary brain metastasis. • Compared with other tumor volumes of interest, the NODDI radiomics model based on solid tumor regions performed best in distinguishing the two types of tumors. • The performance of the single-parameter NODDI model was inferior to that of the combined-parameter NODDI model.

Neurite Orientation Dispersion and Density Imaging (NODDI) of Brain Microstructure in Adolescent Cannabis and Nicotine Use.

Despite evidence suggesting deleterious effects of cannabis and nicotine tobacco product (NTP) use on white matter integrity, there have been limited studies examining white matter integrity among users of both cannabis and nicotine. Further, updated white matter methodology provides opportunities to investigate use patterns on neurite orientation dispersion and density (NODDI) indices and subtle tissue changes related to the intra- and extra-neurite compartment. We aimed to investigate how cannabis and NTP use among adolescents and young adults interacts to impact the white matter integrity microstructure. A total of 221 participants between the ages of 16 and 22 completed the Customary Drinking and Drug Use Record (CDDR) to measure substance use, and underwent a magnetic resonance imaging (MRI) session. Participants were divided into NTP-control and NTP groupings and cannabis-control and cannabis groupings (≥26 NTP/cannabis uses in past 6 months). Tract-Based Spatial Statistics (TBSS) and two-way between-subjects ANOVA investigated the effects of NTP use group, cannabis use group, and their interaction on fractional anisotropy (FA) and NODDI indices while controlling for age and biological sex. NTP use was associated with decreased FA values and increased orientation dispersion in the left anterior capsule. There were no significant effects of cannabis use or the interaction of NTP and cannabis use on white matter outcomes. NTP use was associated with altered white matter integrity in an adolescent and young adult sample. Findings suggest that NTP-associated alterations may be linked to altered fiber tract geometry and dispersed neurite structures versus myelination, as well as differential effects of NTP and cannabis use on white matter structure. Future work is needed to investigate how altered white matter is related to downstream behavioral effects from NTP use.

Neurite Damage in Patients with Migraine.

We examined neurite orientation dispersion and density imaging in patients with migraine. We found that patients with medication overuse headache exhibited lower orientation dispersion than those without. Moreover, orientation dispersion in the body of the corpus callosum was statistically negatively correlated with migraine attack frequencies. These findings indicate that neurite dispersion is damaged in patients with chronic migraine. Our study results indicate the orientation preference of neurite damage in migraine.