Neurite Orientation Dispersion Research Articles

Corpus callosum structural characteristics in very preterm children and adolescents: Developmental trajectory and relationship to cognitive functioning

Previous studies suggest that structural alteration of the corpus callosum, i.e., the largest white matter commissural pathway, occurs after a preterm birth in the neonatal period and lasts across development. The present study aims to unravel corpus callosum structural characteristics across childhood and adolescence in very preterm (VPT) individuals, and their associations with general intellectual, executive and socio-emotional functioning. Neuropsychological assessments, T1-weighted and multi-shell diffusion MRI were collected in 79 VPT and 46 full term controls aged 6–14 years. Volumetric, diffusion tensor and neurite orientation dispersion and density imaging (NODDI) measures were extracted on 7 callosal portions using TractSeg. A multivariate data-driven approach (partial least squares correlation) and a cohort-based age normative modelling approach were used to explore associations between callosal characteristics and neuropsychological outcomes. The VPT and a full-term control groups showed similar trends of white-matter maturation over time, i.e., increase FA and reduced ODI, in all callosal segments, that was associated with increase in general intellectual functioning. However, using a cohort-based age-related normative modelling, findings show atypical pattern of callosal development in the VPT group, with reduced callosal maturation over time that was associated with poorer general intellectual and working memory functioning, as well as with lower gestational age.

The effect of mindfulness-based intervention on neurobehavioural functioning and its association with white-matter microstructural changes in preterm young adolescents

Very preterm (VPT) young adolescents are at high risk of executive, behavioural and socio-emotional difficulties. Previous research has shown significant evidence of the benefits of mindfulness-based intervention (MBI) on these abilities. This study aims to assess the association between the effects of MBI on neurobehavioral functioning and changes in white-matter microstructure in VPT young adolescents who completed an 8-week MBI program. Neurobehavioural assessments (i.e., neuropsychological testing, parents- and self-reported questionnaires) and multi-shell diffusion MRI were performed before and after MBI in 32 VPT young adolescents. Combined diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) measures were extracted on well-defined white matter tracts (TractSeg). A multivariate data-driven approach (partial least squares correlation) was used to explore associations between MBI-related changes on neurobehavioural measures and microstructural changes. The results showed an enhancement of global executive functioning using parent-reported questionnaire after MBI that was associated with a general pattern of increase in fractional anisotropy (FA) and decrease in axonal dispersion (ODI) in white-matter tracts involved in executive processes. Young VPT adolescents with lower gestational age at birth showed the greatest gain in white-matter microstructural changes after MBI.

Changes in white matter microstructure following serial ketamine infusions in treatment resistant depression.

Ketamine produces fast-acting antidepressant effects in treatment resistant depression (TRD). Though prior studies report ketamine-related changes in brain activity in TRD, understanding of ketamine's effect on white matter (WM) microstructure remains limited. We thus sought to examine WM neuroplasticity and associated clinical improvements following serial ketamine infusion (SKI) in TRD. TRD patients (N= 57, 49.12% female, mean age: 39.9) received four intravenous ketamine infusions (0.5mg/kg) 2-3 days apart. Diffusion-weighted scans and clinical assessments (Hamilton Depression Rating Scale [HDRS-17]; Snaith Hamilton Pleasure Scale [SHAPS]) were collected at baseline and 24-h after SKI. WM measures including the neurite density index (NDI) and orientation dispersion index (ODI) from the neurite orientation dispersion and density imaging (NODDI) model, and fractional anisotropy (FA) from the diffusion tensor model were compared voxelwise pre- to post-SKI after using Tract-Based Spatial Statistics workflows to align WM tracts across subjects/time. Correlations between change in WM metrics and clinical measures were subsequently assessed. Following SKI, patients showed significant improvements in HDRS-17 (p-value=1.8 E-17) and SHAPS (p-value=1.97 E-10). NDI significantly decreased in occipitotemporal WM pathways (p< .05, FWER/TFCE corrected). ΔSHAPS significantly correlated with ΔNDI in the left internal capsule and left superior longitudinal fasciculus (r= -0.614, p-value=6.24E-09). No significant changes in ODI or FA were observed. SKI leads to significant changes in the microstructural features of neurites within occipitotemporal tracts, and changes in neurite density within tracts connecting the basal ganglia, thalamus, and cortex relate to improvements in anhedonia. NODDI may be more sensitive for detecting ketamine-induced WM changes than DTI.

Machine learning classification of chronic traumatic brain injury using diffusion tensor imaging and NODDI: A replication and extension study

Individuals with acute and chronic traumatic brain injury (TBI) are associated with unique white matter (WM) structural abnormalities, including fractional anisotropy (FA) differences. Our research group previously used FA as a feature in a linear support vector machine (SVM) pattern classifier, observing high classification between individuals with and without acute TBI (i.e., an area under the curve [AUC] value of 75.50%). However, it is not known whether FA could similarly classify between individuals with and without history of chronic TBI. Here, we attempted to replicate our previous work with a new sample, investigating whether FA could similarly classify between incarcerated men with (n = 80) and without (n = 80) self-reported history of chronic TBI. Additionally, given limitations associated with FA, including underestimation of FA values in WM tracts containing crossing fibers, we extended upon our previous study by incorporating neurite orientation dispersion and density imaging (NODDI) metrics, including orientation dispersion (ODI) and isotropic volume (Viso). A linear SVM based classification approach, similar to our previous study, was incorporated here to classify between individuals with and without self-reported chronic TBI using FA and NODDI metrics as separate features. Overall classification rates were similar when incorporating FA and NODDI ODI metrics as features (AUC: 82.50%). Additionally, NODDI-based metrics provided the highest sensitivity (ODI: 85.00%) and specificity (Viso: 82.50%) rates. The current study serves as a replication and extension of our previous study, observing that multiple diffusion MRI metrics can reliably classify between individuals with and without self-reported history of chronic TBI.

An Investigation of Differences in White Matter Tract Patterns in Alcohol Use Disorder: Standard Statistical and Covariance Analyses

Background: Magnetic resonance imaging (MRI) studies have been used to demonstrate differences in white matter (WM) in the brains of individuals with alcohol use disorder (AUD). Alcohol use is known to be deleterious on WM integrity, and there are reports of an inverse relationship between WM fractional anisotropy (FA) and self-reported alcohol consumption. Still, the specific WM tracts which are affected remain unclear. This study sought to determine whether alcohol use differentially alters FA and neurite microstructure in WM regions of interest (ROIs). We used diffusion weighted MRI to compare metrics of WM integrity between non- treatment seeking individuals with AUD and social drinkers (SD).&#x0D; Methods: Thirteen subjects with AUD and 21 SD underwent hybrid diffusion imaging (HYDI) on a 3T Siemens MRI scanner. HYDI data were processed with diffusion tensor imaging and Neurite Orientation Dispersion and Density Index (NODDI) modeling to produce parametric images of outcome metrics. All parametric images were converted to standard space before extraction of average parameter values from regions of interest defined by the John Hopkins University 1 mm WM atlas. For each metric, independent t-tests were used to test for group differences. Covariance analyses will be used to examine differences in covariance matrix structure between groups.&#x0D; Results: Compared to social drinkers, participants with AUD had significantly lower FA, higher radial diffusivity, and higher orientation dispersion (OD) in subregions of the corpus callosum (p&lt;0.05). AUD was also associated with higher OD in the cingulate gyri (p&lt;0.01).&#x0D; Conclusion: Individuals with AUD had significantly altered WM metrics in multiple tracts, consistent with previous research. This is also the first report of NODDI metrics in AUD; the higher OD may reflect WM disorganization. Ultimately, understanding the anatomic variance between groups will help to elucidate connectivity differences that may either predispose individuals to AUD and/or which are disrupted by chronic alcohol consumption.

Association of sub-acute changes in plasma amino acid levels with long-term brain pathologies in a rat model of moderate-severe traumatic brain injury.

Traumatic brain injury (TBI) induces a cascade of cellular alterations that are responsible for evolving secondary brain injuries. Changes in brain structure and function after TBI may occur in concert with dysbiosis and altered amino acid fermentation in the gut. Therefore, we hypothesized that subacute plasma amino acid levels could predict long-term microstructural outcomes as quantified using neurite orientation dispersion and density imaging (NODDI). Fourteen 8-10-week-old male rats were randomly assigned either to sham (n = 6) or a single moderate-severe TBI (n = 8) procedure targeting the primary somatosensory cortex. Venous blood samples were collected at days one, three, seven, and 60 post-procedure and NODDI imaging were carried out at day 60. Principal Component Regression analysis was used to identify time dependent plasma amino acid concentrations after in the subacute phase post-injury that predicted NODDI metric outcomes at day 60. The TBI group had significantly increased plasma levels of glutamine, arginine, alanine, proline, tyrosine, valine, isoleucine, leucine, and phenylalanine at days three-seven post-injury. Higher levels of several neuroprotective amino acids, especially the branched-chain amino acids (valine, isoleucine, leucine) and phenylalanine, as well as serine, arginine, and asparagine at days three-seven post-injury were also associated with lower isotropic diffusion volume fraction measures in the ventricles and thus lesser ventricular dilation at day 60. In the first such study, we examined the relationship between the long-term post-TBI microstructural outcomes across whole brain and the subacute changes in plasma amino acid concentrations. At days three to seven post-injury, we observed that increased plasma levels of several amino acids, particularly the branched-chain amino acids and phenylalanine, were associated with lesser degrees of ventriculomegaly and hydrocephalus TBI neuropathology at day 60 post-injury. The results imply that altered amino acid fermentation in the gut may mediate neuroprotection in the aftermath of TBI.

Dynamic white matter changes in recovered COVID-19 patients: a two-year follow-up study.

Background and purpose: Long COVID with regard to the neurological system deserves more attention, as a surge of treated patients are being discharged from the hospital. As the dynamic changes in white matter after two years remain unknown, this characteristic was the focus of this study. Methods: We investigated 17 recovered COVID-19 patients at two years after discharge. Diffusion tensor imaging, neurite orientation dispersion and density imaging were performed to identify white matter integrity and changes from one to two years after discharge. Data for 13 revisited healthy controls were collected as a reference. Subscales of the Wechsler Intelligence scale were used to assess cognitive function. Repeated-measures ANOVA was used to detect longitudinal changes in 17 recovered COVID-19 patients and 13 healthy controls after one-year follow-up. Correlations between diffusion metrics, cognitive function, and other clinical characteristics (i.e., inflammatory factors) were also analyzed. Results: Longitudinal analysis showed the recovery trends of large-scale brain regions, with small-scale brain region deterioration from one year to two years after SARS-CoV-2 infection. However, persistent white matter abnormalities were noted at two years after discharge. Longitudinal changes of cognitive function showed no group difference. But cross-sectional cognitive difference between recovered COVID-19 patients and revisited HCs was detected. Inflammation levels in the acute stage correlated positively with white matter abnormalities and negatively with cognitive function. Moreover, the more abnormal the white matter was at two years, the greater was the cognitive deficit present. Conclusion: Recovered COVID-19 patients showed longitudinal recovery trends of white matter. But also had persistent white matter abnormalities at two years after discharge. Inflammation levels in the acute stage may be considered predictors of cognition and white matter integrity, and the white matter microstructure acts as a biomarker of cognitive function in recovered COVID-19 patients. These findings provide an objective basis for early clinical intervention.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping.

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

Cortical microstructural abnormalities in amyotrophic lateral sclerosis: a gray matter-based spatial statistics study.

Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity. This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R. In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05). The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.

White matter microstructure and serum biomarkers of inflammation in psychogenic non-epileptic seizures

BackgroundNeuroinflammation may contribute to the pathophysiology of psychogenic non-epileptic seizures (PNES). However, it is unclear whether and to what degree comorbid psychiatric symptoms explain this association. In this study, we investigated the neuroinflammatory signature of PNES and how it compares to that of people with psychiatric conditions (PwPCs). MethodsWe prospectively assessed differences in neurite density (NDI), orientation dispersion (ODI), and isotropic diffusion (F-ISO) in 23 participants with PNES and 27 PwPCs, and their relationships to serum levels of tumor necrosis factor (TNF)-α, TNF receptor 1 (TNF-R1), TNF-related apoptosis-inducing ligand (TRAIL), interleukin (IL)-6, intercellular adhesion molecule (ICAM)-1, and monocyte chemoattractant protein (MCP)-1 using voxelwise multiple linear regressions. Pearson correlations between serum biomarkers and clinical symptoms were also obtained. ResultsThere were no white matter (WM) microstructural differences between groups. In PNES, TNF-R1 was negatively associated with NDI in the right uncinate fasciculus (UF) and positively associated with F-ISO in the left UF. IL-6 was positively associated with NDI and negatively with F-ISO in the left UF. ICAM-1 was positively associated with ODI in the left UF. TNF-α was negatively associated with ODI in the left cingulum bundle. The opposite relationships were observed in PwPCs. Higher TNF-R1 was associated with higher depression, anxiety, lower emotional quality of life, and higher levels of disability in PNES. ConclusionsFor the first time, we report relationships between peripheral inflammatory biomarkers and WM integrity in PNES, including abnormalities in the UF and cingulum bundle. Our results suggest that serum biomarkers of inflammation may, with additional studies, become a useful aid to PNES diagnosis, especially in settings where video-EEG is not available. The lack of group differences in WM microstructure suggests that previously identified WM abnormalities in PNES versus healthy controls may be related to psychological comorbidities of PNES.

Investigating Longitudinal Continuity of Persistent White Matter Alterations in Sport-related Concussion Using Individualized Analyses

Background: Sport-related concussion (SRC) has been shown to lead to acute and long-term alterations in white matter (WM) organization. The Centers for Disease Control estimates around 283,000 children each year seek medical attention for SRC/recreation-related traumatic brain injury. However, literature on subject-specific longitudinal WM abnormalities in SRC is limited.Purpose: Given the heterogeneous nature of SRC on WM microstructure, the goal of this study is to investigate the longitudinal continuity of persistent white matter alterations using a subject-specific approach.&#x0D; Methods: MRI is a non-invasive imaging modality suitable for detecting neuropathophysiological changes after SRC. Compared to conventional anatomical MRI, using diffusion MRI to probe WM microarchitecture may provide additional sensitivity.The diffusion MRI data from 50 participants were obtained from the CARE consortium, a prospective multisite study examining the natural history of concussion. Each concussed athlete underwent MRI scan at three time points: (1) 24-48 hours after concussion, (2) asymptomatic state, and (3) 7-days after returned to play. Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were computed and Z-scored based on a normal distribution template created from non-contact sport controls. Potential WM alterations indicated by extreme deviations of Z-score maps were calculated for all diffusion metrics in each concussed participant and time point.&#x0D; Results: WM alterations persistent across all three timepoints manifested in 76%, 62%, and 82% of the participants as quantified by increases of mean, axial, and radial diffusivity, respectively. 58% of the participants had fractional anisotropy decreases. For NODDI metrics, 82% and 86% of the participants showed increases of isotropic volume fraction and orientation dispersion index, respectively.&#x0D; Conclusion: This study demonstrated that by applying subject-specific analysis, extreme Z-score voxels can be identified across time in the same or spatially proximal brain regions suggesting persistent WM abnormalities beyond apparent clinical recovery.

Applications of advanced diffusion MRI in early brain development: a comprehensive review.

Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.

Fiber-specific structural properties relate to reading skills in children and adolescents.

Recent studies suggest that the cross-sectional relationship between reading skills and white matter microstructure, as indexed by fractional anisotropy, is not as robust as previously thought. Fixel-based analyses yield fiber-specific micro- and macrostructural measures, overcoming several shortcomings of the traditional diffusion tensor model. We ran a whole-brain analysis investigating whether the product of fiber density and cross-section (FDC) related to single-word reading skills in a large, open, quality-controlled dataset of 983 children and adolescents ages 6-18. We also compared FDC between participants with (n = 102) and without (n = 570) reading disabilities. We found that FDC positively related to reading skills throughout the brain, especially in left temporoparietal and cerebellar white matter, but did not differ between reading proficiency groups. Exploratory analyses revealed that among metrics from other diffusion models - diffusion tensor imaging, diffusion kurtosis imaging, and neurite orientation dispersion and density imaging - only the orientation dispersion and neurite density indexes from NODDI were associated (inversely) with reading skills. The present findings further support the importance of left-hemisphere dorsal temporoparietal white matter tracts in reading. Additionally, these results suggest that future DWI studies of reading and dyslexia should be designed to benefit from advanced diffusion models, include cerebellar coverage, and consider continuous analyses that account for individual differences in reading skill.

Differentiation of Perilesional Edema in Glioblastomas and Brain Metastases: Comparison of Diffusion Tensor Imaging, Neurite Orientation Dispersion and Density Imaging and Diffusion Microstructure Imaging

Although the free water content within the perilesional T2 hyperintense region should differ between glioblastomas (GBM) and brain metastases based on histological differences, the application of classical MR diffusion models has led to inconsistent results regarding the differentiation between these two entities. Whereas diffusion tensor imaging (DTI) considers the voxel as a single compartment, multicompartment approaches such as neurite orientation dispersion and density imaging (NODDI) or the recently introduced diffusion microstructure imaging (DMI) allow for the calculation of the relative proportions of intra- and extra-axonal and also free water compartments in brain tissue. We investigate the potential of water-sensitive DTI, NODDI and DMI metrics to detect differences in free water content of the perilesional T2 hyperintense area between histopathologically confirmed GBM and brain metastases. Respective diffusion metrics most susceptible to alterations in the free water content (MD, V-ISO, V-CSF) were extracted from T2 hyperintense perilesional areas, normalized and compared in 24 patients with GBM and 25 with brain metastases. DTI MD was significantly increased in metastases (p = 0.006) compared to GBM, which was corroborated by an increased DMI V-CSF (p = 0.001), while the NODDI-derived ISO-VF showed only trend level increase in metastases not reaching significance (p = 0.060). In conclusion, diffusion MRI metrics are able to detect subtle differences in the free water content of perilesional T2 hyperintense areas in GBM and metastases, whereas DMI seems to be superior to DTI and NODDI.

Integrating multimodality magnetic resonance imaging to the Allen Mouse Brain Common Coordinate Framework.

High-resolution magnetic resonance imaging (MRI) affords unique image contrasts to nondestructively probe the tissue microstructure; validation of MRI findings with conventional histology is essential to better understand the MRI contrasts. However, the dramatic difference in the spatial resolution and image contrast of these two techniques impedes accurate comparison between MRI metrics and traditional histology. To better validate various MRI metrics, we acquired whole mouse brain multigradient recalled-echo and multishell diffusion MRI datasets at 25-μm isotropic resolution. The recently developed Allen Mouse Brain Common Coordinate Framework (CCFv3) provides opportunities to integrate multimodal and multiscale datasets of the whole mouse brain in a common three-dimensional (3D) space. The T2*, quantitative susceptibility mapping, diffusion tensor imaging, and neurite orientation dispersion and density imaging parameters were compared with both serial two-photon tomography images and 3D Nissl staining images in the CCFv3 at the same spatial resolution. The correlation between MRI and Nissl staining strongly depends on different metrics and different regions of the brain. Integrating different imaging modalities to the same space may substantially improve our understanding of the complexity of the brain at different scales.

Diffusion radiomics for subtyping and clustering in autism spectrum disorder: A preclinical study

Autism spectrum disorder (ASD) is a highly prevalent, heterogenous neurodevelopmental disorder. Neuroimaging methods such as functional, structural, and diffusion MRI have been used to identify candidate imaging biomarkers for ASD, but current findings remain non-specific and likely arise from the heterogeneity present in ASD. To account for this, efforts to subtype ASD have emerged as a potential strategy for both the study of ASD and advancement of tailored behavioral therapies and therapeutics. Towards these ends, to improve upon current neuroimaging methods, we propose combining biologically sensitive neurite orientation dispersion and density index (NODDI) diffusion MR imaging with radiomics image processing to create a new methodological approach that, we hypothesize, can sensitively and specifically capture neurobiology. We demonstrate this method can sensitively distinguish differences between four genetically distinct rat models of ASD (Fmr1, Pten, Nrxn1, Disc1). Further, we demonstrate diffusion radiomic analyses hold promise for subtyping in ASD as we show unsupervised clustering of NODDI radiomic data generates clusters specific to the underlying genetic differences between the animal models. Taken together, our findings suggest the unique application of radiomic analysis on NODDI diffusion MRI may have the capacity to sensitively and specifically disambiguate the neurobiological heterogeneity present in the ASD population.

Hypertensive Aspects of Cardiometabolic Disorders Are Associated with Lower Brain Microstructure, Perfusion, and Cognition.

Cardiometabolic disorders (hypertension, diabetes) are key modifiable risk factors for Alzheimer's disease and related disorders. They often co-occur; yet, the extent to which they independently affect brain structure and function is unclear. We hypothesized their combined effect is greater in associations with cognitive function and neuroimaging biomarkers of white matter (WM) health and cerebral perfusion in a diverse older adult cohort. Participants aged 50-85 years received: clinical evaluation, oral glucose tolerance testing, neuroimaging, cognitive testing, and adjudication. Neuroimaging included: T1 (gray [GM]/WM segmentation, regional volumes/thicknesses); FLAIR (WM hyperintensity volume [WMHv]; arterial spin labeling (cerebral blood flow); diffusion tensor imaging (fractional anisotropy [FA]); and neurite orientation dispersion and density imaging (Free Water). Hypertension (HTN) and impaired glucose tolerance (IGT) were staged and cardiometabolic status was categorized (HTN only, IGT only, IGT+HTN, neither). Multivariable linear regression modeled associations with cognitive and neuroimaging measures (covariates: age, gender, race). MRI was available for 478 participants (35% mild cognitive impairment, 10% dementia) with mean age 70±8 years, 74% with HTN, 61% with IGT, and 15% self-identified as Black/African-American. IGT+HTN was significantly associated with cognitive impairment, higher WM Free Water and WMHv, lower FA, and lower GM perfusion compared to neither factor. HTN alone was associated with poorer cognition and lower GM perfusion. Cardiometabolic factors were not associated with GM macrostructure (volumes, temporal lobe cortical thickness) or cognitive status. HTN and its co-occurrence with IGT (HTN+IGT) were associated with lower global cognitive performance and reduced GM perfusion and impaired WM microstructure.

Vascular and Microstructural Markers of Cognitive Pathology

AbstractBackgroundArterial stiffness may play a role in the development of dementia, presumably through its effects on white matter integrity and hyperintensities (WMH). However, relationships among arterial stiffness, white matter microstructure, and WMH volumes remain poorly understood. Arterial stiffness increases monotonically with age and its increase is accelerated by cardiometabolic disorders (e.g., hypertension , metabolic syndrome, diabetes). Further exploration of these relationships is key to the development of targeted therapies, early management, and detection.MethodArterial stiffness was measured using carotid‐femoral pulse wave velocity (cfPWV) in ADRC participants with baseline systolic blood pressure (SBP) measurements, detailed cognitive testing, cognitive adjudication, and brain MRI. We examined associations of cfPWV and SBP with cognitive function (Montreal Cognitive Assessment [MoCA], Preclinical Alzheimer’s Cognitive Composite [PACC5], and domain measures of memory and executive function) and brain MRI measures of: macrostructure (volume of gray matter [GM] and WMH from T1‐weighted and FLAIR imaging), white matter microstructure (neurite orientation dispersion and density imaging [NODDI] free water [FW] and diffusion tensor imaging [DTI] fractional anisotropy [FA]), and cerebral blood flow (CBF) in white matter (WM) and GM. Age, race, gender, education, and APOE‐4 status were included as covariates and in interaction terms in linear regression analyses.ResultAmong 458 participants with a mean age 70±8 years and cognitive adjudication (44 dementia, 157 MCI, 257 normal cognition; Table 1), higher cfPWV was associated with worse cognitive performance (MoCA, PACC5), as was SBP (MoCA, PACC5, executive domain, language domain; Table 2). Higher cfPWV was associated with differences in WM microstructure (higher FW, lower FA) and higher WMH volume. While no overall associations between cfPWV and CBF were detected, cfPWV had stronger associations with FW, FA, and WMH in men. Higher SBP was associated with higher FW, higher WMH volume, and lower WM and GM CBF (Table 3). SBP had stronger associations with WMH in younger participants (&lt;70y) and GM CBF in Black/AA participants and participants with impaired fasting glucose. No other interactions were detected.ConclusionsArterial stiffness is associated with microstructural and macrostructural differences and poorer global and executive cognitive function.

Genetic analyses of diffusion MRI phenotypes: a lifespan exploration of cSVD determinants

AbstractBackgroundCerebral small vessel disease (cSVD) is a leading cause of vascular cognitive impairment and dementia. Mounting evidence suggests that early life factors contribute to cSVD. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI‐marker of cSVD in older age, were recently found to show strong associations with white matter microstructure on diffusion tensor imaging (DTI) already in young adults in their twenties. Here we aimed to use multi‐shell diffusion imaging to further explore genetic determinants of white matter microstructure across the adult lifespan and its relation with cSVD.MethodIn 1,758 participants (mean age: 22.1 [18 to 35] years) from the i‐Share student cohort who underwent multi‐shell diffusion imaging, we used neurite orientation dispersion and density imaging (NODDI) to generate tissue‐based markers of white matter microstructure including neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) in 28 brain regions. We ran genome‐wide association studies (GWAS) of all 84 NODDI markers in i‐Share and looked up genome‐wide significant variants in UK Biobank (N = 33,224, mean age: 64.3 [45 to 82] years) to identify loci with a lifecourse effect on these phenotypes. Next, we studied the association of genetically determined WMH volume and blood pressure with NODDI phenotypes in i‐Share using Mendelian randomization (MR).ResultThis first GWAS of 84 NODDI phenotypes in young adults identified 21 genome‐wide significant loci. Three of them, associated mostly with NDI, also showed significant association with NODDI phenotypes in middle‐aged to older UK Biobank participants, including a known WMH locus near VCAN, a cerebrovascular matrisome gene. Using MR we found that genetically determined WMH, previously shown to predict Alzheimer‐type dementia, was associated with lower NDI in young adults. In contrast, genetically determined blood pressure, although an important risk factor for WMH volume, did not show any significant association with NODDI phenotypes in young adults.ConclusionOur results suggest that NODDI markers, especially NDI, have a substantial genetic component already in early adulthood and may inform early mechanisms underlying the vascular contribution to dementia. Replication of these findings in additional CHARGE cohorts (Rhineland study, Framingham Heart study) is underway.

Cortical Microstructure Mediates CSF Amyloid and Tau Associations with Episodic Memory Performance

AbstractBackgroundEpisodic memory impairment is common in early stages of Alzheimer’s disease (AD) and has been linked to atrophy in cortical regions that are vulnerable to AD neuropathological processes (e.g., amyloid and tau accumulation). Volumetric measures are relatively insensitive to microstructural brain changes that can occur in earlier disease stages. Microstructural properties of brain tissue can be non‐invasively assessed using advanced diffusion MRI (dMRI) models such as neurite orientation dispersion and density imaging (NODDI). While a number of studies have related white matter microstructure to AD pathology and memory, few have evaluated advanced dMRI indices in cortical gray matter where the earliest histopathological changes are thought to occur.MethodWe evaluated 66 ADNI participants (age 71.8±6.2 years; 25 Males; 46 CN/18 MCI/2 AD) with available MRI (T1‐weighted and multi‐shell diffusion) and CSF Aβ1–42, pTau181, and pTau181/Aβ1–42 data (Fig1A). Episodic memory was assessed using WMS‐R delayed logical memory scores (Del‐Mem). We estimated average NODDI ICVF, ECVF, ISOVF, and ODI (Fig1B) in an AD‐metaROI of cortical gray matter regions that are sensitive to early AD (Fig1C,D). We tested whether the effect of CSF biomarkers on Del‐Mem were mediated by metaROI measures (Fig2A), adjusting for age, sex, education, and MRI site as a grouping variable. For comparison, we re‐ran analyses with AD‐metaROI cortical thickness as the mediator.ResultLower CSF Aβ1–42 and higher pTau181/Aβ1–42 were significantly associated with lower Del‐Mem performance (FDR; q=0.05); pTau181 was not associated (Fig2B).Lower cortical ICVF, ODI, and thickness and higher ISOVF were associated both with lower Aβ1–42 and higher pTau181/Aβ1–42 (Fig2C).The effect of Aβ1–42 on Del‐Mem was fully mediated by ICVF. The effect of pTau181/Aβ1–42 on Del‐Mem was partially mediated by ISOVF. Del‐Mem was not mediated by ODI or thickness (Table1). Sensitivity analyses in the 64 non‐demented individuals revealed comparable results.ConclusionLower cortical ICVF and higher ISOVF with greater Aβ and pTau/Aβ burden, respectively, may indicate neuronal loss or edema. While both ICVF and ISOVF findings can be driven by reduced diffusion restriction, larger pTau/Aβ effects on episodic memory mediated through ISOVF may indicate that tau hyperphosphorylation and aggregation induces a greater degree of inflammation, neuronal dysfunction and death.