Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry

Age-related alterations in human cortical microstructure across the lifespan: Insights from high-gradient diffusion MRI

The human brain undergoes age-related microstructural alterations across the lifespan. Soma and Neurite Density Imaging (SANDI), a novel biophysical model of diffusion MRI, provides estimates of cell body (soma) radius and density, and neurite density in gray matter. The goal of this cross-sectional study was to assess the sensitivity of high-gradient diffusion MRI toward age-related alterations in cortical microstructure across the adult lifespan using SANDI. Seventy-two cognitively unimpaired healthy subjects (ages 19-85 years; 40 females) were scanned on the 3T Connectome MRI scanner with a maximum gradient strength of 300mT/m using a multi-shell diffusion MRI protocol incorporating 8 b-values and diffusion time of 19 ms. Intra-soma signal fraction obtained from SANDI model-fitting to the data was strongly correlated with age in all major cortical lobes (r = -0.69 to -0.60, FDR-p < 0.001). Intra-soma signal fraction (r = 0.48-0.63, FDR-p < 0.001) and soma radius (r = 0.28-0.40, FDR-p < 0.04) were significantly correlated with cortical volume in the prefrontal cortex, frontal, parietal, and temporal lobes. The strength of the relationship between SANDI metrics and age was greater than or comparable to the relationship between cortical volume and age across the cortical regions, particularly in the occipital lobe and anterior cingulate gyrus. In contrast to the SANDI metrics, all associations between diffusion tensor imaging (DTI) and diffusion kurtosis imaging metrics and age were low to moderate. These results suggest that high-gradient diffusion MRI may be more sensitive to underlying substrates of neurodegeneration in the aging brain than DTI and traditional macroscopic measures of neurodegeneration such as cortical volume and thickness.

Development of white matter in young adulthood: The speed of brain aging and its relationship with changes in fractional anisotropy

White matter (WM) development has been studied extensively, but most studies used cross-sectional data, and to the best of our knowledge, none of them considered the possible effects of biological (vs. chronological) age. Therefore, we conducted a longitudinal multimodal study of WM development and studied changes in fractional anisotropy (FA) in the different WM tracts and their relationship with cortical thickness-based measures of brain aging in young adulthood. A total of 105 participants from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) prenatal birth cohort underwent magnetic resonance imaging (MRI) at the age of 23-24, and the age of 28-30 years. At both time points, FA in the different WM tracts was extracted using the JHU atlas, and brain age gap estimate (BrainAGE) was calculated using the Neuroanatomical Age Prediction using R (NAPR) model based on cortical thickness maps. Changes in FA and the speed of cortical brain aging were calculated as the difference between the respective variables in the late vs. early 20s. We demonstrated tract-specific increases as well as decreases in FA, which indicate that the WM microstructure continues to develop in the third decade of life. Moreover, the significant interaction between the speed of cortical brain aging, tract, and sex on mean FA revealed that a greater speed of cortical brain aging in young adulthood predicted greater decreases in FA in the bilateral cingulum and left superior longitudinal fasciculus in young adult men. Overall, these changes in FA in the WM tracts in young adulthood point out the protracted development of WM microstructure, particularly in men.

Trem2-deficiency aggravates and accelerates age-related myelin degeneration

Aging is the greatest known risk factor for most neurodegenerative diseases. Myelin degeneration is an early pathological indicator of these diseases and a normal part of aging; albeit, to a lesser extent. Despite this, little is known about the contribution of age-related myelin degeneration on neurodegenerative disease. Microglia participate in modulating white matter events from demyelination to remyelination, including regulation of (de)myelination by the microglial innate immune receptor triggering receptor expressed on myeloid cells 2 (TREM2). Here, we demonstrate Trem2-deficiency aggravates and accelerates age-related myelin degeneration in the striatum. We show TREM2 is necessary for remyelination by recruiting reparative glia and mediating signaling that promotes OPC differentiation/maturation. In response to demyelination, TREM2 is required for phagocytosis of large volumes of myelin debris. In addition to lysosomal regulation, we show TREM2 can modify the ER stress response, even prior to overt myelin debris, that prevents lipid accumulation and microglial dysfunction. These data support a role for Trem2-dependent interactions in age-related myelin degeneration and suggest a basis for how early dysfunctional microglia could contribute to disease pathology through insufficent repair, defective phagocytosis, and the ER stress response.

Chronic cannabis use associated with subcortical topological reorganization of structural connectivity in adults

BACKGROUND

Cannabis is commonly used in the United States. However, chronic cannabis use has been linked to alterations in white matter (WM) integrity. Studies investigating WM in people who use cannabis (PWC) have produced varying results, which may be due to a variety of factors, including a focus on individual WM tracts. Here, we examined WM connectivity using a module-based approach to help clarify whether cannabis use is associated with differences in WM organization.

METHODS

Connectomics is used to map complex networks of inter and intra-connected cortical and subcortical regions. A key concept of brain organization is the presence of groups of densely interconnected regions, referred to as modules. Here, we used WM structural connectivity estimates to compare connectome organization between adults who used cannabis regularly (n=53), and adults who did not use cannabis (n=60). We quantified aspects of network organization both across the whole brain and within specific modules.

RESULTS

There were no significant results between groups after correcting for multiple comparisons for whole-brain metrics. When considering group differences in network organization metrics for 10 identified modules, we observed that adult PWC showed higher within-module degree, local efficiency, and network strength in a right subcortical module relative to adults that did not use cannabis.

CONCLUSIONS

These results suggest that cannabis use in adults is associated with alterations of subcortical WM network organization. The observed differences in WM organization may be due to the involvement of the endocannabinoid system in the alteration of WM growth processes.

Structural MRI analysis of age-related changes and sex differences in marmoset brain volume

The field of aging biology, which aims to extend healthy lifespans and prevent age-related diseases, has turned its focus to the Callithrix jacchus (common marmoset) to understand the aging process better. This study utilized magnetic resonance imaging (MRI) to non-invasively analyze the brains of 216 marmosets, investigating age-related changes in brain structure; the relationship between body weight and brain volume; and potential differences between males and females. The key findings revealed that, similar to humans, Callithrix jacchus experiences a reduction in total intracranial volume, cortex, subcortex, thalamus, and cingulate volumes as they age, highlighting site-dependent changes in brain tissue. Notably, the study also uncovered sex differences in cerebellar volume. These insights into the structural connectivity and volumetric changes in the marmoset brain throughout aging contribute to accumulating valuable knowledge in the field, promising to inform future aging research and interventions for enhancing healthspan.

Differential Tractography: A Biomarker for Neuronal Function in Neurodegenerative Disease

GM1 gangliosidosis is an ultra-rare inherited neurodegenerative lysosomal storage disorder caused by biallelic mutations in the GLB1 gene. GM1 is uniformly fatal and has no approved therapies, although clinical trials investigating gene therapy as a potential treatment for this condition are underway. Novel outcome measures or biomarkers demonstrating the longitudinal effects of GM1 and potential recovery due to therapeutic intervention are urgently needed to establish efficacy of potential therapeutics. One promising tool is differential tractography, a novel imaging modality utilizing serial diffusion weighted imaging (DWI) to quantify longitudinal changes in white matter microstructure. In this study, we present the novel use of differential tractography in quantifying the progression of GM1 alongside age-matched neurotypical controls. We analyzed 113 DWI scans from 16 GM1 patients and 32 age-matched neurotypical controls to investigate longitudinal changes in white matter pathology. GM1 patients showed white matter degradation evident by both the number and size of fiber tract loss. In contrast, neurotypical controls showed longitudinal white matter improvements as evident by both the number and size of fiber tract growth. We also corroborated these findings by documenting significant correlations between cognitive global impression (CGI) scores of clinical presentations and our differential tractography derived metrics in our GM1 cohort. Specifically, GM1 patients who lost more neuronal fiber tracts also had a worse clinical presentation. This result demonstrates the importance of differential tractography as an important biomarker for disease progression in GM1 patients with potential extension to other neurodegenerative diseases and therapeutic intervention.

Evidence for Altered White Matter Organization After Mild Traumatic Brain Injury: A Scoping Review on the Use of Diffusion Magnetic Resonance Imaging and Blood-Based Biomarkers to Investigate Acute Pathology and Relationship to Persistent Post-Concussion Symptoms

Mild traumatic brain injury (mTBI) is the most common form of traumatic brain injury. Post-concussive symptoms typically resolve after a few weeks although up to 20% of people experience these symptoms for >3 months, termed persistent post-concussive symptoms (PPCS). Subtle white matter (WM) microstructural damage is thought to underlie neurological and cognitive deficits experienced post-mTBI. Evidence suggests that diffusion magnetic resonance imaging (dMRI) and blood-based biomarkers could be used as surrogate markers of WM organization. We conducted a scoping review according to PRISMA-ScR guidelines, aiming to collate evidence for the use of dMRI and/or blood-based biomarkers of WM organization, in mTBI and PPCS, and document relationships between WM biomarkers and symptoms. We focused specifically on biomarkers of axonal or myelin integrity post-mTBI. Biomarkers excluded from this review therefore included the following: astroglial, perivascular, endothelial, and inflammatory markers. A literature search performed across four databases, EMBASE, Scopus, Google Scholar, and ProQuest, identified 100 records: 68 analyzed dMRI, 28 assessed blood-based biomarkers, and 4 used both. Blood biomarker studies commonly assessed axonal cytoskeleton proteins (i.e., tau); dMRI studies assessed measures of WM organization (i.e., fractional anisotropy). Significant biomarker alterations were frequently associated with heightened symptom burden and prolonged recovery time post-injury. These data suggest that dMRI and blood-based biomarkers may be useful proxies of WM organization, although few studies assessed these complementary measures in parallel, and the relationship between modalities remains unclear. Further studies are warranted to assess the benefit of a combined biomarker approach in evaluating alterations to WM organization after mTBI.

Transcallosal white matter and cortical gray matter variations in autistic adults ages 30-73 years: A bi-tensor free water imaging approach

Background: Autism spectrum disorder (ASD) has long been recognized as a lifelong condition, but brain aging studies in autistic adults aged >30 years are limited. Free water, a novel brain imaging marker derived from diffusion MRI (dMRI), has shown promise in differentiating typical and pathological aging and monitoring brain degeneration. We aimed to examine free water and free water corrected dMRI measures to assess white and gray matter microstructure and their associations with age in autistic adults. Methods: Forty-three autistic adults ages 30-73 years and 43 age, sex, and IQ matched neurotypical controls participated in this cross-sectional study. We quantified fractional anisotropy (FA), free water, and free water-corrected FA (fwcFA) across 32 transcallosal white matter tracts and 94 gray matter areas in autistic adults and neurotypical controls. Follow-up analyses assessed age effect on dMRI metrics of the whole brain for both groups and the relationship between dMRI metrics and clinical measures of ASD in regions that significantly differentiated autistic adults from controls. Results: We found globally elevated free water in 24 transcallosal tracts in autistic adults. We identified negligible differences in dMRI metrics in gray matter between the two groups. Age-associated FA reductions and free water increases were featured in neurotypical controls; however, this brain aging profile was largely absent in autistic adults. Additionally, greater autism quotient (AQ) total raw score was associated with increased free water in the inferior frontal gyrus pars orbitalis and lateral orbital gyrus in autistic adults. Limitations: All autistic adults were cognitively capable individuals, minimizing the generalizability of the research findings across the spectrum. This study also involved a cross-sectional design, which limited inferences about the longitudinal microstructural changes of white and gray matter in ASD. Conclusions: We identified differential microstructural configurations between white and gray matter in autistic adults and that autistic individuals present more heterogeneous brain aging profiles compared to controls. Our clinical correlation analysis offered new evidence that elevated free water in some localized white matter tracts may critically contribute to autistic traits in ASD. Our findings underscored the importance of quantifying free water in dMRI studies of ASD.

Towards a neurodevelopmental cognitive perspective of temporal processing

The ability to organize and memorize the unfolding of events over time is a fundamental feature of cognition, which develops concurrently with the maturation of the brain. Nonetheless, how temporal processing evolves across the lifetime as well as the links with the underlying neural substrates remains unclear. Here, we intend to retrace the main developmental stages of brain structure, function, and cognition linked to the emergence of timing abilities. This neurodevelopmental perspective aims to untangle the puzzling trajectory of temporal processing aspects across the lifetime, paving the way to novel neuropsychological assessments and cognitive rehabilitation strategies.

Effects of Aging, Fitness, and Cerebrovascular Status on White Matter Microstructural Health

White matter (WM) microstructural health declines with increasing age, with evidence suggesting that improved cardiorespiratory fitness (CRF) may mitigate this decline. Specifically, higher fit older adults tend to show preserved WM microstructural integrity compared to their lower fit counterparts. However, the extent to which fitness and aging independently impact WM integrity across the adult lifespan is still an open question, as is the extent to which cerebrovascular health mediates these relationships. In a large sample (N = 125, aged 25-72), we assessed the impact of age and fitness on fractional anisotropy (FA, derived using diffusion weighted imaging, DWI) and probed the mediating role of cerebrovascular health (derived using diffuse optical tomography of the cerebral arterial pulse, pulse-DOT) in these relationships. After orthogonalizing age and fitness and computing a PCA on whole brain WM regions, we found several WM regions impacted by age that were independent from the regions impacted by fitness (hindbrain areas, including brainstem and cerebellar tracts), whereas other areas showed interactive effects of age and fitness (midline areas, including fornix and corpus callosum). Critically, cerebrovascular health mediated both relationships suggesting that vascular health plays a linking role between age, fitness, and brain health. Secondarily, we assessed potential sex differences in these relationships and found that, although females and males generally showed the same age-related FA declines, males exhibited somewhat steeper declines than females. Together, these results suggest that age and fitness impact specific WM regions and highlight the mediating role of cerebrovascular health in maintaining WM health across adulthood.

Quantitative susceptibility mapping for susceptibility source separation with adaptive relaxometric constant estimation (QSM-ARCS) from solely gradient-echo data

To separate the contributions of paramagnetic and diamagnetic sources within a voxel, a magnetic susceptibility source separation method based solely on gradient-echo data has been developed. To measure the opposing susceptibility sources more accurately, we propose a novel single-orientation quantitative susceptibility mapping method with adaptive relaxometric constant estimation (QSM-ARCS) for susceptibility source separation. Moreover, opposing susceptibilities and their anisotropic effects were determined in healthy volunteers in the white matter. Multiple spoiled gradient echo and diffusion tensor imaging of ten healthy volunteers was obtained using a 3 T magnetic resonance scanner. After the opposing susceptibility and fractional anisotropy (FA) maps had been reconstructed, the parametric maps were spatially normalized. To evaluate the agreements of QSM-ARCS against the susceptibility source separation method using R2 and R2* maps (χ-separation) by Bland-Altman plots, the opposing susceptibility values were measured using white and deep gray matter atlases. We then evaluated the relationships between the opposing susceptibilities and FAs in the white matter and used a field-to-fiber angle to assess the fiber orientation dependencies of the opposing susceptibilities. The susceptibility maps in QSM-ARCS were successfully reconstructed without large artifacts. In the Bland-Altman analyses, the opposing QSM-ARCS susceptibility values excellently agreed with the χ-separation maps. Significant inverse and proportional correlations were observed between FA and the negative and positive susceptibilities estimated by QSM-ARCS. The fiber orientation dependencies of the negative susceptibility represented a nonmonotonic feature. Conversely, the positive susceptibility increased linearly with the fiber angle with respect to the B0 field. The QSM-ARCS could accurately estimate the opposing susceptibilities, which were identical values of χ-separation, even using gradient echo alone. The opposing susceptibilities might offer direct biomarkers for assessment of the myelin and iron content in glial cells and, through the underlying magnetic sources, provide biologic insights toward clinical transition.

A Novel Registration Framework for Aligning Longitudinal Infant Brain Tensor Images

Registering longitudinal infant brain images is challenging, as the infant brain undergoes rapid changes in size, shape and tissue contrast in the first months and years of life. Diffusion tensor images (DTI) have relatively consistent tissue properties over the course of infancy compared to commonly used T1 or T2-weighted images, presenting great potential for infant brain registration. Moreover, groupwise registration has been widely used in infant neuroimaging studies to reduce bias introduced by predefined atlases that may not be well representative of samples under study. To date, however, no methods have been developed for groupwise registration of tensor-based images. Here, we propose a novel registration approach to groupwise align longitudinal infant DTI images to a sample-specific common space. Longitudinal infant DTI images are first clustered into more homogenous subgroups based on image similarity using Louvain clustering. DTI scans are then aligned within each subgroup using standard tensor-based registration. The resulting images from all subgroups are then further aligned onto a sample-specific common space. Results show that our approach significantly improved registration accuracy both globally and locally compared to standard tensor-based registration and standard fractional anisotropy-based registration. Additionally, clustering based on image similarity yielded significantly higher registration accuracy compared to no clustering, but comparable registration accuracy compared to clustering based on chronological age. By registering images groupwise to reduce registration bias and capitalizing on the consistency of features in tensor maps across early infancy, our groupwise registration framework facilitates more accurate alignment of longitudinal infant brain images.

Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer's Disease in the UK Biobank

Background

During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging.

Methods

We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (n = 2678; agescan 1 = 62.38 ± 7.23 years; agescan 2 = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer's disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (n = 2329) and cross-sectional (n = 31,056) UKB validation data.

Results

Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages.

Conclusions

We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.

Anisotropy of the R1/T2* value dependent on white matter fiber orientation with respect to the B0 field

The R1 (1/T1) map divided by the T2* map (R1/T2* map) draws attention as a high-resolution myelin-related map. However, both R1 and R2* (1/T2*) values demonstrate anisotropy dependent on the white matter (WM) fiber orientation with respect to the static magnetic (B0) field. Therefore, this study primarily aimed to investigate the comprehensive impact of these angular-dependent anisotropies on the R1/T2* value. This study enrolled 10 healthy human volunteers (age = 25 ± 1.3) on the 3.0 T MRI system. For R1/T2* map calculation, whole brain R1 and T2* maps were repeatedly obtained in three head tilt positions by magnetization-prepared two rapid gradient echoes and multiple spoiled gradient echo sequences, respectively. Afterward, all maps were spatially normalized and registered to the Johns Hopkins University WM atlas. R1/T2*, R1, and R2* values were binned for fiber orientation related to the B0 field, which was estimated from diffusion-weighted echo-planar imaging data with 3° intervals, to investigate angular-dependent anisotropies in vivo. A larger change in the R1/T2* value in the global WM region as a function of fiber orientation with respect to the B0 field was observed compared to the R1 and R2* values alone. The minimum R1/T2* value at the near magic-angle range was 18.86% lower than the maximum value at the perpendicular angle range. Furthermore, R1/T2* values in the corpus callosum tract and the right and left cingulum cingulate gyrus tracts changed among the three head tilt positions due to fiber orientation changes. In conclusion, the R1/T2* value demonstrates distinctive and complicated angular-dependent anisotropy indicating the trends of both R1 and R2* values and may provide supplemental information for detecting slight changes in the microstructure of myelin and axons.

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

Age-related constraints on the spatial geometry of the brain

Age-related structural brain changes may be better captured by assessing complex spatial geometric differences rather than isolated changes to individual regions. We applied a novel analytic method to quantify age-related changes to the spatial anatomy of the brain by measuring expansion and compression of global brain shape and the distance between cross-hemisphere homologous regions. To test how global brain shape and regional distances are affected by aging, we analyzed 2,603 structural MRIs (range: 30-97 years). Increasing age was associated with global shape expansion across inferior-anterior gradients, global compression across superior-posterior gradients, and regional expansion between frontotemporal homologues. Specific patterns of global and regional expansion and compression were further associated with clinical impairment and distinctly related to deficits in various cognitive domains. These findings suggest that changes to the complex spatial anatomy and geometry of the aging brain may be associated with reduced efficiency and cognitive dysfunction in older adults.

White matter trajectories over the lifespan

White matter (WM) changes occur throughout the lifespan at a different rate for each developmental period. We aggregated 10879 structural MRIs and 6186 diffusion-weighted MRIs from participants between 2 weeks to 100 years of age. Age-related changes in gray matter and WM partial volumes and microstructural WM properties, both brain-wide and on 29 reconstructed tracts, were investigated as a function of biological sex and hemisphere, when appropriate. We investigated the curve fit that would best explain age-related differences by fitting linear, cubic, quadratic, and exponential models to macro and microstructural WM properties. Following the first steep increase in WM volume during infancy and childhood, the rate of development slows down in adulthood and decreases with aging. Similarly, microstructural properties of WM, particularly fractional anisotropy (FA) and mean diffusivity (MD), follow independent rates of change across the lifespan. The overall increase in FA and decrease in MD are modulated by demographic factors, such as the participant's age, and show different hemispheric asymmetries in some association tracts reconstructed via probabilistic tractography. All changes in WM macro and microstructure seem to follow nonlinear trajectories, which also differ based on the considered metric. Exponential changes occurred for the WM volume and FA and MD values in the first five years of life. Collectively, these results provide novel insight into how changes in different metrics of WM occur when a lifespan approach is considered.

Spatiotemporal Patterns of White Matter Maturation after Pre-Adolescence: A Diffusion Kurtosis Imaging Study

Diffusion tensor imaging (DTI) enables the assessment of changes in brain tissue microstructure during maturation and ageing. In general, patterns of cerebral maturation and decline render non-monotonic lifespan trajectories of DTI metrics with age, and, importantly, the rate of microstructural changes is heterochronous for various white matter fibres. Recent studies have demonstrated that diffusion kurtosis imaging (DKI) metrics are more sensitive to microstructural changes during ageing compared to those of DTI. In a previous work, we demonstrated that the Cohen's d of mean diffusional kurtosis (dMK) represents a useful biomarker for quantifying maturation heterochronicity. However, some inferences on the maturation grades of different fibre types, such as association, projection, and commissural, were of a preliminary nature due to the insufficient number of fibres considered. Hence, the purpose of this follow-up work was to further explore the heterochronicity of microstructural maturation between pre-adolescence and middle adulthood based on DTI and DKI metrics. Using the effect size of the between-group parametric changes and Cohen's d, we observed that all commissural fibres achieved the highest level of maturity, followed by the majority of projection fibres, while the majority of association fibres were the least matured. We also demonstrated that dMK strongly correlates with the maxima or minima of the lifespan curves of DTI metrics. Furthermore, our results provide substantial evidence for the existence of spatial gradients in the timing of white matter maturation. In conclusion, our data suggest that DKI provides useful biomarkers for the investigation of maturation spatial heterogeneity and heterochronicity.

Association of Blood Pressure With Brain White Matter Microstructural Integrity Assessed With MRI Diffusion Tensor Imaging in Healthy Young Adults

BACKGROUND

High blood pressure (BP) in middle-aged and older adults is associated with a brain white matter (WM) microstructural abnormality. However, little evidence is available in healthy young adults. We investigated the associations between high BP and WM microstructural integrity in young adults.

METHODS

This study included 1015 healthy young adults (542 women, 22-37 years) from the Human Connectome Project. Brachial systolic and diastolic BP were measured using a semiautomatic or manual sphygmomanometer. Diffusion-weighted magnetic resonance imaging was acquired to obtain diffusion tensor imaging metrics of free water (FW) content, FW-corrected WM fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity. Using whole-brain voxel-wise linear regression models and ANCOVA, we examined associations of BP and hypertension stage with diffusion tensor imaging metrics after adjusting for age, sex, education, body mass index, smoking status, alcohol consumption history, and differences in the b value used for diffusion magnetic resonance imaging.

RESULTS

Systolic and diastolic BP of the sample (mean±SD) were 122.8±13.0 and 76.0±9.9 mm Hg, respectively. Associations of BP with diffusion tensor imaging metrics revealed regional heterogeneity for FW-corrected fractional anisotropy. High BP and high hypertension stage were associated with higher FW and lower FW-corrected axial diffusivity, FW-corrected radial diffusivity, and FW-corrected mean diffusivity. Moreover, associations of high diastolic BP and hypertension stage with high FW were found only in men not in women.

CONCLUSIONS

High BP in young adults is associated with altered brain WM microstructural integrity, suggesting that high BP may have damaging effects on brain WM microstructural integrity in early adulthood, particularly in men.

Toward diffusion tensor imaging as a biomarker in neurodegenerative diseases: technical considerations to optimize recordings and data processing

Neuroimaging biomarkers have shown high potential to map the disease processes in the application to neurodegenerative diseases (NDD), e.g., diffusion tensor imaging (DTI). For DTI, the implementation of a standardized scanning and analysis cascade in clinical trials has potential to be further optimized. Over the last few years, various approaches to improve DTI applications to NDD have been developed. The core issue of this review was to address considerations and limitations of DTI in NDD: we discuss suggestions for improvements of DTI applications to NDD. Based on this technical approach, a set of recommendations was proposed for a standardized DTI scan protocol and an analysis cascade of DTI data pre-and postprocessing and statistical analysis. In summary, considering advantages and limitations of the DTI in NDD we suggest improvements for a standardized framework for a DTI-based protocol to be applied to future imaging studies in NDD, towards the goal to proceed to establish DTI as a biomarker in clinical trials in neurodegeneration.

Cortical thickness reductions associate with brain network architecture in major depressive disorder

BACKGROUND

Cortical thickness reductions in major depressive disorder are distributed across multiple regions. Research has indicated that cortical atrophy is influenced by connectome architecture on a range of neurological and psychiatric diseases. However, whether connectome architecture contributes to changes in cortical thickness in the same manner as it does in depression is unclear. This study aims to explain the distribution of cortical thickness reductions across the cortex in depression by brain connectome architecture.

METHODS

Here, we calculated a differential map of cortical thickness between 110 depression patients and 88 age-, gender-, and education level-matched healthy controls by using T1-weighted images and a structural network reconstructed through the diffusion tensor imaging of control group. We then used a neighborhood deformation model to explore how cortical thickness change in an area is influenced by areas structurally connected to it.

RESULTS

We found that cortical thickness in the frontoparietal and default networks decreased in depression, regional cortical thickness changes were related to reductions in their neighbors and were mainly limited by the frontoparietal and default networks, and the epicenter was in the prefrontal lobe.

CONCLUSION

Current findings suggest that connectome architecture contributes to the irregular topographic distribution of cortical thickness reductions in depression and cortical atrophy is restricted by and dependent on structural foundation.

Brain asymmetries from mid- to late life and hemispheric brain age

The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N=48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.

Evaluation of tractography-based myelin-weighted connectivity across the lifespan

Introduction

Recent studies showed that the myelin of the brain changes in the life span, and demyelination contributes to the loss of brain plasticity during normal aging. Diffusion-weighted magnetic resonance imaging (dMRI) allows studying brain connectivity in vivo by mapping axons in white matter with tractography algorithms. However, dMRI does not provide insight into myelin; thus, combining tractography with myelin-sensitive maps is necessary to investigate myelin-weighted brain connectivity. Tractometry is designated for this purpose, but it suffers from some serious limitations. Our study assessed the effectiveness of the recently proposed Myelin Streamlines Decomposition (MySD) method in estimating myelin-weighted connectomes and its capacity to detect changes in myelin network architecture during the process of normal aging. This approach opens up new possibilities compared to traditional Tractometry.

Methods

In a group of 85 healthy controls aged between 18 and 68 years, we estimated myelin-weighted connectomes using Tractometry and MySD, and compared their modulation with age by means of three well-known global network metrics.

Results

Following the literature, our results show that myelin development continues until brain maturation (40 years old), after which degeneration begins. In particular, mean connectivity strength and efficiency show an increasing trend up to 40 years, after which the process reverses. Both Tractometry and MySD are sensitive to these changes, but MySD turned out to be more accurate.

Conclusion

After regressing the known predictors, MySD results in lower residual error, indicating that MySD provides more accurate estimates of myelin-weighted connectivity than Tractometry.

Age-Related Decline in Brain Myelination: Quantitative Macromolecular Proton Fraction Mapping, T2-FLAIR Hyperintensity Volume, and Anti-Myelin Antibodies Seven Years Apart

Age-related myelination decrease is considered one of the likely mechanisms of cognitive decline. The present preliminary study is based on the longitudinal assessment of global and regional myelination of the normal adult human brain using fast macromolecular fraction (MPF) mapping. Additional markers were age-related changes in white matter (WM) hyperintensities on FLAIR-MRI and the levels of anti-myelin autoantibodies in serum. Eleven healthy subjects (33-60 years in the first study) were scanned twice, seven years apart. An age-related decrease in MPF was found in global WM, grey matter (GM), and mixed WM-GM, as well as in 48 out of 82 examined WM and GM regions. The greatest decrease in MPF was observed for the frontal WM (2-5%), genu of the corpus callosum (CC) (4.0%), and caudate nucleus (5.9%). The age-related decrease in MPF significantly correlated with an increase in the level of antibodies against myelin basic protein (MBP) in serum (r = 0.69 and r = 0.63 for global WM and mixed WM-GM, correspondingly). The volume of FLAIR hyperintensities increased with age but did not correlate with MPF changes and the levels of anti-myelin antibodies. MPF mapping showed high sensitivity to age-related changes in brain myelination, providing the feasibility of this method in clinics.

Development of white matter fiber covariance networks supports executive function in youth

During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.

Whole Brain and Corpus Callosum Fractional Anisotropy Differences in Patients with Cognitive Impairment

Diffusion tensor imaging (DTI) is an MRI analysis method that could help assess cognitive impairment (CI) in the ageing population more accurately. In this research, we evaluated fractional anisotropy (FA) of whole brain (WB) and corpus callosum (CC) in patients with normal cognition (NC), mild cognitive impairment (MCI), and moderate/severe cognitive impairment (SCI). In total, 41 participants were included in a cross-sectional study and divided into groups based on Montreal Cognitive Assessment (MoCA) scores (NC group, nine participants, MCI group, sixteen participants, and SCI group, sixteen participants). All participants underwent an MRI examination that included a DTI sequence. FA values between the groups were assessed by analysing FA value and age normative percentile. We did not find statistically significant differences between the groups when analysing CC FA values. Both approaches showed statistically significant differences in WB FA values between the MCI-SCI and MCI-NC groups, where the MCI group participants showed the highest mean FA and highest mean FA normative percentile results in WB.

Autism spectrum disorder-specific changes in white matter connectome edge density based on functionally defined nodes

Introduction

Autism spectrum disorder (ASD) is associated with both functional and microstructural connectome disruptions. We deployed a novel methodology using functionally defined nodes to guide white matter (WM) tractography and identify ASD-related microstructural connectome changes across the lifespan.

Methods

We used diffusion tensor imaging and clinical data from four studies in the national database for autism research (NDAR) including 155 infants, 102 toddlers, 230 adolescents, and 96 young adults - of whom 264 (45%) were diagnosed with ASD. We applied cortical nodes from a prior fMRI study identifying regions related to symptom severity scores and used these seeds to construct WM fiber tracts as connectome Edge Density (ED) maps. Resulting ED maps were assessed for between-group differences using voxel-wise and tract-based analysis. We then examined the association of ASD diagnosis with ED driven from functional nodes generated from different sensitivity thresholds.

Results

In ED derived from functionally guided tractography, we identified ASD-related changes in infants (pFDR ≤ 0.001-0.483). Overall, more wide-spread ASD-related differences were detectable in ED based on functional nodes with positive symptom correlation than negative correlation to ASD, and stricter thresholds for functional nodes resulted in stronger correlation with ASD among infants (z = -6.413 to 6.666, pFDR ≤ 0.001-0.968). Voxel-wise analysis revealed wide-spread ED reductions in central WM tracts of toddlers, adolescents, and adults.

Discussion

We detected early changes of aberrant WM development in infants developing ASD when generating microstructural connectome ED map with cortical nodes defined by functional imaging. These were not evident when applying structurally defined nodes, suggesting that functionally guided DTI-based tractography can help identify early ASD-related WM disruptions between cortical regions exhibiting abnormal connectivity patterns later in life. Furthermore, our results suggest a benefit of involving functionally informed nodes in diffusion imaging-based probabilistic tractography, and underline that different age cohorts can benefit from age- and brain development-adapted image processing protocols.

High resolution 0.5mm isotropic T1-weighted and diffusion tensor templates of the brain of non-demented older adults in a common space for the MIITRA atlas

High quality, high resolution T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates located in a common space can enhance the sensitivity and precision of template-based neuroimaging studies. However, such multimodal templates have not been constructed for the older adult brain. The purpose of this work which is part of the MIITRA atlas project was twofold: (A) to develop 0.5 mm isotropic resolution T1w and DTI templates that are representative of the brain of non-demented older adults and are located in the same space, using advanced multimodal template construction techniques and principles of super resolution on data from a large, diverse, community cohort of 400 non-demented older adults, and (B) to systematically compare the new templates to other standardized templates. It was demonstrated that the new MIITRA-0.5mm T1w and DTI templates are well-matched in space, exhibit good definition of brain structures, including fine structures, exhibit higher image sharpness than other standardized templates, and are free of artifacts. The MIITRA-0.5mm T1w and DTI templates allowed higher intra-modality inter-subject spatial normalization precision as well as higher inter-modality intra-subject spatial matching of older adult T1w and DTI data compared to other available templates. Consequently, MIITRA-0.5mm templates allowed detection of smaller inter-group differences for older adult data compared to other templates. The MIITRA-0.5mm templates were also shown to be most representative of the brain of non-demented older adults compared to other templates with submillimeter resolution. The new templates constructed in this work constitute two of the final products of the MIITRA atlas project and are anticipated to have important implications for the sensitivity and precision of studies on older adults.

Neurocognitive predictors of food memory in healthy adults - A preregistered analysis

Memory processes have long been known to determine food choices (Rozin & Zellner, 1985) but recognition memory of food and its cognitive, homeostatic and neuroanatomical predictors are still largely understudied. 60 healthy, overweight, non-restrictive eating adults (20 females) took part in a food wanting and subsequent food recognition and lure discrimination task at four time points after a standardized breakfast shake. With advanced tractography of 3 T diffusion-weighted imaging data, we investigated the influence of the uncinate fasciculus' (UF) brain microstructure on the interplay of food wanting and memory processes. The analysis was preregistered in detail and conducted with Bayesian multilevel regression modeling. Target recognition (d') and lure discrimination (LDI) performance of food tended to be higher than of art images while single image food memory accuracy evidently dominated art memory. On this single item level, wanting enhanced recognition accuracy and caloric content enhanced food memory accuracy. The enhancement by reward anticipation was most pronounced during memory encoding. Subjective hunger level did not predict performance on the memory task. The microstructure of the UF did neither evidently affect memory performance outcomes nor moderate the wanting enhancement of the recognition accuracy. Interestingly, female participants outperformed males on the memory task, and individuals with stronger neuroticism showed poorer memory performance. We shed light on to date understudied processes in food decision-making: reward anticipation influenced recognition accuracy and food memory was enhanced by higher caloric content, both effects might shape food decisions. Our findings indicate that brain microstructure does not affect food decision processes in adult populations with overweight. We suggest extending investigation of this interplay to brain activity as well as to populations with eating behaviour disorders.

Neuroanatomical differences in Latinx children from rural farmworker families and urban non-farmworker families and related associations with pesticide exposure

Exposure to pesticides in humans may lead to changes in brain structure and function and increase the likelihood of experiencing neurodevelopmental disorders. Despite the potential risks, there is limited neuroimaging research on the effects of pesticide exposure on children, particularly during the critical period of brain development. Here we used voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) from magnetic resonance images (MRI) to investigate neuroanatomical differences between Latinx children (n = 71) from rural, farmworker families (FW; n = 48) and urban, non-farmworker families (NFW; n = 23). Data presented here serves as a baseline for our ongoing study examining the longitudinal effects of living in a rural environment on neurodevelopment and cognition in children. The VBM analysis revealed that NFW children had higher volume in several distinct regions of white matter compared to FW children. Tract-based spatial statistics (TBSS) of DTI data also indicated NFW children had higher fractional anisotropy (FA) in several key white matter tracts. Although the difference was not as pronounced as white matter, the VBM analysis also found higher gray matter volume in selected regions of the frontal lobe in NFW children. Notably, white matter and gray matter findings demonstrated a high degree of overlap in the medial frontal lobe, a brain region predominantly linked to decision-making, error processing, and attention functions. To gain further insights into the underlying causes of the observed differences in brain structure between the two groups, we examined the association of organochlorine (OC) and organophosphate (OP) exposure collected from passive dosimeter wristbands with brain structure. Based on our previous findings within this data set, demonstrating higher OC exposure in children from non-farmworker families, we hypothesized OC might play a critical role in structural differences between NFW and FW children. We discovered a significant positive correlation between the number of types of OC exposure and the structure of white matter. The regions with significant association with OC exposure were in agreement with the findings from the FW-NFW groups comparison analysis. In contrast, OPs did not have a statistically significant association with brain structure. This study is among the first multimodal neuroimaging studies examining the brain structure of children exposed to agricultural pesticides, specifically OC. These findings suggest OC pesticide exposure may disrupt normal brain development in children, highlighting the need for further neuroimaging studies within this vulnerable population.

A deep neural network estimation of brain age is sensitive to cognitive impairment and decline

The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62×10-32; T1: r=0.61, p=1.45×10-26, FW+T1: r=0.77, p=6.48×10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: β=-1.094, p=6.32×10-7; T1: β=-1.331, p=6.52×10-7; FW+T1: β=-1.476, p=2.53×10-10; executive function, FW: β=-1.276, p=1.46×10-9; T1: β=-1.337, p=2.52×10-7; FW+T1: β=-1.850, p=3.85×10-17) and longitudinal cognition (memory, FW: β=-0.091, p=4.62×10-11; T1: β=-0.097, p=1.40×10-8; FW+T1: β=-0.101, p=1.35×10-11; executive function, FW: β=-0.125, p=1.20×10-10; T1: β=-0.163, p=4.25×10-12; FW+T1: β=-0.158, p=1.65×10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline.

Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging

Introduction

It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging.

Methods

Diffusion MRI data from several well-established longitudinal cohorts of aging (Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], Vanderbilt Memory & Aging Project [VMAP]) were free-water corrected and harmonized. This dataset included 1723 participants (age at baseline: 72.8 ± 8.87 years, 49.5% male) and 4605 imaging sessions (follow-up time: 2.97 ± 2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42 ± 1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed.

Results

While we found a global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging.

Conclusions

There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes.

HIGHLIGHTS

Longitudinal data were free-water corrected and harmonized.Global effects of white matter decline were seen in normal and abnormal aging.The free-water metric was most vulnerable to abnormal aging.Cingulum free-water was the most vulnerable to abnormal aging.

Spherical means-based free-water volume fraction from diffusion MRI increases non-linearly with age in the white matter of the healthy human brain

The term free-water volume fraction (FWVF) refers to the signal fraction that could be found as the cerebrospinal fluid of the brain, which has been demonstrated as a sensitive measure that correlates with cognitive performance and various neuropathological processes. It can be quantified by properly fitting the isotropic component of the magnetic resonance (MR) signal in diffusion-sensitized sequences. Using N=287 healthy subjects (178F/109M) aged 25-94, this study examines in detail the evolution of the FWVF obtained with the spherical means technique from multi-shell acquisitions in the human brain white matter across the adult lifespan, which has been previously reported to exhibit a positive trend when estimated from single-shell data using the bi-tensor signal representation. We found evidence of a noticeably non-linear gain after the sixth decade of life, with a region-specific variate and varying change rate of the spherical means-based multi-shell FWVF parameter with age, at the same time, a heteroskedastic pattern across the adult lifespan is suggested. On the other hand, the FW corrected diffusion tensor imaging (DTI) leads to a region-dependent flattened age-related evolution of the mean diffusivity (MD) and fractional anisotropy (FA), along with a considerable reduction in their variability, as compared to the studies conducted over the standard (single-component) DTI. This way, our study provides a new perspective on the trajectory-based assessment of the brain and explains the conceivable reason for the variations observed in FA and MD parameters across the lifespan with previous studies under the standard diffusion tensor imaging.

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

Functional alterations in bipartite network of white and grey matters during aging

The effects of normal aging on functional connectivity (FC) within various brain networks of gray matter (GM) have been well-documented. However, the age effects on the networks of FC between white matter (WM) and GM, namely WM-GM FC, remains unclear. Evaluating crucial properties, such as global efficiency (GE), for a WM-GM FC network poses a challenge due to the absence of closed triangle paths which are essential for assessing network properties in traditional graph models. In this study, we propose a bipartite graph model to characterize the WM-GM FC network and quantify these challenging network properties. Leveraging this model, we assessed the WM-GM FC network properties at multiple scales across 1,462 cognitively normal subjects aged 22-96 years from three repositories (ADNI, BLSA and OASIS-3) and investigated the age effects on these properties throughout adulthood and during late adulthood (age ≥70 years). Our findings reveal that (1) heterogeneous alterations occurred in region-specific WM-GM FC over the adulthood and decline predominated during late adulthood; (2) the FC density of WM bundles engaged in memory, executive function and processing speed declined with age over adulthood, particularly in later years; and (3) the GE of attention, default, somatomotor, frontoparietal and limbic networks reduced with age over adulthood, and GE of visual network declined during late adulthood. These findings provide unpresented insights into multi-scale alterations in networks of WM-GM functional synchronizations during normal aging. Furthermore, our bipartite graph model offers an extendable framework for quantifying WM-engaged networks, which may contribute to a wide range of neuroscience research.

Association of retinal nerve layers thickness and brain imaging in healthy young subjects from the i-Share-Bordeaux study

Given the anatomical and functional similarities between the retina and the brain, the retina could be a "window" for viewing brain structures. We investigated the association between retinal nerve fiber layers (peripapillary retinal nerve fiber layer, ppRNFL; macular ganglion cell-inner plexiform layer, GC-IPL; and macular ganglion cell complex, GCC), and brain magnetic resonance imaging (MRI) parameters in young health adults. We included 857 students (mean age: 23.3 years, 71.3% women) from the i-Share study. We used multivariate linear models to study the cross-sectional association of each retinal nerve layer thickness assessed by spectral-domain optical coherence tomography (SD-OCT) with structural (volumes and cortical thickness), and microstructural brain markers, assessed on MRI globally and regionally. Microstructural MRI parameters included diffusion tensor imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI). On global brain analysis, thicker ppRNFL, GC-IPL and GCC were all significantly associated with patterns of diffusion metrics consistent with higher WM microstructural integrity. In regional analyses, after multiple testing corrections, our results suggested significant associations of some retinal nerve layers with brain regional gray matter occipital volumes and with diffusion MRI parameters in a region involved in the visual pathway and in regions containing associative tracts. No associations were found with global volumes or with global or regional cortical thicknesses. Results of this study suggest that some retinal nerve layers may reflect brain structures. Further studies are needed to confirm these results in young subjects.

White matter microstructural integrity continues to develop from adolescence to young adulthood in mice and humans: Same phenotype, different mechanism

As direct evaluation of a mouse model of human neurodevelopment, adolescent and young adult mice and humans underwent MR diffusion tensor imaging to quantify age-related differences in microstructural integrity of brain white matter fibers. Fractional anisotropy (FA) was greater in older than younger mice and humans. Despite the cross-species commonality, the underlying developmental mechanism differed: whereas evidence for greater axonal extension contributed to higher FA in older mice, evidence for continuing myelination contributed to higher FA in human adolescent development. These differences occurred in the context of species distinctions in overall brain growth: whereas the continued growth of the brain and skull in the murine model can accommodate volume expansion into adulthood, human white matter volume and myelination continue growth into adulthood within a fixed intracranial volume. Appreciation of the similarities and differences in developmental mechanism can enhance the utility of animal models of brain white matter structure, function, and response to exogenous manipulation.

Cognition's dependence on functional network integrity with age is conditional on structural network integrity

Maintaining good cognitive function is crucial for well-being across the lifespan. We proposed that the degree of cognitive maintenance is determined by the functional interactions within and between large-scale brain networks. Such connectivity can be represented by the white matter architecture of structural brain networks that shape intrinsic neuronal activity into integrated and distributed functional networks. We explored how the function-structure connectivity convergence, and the divergence of functional connectivity from structural connectivity, contribute to the maintenance of cognitive function across the adult lifespan. Multivariate analyses were used to investigate the relationship between function-structure connectivity convergence and divergence with multivariate cognitive profiles, respectively. Cognitive function was increasingly dependent on function-structure connectivity convergence as age increased. The dependency of cognitive function on connectivity was particularly strong for high-order cortical networks and subcortical networks. The results suggest that brain functional network integrity sustains cognitive functions in old age, as a function of the integrity of the brain's structural connectivity.

Developmental and age differences in visuomotor adaptation across the lifespan

In the present cross-sectional study, we examined age and sex differences in sensorimotor adaptation. We tested 253 individuals at a local science museum (NEMO Science Museum, Amsterdam). Participants spanned a wide age range (8-70 years old; 54% male), allowing us to examine effects of both development and healthy aging within a single study. Participants performed a visuomotor adaptation task in which they had to adapt manual joystick movements to rotated visual feedback. We assessed the rate of adaptation following the introduction of the visual perturbation (both for early and later stages of adaptation), and the rate of de-adaptation following its removal. Results showed reliable adaptation patterns which did not differ by sex. We observed a quadratic relationship between age and both early adaptation and de-adaptation rates, with younger and older adults exhibiting the fasted adaptation rates. Our findings suggest that both younger and older age are associated with poorer strategic, cognitive processes involved in adaptation. We propose that developmental and age differences in cognitive functions and brain properties may underlie these effects on sensorimotor functioning.

Microstructural Alterations in Tract Development in College Football and Volleyball Players: A Longitudinal Diffusion MRI Study

BACKGROUND AND OBJECTIVES

Repeated impacts in high-contact sports such as American football can affect the brain's microstructure, which can be studied using diffusion MRI. Most imaging studies are cross-sectional, do not include low-contact players as controls, or lack advanced tract-specific microstructural metrics. We aimed to investigate longitudinal changes in high-contact collegiate athletes compared with low-contact controls using advanced diffusion MRI and automated fiber quantification.

METHODS

We examined brain microstructure in high-contact (football) and low-contact (volleyball) collegiate athletes with up to 4 years of follow-up. Inclusion criteria included university and team enrollment. Exclusion criteria included history of neurosurgery, severe brain injury, and major neurologic or substance abuse disorder. We investigated diffusion metrics along the length of tracts using nested linear mixed-effects models to ascertain the acute and chronic effects of subconcussive and concussive impacts, and associations between diffusion changes with clinical, behavioral, and sports-related measures.

RESULTS

Forty-nine football and 24 volleyball players (271 total scans) were included. Football players had significantly divergent trajectories in multiple microstructural metrics and tracts. Longitudinal increases in fractional anisotropy and axonal water fraction, and decreases in radial/mean diffusivity and orientation dispersion index, were present in volleyball but absent in football players (all findings |T-statistic|> 3.5, p value <0.0001). This pattern was present in the callosum forceps minor, superior longitudinal fasciculus, thalamic radiation, and cingulum hippocampus. Longitudinal differences were more prominent and observed in more tracts in concussed football players (n = 24, |T|> 3.6, p < 0.0001). An analysis of immediate postconcussion scans (n = 12) demonstrated a transient localized increase in axial diffusivity and mean/radial kurtosis in the uncinate and cingulum hippocampus (|T| > 3.7, p < 0.0001). Finally, within football players, those with high position-based impact risk demonstrated increased intracellular volume fraction longitudinally (T = 3.6, p < 0.0001).

DISCUSSION

The observed longitudinal changes seen in football, and especially concussed athletes, could reveal diminished myelination, altered axonal calibers, or depressed pruning processes leading to a static, nondecreasing axonal dispersion. This prospective longitudinal study demonstrates divergent tract-specific trajectories of brain microstructure, possibly reflecting a concussive and repeated subconcussive impact-related alteration of white matter development in football athletes.

Mixed longitudinal and cross-sectional analyses of deep gray matter and white matter using diffusion weighted images in premanifest and manifest Huntington's disease

Changes in the brain of patients with Huntington's disease (HD) begin years before clinical onset, so it remains critical to identify biomarkers to track these early changes. Metrics derived from tensor modeling of diffusion-weighted MRIs (DTI), that indicate the microscopic brain structure, can add important information to regional volumetric measurements. This study uses two large-scale longitudinal, multicenter datasets, PREDICT-HD and IMAGE-HD, to trace changes in DTI of HD participants with a broad range of CAP scores (a product of CAG repeat expansion and age), including those with pre-manifest disease (i.e., prior to clinical onset). Utilizing a fully automated data-driven approach to study the whole brain divided in regions of interest, we traced changes in DTI metrics (diffusivity and fractional anisotropy) versus CAP scores, using sigmoidal and linear regression models. We identified points of inflection in the sigmoidal regression using change-point analysis. The deep gray matter showed more evident and earlier changes in DTI metrics over CAP scores, compared to the deep white matter. In the deep white matter, these changes were more evident and occurred earlier in superior and posterior areas, compared to anterior and inferior areas. The curves of mean diffusivity vs. age of HD participants within a fixed CAP score were different from those of controls, indicating that the disease has an additional effect to age on the microscopic brain structure. These results show the regional and temporal vulnerability of the white matter and deep gray matter in HD, with potential implications for experimental therapeutics.

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.

Measures of MRI Brain Biomarkers in Middle Age According to Average Modified Mediterranean Diet Scores Throughout Young and Middle Adulthood

BACKGROUND

The Mediterranean diet (MedDiet) has been linked with better cognitive function and brain integrity.

OBJECTIVE

To examine the association of modified Mediterranean diet (mMedDiet) scores from early through middle adulthood in relation to volumetric and microstructural midlife MRI brain measures. Assess the association of mMedDiet and brain measures with four cognitive domains. If variables are correlated, determine if brain measures mediate the relationship between mMedDiet and cognition.

METHODS

618 participants (mean age 25.4±3.5 at year 0) of the Coronary Artery Risk Development in Young Adults (CARDIA) study were included. Cumulative average mMedDiet scores were calculated by averaging scores from years 0, 7, and 20. MRI scans were obtained at years 25 and 30. General linear models were used to examine the association between mMedDiet and brain measures.

RESULTS

Higher cumulative average mMedDiet scores were associated with better microstructural white matter (WM) integrity measured by fractional anisotropy (FA) at years 25 and 30 (all ptrend <0.05). Higher mMedDiet scores at year 7 were associated with higher WM FA at year 25 (β= 0.003, ptrend = 0.03). Higher mMedDiet scores at year 20 associated with higher WM FA at years 25 (β= 0.0005, ptrend = 0.002) and 30 (β= 0.0003, ptrend = 0.02). mMedDiet scores were not associated with brain volumes. Higher mMedDiet scores and WM FA were both correlated with better executive function, processing speed, and global cognition (all ptrend <0.05). WM FA did not mediate the association between mMedDiet scores and cognition.

CONCLUSIONS

mMedDiet scores may be associated with microstructural WM integrity at midlife.

C-NODDI: a constrained NODDI model for axonal density and orientation determinations in cerebral white matter

Purpose

Neurite orientation dispersion and density imaging (NODDI) provides measures of neurite density and dispersion through computation of the neurite density index (NDI) and the orientation dispersion index (ODI). However, NODDI overestimates the cerebrospinal fluid water fraction in white matter (WM) and provides physiologically unrealistic high NDI values. Furthermore, derived NDI values are echo-time (TE)-dependent. In this work, we propose a modification of NODDI, named constrained NODDI (C-NODDI), for NDI and ODI mapping in WM.

Methods

Using NODDI and C-NODDI, we investigated age-related alterations in WM in a cohort of 58 cognitively unimpaired adults. Further, NDI values derived using NODDI or C-NODDI were correlated with the neurofilament light chain (NfL) concentration levels, a plasma biomarker of axonal degeneration. Finally, we investigated the TE dependence of NODDI or C-NODDI derived NDI and ODI.

Results

ODI derived values using both approaches were virtually identical, exhibiting constant trends with age. Further, our results indicated a quadratic relationship between NDI and age suggesting that axonal maturation continues until middle age followed by a decrease. This quadratic association was notably significant in several WM regions using C-NODDI, while limited to a few regions using NODDI. Further, C-NODDI-NDI values exhibited a stronger correlation with NfL concentration levels as compared to NODDI-NDI, with lower NDI values corresponding to higher levels of NfL. Finally, we confirmed the previous finding that NDI estimation using NODDI was dependent on TE, while NDI derived values using C-NODDI exhibited lower sensitivity to TE in WM.

Conclusion

C-NODDI provides a complementary method to NODDI for determination of NDI in white matter.

Familial risk for major depression: differential white matter alterations in healthy and depressed participants

BACKGROUND

Major depressive disorder (MDD) has been associated with alterations in brain white matter (WM) microstructure. However, diffusion tensor imaging studies in biological relatives have presented contradicting results on WM alterations and their potential as biomarkers for vulnerability or resilience. To shed more light on associations between WM microstructure and resilience to familial risk, analyses including both healthy and depressed relatives of MDD patients are needed.

METHODS

In a 2 (MDD v. healthy controls, HC) × 2 (familial risk yes v. no) design, we investigated fractional anisotropy (FA) via tract-based spatial statistics in a large well-characterised adult sample (N = 528), with additional controls for childhood maltreatment, a potentially confounding proxy for environmental risk.

RESULTS

Analyses revealed a significant main effect of diagnosis on FA in the forceps minor and the left superior longitudinal fasciculus (ptfce-FWE = 0.009). Furthermore, a significant interaction of diagnosis with familial risk emerged (ptfce-FWE = 0.036) Post-hoc pairwise comparisons showed significantly higher FA, mainly in the forceps minor and right inferior fronto-occipital fasciculus, in HC with as compared to HC without familial risk (ptfce-FWE < 0.001), whereas familial risk played no role in MDD patients (ptfce-FWE = 0.797). Adding childhood maltreatment as a covariate, the interaction effect remained stable.

CONCLUSIONS

We found widespread increased FA in HC with familial risk for MDD as compared to a HC low-risk sample. The significant effect of risk on FA was present only in HC, but not in the MDD sample. These alterations might reflect compensatory neural mechanisms in healthy adults at risk for MDD potentially associated with resilience.

Evidence of An Association Between Cerebral Blood Flow and Microstructural Integrity in Normative Aging Using a Holistic MRI Approach

BACKGROUND

Cerebral tissue integrity decline and cerebral blood flow (CBF) alteration are major aspects of motor and cognitive dysfunctions and neurodegeneration. However, little is known about the association between blood flow and brain microstructural integrity, especially in normal aging.

PURPOSE

To assess the association between CBF and cerebral microstructural integrity.

STUDY TYPE

Cross sectional.

POPULATION

A total of 94 cognitively unimpaired adults (mean age 50.7 years, age range between 22 and 88 years, 56 Men).

FIELD STRENGTH/SEQUENCE

A 3 T; pseudo-continuous arterial spin labeling (pCASL), diffusion tensor imaging (DTI), Bayesian Monte Carlo analysis of multicomponent driven equilibrium steady-state observation of T1 and T2 (BMC-mcDESPOT).

ASSESSMENT

Lobar associations between CBF derived from pCASL, and longitudinal relaxation rate (R1 ), transverse relaxation rate (R2 ) and myelin water fraction (MWF) derived from BMC-mcDESPOT, or radial diffusivity (RD), axial diffusivity (AxD), mean diffusivity (MD) and fractional anisotropy (FA) derived from DTI were assessed.

STATISTICAL TESTS

Multiple linear regression models were used using the mean region of interest (ROI) values for MWF, R1 , R2 , FA, MD, RD, or AxD as the dependent variable and CBF, age, age2 , and sex as the independent variables. A two-sided P value of <0.05 defined statistical significance.

RESULTS

R1 , R2 , MWF, FA, MD, RD, and AxD parameters were associated with CBF in most of the cerebral regions evaluated. Specifically, higher CBF values were significantly associated with higher FA, MWF, R1 and R2 , or lower MD, RD and AxD values.

DATA CONCLUSION

These findings suggest that cerebral tissue microstructure may be impacted by global brain perfusion, adding further evidence to the intimate relationship between cerebral blood supply and cerebral tissue integrity.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 4.

Brain-wide associations between white matter and age highlight the role of fornix microstructure in brain ageing

Unveiling the details of white matter (WM) maturation throughout ageing is a fundamental question for understanding the ageing brain. In an extensive comparison of brain age predictions and age-associations of WM features from different diffusion approaches, we analyzed UK Biobank diffusion magnetic resonance imaging (dMRI) data across midlife and older age (N = 35,749, 44.6-82.8 years of age). Conventional and advanced dMRI approaches were consistent in predicting brain age. WM-age associations indicate a steady microstructure degeneration with increasing age from midlife to older ages. Brain age was estimated best when combining diffusion approaches, showing different aspects of WM contributing to brain age. Fornix was found as the central region for brain age predictions across diffusion approaches in complement to forceps minor as another important region. These regions exhibited a general pattern of positive associations with age for intra axonal water fractions, axial, radial diffusivities, and negative relationships with age for mean diffusivities, fractional anisotropy, kurtosis. We encourage the application of multiple dMRI approaches for detailed insights into WM, and the further investigation of fornix and forceps as potential biomarkers of brain age and ageing.

Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography

White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.

Bio-psycho-social factors' associations with brain age: a large-scale UK Biobank diffusion study of 35,749 participants

Brain age refers to age predicted by brain features. Brain age has previously been associated with various health and disease outcomes and suggested as a potential biomarker of general health. Few previous studies have systematically assessed brain age variability derived from single and multi-shell diffusion magnetic resonance imaging data. Here, we present multivariate models of brain age derived from various diffusion approaches and how they relate to bio-psycho-social variables within the domains of sociodemographic, cognitive, life-satisfaction, as well as health and lifestyle factors in midlife to old age (N = 35,749, 44.6-82.8 years of age). Bio-psycho-social factors could uniquely explain a small proportion of the brain age variance, in a similar pattern across diffusion approaches: cognitive scores, life satisfaction, health and lifestyle factors adding to the variance explained, but not socio-demographics. Consistent brain age associations across models were found for waist-to-hip ratio, diabetes, hypertension, smoking, matrix puzzles solving, and job and health satisfaction and perception. Furthermore, we found large variability in sex and ethnicity group differences in brain age. Our results show that brain age cannot be sufficiently explained by bio-psycho-social variables alone. However, the observed associations suggest to adjust for sex, ethnicity, cognitive factors, as well as health and lifestyle factors, and to observe bio-psycho-social factor interactions' influence on brain age in future studies.

Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging

INTRODUCTION

It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging.

METHODS

Diffusion MRI data from several well-established longitudinal cohorts of aging [Alzheimer's Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory & Aging Project (VMAP)] was free-water corrected and harmonized. This dataset included 1,723 participants (age at baseline: 72.8±8.87 years, 49.5% male) and 4,605 imaging sessions (follow-up time: 2.97±2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42±1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed.

RESULTS

While we found global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging.

CONCLUSIONS

There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes.

HIGHLIGHTS

Longitudinal data was free-water corrected and harmonizedGlobal effects of white matter decline were seen in normal and abnormal agingThe free-water metric was most vulnerable to abnormal agingCingulum free-water was the most vulnerable to abnormal aging.