Age and sex effects on advanced white matter microstructure measures in 15,628 older adults: A UK biobank study

Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure

OBJECTIVE

Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults.

METHODS

Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid β1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract.

RESULTS

AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect.

INTERPRETATION

Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.

Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22-37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92-0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.

Brain signaling becomes less integrated and more segregated with age

The integration-segregation framework is a popular first step to understand brain dynamics because it simplifies brain dynamics into two states based on global vs. local signaling patterns. However, there is no consensus for how to best define what the two states look like. Here, we map integration and segregation to order and disorder states from the Ising model in physics to calculate state probabilities, P int and P seg , from functional MRI data. We find that integration/segregation decreases/increases with age across three databases, and changes are consistent with weakened connection strength among regions rather than topological connectivity based on structural and diffusion MRI data.

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

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

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

Structural changes in corticospinal tract profiling via multishell diffusion models and their relation to overall survival in glioblastoma

PURPOSE

Advanced MR fiber tracking imaging reflects fiber bundle invasion by glioblastoma, particularly of the corticospinal tract (CST), which is more susceptible as the largest downstream fiber tracts. We aimed to investigate whether CST features can predict the overall survival of glioblastoma.

METHODS

In this prospective secondary analysis, 40 participants (mean age, 58 years; 16 male) pathologically diagnosed with glioblastoma were enrolled. Diffusion spectrum MRI was used for CST reconstruction. Fifty morphological and diffusion indicators (DTI, DKI, NODDI, MAP and Q-space) were used to characterize the CST. Optimal parameters capturing fiber bundle damage were obtained through various grouping methods. Eventually, the correlation with overall survival was determined by the hazard ratios (HRs) from various Cox proportional hazard model combinations.

RESULTS

Only intracellular volume fraction (ICVF) and non-Gaussianity (NG) values on the affected tumor level were significant in all four groups or stratified comparisons (all P < .05). During the median follow-up 698 days, only the ICVF on the affected tumor level was independently associated with overall survival, even after adjusting for all classic prognostic factors (HR [95 % CI]: 0.611 [0.403, 0.927], P = .021). Moreover, stratification by the ICVF on the affected tumor level successfully predicted risk (P < .01) and improved the C-index of the multivariate model (from 0.695 to 0.736).

CONCLUSIONS

This study demonstrates a relationship between NODDI-derived CST features, ICVF on the affected tumor level, and overall survival in glioblastoma. Independent of classical prognostic factors for glioblastoma, a lower ICVF on the affected tumor level might predict a lower overall survival.

MRI volumetry and diffusion tensor imaging for diagnosis and follow-up of late post-traumatic injuries

BACKGROUND

Traumatic Brain Injury (TBI) is a major cause of acquired disability and can cause devastating and progressive post-traumatic encephalopathy. TBI is a dynamic condition that continues to evolve over time. A better understanding of the pathophysiology of these late lesions is important for the development of new therapeutic strategies.

OBJECTIVES

The primary objective was to compare the ability of fluid-attenuated reversion recovery (FLAIR) and diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) markers to identify participants with a Glasgow outcome scale extended (GOS-E) score of 7-8, up to 10 years after their original TBI. The secondary objective was to study the brain regionalization of DTI markers. Finally, we analyzed the evolution of late-developing brain lesions using repeated MRI images, also taken up to 10 years after the TBI.

METHODS

In this retrospective study, participants were included from a cohort of people hospitalized following a severe TBI. Following their discharge, they were followed-up and clinically assessed, including a DTI-MRI scan, between 2012 and 2016. We performed a cross-sectional analysis on 97 participants at a median (IQR) of 5 years (3-6) post-TBI, and a further post-TBI longitudinal analysis over 10 years on a subpopulation (n = 17) of the cohort.

RESULTS

Although the area under the curve (AUC) of FLAIR, fractional anisotropy (FA), and mean diffusivity (MD) were not significantly different, only the AUC of FA was statistically greater than 0.5. In addition, only the FA was correlated with clinical outcomes as assessed by GOS-E score (P<10-4). On the cross-sectional analysis, DTI markers allowed study post-TBI white matter lesions by region. In the longitudinal subpopulation analysis, the observed number of brain lesions increased for the first 5 years post-TBI, before stabilizing over the next 5 years.

CONCLUSIONS

This study has shown for the first time that post-TBI lesions can present in a two-phase evolution. These results must be confirmed in larger studies. French Data Protection Agency (Commission nationale de l'informatique et des libertés; CNIL) study registration no: 1934708v0.

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.

Correlates of axonal content in healthy adult span: Age, sex, myelin, and metabolic health

As the emerging treatments that target grey matter pathology in Alzheimer's Disease have limited effectiveness, there is a critical need to identify new neural targets for treatments. White matter's (WM) metabolic vulnerability makes it a promising candidate for new interventions. This study examined the age and sex differences in estimates of axonal content, as well the associations of with highly prevalent modifiable health risk factors such as metabolic syndrome and adiposity. We estimated intra-axonal volume fraction (ICVF) using the Neurite Orientation Dispersion and Density Imaging (NODDI) in a sample of 89 cognitively and neurologically healthy adults (20-79 years). We showed that ICVF correlated positively with age and estimates of myelin content. The ICVF was also lower in women than men, across all ages, which difference was accounted for by intracranial volume. Finally, we found no association of metabolic risk or adiposity scores with the current estimates of ICVF. In addition, the previously observed adiposity-myelin associations (Burzynska et al., 2023) were independent of ICVF. Although our findings confirm the vulnerability of axons to aging, they suggest that metabolic dysfunction may selectively affect myelin content, at least in cognitively and neurologically healthy adults with low metabolic risk, and when using the specific MRI techniques. Future studies need to revisit our findings using larger samples and different MRI approaches, and identify modifiable factors that accelerate axonal deterioration as well as mechanisms linking peripheral metabolism with the health of myelin.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

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.

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.

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.

Evaluating Fiber Orientation Dispersion Measures Computed From Single-Shell Diffusion MRI

Fiber orientation dispersion is one of the fundamental features that can be estimated from diffusion magnetic resonance imaging (dMRI) of the brain. Several approaches have been proposed to estimate dispersion from single- and multi-shell dMRI acquisitions. Here, we derive solutions to bring these proposed methods to a standard orientation dispersion index (ODI) with the goal of making them comparable across different dMRI acquisitions. To illustrate the utility of the measures in studying brain aging, we further examined the age-dependent trajectory of the different single- and multi-shell ODI estimates in the white matter across the lifespan.Clinical Relevance- This work computes metrics of brain microstructure that can be adapted for large neuroimaging initiatives that aim to study the brain's development and aging, and to identify deviations that may serve as biomarkers of brain disease.

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.

Temporal Diffusion Ratio (TDR) for imaging restricted diffusion: Optimisation and pre-clinical demonstration

Temporal Diffusion Ratio (TDR) is a recently proposed dMRI technique (Dell'Acqua et al., proc. ISMRM 2019) which provides contrast between areas with restricted diffusion and areas either without restricted diffusion or with length scales too small for characterisation. Hence, it has a potential for informing on pore sizes, in particular the presence of large axon diameters or other cellular structures. TDR employs the signal from two dMRI acquisitions obtained with the same, large, b-value but with different diffusion gradient waveforms. TDR is advantageous as it employs standard acquisition sequences, does not make any assumptions on the underlying tissue structure and does not require any model fitting, avoiding issues related to model degeneracy. This work for the first time introduces and optimises the TDR method in simulation for a range of different tissues and scanner constraints and validates it in a pre-clinical demonstration. We consider both substrates containing cylinders and spherical structures, representing cell soma in tissue. Our results show that contrasting an acquisition with short gradient duration, short diffusion time and high gradient strength with an acquisition with long gradient duration, long diffusion time and low gradient strength, maximises the TDR contrast for a wide range of pore configurations. Additionally, in the presence of Rician noise, computing TDR from a subset (50% or fewer) of the acquired diffusion gradients rather than the entire shell as proposed originally further improves the contrast. In the last part of the work the results are demonstrated experimentally on rat spinal cord. In line with simulations, the experimental data shows that optimised TDR improves the contrast compared to non-optimised TDR. Furthermore, we find a strong correlation between TDR and histology measurements of axon diameter. In conclusion, we find that TDR has great potential and is a very promising alternative (or potentially complement) to model-based approaches for informing on pore sizes and restricted diffusion in general.

Adult lifespan maturation and degeneration patterns in gray and white matter: A mean apparent propagator (MAP) MRI study

The relationship between brain microstructure and aging has been the subject of intense study, with diffusion MRI perhaps the most effective modality for elucidating these associations. Here, we used the mean apparent propagator (MAP)-MRI framework, which is suitable to characterize complex microstructure, to investigate age-related cerebral differences in a cohort of cognitively unimpaired participants and compared the results to those derived using diffusion tensor imaging. We studied MAP-MRI metrics, among them the non-Gaussianity (NG) and propagator anisotropy (PA), and established an opposing pattern in white matter of higher NG alongside lower PA among older adults, likely indicative of axonal degradation. In gray matter, however, these two indices were consistent with one another, and exhibited regional pattern heterogeneity compared to other microstructural parameters, which could indicate fewer neuronal projections across cortical layers along with an increased glial concentration. In addition, we report regional variations in the magnitude of age-related microstructural differences consistent with the posterior-anterior shift in aging paradigm. These results encourage further investigations in cognitive impairments and neurodegeneration.

Sensory processing sensitivity and axonal microarchitecture: identifying brain structural characteristics for behavior

Previous research using functional MRI identified brain regions associated with sensory processing sensitivity (SPS), a proposed normal phenotype trait. To further validate SPS, to characterize it anatomically, and to test the usefulness in psychology of methodologies that assess axonal properties, the present study correlated SPS proxy questionnaire scores (adjusted for neuroticism) with diffusion tensor imaging (DTI) measures. Participants (n = 408) from the Human Connectome Project were studied. Voxelwise analysis showed that mean- and radial diffusivity correlated positively with SPS scores in the right and left subcallosal and anterior-ventral cingulum bundle, and the right forceps minor of the corpus callosum, all frontal cortex areas generally underlying emotion, motivation, and cognition. Further analyses showed correlations throughout medial frontal cortical regions in the right and left ventromedial prefrontal cortex, including the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate, and arcuate fasciculus. Fractional anisotropy was negatively correlated with SPS scores in white matter (WM) of the right premotor/motor/somatosensory/supramarginal gyrus regions. Region of interest (ROI) analysis showed small effect sizes (- 0.165 to 0.148) in WM of the precuneus and inferior frontal gyrus. Other ROI effects were found in the dorsal-, ventral visual pathways and primary auditory cortex. The results reveal that in a large group of participants, axonal microarchitectural differences can be identified with SPS traits that are subtle and in the range of typical behavior. The results suggest that the heightened sensory processing in people who show that SPS may be influenced by the microstructure of WM in specific cortical regions. Although previous fMRI studies had identified most of these areas, the DTI results put a new focus on brain areas related to attention and cognitive flexibility, empathy, emotion, and first levels of sensory processing, as in primary auditory cortex. Psychological trait characterization may benefit from DTI methodology by identifying influential brain systems for traits.

Comparison of region-of-interest delineation methods for diffusion tensor imaging in patients with cervical spondylotic radiculopathy

Background

Diffusion tensor imaging is a promising technique for determining the responsible lesion of cervical radiculopathy, but the selection and delineation of the region of interest (ROI) affect the results. This study explored the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy (CSR).

Methods

This retrospective study included CSR patients who underwent DTI imaging. The images were analyzed independently by two radiologists. Four delineation methods were used: freehand method, maximum roundness, quadrilateral method, and multi-point averaging method. They re-examined the images 6 weeks later. The intra-class correlation coefficient (ICC) was used to investigate the consistency between the two measurements and the reproducibility between two radiologists.

Results

Forty-two CSR patients were included in this study. The distribution of the compressed nerve roots was five C4, eight C5, sixteen C6, eleven C7, and two C8. No differences were found among the four methods in fractional anisotropy (FA) or apparent diffusion coefficient (ADC), irrespective of radiologists (all P>0.05). Similar results were observed between the first and second measurements (all P>0.05), but some significant differences were observed for radiologist 2 for the four-small rounds method (P=0.033). The freehand and single largest circle methods were the two methods with the highest ICC between the two measurements and the two radiologists (all ICC >0.90).

Conclusion

The freehand and single largest circle methods were the most consistent methods for delineating DTI ROI in patients with CSR.

Aging and white matter microstructure and macrostructure: a longitudinal multi-site diffusion MRI study of 1218 participants

Quantifying the microstructural and macrostructural geometrical features of the human brain's connections is necessary for understanding normal aging and disease. Here, we examine brain white matter diffusion magnetic resonance imaging data from one cross-sectional and two longitudinal data sets totaling in 1218 subjects and 2459 sessions of people aged 50-97 years. Data was drawn from well-established cohorts, including the Baltimore Longitudinal Study of Aging data set, Cambridge Centre for Ageing Neuroscience data set, and the Vanderbilt Memory & Aging Project. Quantifying 4 microstructural features and, for the first time, 11 macrostructure-based features of volume, area, and length across 120 white matter pathways, we apply linear mixed effect modeling to investigate changes in pathway-specific features over time, and document large age associations within white matter. Conventional diffusion tensor microstructure indices are the most age-sensitive measures, with positive age associations for diffusivities and negative age associations with anisotropies, with similar patterns observed across all pathways. Similarly, pathway shape measures also change with age, with negative age associations for most length, surface area, and volume-based features. A particularly novel finding of this study is that while trends were homogeneous throughout the brain for microstructure features, macrostructural features demonstrated heterogeneity across pathways, whereby several projection, thalamic, and commissural tracts exhibited more decline with age compared to association and limbic tracts. The findings from this large-scale study provide a comprehensive overview of the age-related decline in white matter and demonstrate that macrostructural features may be more sensitive to heterogeneous white matter decline. Therefore, leveraging macrostructural features may be useful for studying aging and could facilitate comparisons in a variety of diseases or abnormal conditions.

The Association Between Selenium, Selenoprotein P (SEPP1), Fluid Intelligence, and Exercise in the UK Biobank Cohort

BACKGROUND

In the mouse hippocampus, exercise boosts neurogenesis. Increased levels of the selenium transport protein selenoprotein P (SEPP1) in the serum of exercised animals may contribute to the impact of exercise. SEPP1 is a protein that aids in the delivery of selenium to the brain. The effect of exercise on mouse brain precursor cell proliferation was diminished when SEPP1 or its receptor were genetically depleted. Selenium supplementation in the diet had the same effect as exercise in reducing some of the cognitive impairments associated with aging.

METHODS

In the current analysis, we sought to determine the association of selenium, the SEPP1 gene, fluid intelligence, and exercise in the UK Biobank Cohort. We analyzed SEPP1 single nucleotide polymorphism (SNP) rs7579, a single nucleotide variation (SNV), position chr5:42800706, C > T, minor allele frequency T = 0.281. Its consequence is a 3'- UTR variant. The 3'-UTR contains regulatory regions that post-transcriptionally influence gene expression and is responsible for selenoprotein synthesis. SNP rs7579 has been implicated in multiple forms of cancer. The univariate general linear model of SPSS (IBM Corp., Armonk, NY) was used to rule out the effects of age, years of education, and vigorous activity on fluid intelligence score, with fluid intelligence score as the dependent variable, rs7579 genotype, and selenium supplements as fixed factors, and age, years of education, and vigorous activity as covariates.

RESULTS

The effect of rs7579 genotype on fluid intelligence score was insignificant (p = 0.702). The effect of selenium supplements on fluid intelligence score was insignificant (p = 0.107). The interaction of rs7579 genotype and selenium supplements was insignificant (p = 0.911) and unrelated to the significant effects of age (p < 0.001), years of education (p < 0.001), and vigorous activity (p < 0.001) on fluid intelligence score.  Conclusion: Our multivariate analysis of SEPP1 genotype, selenium supplement use, and fluid intelligence scores is consistent with the negligible effect selenium supplements seem to have on cognition. Selenium is found in nuts, dairy products, and grains. These foods can provide sufficient selenium for health. Selenium supplements are not recommended.

Age Differences in Diffusivity in the Locus Coeruleus and its Ascending Noradrenergic Tract

The noradrenergic locus coeruleus (LC) is a small brainstem nucleus that promotes arousal and attention. Recent studies have examined the microstructural properties of the LC using diffusion-weighted magnetic resonance imaging and found unexpected age-related differences in fractional anisotropy - a measure of white matter integrity. Here, we used two datasets (Berlin Aging Study-II, N = 301, the Leipzig Study for Mind-Body-Emotion Interactions, N = 220), to replicate published findings and expand them by investigating diffusivity in the LC’s ascending noradrenergic bundle. In younger adults, LC fractional anisotropy was significantly lower, compared to older adults. However, in the LC’s ascending noradrenergic bundle, we observed significantly higher fractional anisotropy in younger adults, relative to older adults. These findings indicate that diffusivity in the LC versus the ascending noradrenergic bundle are both susceptible to structural changes in aging that have opposing effects on fractional anisotropy.

Neurite Orientation Dispersion and Density Imaging in Psychiatric Disorders: A Systematic Literature Review and a Technical Note

While major psychiatric disorders lack signature diagnostic neuropathologies akin to dementias, classic postmortem studies have established microstructural involvement, i.e., cellular changes in neurons and glia, as a key pathophysiological finding. Advanced magnetic resonance imaging techniques allow mapping of cellular tissue architecture and microstructural abnormalities in vivo, which holds promise for advancing our understanding of the pathophysiology underlying psychiatric disorders. Here, we performed a systematic review of case-control studies using neurite orientation dispersion and density imaging (NODDI) to assess brain microstructure in psychiatric disorders and a selective review of technical considerations in NODDI. Of the 584 potentially relevant articles, 18 studies met the criteria to be included in this systematic review. We found a general theme of abnormal gray and white matter microstructure across the diagnostic spectrum. We also noted significant variability in patterns of neurite density and fiber orientation within and across diagnostic groups, as well as associations between brain microstructure and phenotypical variables. NODDI has been successfully used to detect subtle microstructure abnormalities in patients with psychiatric disorders. Given that NODDI indices may provide a more direct link to pathophysiological processes, this method may not only contribute to advancing our mechanistic understanding of disease processes, it may also be well positioned for next-generation biomarker development studies.

A Component or Multiple Components of Bleeding Gums May Ameliorate Both Glaucoma and Alzheimer’s Disease

Background: Although clinical studies have shown an increased prevalence of primary open-angle glaucoma (POAG) in patients with Alzheimer’s disease (AD), a population-based epidemiologic study from Denmark found no increased risk of Alzheimer’s disease in patients with glaucoma, and other studies have failed to demonstrate a link. However, a possible relationship between POAG and AD might manifest in their association with oral pathology. Dental caries, periodontal disease, stomatitis, and the related inflammatory burden increase AD risk, while oral pathology and the oral microbiome correlate with POAG vulnerability. To further examine the relationship, we analyzed POAG, AD, and oral disease in the UK Biobank (UKBB) cohort.

Methods: Our analysis included all subjects with POAG and AD. POAG diagnosis was ascertained using the 10th Revision of the International Classification of Diseases (ICD-10), H40.11. AD diagnosis was ascertained using the 10th Revision of the International Classification of Diseases (ICD-10), G30. Oral cavity, ulceration, stomatitis, periodontitis, teeth, and dental problems were in UKBB data field 6149.

Results: A “yes” answer to a question about bleeding gums is associated with a greater proportional POAG reduction (24.2%) than a “yes” answer to having none of the six listed problems (6.3%). Similarly, bleeding gums were associated with a greater proportional AD reduction (46.2% versus 16.9%). Logistic regression controlling for age and sex showed that bleeding gums (no/yes) were negatively associated with AD (odds ratio (OR) = 0.713, 95% confidence interval (CI) = 0.521-0.976, p = 0.035). Age-weighted least-squares linear regression showed that the lower corneal-compensated intraocular pressure (IOP) in the left eye was associated with bleeding gums (unstandardized regression coefficient = -0.174, p < 0.001), controlling for type 2 diabetes and past smoking.

Conclusion: It is difficult to predict what component or components of periodontal inflammation might be ameliorating POAG and AD. Prostaglandin is a possibility. Identification of the component or components could lead to new treatments for POAG and AD. Further studies are warranted.