Mean Diffusivity Research Articles

Automatic deep learning segmentation of the hippocampus on high-resolution diffusion magnetic resonance imaging and its application to the healthy lifespan.

Diffusion tensor imaging (DTI) can provide unique contrast and insight into microstructural changes with age or disease of the hippocampus, although it is difficult to measure the hippocampus because of its comparatively small size, location, and shape. This has been markedly improved by the advent of a clinically feasible 1-mm isotropic resolution 6-min DTI protocol at 3 T of the hippocampus with limited brain coverage of 20 axial-oblique slices aligned along its long axis. However, manual segmentation is too laborious for large population studies, and it cannot be automatically segmented directly on the diffusion images using traditional T1 or T2 image-based methods because of the limited brain coverage and different contrast. An automatic method is proposed here that segments the hippocampus directly on high-resolution diffusion images based on an extension of well-known deep learning architectures like UNet and UNet++ by including additional dense residual connections. The method was trained on 100 healthy participants with previously performed manual segmentation on the 1-mm DTI, then evaluated on typical healthy participants (n = 53), yielding an excellent voxel overlap with a Dice score of ~ 0.90 with manual segmentation; notably, this was comparable with the inter-rater reliability of manually delineating the hippocampus on diffusion magnetic resonance imaging (MRI) (Dice score of 0.86). This method also generalized to a different DTI protocol with 36% fewer acquisitions. It was further validated by showing similar age trajectories of volumes, fractional anisotropy, and mean diffusivity from manual segmentations in one cohort (n = 153, age 5-74 years) with automatic segmentations from a second cohort without manual segmentations (n = 354, age 5-90 years). Automated high-resolution diffusion MRI segmentation of the hippocampus will facilitate large cohort analyses and, in future research, needs to be evaluated on patient groups.

High O3 pollution initiated by cold front passage over Pearl River Estuary

The influence of cold fronts on the formation of ozone (O3) pollution, particularly the contributions of physical and chemical processes to O3 abundance during the passage of cold fronts in winter over the Pearl River Estuary (PRE) region was still unclear. This study provided an in-depth analysis on the occurrence of high O3 pollution based on data from field measurements and simulation of a chemical transport model (i.e., WRF-Chem) over the PRE region during winter 2021 when cold fronts were frequently observed. Totally 7 high O3 episode days were observed during pre- and post-frontal stages at DWS (i.e., Da Wan Shan island), a downwind island site of the inland Pearl River Delta (PRD) region, which were accompanied with the prevailing northerly wind patterns with insignificant variations of wind speeds in a stable boundary layer over the whole PRE region. The quantitative analysis based on simulation results indicated that horizontal transport and chemical processes accounted for the buildup of O3 abundance at DWS, with the highest mean rates of 7.3 and 5.6 ppbv/h at pre- and post-frontal stages, respectively. The high contributions from horizontal transport to O3 levels at DWS were associated with the persistent northerly winds with small variations, while the contributions of chemical processes were varied with the abundance of precursors and meteorological conditions. However, vertical transport made negative contributions to O3 abundance, with the most significant mean diffusion rate of −2.6 ppbv/h at the frontal stage because of the control of high-pressure system, while the less influence of vertical transport at pre- and post-frontal stages was associated with the weak pressure gradient forces and wind patterns. The sensitivity analysis further demonstrated that the emissions of precursors from the inland PRD region contributed 50–76% to O3 abundance over PRE at different stages. Overall, the above results quantitatively confirmed the dominant role of transport from inland PRD to the O3 pollution over the downwind PRE region and were helpful for better understanding of O3 pollution in winter over PRE.

The role of formal schooling in the development of children's reading and arithmetic white matter networks.

Children's white matter development is driven by experience, yet it remains poorly understood how it is shaped by attending formal education. A small number of studies compared children before and after the start of formal schooling to understand this, yet they do not allow to separate maturational effects from schooling-related effects. A clever way to (quasi-)experimentally address this issue is the longitudinal school cut-off design, which compares children who are similar in age but differ in schooling (because they are born right before or after the cut-off date for school entry). We used for the first time such a longitudinal school cut-off design to experimentally investigate the effect of schooling on children's white matter networks. We compared "young" first graders (schooling group, n=34; Mage=68 months; 20 girls) and "old" preschoolers (non-schooling group, n=33; Mage=66 months; 18 girls) that were similar in age but differed in the amount of formal instruction they received. Our study revealed that changes in fractional anisotropy and mean diffusivity in five a priori selected white matter tracts during the transition from preschool to primary school were predominantly driven by age-related maturation. We did not find specific schooling effects on white matter, despite their strong presence for early reading and early arithmetic skills. The present study is the first to disentangle the effects of age-related maturation and schooling on white matter within a longitudinal cohort of 5-year-old preschoolers. RESEARCH HIGHLIGHTS: White matter tracts that have been associated with reading and arithmetic may be susceptible to experience-dependent neuroplasticity when children learn to read and calculate. This longitudinal study used the school cut-off design to isolate schooling-induced from coinciding maturational influences on children's white matter development. White matter changes during the transition from preschool to primary school are predominantly driven by age-related maturation and not by schooling effects. Strong effects of schooling on behavior were shown for early reading and early arithmetic, but not for verbal ability and spatial ability.

Leptin bioavailability and markers of brain atrophy and vascular injury in the middle age.

We investigated the associations of leptin markers with cognitive function and magnetic resonance imaging (MRI) measures of brain atrophy and vascular injury in healthy middle-aged adults. We included 2262 cognitively healthy participants from the Framingham Heart Study with neuropsychological evaluation; of these, 2028 also had available brain MRI. Concentrations of leptin, soluble leptin receptor (sOB-R), and their ratio (free leptin index [FLI]), indicating leptin bioavailability, were measured using enzyme-linked immunosorbent assays. Cognitive and MRI measures were derived using standardized protocols. Higher sOB-R was associated with lower fractional anisotropy (FA, β=-0.114±0.02, p<0.001), and higher free water (FW, β=0.091±0.022, p<0.001) and peak-width skeletonized mean diffusivity (PSMD, β=0.078±0.021, p<0.001). Correspondingly, higher FLI was associated with higher FA (β=0.115±0.027, p<0.001) and lower FW (β=-0.096±0.029, p=0.001) and PSMD (β=-0.085±0.028, p=0.002). Higher leptin bioavailability was associated with better white matter (WM) integrity in healthy middle-aged adults, supporting the putative neuroprotective role of leptin in late-life dementia risk. Higher leptin bioavailability was related to better preservation of white matter microstructure. Higher leptin bioavailability during midlife might confer protection against dementia. Potential benefits might be even stronger for individuals with visceral obesity. DTI measures might be sensitive surrogate markers of subclinical neuropathology.

Spatial and temporal patterns of cortical mean diffusivity in Alzheimer's disease and suspected non-Alzheimer's disease pathophysiology.

The spatial and temporal patterns of cortical mean diffusivity (cMD), as well as its association with Alzheimer's disease (AD) and suspected non-Alzheimer's pathophysiology (SNAP), are not yet fully understood. We compared baseline (n=617) and longitudinal changes (n=421) of cMD, cortical thickness, and gray matter volume and their relations to vascular risk factors, amyloid beta (Aβ), and tau positron emission tomography (PET), and longitudinal cognitive decline in Aβ PET negative and positive older adults. cMD increases were more sensitive to detecting brain structural alterations than cortical thinning and gray matter atrophy. Tau-related cMD increases partially mediated Aβ-related cognitive decline in AD, whereas vascular disease-related increased cMD levels substantially mediated age-related cognitive decline in SNAP. These findings revealed the dynamic changes of microstructural and macrostructural indicators and their associations with AD and SNAP, providing novel insights into understanding upstream and downstream events of cMD in neurodegenerative disease. Cortical mean diffusivity (cMD) was more sensitive to detecting structural changes than macrostructural factors. Tau-related cMD increases partially mediated amyloid beta-related cognitive decline in Alzheimer's disease (AD). White matter hyperintensity-related higher cMD mainly explained the age-related cognitive decline in suspected non-Alzheimer's pathophysiology (SNAP). cMD may assist in tracking earlier neurodegenerative signs in AD and SNAP.

A worldwide study of white matter microstructural alterations in people living with Parkinson’s disease

The progression of Parkinson’s disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences. Diffusion-weighted MRI data from 1654 participants diagnosed with PD (age: 20–89 years; 33% female) and 885 controls (age: 19–84 years; 47% female) were analyzed using the ENIGMA-DTI protocol to evaluate white matter microstructure. Skeletonized maps of fractional anisotropy (FA) and mean diffusivity (MD) were compared across Hoehn and Yahr (HY) disease groups and controls to reveal the profile of white matter alterations at different stages. We found an enhanced, more widespread pattern of microstructural alterations with each stage of PD, with eventually lower FA and higher MD in almost all regions of interest: Cohen’s d effect sizes reached d = −1.01 for FA differences in the fornix at PD HY Stage 4/5. The early PD signature in HY stage 1 included higher FA and lower MD across the entire white matter skeleton, in a direction opposite to that typical of other neurodegenerative diseases. FA and MD were associated with motor and non-motor clinical dysfunction. While overridden by degenerative changes in the later stages of PD, early PD is associated with paradoxically higher FA and lower MD in PD, consistent with early compensatory changes associated with the disorder.

An integration of neuroimaging and serum proteomics analysis suggests immune and inflammation are associated with white matter microstructure changes in cerebral small vessel disease with depressive symptoms

IntroductionDepressive symptoms are a common concomitant of cerebral small vessel disease (CSVD), of which pathogenesis requires more study. White matter microstructural abnormalities and proteomic alternation have been widely reported regarding depression in the elderly with CSVD. Exploring the relationship between cerebral white matter microstructural alterations and serum proteins may complete the explanation of molecular mechanisms for the findings from neuroimaging research of CSVD combined with depressive symptoms. MethodsAn untargeted proteomics approach based on mass spectrometry was used to obtain serum proteomic profiles, which were clustered into co-expression protein modules. White matter microstructural integrity was measured using the FMRIB Software Library (FSL) and MATLAB to analyze diffusion tensor imaging (DTI) data and calculate the differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) for 50 regions of interest (ROI). Integrating the proteome with the DTI results, weighted gene co-expression analysis (WGCNA) was used to identify protein modules related to white matter microstructural alterations, and the proteins of the corresponding modules were analyzed for functional enrichment through bioinformatics techniques. ResultsDTI measurements were analCerebral small vessel disease (CSVD); Depression; Diffusion tensor imaging (DTI); Proteomics; Inflammationyzed between individuals with CSVD and depressive symptoms (CSVD+D) (n = 24) and those without depressive symptoms (CSVD-D) (n = 35). Results showed an overall increase in MD, AD, and RD within the left hemisphere of the CSVD+D group, suggesting widespread loss of white matter integrity and axonal demyelination, including left superior longitudinal fasciculus (SLF), left posterior corona radiata (PCR) and right external capsule (EC). We identified two protein modules associated with DTI diffusivity, and functional enrichment analyses revealed that complement and coagulation cascades and immune responses participate in the alternation of white matter microstructure in the CSVD+D group. ConclusionThe results suggested immune- and inflammation-related mechanism was associated with white matter microstructure changes in CSVD with depressive symptoms

Effect of worry, depressed affect, and sensitivity to environmental stress owing to neurotic personality on MRI markers of cerebral small vessel disease: A univariable and multivariable Mendelian randomization study

ObjectiveNeuroticism was found to be associated with cerebral small vessel disease (CSVD) in observational studies. We aimed to explore the causal relationship between distinct components of neuroticism and CSVD. MethodsTwo-sample mendelian randomization (MR) study was conducted to explore the bidirectional causal relationships between three genetically distinct subclusters of neuroticism (depressed affect, worry, and sensitivity to environmental stress and adversity [SESA]) and MRI markers of CSVD using publicly available genome-wide association studies (GWAS) data. Inverse variance weighted (IVW) method was used for the primary causal estimates. Alternative MR approaches and extensive sensitivity analyses were conducted to ensure the robustness of the findings. Multivariable MR (MVMR) analysis was used to estimate the direct causal effects with adjustment of other known risk factors for CSVD. ResultsGenetically determined SESA was significantly associated with reduced fractional anisotropy (FA) (beta: -1.94, 95%CI: -3.04 to -0.84, p=5.29e-4), and associated with increased mean diffusivity (MD) (beta=1.55, 95%CI: 0.29 to 2.81, p=0.016) and white matter hyperintensities (WMH) (beta=0.25, 95% CI: 0.03 to 0.47, p=0.029) at the nominally significant level. MVMR analysis suggested the significant associations remained significant after accounting for body mass index (BMI), smoking, alcohol drinking, type 2 diabetes (T2D), hypertension, and depression. The other two neuroticism subclusters (depressed affect and worry) didn't have significant causal effects on the MRI markers. In the reverse MR analysis with the MRI markers as exposures, no significant associations were found. ConclusionThis study supported the casual role of SESA in the development of CSVD. Further research to explore the underlying mechanism are warranted.

Fractional Anisotropy is a More Sensitive Diagnostic Biomarker Than Mean Kurtosis for Patients with Parkinson Disease with Cognitive Dysfunction: A Diffusional Kurtosis Map Tract-Based Spatial Statistics Study.

There is heterogeneity of white matter damage in Parkinson's disease patients with different cognitive states. Our aim was to find sensitive diffusional kurtosis imaging biomarkers to differentiate the white matter damage pattern of mild cognitive impairment and dementia. Nineteen patients with Parkinson disease with mild cognitive impairment and 18 patients with Parkinson disease with dementia were prospectively enrolled. All participants underwent MR examination with 3D-T1-weighted image and diffusional kurtosis imaging sequences. Demographic data were compared between the 2 groups. Voxelwise statistical analyses of diffusional kurtosis imaging parameters were performed using tract-based spatial statistics. The receiver operator characteristic curve of significantly different metrics was graphed. The correlation of significantly different metrics with global cognitive status was analyzed. Compared with the Parkinson disease with mild cognitive impairment group, the fractional anisotropy and mean kurtosis values decreased in 4 independent clusters in the forceps minor, forceps major, inferior fronto-occipital fasciculus, and the inferior and superior longitudinal fasciculus in patients with Parkinson disease with dementia; the mean diffusivity decreased in 1 cluster in the forceps minor. The fractional anisotropy value in the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus would be the diffusional kurtosis imaging marker for the differential diagnosis of Parkinson disease with mild cognitive impairment and patients with Parkinson disease with dementia, with the best diagnostic efficiency of 0.853. The fractional anisotropy values in the forceps minor (β = 84.20, P < .001) and years of education (β = 0.38, P = .014) were positively correlated with the Montreal Cognitive Assessment. The diffusional kurtosis imaging-derived fractional anisotropy and mean kurtosis can detect the different white matter damage patterns of Parkinson disease with mild cognitive impairment and Parkinson disease with dementia. Fractional anisotropy is more sensitive than mean kurtosis in the differential diagnosis; fractional anisotropy derived from diffusional kurtosis imaging could become a promising imaging marker for the differential diagnosis of Parkinson disease with mild cognitive impairment and Parkinson disease with dementia.

Role of diffusion tensor imaging of extra ocular muscles and orbital fat in Graves’s ophthalmopathy and relation to disease activity

BackgroundGraves’ ophthalmopathy (GO) is one of the most common autoimmune inflammatory disorders affecting the orbit that characterized by swelling of extra ocular muscles (EOMs) and expansion of the orbital fat. Diffusion tensor imaging (DTI) could assess the microstructural integrity of tissue. We aimed at this study to assess the role of DTI in the evaluation of EOMs and orbital fat in GO and identify the relationship with disease activity.ResultsCase–control study included 40 patients diagnosed as Graves’ disease (20 active and 20 inactive) and 10 health control subjects underwent DTI. Low fraction anisotropy (FA) and high mean diffusivity (MD) of inferior rectus (IR), medial rectus (MR) and orbital fat in GO versus healthy control (HC), while high FA and high MD in active group versus inactive group. In order to differentiate between GO and HC; FA cutoff point of IR, MR& orbital fat were 0.46, 0.45 and 0.26 with sensitivity 98.8%,98.8% and 93.8% and specificity 95.0%, 95.0% and 85%, respectively. MD cutoff point for IR, MR and orbital fat 1.24, 1.27 and 1.275 with sensitivity 97.5%, 98.8% and 98.8% and specificity 95.0%, 95% and 95%, respectively. To differentiate between active and inactive GO; FA cutoff point of IR, MR and orbital fat were 0.35, 0.36 and 0.22 respectively with sensitivity 80.0%, 82.5% and 72.5% and specificity 95.0%, 85.0% and 65.0%, respectively. MD cutoff point for IR, MR and orbital fat were 1.58, 1.63 and 1.54 respectively with sensitivity 90.0%, 97.5% and 85.0%, and specificity 90.0%, 80.0% and 62.5%, respectively.ConclusionsDTI parameters (FA and MD) of EOMs and orbital fat are considered as crucial radiological biomarkers for diagnosis of GO and could quantitatively differentiate active form inactive disease.

Non-invasive Assessment of Microstructural Changes After CyberKnife Radiosurgery for Trigeminal Neuralgia Using Diffusion Tensor Imaging

Background and Aims: Given the absence of a universally accepted non-invasive and objective clinical tool to predict a patient’s response to stereotactic radiosurgery for Trigeminal Neuralgia (TN), this research endeavoured to appraise the potential of Diffusion Tensor Imaging as a predictive tool in managing TN. Objective: This study aimed to assess microstructural changes in the trigeminal nerve following CyberKnife radiosurgery (CKRS) for TN using diffusion tensor imaging (DTI) and to correlate these changes with clinical outcomes. Methods: Twenty-eight TN patients treated with CKRS underwent pre and 4-month post-treatment Three-Tesla magnetic resonance imaging scans with DTI metrics, including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD), were collected. Clinical outcomes were assessed using the Barrow Neurological Institute Pain Intensity Score (BNI-PIS) at fourth, sixth and ninth months post-CKRS. Results: Twenty-four patients reported good pain relief (responders), while four patients did not experience adequate relief (non-responders). Responders exhibited significantly lower FA (mean drop of 13.8%, P &lt; .001) and lower RA (mean drop of 16.1%, P &lt; .001) compared to non-responders. RD, AD and MD remained constant across the study cohort. Conclusion: DTI metrics, particularly FA and RA, at 4 months post-CKRS, emerged as predictors of long-term treatment effectiveness for TN. These findings suggest the potential utility of DTI in evaluating microstructural changes in the trigeminal nerve post-CKRS and predicting clinical outcomes.

Amyloid, Tau, and APOE in Alzheimer's Disease: Impact on White Matter Tracts.

Alzheimer's disease (AD) is characterized by cognitive decline and memory loss due to the abnormal accumulation of amyloid-beta (Aβ) plaques and tau tangles in the brain; its onset and progression also depend on genetic factors such as the apolipoprotein E (APOE) genotype. Understanding how these factors affect the brain's neural pathways is important for early diagnostics and interventions. Tractometry is an advanced technique for 3D quantitative assessment of white matter tracts, localizing microstructural abnormalities in diseased populations in vivo. In this work, we applied BUAN (Bundle Analytics) tractometry to 3D diffusion MRI data from 730 participants in ADNI3 (phase 3 of the Alzheimer's Disease Neuroimaging Initiative; age range: 55-95 years, 349M/381F, 214 with mild cognitive impairment, 69 with AD, and 447 cognitively healthy controls). Using along-tract statistical analysis, we assessed the localized impact of amyloid, tau, and APOE genetic variants on the brain's neural pathways. BUAN quantifies microstructural properties of white matter tracts, supporting along-tract statistical analyses that identify factors associated with brain microstructure. We visualize the 3D profile of white matter tract associations with tau and amyloid burden in Alzheimer's disease; strong associations near the cortex may support models of disease propagation along neural pathways. Relative to the neutral genotype, APOE ϵ3/ϵ3, carriers of the AD-risk conferring APOE ϵ4 genotype show microstructural abnormalities, while carriers of the protective ϵ2 genotype also show subtle differences. Of all the microstructural metrics, mean diffusivity (MD) generally shows the strongest associations with AD pathology, followed by axial diffusivity (AxD) and radial diffusivity (RD), while fractional anisotropy (FA) is typically the least sensitive metric. Along-tract microstructural metrics are sensitive to tau and amyloid accumulation, showing the potential of diffusion MRI to track AD pathology and map its impact on neural pathways.

Effects of post-acute COVID-19 syndrome on cerebral white matter and emotional health among non-hospitalized individuals.

Post-acute COVID syndrome (PACS) is a growing concern, given its impact on mental health and quality of life. However, its effects on cerebral white matter remain poorly understood, particularly in non-hospitalized cohorts. The goals of this cross-sectional, observational study were to examine (1) whether PACS was associated with distinct alterations in white matter microstructure, compared to symptom-matched non-COVID viral infection; and (2) whether microstructural alterations correlated with indices of post-COVID emotional health. Data were collected for 54 symptomatic individuals who tested positive for COVID-19 (mean age 41 ± 12 yrs., 36 female) and 14 controls who tested negative for COVID-19 (mean age 41 ± 14 yrs., 8 female), with both groups assessed an average of 4-5 months after COVID testing. Diffusion magnetic resonance imaging data were collected, and emotional health was assessed via the NIH emotion toolbox, with summary scores indexing social satisfaction, well-being and negative affect. Despite similar symptoms, the COVID-19 group had reduced mean and axial diffusivity, along with increased mean kurtosis and neurite dispersion, in deep white matter. After adjusting for social satisfaction, higher levels of negative affect in the COVID-19 group were also correlated with increased mean kurtosis and reduced free water in white matter. These results provide preliminary evidence that indices of white matter microstructure distinguish PACS from symptomatic non-COVID infection. Moreover, white matter effects seen in PACS correlate with the severity of emotional sequelae, providing novel insights into this highly prevalent disorder.

Association of glycosylated hemoglobin concentrations with structural and functional brain changes in the normoglycemic population: A systematic review.

Optimal glucose control is crucial for maintaining brain health and preventing metabolic and cognitive disorders in the general population. Glycosylated hemoglobin (HbA1c) serves as a key marker for assessing glucose intolerance and its impact on brain structure and function in healthy individuals. However, existing literature presents conflicting findings, necessitating a systematic review to consolidate current knowledge in this domain. This systematic review examines 26 English-language studies involving participants aged 15 years and above, investigating the relationship between HbA1c levels and brain health. Studies focusing on normal/general populations and utilizing magnetic resonance imaging (MRI) as the imaging modality were included. Exclusion criteria encompassed review articles, abstracts, letters, animal studies, and research involving neuropsychiatric or metabolic diseases. Data were gathered from PubMed, Scopus, and Web of Science databases up to November 2023. Analysis reveals significant associations between HbA1c levels and various brain metrics, including volume, cortical thickness, fractional anisotropy, mean diffusivity, activity, and connectivity. However, findings exhibit inconsistency, likely attributed to disparities in sample characteristics and study sizes. Notably, hippocampal volume, white matter hyperintensity, and ventral attention network connectivity emerge as frequently affected structures and functions, mirroring trends observed in diabetic populations. Despite inconclusive evidence, glucose intolerance appears to exert considerable influence on select brain structures and functions in individuals without diagnosed metabolic disorders. Understanding these associations is critical for mitigating the risk of cognitive decline and dementia in healthy populations. Future investigations should aim to elucidate the intricate relationship between HbA1c concentrations and brain health parameters in normoglycemic individuals.

Synergistic effects of GFAP and Aβ42: Implications for white matter integrity and verbal memory across the cognitive spectrum

BackgroundPlasma glial fibrillary acidic protein (GFAP), an astrocytic biomarker, has previously been linked with Alzheimer's disease (AD) status, amyloid levels, and memory performance in older adults. The neuroanatomical pathways by which astrogliosis/astrocyte reactivity might impact cognitive outcomes remains unclear. We evaluated whether plasma GFAP and amyloid levels had a synergistic effect on fornix structure, which is critically involved in AD-associated cholinergic pathways. We also examined whether fornix structure mediates associations between GFAP and verbal memory. MethodsIn a cohort of both asymptomatic and symptomatic older adults (total n = 99), we assessed plasma GFAP, amyloid-β42 (Aβ42), other AD-related proteins, and vascular markers, and we conducted comprehensive memory testing. Tractography-based methods were used to assess fornix structure with whole brain diffusion metrics to control for diffuse alterations in brain white matter. ResultsIn individuals in the low plasma amyloid-β42 (Aβ42) group, higher plasma GFAP was associated with lower fractional anisotropy (FA; p = 0.007), higher mean diffusivity (MD; p < 0.001), higher radial diffusivity (RD; p < 0.001), and higher axial diffusivity (DA; p = 0.001) in the left fornix. These associations were independent of APOE gene status, plasma levels of total tau and neurofilament light, plasma vascular biomarkers, and whole brain diffusion metrics. In a sub-analysis of participants in the low plasma Aβ42 group (n = 33), fornix structure mediated the association between higher plasma GFAP levels and lower verbal memory performance. DiscussionHigher plasma GFAP was associated with altered fornix microstructure in the setting of greater amyloid deposition. We also expanded on our prior GFAP-verbal memory findings by demonstrating that in the low plasma Aβ42 group, left fornix integrity may be a primary white matter conduit for the negative associations between GFAP and verbal memory performance. Overall, these findings suggest that astrogliosis/astrocyte reactivity may play an early, pivotal role in AD pathogenesis, and further demonstrate that high GFAP and low Aβ42 in plasma may reflect a particularly detrimental synergistic role in forniceal-memory pathways.

Mapping macrostructural and microstructural brain alterations in patients with neuronal intranuclear inclusion disease.

Neuronal intranuclear inclusion disease (NIID) is a rare complex neurodegenerative disorder presents with various radiological features. The study aimed to investigate the structural abnormalities in NIID using multi-shell diffusion MR. Twenty-eight patients with adult-onset NIID and 32 healthy controls were included. Volumetric and diffusion MRI measures, including volume, fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) of six brain structures, including cortex, subcortical GM, cerebral WM, cerebellar GM and WM, and brainstem, were obtained and compared between NIID and healthy controls. Associations between MRI measures and clinical variables were investigated. Brain lesions of NIID included corticomedullary junction lesions on DWI, confluent leukoencephalopathy, lesions on callosum, cerebellar middle peduncle, cerebellar paravermal area and brainstem, and brain atrophy. Compared to healthy controls, NIID showed extensive volume loss of all the six brain regions (all p < 0.001); lower FA in cerebral WM (p < 0.001); higher MD in all WM regions; lower ODI in cortex (p < 0.001); higher ODI in subcortical GM (p < 0.001) and brainstem (p = 0.016); lower ICVF in brainstem (p = 0.001), and cerebral WM (p < 0.001); higher ISOVF in all the brain regions (p < 0.001). Higher MD of cerebellar WM was associated with worse cognitive level as evaluated by MoCA scores (p = 0.011). NIID patients demonstrated widespread brain atrophy but heterogeneous diffusion alterations. Cerebellar WM integrity impairment was correlated with the cognitive decline. The findings of the current study offer a sophisticated picture of brain structural alterations in NIID.

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

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

Evaluation of microstructural brain changes in post-coronavirus disease 2019 (COVID-19) patients with neurological symptoms: a cross-sectional study.

Changes in both the vascular system and brain tissues can occur after a prior episode of coronavirus disease 2019 (COVID-19), detectable through modifications in diffusion parameters using magnetic resonance imaging (MRI) techniques. These changes in diffusion parameters may be particularly prominent in highly organized structures such as the corpus callosum (CC), including its major components, which have not been adequately studied following COVID-19 infection. Therefore, the study aimed to evaluate microstructural changes in whole-brain (WB) diffusion, with a specific focus on the CC. A total of 101 probands (age range from 18 to 69 years) participated in this retrospective study, consisting of 55 volunteers and 46 post-COVID-19 patients experiencing neurological symptoms. The participants were recruited from April 2022 to September 2023 at the Institute for Clinical and Experimental Medicine in Prague, Czech Republic. All participants underwent MRI examinations on a 3T MR scanner with a diffusion protocol, complemented by additional MRI techniques. Two volunteers and five patients were excluded from the study due to motion artefacts, severe hypoperfusion or the presence of lesions. Participants were selected by a neurologist based on clinical examination and a serological test for COVID-19 antibodies. They were then divided into three groups: a control group of healthy volunteers (n=28), an asymptomatic group (n=25) with a history of infection but no symptoms, and a symptomatic group (n=41) with a history of COVID-19 and neurological symptoms. Symptomatic patients did not exhibit neurological symptoms before contracting COVID-19. Diffusion data underwent eddy current and susceptibility distortion corrections, and fiber tracking was performed using default parameters in DSI studio. Subsequently, various diffusion metrics, were computed within the reconstructed tracts of the WB and CC. To assess the impact of COVID-19 and its associated symptoms on diffusion indices within the white matter of the WB and CC regions, while considering age, we employed a statistical analysis using a linear mixed-effects model within the R framework. Statistical analysis revealed a significant difference in mean diffusivity (MD) between the symptomatic and control groups in the forceps minor (P=0.001) and CC body (P=0.003). In addition to changes in diffusion, alterations in brain perfusion were observed in two post-COVID-19 patients who experienced a severe course. Furthermore, hyperintense lesions were identified in subcortical and deep white matter areas in the vast majority of symptomatic patients. The main finding of our study was that post-COVID-19 patients exhibit increased MD in the forceps minor and body of the CC. This finding suggests a potential association between microstructural brain changes in post-COVID-19 patients and reported neurological symptoms, with significant implications for research and clinical applications.

Monoexponential and advanced diffusion-weighted imaging for hepatic fibrosis staging based on high inter-examiner reliability.

To determine the diagnostic efficiencies of multiple diffusion-weighted imaging (DWI) techniques for hepatic fibrosis (HF) staging under the premise of high inter-examiner reliability. Participants with biopsy-confirmed HF were recruited and divided into the early HF (EHF) and advanced HF (AHF) groups; healthy volunteers (HVs) served as controls. Two examiners analyzed intravoxel incoherent motion (IVIM) using the IVIM-DWI and diffusion kurtosis imaging (DKI) models. Intravoxel incoherent motion-DWI, DKI, and diffusion tensor imaging parameters with intraclass correlation coefficients (ICCs) of ≥0.6 were used to create regression models: HVs vs. EHF and EHF vs. AHF. We enrolled 48 HVs, 59 EHF patients, and 38 AHF patients. Mean, radial, and axial kurtosis; fractional anisotropy; mean, radial, and axial diffusivity; and α exhibited excellent reliability (ICCs: 0.80-0.98). Fractional anisotropy of kurtosis, f, and apparent diffusion coefficient showed good reliability (ICCs: 0.69-0.92). The real (0.58-0.67), pseudo- (0.27-0.76), and distributed diffusion coefficients (0.58-0.67) showed low reliability. In the HVs versus (vs.) EHF model, α (p=0.008) and ADC (p=0.011) presented statistical differences (area under curve [AUC]: 0.710). In the EHF vs. AHF model, α (p=0.04) and distributed diffusion coefficient (p=0.02) presented significant differences (AUC: 0.758). Under the premise of high inter-examiner reliability, DWI and IVIM-derived stretched-exponential model parameters may help stage HF.

Microstructural Changes in the Corpus Callosum in Neurodegenerative Diseases.

The corpus callosum, the largest white matter structure in the brain, plays a crucial role in interhemispheric communication and cognitive function. This review examines the microstructural changes observed in the corpus callosum across various neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis (ALS). New neuroimaging studies, mainly those that use diffusion tensor imaging (DTI) and advanced tractography methods, were put together to show how changes have happened in the organization of white matter and the connections between them. Some of the most common ways the corpus callosum breaks down are discussed, including less fractional anisotropy, higher mean diffusivity, and atrophy in certain regions. The relationship between these microstructural changes and cognitive decline, motor dysfunction, and disease progression is explored. Additionally, we consider the potential of corpus callosum imaging as a biomarker for early disease detection and monitoring. Studies show that people with these disorders have lower fractional anisotropy and higher mean diffusivity in the corpus callosum, often in ways that are specific to the disease. These changes often happen before gray matter atrophy and are linked to symptoms, which suggests that the corpus callosum could be used as an early sign of neurodegeneration. The review also highlights the implications of these findings for understanding disease mechanisms and developing therapeutic strategies. Future directions, including the application of advanced imaging techniques and longitudinal studies, are discussed to elucidatethe role of corpus callosum degeneration in neurodegenerative processes. This review underscores the importance of the corpus callosum in understanding the pathophysiology of neurodegenerative diseases and its potential as a target for therapeutic interventions.