Matter Microstructural Changes Research Articles

Atypical connectome topography and signal flow in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.

Distinct longitudinal brain white matter microstructure changes and associated polygenic risk of common psychiatric disorders and Alzheimer’s disease in the UK Biobank

BackgroundDuring 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 process has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, in particular, in terms of WM features, provides a cornerstone in the understanding of aging. MethodsWe use longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (N=2,678; 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 (PGRS) for the most common neurodegenerative disorder, Alzheimer's disease, and common psychiatric disorders (uni- and bipolar depression, anxiety, obsessive-compulsive, autism, schizophrenia, attention-deficit-hyperactivity) in longitudinal (N=2,329) and cross-sectional UKB validation data (N=31,056). ResultsOur findings indicate spatially distributed WM changes across the brain, as well as distributed associations of PGRS with WM. Importantly, brain longitudinal changes reflected the 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. ConclusionsWe exctend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain ageing processes. Further longitudinal research is warranted to examine ageing-related gene-brain associations.

White and gray matter integrity evaluated by MRI-DTI can serve as noninvasive and reliable indicators of structural and functional alterations in chronic neurotrauma

We aimed to evaluate whether white and gray matter microstructure changes observed with magnetic resonance imaging (MRI)-based diffusion tensor imaging (DTI) can be used to reflect the progression of chronic brain trauma. The MRI-DTI parameters, neuropathologic changes, and behavioral performance of adult male Wistar rats that underwent moderate (2.1 atm on day “0”) or repeated mild (1.5 atm on days “0” and “2”) traumatic brain injury (TBI or rmTBI) or sham operation were evaluated at 7 days, 14 days, and 1–9 months after surgery. Neurobehavioral tests showed that TBI causes long-term motor, cognitive and neurological deficits, whereas rmTBI results in more significant deficits in these paradigms. Both histology and MRI show that rmTBI causes more significant changes in brain lesion volumes than TBI. In vivo DTI further reveals that TBI and rmTBI cause persistent microstructural changes in white matter tracts (such as the body of the corpus callosum, splenium of corpus callus, internal capsule and/or angular bundle) of both two hemispheres. Luxol fast blue measurements reveal similar myelin loss (as well as reduction in white matter thickness) in ipsilateral and contralateral hemispheres as observed by DTI analysis in injured rats. These data indicate that the disintegration of microstructural changes in white and gray matter parameters analyzed by MRI-DTI can serve as noninvasive and reliable markers of structural and functional level alterations in chronic TBI.

Cumulative Dosage of Intrathecal Chemotherapy Agents Predicts White Matter Integrity in Long-Term Survivors of Acute Lymphoblastic Leukemia: A PETALE Study.

Acute lymphoblastic leukemia (ALL) stands as the most prevalent form of pediatric cancer in North America, with a current five-year survival rate of 85%. While more children achieved ALL remission and transition into adulthood, the prevalence of long-term treatment-related effects, especially neurocognitive sequelae, remains significant. This study pursues two objectives. Firstly, it investigates if Magnetization Transfer Ratio (MTR), a method assessing myelin integrity, is sensitive to white matter (WM) microstructural changes in long-term ALL survivors and whether these relate to cognitive impairments. Secondly, it examines the dose-related effects of chemotherapy agents on the MTR and its relationship to other risk factors such as female sex, early age diagnosis, and cranial radiotherapy. Magnetization transfer imaging was utilized to assess WM integrity in 35 survivors at a mean of 18.9 years after the onset of ALL (range since diagnosis: 6.9-26.8). Additionally, 21 controls matched for age, sex, and education level, with no history of cancer, were included. MTR was extracted from both the entire brain's WM and the corpus callosum through semi-automated procedures. The results indicated lower MTR means in survivors, which is linked to cognitive function. Negative associations between MTR means and intrathecal agents' (MTX, cytarabine, and hydrocortisone) cumulative doses received were highlighted. This study offers valuable insights into the connections between myelin deterioration, cognitive impairment, and the implications of IT chemotherapy, enhancing our understanding of ALL survivorship dynamics. It underscores MTR's relevance in monitoring neurotoxicity during oncological drug follow-up examinations.

Fronto-limbic white matter microstructural changes in psychiatrically healthy adults with childhood trauma.

Childhood trauma (CT) may influence brain white matter microstructure; however, few studies have examined the differential impact of distinct CT types on white matter microstructure in psychiatrically healthy adults living in a developing country. In adults without significant medical or psychiatric disorders, we investigated the association(s) between CT, including abuse and neglect, and fractional anisotropy (FA) of limbic tracts previously shown to be associated with CT. Participants underwent diffusion tensor imaging and completed the Childhood Trauma Questionnaire. Multivariate analysis of variance models were used to test the effects of total overall CT, as well as CT subtypes, on FA in six fronto-limbic tracts, adjusting for age, sex, and educational level. The final sample included 69 adults (age 47 ± 17 years; 70% female). Overall, CT had a significant main effect on FA for tracts of interest (p < .001). Greater CT severity was associated with lower FA for the bilateral and left stria terminalis (uncorrected) as well as the bilateral, left, and right anterior limb of the internal capsule (ALIC; corrected). Exposure to total non-violent/deprivational trauma specifically was associated with lower FA of the bilateral, left, and right ALIC, suggesting that distinct types of CT are associated with differential white matter changes in apparently healthy adults. The ALIC predominantly carries fibers connecting the thalamus with prefrontal cortical regions. Microstructural alterations in the ALIC may be associated with functional brain changes, which may be adaptive or increase the risk of accelerated age-related cognitive decline, maladaptive behaviors, and subsyndromal psychiatric symptoms.

Prenatal alcohol exposure and white matter microstructural changes across the first 6–7 years of life: A longitudinal diffusion tensor imaging study of a South African birth cohort

Prenatal alcohol exposure (PAE) can affect brain development in early life, but few studies have investigated the effects of PAE on trajectories of white matter tract maturation in young children. Here we used diffusion weighted imaging (DWI) repeated over three time points, to measure the effects of PAE on patterns of white matter microstructural development during the pre-school years. Participants were drawn from the Drakenstein Child Health Study (DCHS), an ongoing birth cohort study conducted in a peri-urban community in the Western Cape, South Africa. A total of 342 scans acquired from 237 children as neonates (N = 82 scans: 30 PAE; 52 controls) and at ages 2–3 (N = 121 scans: 27 PAE; 94 controls) and 6–7 years (N = 139 scans: 45 PAE; 94 controls) were included. Maternal alcohol use during pregnancy and other antenatal covariates were collected from 28 to 32 weeks’ gestation. Linear mixed effects models with restricted maxium likelihood to accommodate missing data were implemented to investigate the effects of PAE on fractional anisotropy (FA) and mean diffusivity (MD) in specific white matter tracts over time, while adjusting for child sex and maternal education. We found significant PAE-by-time effects on trajectories of FA development in the left superior cerebellar peduncle (SCP-L: p = 0.001; survived FDR correction) and right superior longitudinal fasciculus (SLF-R: p = 0.046), suggesting altered white matter development among children with PAE. Compared with controls, children with PAE demonstrated a more rapid change in FA in these tracts from the neonatal period to 2–3 years of age, followed by a more tapered trajectory for the period from 2–3 to 6–7 years of age, with these trajectories differing from unexposed control children. Given their supporting roles in various aspects of neurocognitive functioning (i.e., motor regulation, learning, memory, language), altered patterns of maturation in the SCP and SLF may contribute to a spectrum of physical, social, emotional, and cognitive difficulties often experienced by children with PAE. This study highlights the value of repeated early imaging in longitudinal studies of PAE, and focus for early childhood as a critical window of potential susceptibility as well as an opportunity for early intervention.

Brain white matter microstructural changes in chemotherapy-treated older long-term breast cancer survivors.

To assess white matter microstructural changes in older long-term breast cancer survivors 5-15 years post-chemotherapy treatment. Breast cancer survivors aged 65 years or older who underwent chemotherapy (C+) and who did not undergo chemotherapy (C-) and age- and sex-matched healthy controls (HC) were enrolled at time point 1 (TP1) and followed for 2 years for time point 2 (TP2). All participants underwent brain MRI with diffusion tensor images and neuropsychological (NP) testing with the NIH Toolbox Cognition Battery. Tract-based spatial statistics (TBSS) analysis was performed on the diffusion tensor images to assess white matter microstructural changes with the fractional anisotropy (FA) parameter. There were significant longitudinal alterations in FA within the C+ group over time. The C+ group showed diminished FA in the body and genu of corpus callosum, anterior corona radiate, and external capsule on both the whole brain and region of interest (ROI) based analyses after p < 0.05 family-wise error (FWE) correction. However, there were no significant group differences between the groups at TP1. Additionally, at TP1, a positive correlation (R = 0.58, p = 0.04) was observed between the FA value of the anterior corona radiata and the crystallized composite score in the C+ group. Brain white matter microstructural alterations may be the underlying neural correlates of cognitive changes in older breast cancer survivors who had chemotherapy treatment years ago.

Exploring individual fixel-based white matter abnormalities in epilepsy.

Diffusion MRI has provided insight into the widespread structural connectivity changes that characterize epilepsies. Although syndrome-specific white matter abnormalities have been demonstrated, studies to date have predominantly relied on statistical comparisons between patient and control groups. For diffusion MRI techniques to be of clinical value, they should be able to detect white matter microstructural changes in individual patients. In this study, we apply an individualized approach to a technique known as fixel-based analysis, to examine fibre-tract-specific abnormalities in individuals with epilepsy. We explore the potential clinical value of this individualized fixel-based approach in epilepsy patients with differing syndromic diagnoses. Diffusion MRI data from 90 neurologically healthy control participants and 10 patients with epilepsy (temporal lobe epilepsy, progressive myoclonus epilepsy, and Dravet Syndrome, malformations of cortical development) were included in this study. Measures of fibre density and cross-section were extracted for all participants across brain white matter fixels, and mean values were computed within select tracts-of-interest. Scanner harmonized and normalized data were then used to compute Z-scores for individual patients with epilepsy. White matter abnormalities were observed in distinct patterns in individual patients with epilepsy, both at the tract and fixel level. For patients with specific epilepsy syndromes, the detected white matter abnormalities were in line with expected syndrome-specific clinical phenotypes. In patients with lesional epilepsies (e.g. hippocampal sclerosis, periventricular nodular heterotopia, and bottom-of-sulcus dysplasia), white matter abnormalities were spatially concordant with lesion location. This proof-of-principle study demonstrates the clinical potential of translating advanced diffusion MRI methodology to individual-patient-level use in epilepsy. This technique could be useful both in aiding diagnosis of specific epilepsy syndromes, and in localizing structural abnormalities, and is readily amenable to other neurological disorders. We have included code and data for this study so that individualized white matter changes can be explored robustly in larger cohorts in future work.

Unique information from common diffusion MRI models about white-matter differences across the human adult lifespan

Abstract Diffusion Magnetic Resonance Imaging (dMRI) is sensitive to white matter microstructural changes across the human lifespan. Several models have been proposed to provide more sensitive and specific metrics than those provided by the conventional Diffusion Tensor Imaging (DTI) analysis. However, previous results using different metrics have led to contradictory conclusions regarding the effect of age on fibre demyelination and axonal loss in adults. Moreover, it remains unclear whether these metrics provide distinct information about the effects of age, for example, on different white-matter tracts. To address this, we analysed dMRI data from 651 adults approximately uniformly aged from 18 to 88 years in the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) cohort, using six dMRI metrics: Fractional Anisotropy (FA) from standard DTI; Mean Signal Diffusion (MSD) and Mean Signal Kurtosis (MSK) from Diffusional Kurtosis Imaging (DKI) applied to directional averaged diffusion-weighted signals; and Neurite Density Index (NDI), Orientation Dispersion Index (ODI), and isotropic Free water volume fraction (Fiso) estimated from Neurite Orientation Dispersion and Density Imaging (NODDI). Averaging across white-matter regions-of-interest (ROIs), second-order polynomial fits revealed that MSD, MSK, and Fiso showed the strongest effects of age, with significant quadratic components suggesting more rapid and sometimes inverted effects in old age. Analysing the data in different age subgroups revealed that some apparent discrepancies in previous studies may be explained by the use of cohorts with different age ranges. Factor analysis of the six metrics across all ROIs revealed three independent factors that can be associated to 1) tissue microscopic properties (e.g., differences in fibre density/myelin), 2) free-water contamination, and 3) tissue configuration complexity (e.g., crossing, dispersing, fanning fibres). While FA captures a combination of different factors, other dMRI metrics are strongly aligned to specific factors (NDI and MSK with Factor 1, Fiso with Factor 2, and ODI with Factor 3). To assess whether directional diffusion and kurtosis quantities provide additional information about the effects of age, further factor analyses were also performed, which showed that additional information about the effects of age may be present in radial and axial kurtosis estimates (but not standard axial and radial diffusivity). In summary, our study offers an explanation for previous discrepancies reported in dMRI ageing studies and provides further insights on the interpretation of different dMRI metrics in the context of white-matter microstructural properties.

Free Water MR Imaging of White Matter Microstructural Changes is a Sensitive Marker of Amyloid Positivity in Alzheimer's Disease

BackgroundExtracellular free water (FW) resulting from white matter degeneration limits the sensitivity of diffusion tensor imaging (DTI) in predicting Alzheimer's disease (AD).PurposeTo evaluate the sensitivity of FW‐DTI in detecting white matter microstructural changes in AD. To validate the effectiveness of FW‐DTI indices to predict amyloid‐beta (Aβ) positivity in mild cognitive impairment (MCI) subtypes.Study TypeRetrospective.PopulationThirty‐eight Aβ‐negative cognitively healthy (CH) controls (68.74 ± 8.28 years old, 55% female), 15 Aβ‐negative MCI patients (MCI‐n) (68.87 ± 8.83 years old, 60% female), 29 Aβ‐positive MCI patients (MCI‐p) (73.03 ± 7.05 years old, 52% female), and 29 Aβ‐positive AD patients (72.93 ± 9.11 years old, 55% female).Field Strength/Sequence3.0T; DTI, T1‐weighted, T2‐weighted, T2 star‐weighted angiography, and Aβ PET (18F‐florbetaben or 11C‐PIB).AssessmentFW‐corrected and standard diffusion indices were analyzed using trace‐based spatial statistics. Area under the curve (AUC) in distinguishing MCI subtypes were compared using support vector machine (SVM).Statistical TestsChi‐squared test, one‐way analysis of covariance, general linear regression analyses, nonparametric permutation tests, partial Pearson's correlation, receiver operating characteristic curve analysis, and linear SVM. A P value &lt;0.05 was considered statistically significant.ResultsCompared with CH/MCI‐n/MCI‐p, AD showed significant change in tissue compartment indices of FW‐DTI. No difference was found in the FW index among pair‐wise group comparisons (the minimum FWE‐corrected P = 0.114). There was a significant association between FW‐DTI indices and memory and visuospatial function. The SVM classifier with tissue radial diffusivity as an input feature had the best classification performance of MCI subtypes (AUC = 0.91), and the classifying accuracy of FW‐DTI was all over 89.89%.Data ConclusionFW‐DTI indices prove to be potential biomarkers of AD. The classification of MCI subtypes based on SVM and FW‐DTI indices has good accuracy and could help early diagnosis.Evidence Level4Technical EfficacyStage 2

Amyloid and tau pathology are associated with white matter properties in cognitively unimpaired older adults at risk of AD dementia

AbstractBackgroundWhite matter changes are hypothesized to be among the earliest changes occurring in the course of Alzheimer’s disease (AD). We investigated associations between AD pathology, namely amyloid and tau, and white matter microstructural changes in cognitively unimpaired individuals at risk of AD dementia. We expected higher levels of pathology to be related to lower free‐water‐corrected fractional anisotropy.MethodWe studied 223 cognitively normal older adults with PET and multi‐shell diffusion MRI from the PREVENT‐AD cohort. We first measured standardized uptake value ratios (SUVRs) in 40 brain regions for amyloid‐ß (Aß, i.e., lateral and medial prefrontal, parietal, lateral temporal, and cingulate cortical regions in both hemispheres) and 26 brain regions for tau (i.e., Braak stages I, III, and IV). We then used TractSeg, a deep learning framework, to segment 49 well‐established white matter bundles. We mapped free‐water‐corrected fractional anisotropy (FAT) in those bundles. Lastly, to explore the relationships between AD pathology and white matter microstructure across bundles, we applied two separate partial least squares analyses: one for Aß pathology and one for tau (Figure 1).ResultWe found one significant latent variable relating Aß pathology to FAT. Specifically, higher levels of Aß pathology were associated with the combination of higher levels of FAT within the rostral body of the uncinate fascicle and superior longitudinal fascicle (Figure 2A). We found two significant latent variables relating tau pathology to FAT for which higher levels of tau pathology were associated with elevated FAT within the uncinate fascicle, thalamo‐occipital bundle, optic radiation, inferior occipitofrontal fascicle, inferior longitudinal fascicle, middle longitudinal fascicle, etc. (Figure 2B).ConclusionIn cognitively unimpaired individuals at risk of AD, increased Aß and tau pathology were associated with higher levels of FAT in AD‐related bundles. These unexpected findings may suggest an inverted U‐shape pattern between AD pathology and FAT in the preclinical phase of AD for which FAT values would start by increasing before decreasing later in the course of the disease. This first increase might be a marker of early pathological processes such as neuroinflammation or swelling.

Longitudinal free‐water changes in dementia with Lewy bodies

AbstractBackgroundDiffusion‐weighted MRI (dMRI) examines tissue microstructure integrity and white matter pathways in vivo. Prior dementia with Lewy bodies (DLB) studies focused on white matter or voxel‐based techniques. Less is known about longitudinal white and grey matter microstructural changes in DLB. We aimed to characterize longitudinal diffusion microstructural changes in individuals with DLB.MethoddMRI scans were collected on individuals with DLB from the Mayo Clinic Longitudinal Imaging Biomarkers of DLB Program. Demographics, clinical evaluations and MRI were collected at baseline, and 12‐ or 24‐months. Free water (FW) and FW‐corrected fractional anisotropy (FAT) were analyzed in grey and white matter using 122 bilateral template regions and tracts of interest from the Mayo Clinic Adult Lifespan Template. Primary outcomes were differences in FW and FAT between baseline and 12‐ or 24‐months.ResultWe identified 23 individuals with DLB or mild cognitive impairment with Lewy bodies (MCI‐LB) from baseline to 12‐months [mean age 69.3 years (SD 9.5); 95.8% male], and 16 individuals from baseline to 24‐months [mean age 67.5 years (SD 9.3); 100% male]. Participants at both time‐points showed worsening in Montreal Cognitive Assessment and Movement Disorders Society Unified Parkinson’s Disease Rating Scale motor scores (p&lt;0.05). We found significant differences in FW, but not FAT, from baseline to 12‐months. Significant increases in FW at both time‐points compared to baseline were observed in the insula, putamen, parahippocampal, and rolandic operculum regions (pfdr&lt;0.05). We found additional more widespread microstructural changes from baseline to 24‐months, with increased FW in the amygdala, entorhinal, mid and posterior cingulum, inferior frontal, hippocampal, pallidum, precuneus and retrosplenial regions (pfdr&lt;0.05). We found decreased FAT from baseline to 24‐months in the cerebellar and superior occipital regions (pfdr&lt;0.01).ConclusionLonger follow‐up at 24‐months identified broader networks of free water changes in individuals with DLB. Results support dMRI as a promising, non‐invasive tool to track disease progression in DLB. More investigation is needed to evaluate the relationship of microstructural changes with clinical progression in DLB.

Perioperative Extracellular Brain Free-Water Changes for Older Adults Electing Total Knee Arthroplasty with General versus Spinal Anesthesia: A Pilot Study.

Recent research shows that older adults electing to undergo total knee arthroplasty with general anesthesia have a pre- to postoperative acute increase in molecular free-water within their cerebral white matter. It is unknown if this change is similar for individuals who elect spinal anesthesia methods. To explore white matter microstructural changes in a pilot sample of older adults undergoing total knee arthroplasty and receiving general or spinal anesthesia. We assessed acute perioperative changes in brain white matter free-water in a limited number of older adults electing total knee arthroplasty under spinal anesthesia (n = 5) and matched groups of older adults who received general anesthesia (n = 5) or had no surgery (n = 5). Patterns of free-water changes were also compared in the larger group of older adults electing total knee arthroplasty under general anesthesia (n = 61) and older adults with chronic knee pain who received no surgical intervention (n = 65). Our pilot results suggest older adults receiving general anesthesia had pre- to post-surgery free-water increases extensively throughout their white matter whereas those receiving spinal anesthesia appeared to have less consistent free-water increases. Our pilot results possibly suggest different patterns of perioperative brain white matter free-water changes based on anesthetic approach. We recommend future, larger studies to further examine the effects of anesthetic approach on perioperative brain free-water. The results of our study have potential implications for acute and chronic cognitive changes, perioperative complications, neurodegenerative processes including Alzheimer's disease, and understanding neuroinflammation.

Functional MRI and Diffusion Tensor Imaging in Migraine: A Review of Migraine Functional and White Matter Microstructural Changes.

Migraine is a complex and heterogenous disorder whose disease mechanisms remain disputed. This narrative review summarizes functional MRI (fMRI) and diffusion tensor imaging (DTI) findings and interprets their association with migraine symptoms and subtype to support and expand our current understanding of migraine pathophysiology. Our PubMed search evaluated and included fMRI and DTI studies involving comparisons between migraineurs vs healthy controls, migraineurs with vs without aura, and episodic vs chronic migraineurs. Migraineurs demonstrate changes in functional connectivity (FC) and regional activation in numerous pain-related networks depending on migraine phase, presence of aura, and chronicity. Changes to diffusion indices are observed in major cortical white matter tracts extending to the brainstem and cerebellum, more prominent in chronic migraine and associated with FC changes. Reported changes in FC and regional activation likely relate to pain processing and sensory hypersensitivities. Diffuse white matter microstructural changes in dysfunctional cortical pain and sensory pathways complement these functional differences. Interpretations of reported fMRI and DTI measure trends have not achieved a clear consensus due to inconsistencies in the migraine neuroimaging literature. Future fMRI and DTI studies should establish and implement a uniform methodology that reproduces existing results and directly compares migraineurs with different subtypes. Combined fMRI and DTI imaging may provide better pathophysiological explanations for nonspecific FC and white matter microstructural differences.

Psychological factors and brain magnetic resonance imaging metrics associated with fatigue in persons with multiple sclerosis

BackgroundBesides demographics and clinical factors, psychological variables and brain-tissue changes have been associated with fatigue in persons with multiple sclerosis (pwMS). Identifying predictors of fatigue could help to improve therapeutic approaches for pwMS.Therefore, we investigated predictors of fatigue using a multifactorial approach. Methods136 pwMS and 49 normal controls (NC) underwent clinical, neuropsychological, and magnetic resonance imaging examinations. We assessed fatigue using the “Fatigue Scale for Motor and Cognitive Functions”, yielding a total, motor, and cognitive fatigue score. We further analyzed global and subcortical brain volumes, white matter lesions and microstructural changes (examining fractional anisotropy; FA) along the cortico striatal thalamo cortical (CSTC) loop. Potential demographic, clinical, psychological, and magnetic resonance imaging predictors of total, motor, and cognitive fatigue were explored using multifactorial linear regression models. Results53% of pwMS and 20% of NC demonstrated fatigue. Besides demographics and clinical data, total fatigue in pwMS was predicted by higher levels of depression and reduced microstructural tissue integrity in the CSTC loop (adjusted R2 = 0.52, p < 0.001). More specifically, motor fatigue was predicted by lower education, female sex, higher physical disability, higher levels of depression, and self-efficacy (adjusted R2 = 0.54, p < 0.001). Cognitive fatigue was also predicted by higher levels of depression and lower self-efficacy, but in addition by FA reductions in the CSTC loop (adjusted R2 = 0.45, p < 0.001). ConclusionsOur results indicate that depression and self-efficacy strongly predict fatigue in MS. Incremental variance in total and cognitive fatigue was explained by microstructural changes along the CSTC loop, beyond demographics, clinical, and psychological variables.

White matter microstructure and connectivity changes after surgery in male adults with obstructive sleep apnea: recovery or reorganization?

Obstructive sleep apnea (OSA) is a prevalent clinical problem significantly affecting cognitive functions. Surgical treatment is recommended for those unable to use continuous positive airway pressure. We aimed to investigate the therapeutic effect of upper airway surgery on the white matter (WM) microstructure and brain connectivity in patients with OSA. Twenty-one male patients with moderate-to-severe OSA were recruited for multi-level upper airway surgery. Overnight polysomnography (PSG), neuropsychiatric tests, and brain MRI scans were acquired before and 6.1 ± 0.8 months after surgery. Nineteen male patients with untreated OSA were also included as a reference group. We calculated the longitudinal changes of diffusion tensor imaging (DTI) parameters, including fractional anisotropy (ΔFA) and mean/axial/radial diffusivity (ΔMD/AD/RD). We also assessed changes in network properties based on graph theory. Surgically treated patients showed improvement in PSG parameters and verbal memory after surgery. Globally, ΔFA was significantly higher and ΔRD was lower in the surgery group than in the untreated group. Especially ΔFA of the tracts involved in the limbic system was higher after surgery. In network analysis, higher Δbetweenness and lower Δclustering coefficients were observed in the surgical group than in the untreated group. Finally, the improvement of verbal memory after surgery positively correlated with ΔFA in superior thalamic radiation (p = 0.021), fronto aslant tracts (p = 0.027), and forceps minor tracts (p = 0.032). Surgical treatment of OSA can alleviate alterations in WM integrity and disruptions in local networks, particularly for the tracts involved in the limbic system. These findings may further explain the cognitive improvement observed after the treatment of OSA.

Correlation between lenticulostriate arteries and white matter microstructure changes in patients with cerebral small vessel disease.

To explore the correlation between the number of lenticulostriate arteries (LSAs) and the white matter features in cerebral small vessel diseases (CSVD) by 3T magnetic resonance imaging (MRI). Seventy-one patients with diagnoses of CSVD were prospectively enrolled to undergo 3T MRI examination, including high-resolution vascular wall imaging (VWI) and diffusion tensor imaging (DTI). The LSAs were observed and counted on VWI, and the patients were divided into three groups according to the LSA counts. The presence of white matter hyperintensities (WMHs), lacunes, cerebral microbleeds (CMBs), and enlarged perivascular spaces (EPVS) was assessed in each patient, and a composite CSVD score was calculated. Periventricular and deep white matter hyperintensity (PVWMH, DWMH) volume ratios were obtained based on automatic segmentation. Fractional anisotropy (FA) and mean diffusivity (MD) were processed by using tract-based spatial statistics (TBSS) analysis. These parameters were compared among the three groups. Correlations between the LSA counts and white matter features were also analyzed. There were differences in WMHs (P = 0.001), CMBs (P < 0.001), EPVS (P = 0.017), composite CSVD scores (P < 0.001), PVWMH volume ratios (P = 0.001), DWMH volume ratios (P < 0.001), global FA (P = 0.001), and global MD (P = 0.002) among the three groups. There were correlations between the LSA counts and WMHs (r = -0.45, P < 0.001), CMBs (r = -0.44, P < 0.001), EPVS (r = -0.28, P = 0.020), the composite CSVD score (r = -0.52, P < 0.001), DWMH volume ratio (r = -0.47, P < 0.001), PWMH volume ratio (r = -0.34, P = 0.004), global FA (r = 0.36, P = 0.002), and global MD (r = -0.33, P = 0.005). Diabetes mellitus (OR 3.36, 95% CI 1.06-10.63; P = 0.039) and increased DWMH volume ratios (OR 1.04, 95% CI 1.00-1.08; P = 0.048) were independent risk factors for a decrease in LSA counts. TBSS analysis showed differences among the three groups in global FA and MD after adjusting for age and sex (P < 0.05). The LSA counts was associated with white matter microstructure changes in CSVD and has the potential to represent the extent of subcortical microvascular damage in CSVD patients.

Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET

Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r=-0.55, p <0.001, df=31) but not CN (r=0.13, p=0.62, df=15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.

Diffusion tensor imaging techniques show that parkin gene S/N167 polymorphism is responsible for extensive brain white matter damage in patients with Parkinson's disease

ObjectiveTo explore the influence of disease and genetic factors on the white matter microstructure in patients with PD. The white matter microstructural changes in the substantia nigra-striatum system were detected by diffusion tensor imaging (DTI) using the region of interest (ROI) and diffusion tensor tracer (DTT) methods. MethodsPatients with primary Parkinson's disease (PD) without a family history of PD were selected and divided into PD-G/G and PD-G/A groups according to their parkin S/N167 polymorphism. Control groups matched for age, sex, and gene type (G/G and G/A) were also included. Three-dimensional brain volume imaging (3D-BRAVO) and DTI were performed. The microstructural changes in the substantia nigra-striatum system were evaluated by the ROI and DTT methods. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Hoehn-Yahr (H–Y) staging, and the third part of the Unified Parkinson's Disease Rating (UPDRS-III) scales evaluated the cognitive and motor function impairment in patients with PD. Independent samples t-test compared normally-distributed data, and the Wilcoxon rank sum test compared measurement or categorical non-normally distributed data. Multiple regression analysis was used to analyze the correlation between various DTI indicators and the MMSE, MoCA, UPDRS-III, and H–Y scores in the PD-G/G and PD-G/A groups. P < 0.05 was considered statistically significant. ResultsThe white matter microstructural changes in the nigrostriatal pathway differed significantly between the PD or PD-G/A and the control group (P < 0.05)The ROI method showed that the left globus pallidus radial diffusivity (RD) value was negatively correlated with the MMSE score (r = −0.404, P = 0.040), and the left substantia nigra (LSN) fractional anisotropy (FA) value was positively correlated with the MoCA score (r = 0.405, P = 0.040) and negatively with the H–Y stage (r = −0.479, P = 0.013).The DTT method showed that the MMSE score was positively correlated with the right substantia nigra (RSN) FA value (r = 0.592, P = 0.001) and negatively with its RD value (r = −0.439, P = 0.025). The H–Y grade was negatively correlated with the number of fibers in the RSN (r = −0.406, P = 0.040). The UPDRS-Ⅲ score was positively correlated with the mean diffusivity (r = 0.420, P = 0.033) and RD (r = 0.396, P = 0.045) values of the LSN, and the AD value of the RSN (r = 0.439, P = 0.025). ConclusionThe DTI technique detected extensive white matter fiber damage in patients with PD, primarily in those with the G/A genotype, that led to motor and cognitivesymptoms.

Learning Spectral Fractional Anisotropy and Mean Diffusivity Features as Neuroimaging Biomarkers for Tracking White Matter Integrity Changes in Myotonic Dystrophy Type 1 Patients using Deep Convolutional Neural Networks.

Myotonic dystrophy type 1 (DM1) is a genetic neuromuscular progressive multisystem disease that results in a broad spectrum of clinical central nervous system (CNS) involvement, including problems with memory, attention, executive functioning, and social cognition. Fractional anisotropy and mean diffusivity along-tract data calculated using diffusion tensor imaging techniques play a vital role in assessing white matter microstructural changes associated with neurodegeneration caused by DM1. In this work, a novel spectrogram-based deep learning method is proposed to characterize white matter network alterations in DM1 with the goal of building a deep learning model as neuroimaging biomarkers of DM1. The proposed method is evaluated on fractional anisotropies and mean diffusivities along-tract data calculated for 25 major white matter tracts of 46 DM1 patients and 96 unaffected controls. The evaluation data consists of a total of 7100 spectrogram images. The model achieved 91% accuracy in identifying DM1, a significant improvement compared to previous methods.Clinical relevance- Clinical care of DM1 is particularly challenging due to DM1 multisystem involvement and the disease variability. Patients with DM1 often experience neurological and psychological symptoms, such as excessive sleepiness and apathy, that greatly impact their quality of life. Some of DM1 CNS symptoms may be responsive to treatment. The goal of this research is to gain a deeper understanding of the impact of DM1 on the CNS and to develop a deep learning model that can serve as a biomarker for the disease, with the potential to be used in future clinical trials as an outcome measure.