White Matter Microstructural Changes Research Articles

Return to Play Following Concussion: Role for Imaging?

This review surveys concussion management, focusing on the use of neuroimaging techniques in return to play (RTP) decisions. Clinical assessments traditionally were the foundation of concussion diagnoses. However, their subjective nature prompted an exploration of neuroimaging modalities to enhance diagnosis and management. Magnetic resonance spectroscopy provides information about metabolic changes and alterations in the absence of structural abnormalities. Diffusion tensor imaging uncovers microstructural changes in white matter. Functional magnetic resonance imaging assesses neuronal activity to reveal changes in cognitive and sensorimotor functions. Positron emission tomography can assess metabolic disturbances using radiotracers, offering insight into the long-term effects of concussions. Vestibulo-ocular dysfunction screening and eye tracking assess vestibular and oculomotor function. Although these neuroimaging techniques demonstrate promise, continued research and standardization are needed before they can be integrated into the clinical setting. This review emphasizes the potential for neuroimaging in enhancing the accuracy of concussion diagnosis and guiding RTP decisions.

In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging.

Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables. Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05). The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.

Motivation levels and white matter microstructure in children living with HIV

Central nervous system involvement in HIV infection leads to neurobehavioural sequelae. Although apathy is a well-recognised symptom in adults living with HIV linked to alterations in brain structure, there is scarce research examining motivation in children living with HIV (CLWH). We used the Children’s Motivation Scale (CMS; normative mean = 50, SD = 10) to assess motivation levels in 76 CLWH aged 6–16 years (63 on antiretroviral therapy [ART]; 13 ART-naïve slow progressors) in South Africa. Overall, CLWH scored low on the CMS (mean = 35.70 [SD = 5.87]). Motivation levels were significantly reduced in children taking ART compared to ART-naïve slow progressors (p = 0.02), but were not correlated with markers of HIV disease (CD4 + cell count or viral load), or neurocognitive function (p > 0.05). CMS scores were correlated with diffusion tensor imaging metrics of white matter microstructure in specific frontostriatal brain regions (p < 0.05). On multiple regression, associations with the anterior limb of the internal capsule, a subcortical white matter region, remained significant after adjusting for potential confounders. These findings suggest that reduced motivation may be an important neurobehavioural symptom in CLWH and may reflect changes in white matter microstructure of frontostriatal brain regions.

Hidden Markov Model based Predicting of Alzheimer’s Disease with graph cut segmentation using MR Diffusion Tensor Imaging (DTI)

Alzheimer’s disease (AD) is the predominant aetiology of dementia among the elderly population, accounting for about 60–70% of all instances of cognitive decline. Diffusion tensor imaging (DTI) is a contemporary methodology that enables the cartography of alterations in the microstructure of white matter (WM) in neurological diseases. Nevertheless, the effort of analysing substantial amounts of medical pictures poses significant challenges, prompting researchers to shift their focus towards machine learning. This approach encompasses a collection of computer algorithms that possess the ability to autonomously adjust their output to align with the desired goal. This work proposed the use of a combined approach using Hidden Markov Model (HMM) and MR-DTI, where Diffusion Tensor Imaging (DTI) is employed as a magnetic resonance imaging technique. The purpose of this method is to forecast the occurrence of AD. Furthermore, the statistical analysis demonstrated a significant correlation between microstructural WM changes with both output in the patient groups and cognitive functioning. This finding suggests that these abnormalities in WM might potentially serve as a biomarker for AD. The proposed method is named as Graphcut Hidden MorkovModel (Graph_HMM) is evaluated on ADNI database with statistical analysis and found that it achieves 99.8% of accuracy, 96.4% of sensitivity, 97.4% of specificity and 12.3% of MSE.

Positive Effects of Uric Acid on White Matter Microstructures and Treatment Response in Patients With Schizophrenia.

Schizophrenia involves microstructural changes in white matter (WM) tracts. Oxidative stress is a key factor causing WM damage by hindering oligodendrocyte development and myelin maturation. Uric acid (UA), an endogenous antioxidant, may protect against oxidative stress. We investigated the effect of UA on WM connectivity in antipsychotic-naive or -free patients with early- or chronic-stage schizophrenia. A total of 192 patients with schizophrenia (122 recent-onset [ROS] and 70 chronic [CS]) and 107 healthy controls (HCs) participated in this study. Diffusion tensor imaging data and serum UA levels at baseline were obtained. Fractional anisotropy was lower in the widespread WM regions across the whole brain, and diffusivity measures were higher in both schizophrenia groups than in HCs. The CS group showed lower diffusivity in some WM tracts than the ROS or HC groups. The linear relationship of serum UA levels with axial and mean diffusivity in the right frontal region was significantly different between schizophrenia stages, which was driven by a negative association in the CS group. WM diffusivity associated with serum UA levels correlated with 8-week treatment responses only in patients with CS, suggesting UA to be protective against long-term schizophrenia. UA may protect against the WM damage associated with the progression of schizophrenia by reducing oxidative stress and supporting WM repair against oxidative damage. These results provide insights into the positive role of UA and may facilitate the development of novel disease-modifying therapies.

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.

Correlation between postoperative microstructural changes in cerebral white matter and early postoperative cognitive function in patients undergoing meningioma resection

Objective: To analyze the correlation between microstructure changes in cerebral white matter before and after surgery and early postoperative cognitive function in patients undergoing meningioma resection. Methods: A total of 17 patients who underwent their first meningioma resection at Xuanwu Hospital of Capital Medical University from April 2022 to April 2023 were prospectively included as observation group, with 5 males and 12 females, aged (56.4±7.3) years. Another 15 age- and education-matched patients with cerebral benign tumor were recruited as control group during the same period, with 5 males and 10 females, aged (55.2±8.0) years. Neuropsychological tests (NST), mainly including auditory verbal learning test of Huashan version (AVLT-H), the Montreal cognitive assessment-basic (MoCA-B), clock drawing task-30 (CDT-30), shape trails test-B (STT-B) and animal fluence test (AFT), were conducted at 1 day before surgery, 1 day and within 3-4 days after surgery in the observation group. Simultaneously, magnetic resonance imaging (MRI) scans were performed to collect diffusion tensor imaging (DTI) images at 1 day before surgery and within 3-4 days after surgery. The same NST were conducted at 1 day, 3 days and 6 days after admission in the control group to adjust for learning effects from repeated tests. The microstructure changes of the whole brain white matter were evaluated at the group level by using tract-based spatial statistics (TBSS) technology, including changes of fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD). Then, correlation was performed between DTI indicators with statistically significant and cognitive function. Results: After adjusting for the learning effects, the AVLT-H (R), MoCA-B, and CDT-30 scores decreased, and the evaluation time of STT-B prolonged after surgery in patients with meningioma. And their perioperative decreased values were -0.78 (95%CI:-3.28--0.28) points, -2.22 (95%CI:-4.22--0.72) points, -2.74 (95%CI:-5.29--0.19) points, and 61.49 (95%CI: 5.71-117.27) seconds, respectively, with statistically significant differences (all P<0.05). Group level analysis of TBSS based on DTI images showed decreased FA mainly in the right superior cerebellar peduncle, left posterior limb of internal capsule and genu of corpus callosum, and increased RD mainly in the left anterior corona radiata in patients undergoing meningioma resection, with statistically significant differences (all PFWE<0.05). Linear correlation showed that the perioperative decreased values of FA in genu of corpus callosum and right superior cerebellar peduncle were positively correlated with the perioperative decreased values of AVLT-H (L) after adjusting for learning effects (r=0.72, 0.52, all PFWE<0.05). Conclusions: Patients undergoing meningioma resection are at risk of postoperative cognitive decline. Perioperative decreased values of FA in genu of corpus callosum and right superior cerebellar peduncle based on DTI images are positively correlated with the perioperative decreased values of AVLT-H (L) after adjusting for learning effects.

Baseline symptom-related white matter tracts predict individualized treatment response to 12-week antipsychotic monotherapies in first-episode schizophrenia

There is significant heterogeneity in individual responses to antipsychotic drugs, but there is no reliable predictor of antipsychotics response in first-episode psychosis. This study aimed to investigate whether psychotic symptom-related alterations in fractional anisotropy (FA) and mean diffusivity (MD) of white matter (WM) at the early stage of the disorder may aid in the individualized prediction of drug response. Sixty-eight first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single atypical antipsychotic throughout the first 12 weeks. Clinical symptoms were evaluated using the eight “core symptoms” selected from the Positive and Negative Syndrome Scale (PANSS-8). Follow-up assessments were conducted at the 4th, 8th, and 12th weeks by trained psychiatrists. LASSO regression model and cross-validation were conducted to examine the performance of baseline symptom-related alterations FA and MD of WM in the prediction of individualized treatment outcome. Fifty patients completed both clinical follow-up assessments by the 8th and 12th weeks. 30 patients were classified as responders, and 20 patients were classified as nonresponders. At baseline, the altered diffusion properties of fiber tracts in the anterior thalamic radiation, corticospinal tract, callosum forceps minor, longitudinal fasciculi (ILF), inferior frontal-occipital fasciculi (IFOF) and superior longitudinal fasciculus (SLF) were related to the severity of symptoms. These abnormal fiber tracts, especially the ILF, IFOF, and SLF, significantly predicted the response to antipsychotic treatment at the individual level (AUC = 0.828, P < 0.001). These findings demonstrate that early microstructural WM changes contribute to the pathophysiology of psychosis and may serve as meaningful individualized predictors of response to antipsychotics.

Microstructural white matter changes underlying speech deficits in Parkinson’s disease

Speech impairments are one of the common symptoms of individuals with Parkinson’s disease (PD). However, little is known about the underlying neuroanatomical structural deficits specifically in the basal ganglia-thalamocortical (BGTC) loop in the speech deficits of PD. Here we investigated white matter differences in PD using probabilistic tractography. Diffusion tensor imaging data were downloaded from the Parkinson’s Progression Markers Initiative database. We included three groups of participants: 20 PD individuals with speech deficits, 20 PD individuals without speech deficits, and 20 age- and gender-matched control participants. Overall, PD individuals with speech deficits had higher mean diffusivity in the BGTC pathway in the left hemisphere compared with PD individuals without speech deficits. The present study exhibits that there may be a distinct pathophysiological profile of white matter for speech deficits in PD.

Brain diffusion MRI biomarkers after oncology treatments.

In addition to providing a measurement of the tumor's size and dimensions, magnetic resonance imaging (MRI) provides excellent noninvasive radiographic detection of tumor location. The MRI technique is an important modality that has been shown to be useful in the prognosis, diagnosis, treatment planning, and evaluation of response and recurrence in solid cancers. Diffusion-weighted imaging (DWI) is an imaging technique that quantifies water mobility. This imaging approach is good for identifying sub-voxel microstructure of tissues, correlates with tumor cellularity, and has been proven to be valuable in the early assessment of cytotoxic treatment for a variety of malignancies. Diffusion tensor imaging (DTI) is an MRI method that assesses the preferred amount of water transport inside tissues. This enables precise measurements of water diffusion, which changes according to the direction of white matter fibers, their density, and myelination. This measurement corresponds to some related variables: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), and others. DTI biomarkers can detect subtle changes in white matter microstructure and integrity following radiation therapy (RT) or chemoradiotherapy, which may have implications for cognitive function and quality of life. In our study, these indices were evaluated after brain chemoradiotherapy.

Microstructural alterations in white matter and related neurobiology based on the new clinical subtypes of Parkinson's disease.

The advent of new clinical subtyping systems for Parkinson's disease (PD) has led to the classification of patients into distinct groups: mild motor predominant (PD-MMP), intermediate (PD-IM), and diffuse malignant (PD-DM). Our goal was to evaluate the efficacy of diffusion tensor imaging (DTI) in the early diagnosis, assessment of clinical progression, and prediction of prognosis of these PD subtypes. Additionally, we attempted to understand the pathological mechanisms behind white matter damage using single-photon emission computed tomography (SPECT) and cerebrospinal fluid (CSF) analyses. We classified 135 de novo PD patients based on new clinical criteria and followed them up after 1 year, along with 45 healthy controls (HCs). We utilized tract-based spatial statistics to assess the microstructural changes of white matter at baseline and employed multiple linear regression to examine the associations between DTI metrics and clinical data at baseline and after follow-up. Compared to HCs, patients with the PD-DM subtype demonstrated reduced fractional anisotropy (FA), increased axial diffusivity (AD), and elevated radial diffusivity (RD) at baseline. The FA and RD values correlated with the severity of motor symptoms, with RD also linked to cognitive performance. Changes in FA over time were found to be in sync with changes in motor scores and global composite outcome measures. Furthermore, baseline AD values and their rate of change were related to alterations in semantic verbal fluency. We also discovered the relationship between FA values and the levels of α-synuclein and β-amyloid. Reduced dopamine transporter uptake in the left putamen correlated with RD values in superficial white matter, motor symptoms, and autonomic dysfunction at baseline as well as cognitive impairments after 1 year. The PD-DM subtype is characterized by severe clinical symptoms and a faster progression when compared to the other subtypes. DTI, a well-established technique, facilitates the early identification of white matter damage, elucidates the pathophysiological mechanisms of disease progression, and predicts cognitively related outcomes. The results of SPECT and CSF analyses can be used to explain the specific pattern of white matter damage in patients with the PD-DM subtype.

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.

White matter trajectories over the lifespan.

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

Microstructural Changes in the Cerebral White Matter After 12 Months of CPAP Treatment for Moderate to Severe Obstructive Sleep Apnoea: A TBSS Study.

Continuous positive airway pressure (CPAP) therapy improves clinical symptoms in patients with obstructive sleep apnea (OSA); however, the mechanism of this clinical improvement and how it may be associated with the restoration of white matter (WM) structures in the brain is unclear. Therefore, this study investigated the relationship between the structural recovery of brain WM and improvements in cognitive function and emotion after long-term (12 months) CPAP treatment in patients with OSA. We collected data from 17 patients with OSA before and 12 months after CPAP treatment, including sleep monitoring, clinical assessment, and diffusion tensor imaging (DTI) magnetic resonance imaging. We observed a partial reversible recovery of brain WM (mean and radial diffusion coefficients) after treatment. This recovery involved the commissural fibers (cingulum, body of corpus callosum), projection fibers (retrolenticular part of the internal capsule, posterior thalamic radiation, posterior limb of the internal capsule, superior corona radiata, posterior corona radiata), association fibers (external capsule, superior longitudinal fasciculus, inferior longitudinal fasciculus), and other regions. In addition, the improvements in WM fibers in one part of the brain significantly were correlated with the Hamilton Anxiety Scale and Hamilton Depression Scale scores. Our results suggest that reversible recovery of reduced brain WM integrity due to OSA may require longer CPAP treatment. Moreover, changes in the integrity of the commissural fibers were associated with emotion regulation. These restored WM areas may explain the cognitive and mood improvements observed after OSA treatment.

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.

Alteration of white matter microstructure in patients with sleep disorders after COVID-19 infection

BackgroundThe pathophysiology of coronasomnia remains unclear. This study aimed to investigate changes in white matter (WM) microstructure and inflammatory factors in patients with sleep disorders (SD) characterized by poor sleep quantity, quality, or timing following coronavirus disease 2019 (COVID-19) infection in the acute phase (within one month) and whether these changes could be recovered at 3-month follow-up. Methods29 acute COVID-19 patients with SD (COVID_SD) and 27 acute COVID-19 patients without SD (COVID_NonSD) underwent diffusion tensor imaging (DTI), tested peripheral blood inflammatory cytokines level, and measured Pittsburgh Sleep Quality Index (PSQI), and matched 30 uninfected healthy controls. Analyzed WM abnormalities between groups in acute phase and explored its changes in COVID_SD at 3-month follow-up by using tract-based spatial statistics (TBSS). Correlations between DTI and clinical data were examined using Spearman partial correlation analysis. ResultsBoth COVID_SD and COVID_NonSD exhibited widespread WM microstructure abnormalities. The COVID_SD group showed specific WM microstructure changes in right inferior fronto-occipital fasciculus (IFOF) (lower fractional anisotropy [FA]/axial diffusivity [AD] and higher radial diffusivity [RD]) and left corticospinal tract (CST) (higher FA and lower RD) and higher interleukin-1β (IL-1β) compared with COVID_NonSD group. These WM abnormalities and IL-1β levels were correlated PSQI score. After 3 months, the IFOF integrity and IL-1β levels tended to return to normal accompanied by symptom improvement in the COVID_SD relative to baseline. ConclusionAbnormalities in right IFOF and left CST and elevated IL-1β levels were important neurophenotypes correlated with COVID_SD, which might provide new insights into the pathogenesis of neuroinflammation in SD patients induced by COVID-19.

Different impulse control disorder evolution patterns and white matter microstructural damage in the progression of Parkinson's disease.

The course of impulse control disorders (ICD) varies in the early stage of Parkinson's disease (PD). We aimed to delineate the association between the evolution pattern of ICD and the progression of PD. A total of 321 de novo PD patients from the Parkinson's Progression Markers Initiative database were included. Patients were followed up for a mean of 6.8 years and were classified into different groups according to the evolution patterns of ICD. Disease progression was compared among groups using survival analysis, in which the endpoint was defined as progression to Hoehn and Yahr stage 3 or higher for motor progression and progression to mild cognitive impairment for cognitive decline. In the fourth year of follow-up, four types of ICD evolution patterns were identified: (1) non-ICD-stable (68.2%), a patient who is consistently free of ICD; (2) late-ICD (14.6%), ICD developed during the follow-up of patients; (3) ICD-stable (11.5%), patients showed persistent ICD; and (4) ICD-reversion (5.6%), baseline ICD disappeared during the follow-up of patients with ICD. The ICD-reversion type shows daily life non-motor symptoms [Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS) part I], daily life motor symptoms (MDS-UPDRS part II), rapid eye movement sleep behavior disorder, and anxiety symptoms has a greater impact. PD patients with different ICD evolution patterns had different changes in white matter microstructure at the onset of the disease. Those relevant brain regions are involved in ICD and non-motor functions. Four early ICD evolution patterns are identified in de novo PD, with different prognoses and brain white matter microstructural damage patterns, and they may predict motor progression and cognitive decline in PD patients.

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.

Extracellular free water (FW) resulting from white matter degeneration limits the sensitivity of diffusion tensor imaging (DTI) in predicting Alzheimer's disease (AD). To 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. Retrospective. Thirty-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). 3.0T; DTI, T1-weighted, T2-weighted, T2 star-weighted angiography, and Aβ PET (18F-florbetaben or 11C-PIB). FW-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). Chi-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 <0.05 was considered statistically significant. Compared 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%. FW-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. 4 TECHNICAL EFFICACY: Stage 2.