Brain White Matter Research Articles

Mapping tissue microstructure of brain white matter in vivo in health and disease using diffusion MRI

Abstract Diffusion magnetic resonance imaging offers unique in vivo sensitivity to tissue microstructure in brain white matter, which undergoes significant changes during development and is compromised in virtually every neurological disorder. Yet, the challenge is to develop biomarkers that are specific to micrometer-scale cellular features in a human MRI scan of a few minutes. Here, we quantify the sensitivity and specificity of a multicompartment diffusion modeling framework to the density, orientation, and integrity of axons. We demonstrate that using a machine learning-based estimator, our biophysical model captures the morphological changes of axons in early development, acute ischemia, and multiple sclerosis (total N = 821). The methodology of microstructure mapping is widely applicable in clinical settings and in large imaging consortium data to study development, aging, and pathology.

Functional and structural abnormalities of the speech disorders: a multimodal activation likelihood estimation meta-analysis.

Speech disorders are associated with different degrees of functional and structural abnormalities. However, the abnormalities associated with specific disorders, and the common abnormalities shown by all disorders, remain unclear. Herein, a meta-analysis was conducted to integrate the results of 70 studies that compared 1843 speech disorder patients (dysarthria, dysphonia, stuttering, and aphasia) to 1950 healthy controls in terms of brain activity, functional connectivity, gray matter, and white matter fractional anisotropy. The analysis revealed that compared to controls, the dysarthria group showed higher activity in the left superior temporal gyrus and lower activity in the left postcentral gyrus. The dysphonia group had higher activity in the right precentral and postcentral gyrus. The stuttering group had higher activity in the right inferior frontal gyrus and lower activity in the left inferior frontal gyrus. The aphasia group showed lower activity in the bilateral anterior cingulate gyrus and left superior frontal gyrus. Across the four disorders, there were concurrent lower activity, gray matter, and fractional anisotropy in motor and auditory cortices, and stronger connectivity between the default mode network and frontoparietal network. These findings enhance our understanding of the neural basis of speech disorders, potentially aiding clinical diagnosis and intervention.

Enlarged perivascular spaces are associated with white matter injury, cognition and inflammation in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy.

Enlarged perivascular spaces have been previously reported in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, but their significance and pathophysiology remains unclear. We investigated associations of white matter enlarged perivascular spaces with classical imaging measures, cognitive measures and plasma proteins to better understand what enlarged perivascular spaces represent in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy and whether radiographic measures of enlarged perivascular spaces would be of value in future therapeutic discovery studies for cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. Twenty-four individuals with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy and 24 age- and sex-matched controls were included. Disease status was determined based on the presence of NOTCH3 mutation. Brain imaging measures of white matter hyperintensity, brain parenchymal fraction, white matter enlarged perivascular space volumes, clinical and cognitive measures as well as plasma proteomics were used in models. White matter enlarged perivascular space volumes were calculated via a novel, semiautomated pipeline, and levels of 7363 proteins were quantified in plasma using the SomaScan assay. The relationship of enlarged perivascular spaces with global burden of white matter hyperintensity, brain atrophy, functional status, neurocognitive measures and plasma proteins was modelled with linear regression models. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy and control groups did not exhibit differences in mean enlarged perivascular space volumes. However, increased enlarged perivascular space volumes in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy were associated with increased white matter hyperintensity volume (β = 0.57, P = 0.05), Clinical Dementia Rating Sum-of-Boxes score (β = 0.49, P = 0.04) and marginally with decreased brain parenchymal fraction (β = -0.03, P = 0.10). In interaction term models, the interaction term between cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy disease status and enlarged perivascular space volume was associated with increased white matter hyperintensity volume (β = 0.57, P = 0.02), Clinical Dementia Rating Sum-of-Boxes score (β = 0.52, P = 0.02), Mini-Mental State Examination score (β = -1.49, P = 0.03) and marginally with decreased brain parenchymal fraction (β = -0.03, P = 0.07). Proteins positively associated with enlarged perivascular space volumes were found to be related to leukocyte migration and inflammation, while negatively associated proteins were related to lipid metabolism. Two central hub proteins were identified in protein networks associated with enlarged perivascular space volumes: CXC motif chemokine ligand 8/interleukin-8 and C-C motif chemokine ligand 2/monocyte chemoattractant protein 1. The levels of CXC motif chemokine ligand 8/interleukin-8 were also associated with increased white matter hyperintensity volume (β = 42.86, P = 0.03), and levels of C-C motif chemokine ligand 2/monocyte chemoattractant protein 1 were further associated with decreased brain parenchymal fraction (β = -0.0007, P < 0.01) and Mini-Mental State Examination score (β = -0.02, P < 0.01) and increased Trail Making Test B completion time (β = 0.76, P < 0.01). No proteins were associated with all three studied imaging measures of pathology (brain parenchymal fraction, enlarged perivascular spaces, white matter hyperintensity). Based on associations uncovered between enlarged perivascular space volumes and cognitive functions, imaging and plasma proteins, we conclude that white matter enlarged perivascular space volumes may capture pathologies contributing to chronic brain dysfunction and degeneration in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy.

Reorganization of structural brain networks in Parkinson’s disease with postural instability/gait difficulty

The Postural Instability/Gait Difficulty (PIGD) subtype of Parkinson’s disease (PD) has a faster disease progression, a higher risk of cognitive and motor decline, yet the alterations of structural topological organization remain unknown.Diffusion Tensor Imaging (DTI) and 3D-TI scanning were conducted on 31 PD patients with PIGD (PD-PIGD), 30 PD patients without PIGD (PD-non-PIGD) and 35 Healthy Controls (HCs). Structural networks were constructed using DTI brain white matter fiber tractography. A graph theory approach was applied to characterize the topological properties of complex structural networks, and the relationships between significantly different network metrics and motor deficits were analyzed within the PD-PIGD group.PD-PIGD patients exhibited increased shortest path length compared with PD-non-PIGD and HCs (P < 0.05, respectively). Additionally, PD-PIGD patients exhibited decreased nodal properties, mainly in the cerebellar vermis, prefrontal cortex, paracentral lobule, and visual regions. Notably, the degree centrality of the cerebellar vermis was negatively correlated with the PIGD score (r = −0.390; P = 0.030) and Unified Parkinson’s Disease Rating Scale Part III score (r = −0.436; P = 0.014) in PD-PIGD patients. Furthermore, network-based statistical analysis revealed decreased structural connectivity between the prefrontal lobe, putamen, supplementary motor area, insula, and cingulate gyrus in PD-PIGD patients.Our findings demonstrated that PD-PIGD patients existed abnormal structural connectomes in the cerebellar vermis, frontal-parietal cortex and visual regions. These topological differences can provide a topological perspective for understanding the potential pathophysiological mechanisms of PIGD in PD.

Megalencephalic leukoencephalopathy with subcortical cysts: a variant update and review of the literature.

The leukodystrophy megalencephalic leukoencephalopathy with subcortical cysts (MLC) is characterized by infantile-onset macrocephaly and chronic edema of the brain white matter. With delayed onset, patients typically experience motor problems, epilepsy and slow cognitive decline. No treatment is available. Classic MLC is caused by bi-allelic recessive pathogenic variants in MLC1 or GLIALCAM (also called HEPACAM). Heterozygous dominant pathogenic variants in GLIALCAM lead to remitting MLC, where patients show a similar phenotype in early life, followed by normalization of white matter edema and no clinical regression. Rare patients with heterozygous dominant variants in GPRC5B and classic MLC were recently described. In addition, two siblings with bi-allelic recessive variants in AQP4 and remitting MLC have been identified. The last systematic overview of variants linked to MLC dates back to 2006. We provide an updated overview of published and novel variants. We report on genetic variants from 508 patients with MLC as confirmed by MRI diagnosis (258 from our database and 250 extracted from 64 published reports). We describe 151 unique MLC1 variants, 29 GLIALCAM variants, 2 GPRC5B variants and 1 AQP4 variant observed in these MLC patients. We include experiments confirming pathogenicity for some variants, discuss particularly notable variants, and provide an overview of recent scientific and clinical insight in the pathophysiology of MLC.

White matter brain age as a biomarker of cerebrovascular burden in the ageing brain.

As the brain ages, it almost invariably accumulates vascular pathology, which differentially affects the cerebral white matter. A rich body of research has investigated the link between vascular risk factors and the brain. One of the less studied questions is that among various modifiable vascular risk factors, which is the most debilitating one for white matter health? A white matter specific brain age was developed to evaluate the overall white matter health from diffusion weighted imaging, using a three-dimensional convolutional neural network deep learning model in both cross-sectional UK biobank participants (n = 37,327) and a longitudinal subset (n = 1409). White matter brain age gap (WMBAG) was the difference between the white matter age and the chronological age. Participants with one, two, and three or more vascular risk factors, compared to those without any, showed an elevated WMBAG of 0.54, 1.23, and 1.94years, respectively. Diabetes was most strongly associated with an increased WMBAG (1.39years, p < 0.001) among all risk factors followed by hypertension (0.87years, p < 0.001) and smoking (0.69years, p < 0.001). Baseline WMBAG was associated significantly with processing speed, executive and global cognition. Significant associations of diabetes and hypertension with poor processing speed and executive function were found to be mediated through the WMBAG. White matter specific brain age can be successfully targeted for the examination of the most relevant risk factors and cognition, and for tracking an individual's cerebrovascular ageing process. It also provides clinical basis for the better management of specific risk factors.

Association of Plasma YKL-40 With MRI, CSF, and Cognitive Markers of Brain Health and Dementia.

Higher YKL-40 levels in the CSF are a known biomarker of brain inflammation. We explored the utility of plasma YKL-40 as a biomarker for accelerated brain aging and dementia risk. We performed cross-sectional and prospective analyses of 4 community-based cohorts in the United States or Europe: the Age, Gene/Environment Susceptibility-Reykjavik Study, Atherosclerosis Risk in the Communities study, Coronary Artery Risk Development in Young Adults study, and Framingham Heart Study (FHS). YKL-40 was measured from stored plasma by a single laboratory using Mesoscale Discovery with levels log transformed and standardized within each cohort. Outcomes included MRI total brain volume, hippocampal volume, and white matter hyperintensity volume (WMHV) as a percentage of intracranial volume, a general cognitive composite derived from neuropsychological testing (SD units [SDU]), and the risk of incident dementia. We sought to replicate associations with dementia in the clinic-based ACE csf cohort, which also had YKL-40 measured from the CSF. Meta-analyses of MRI outcomes included 6,558 dementia-free participants, and for analysis of cognition, 6,670. The blood draw preceded MRI/cognitive assessment by up to 10.6 years across cohorts. The mean ages ranged from 50 to 76 years, with 39%-48% male individuals. In random-effects meta-analysis of study estimates, each SDU increase in log-transformed YKL-40 levels was associated with smaller total brain volume (β = -0.33; 95% CI -0.45 to -0.22; p < 0.0001) and poorer cognition (β = -0.04; 95% CI -0.07 to -0.02; p < 0.01), following adjustments for demographic variables. YKL-40 levels did not associate with hippocampal volume or WMHV. In the FHS, each SDU increase in log YKL-40 levels was associated with a 64% increase in incident dementia risk over a median of 5.8 years of follow-up, following adjustments for demographic variables (hazard ratio 1.64; 95% CI 1.25-2.16; p < 0.001). In the ACE csf cohort, plasma and CSF YKL-40 were correlated (r = 0.31), and both were associated with conversion from mild cognitive impairment to dementia, independent of amyloid, tau, and neurodegeneration status. Higher plasma YKL-40 levels were associated with lower brain volume, poorer cognition, and incident dementia. Plasma YKL-40 may be useful for studying the association of inflammation and its treatment on dementia risk.

Associations of Polycystic Ovary Syndrome With Indicators of Brain Health at Midlife in the CARDIA Cohort.

Polycystic ovary syndrome (PCOS) is a common reproductive disorder associated with an adverse cardiometabolic profile early in life. Increasing evidence links cardiovascular risk factors, such as diabetes and hypertension, to accelerated cognitive aging. However, less is known about PCOS and its relationship to brain health, particularly at midlife. Our goal was to investigate possible associations between PCOS and midlife cognitive function and brain MRI findings in an ongoing prospective study. We used data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a geographically diverse prospective cohort study of individuals who were 18-30 years at baseline (1985-1986) and followed for 30 years. We identified women with PCOS from an ancillary study (CARDIA Women's study (CWS); n = 1,163) as those with elevated androgen levels and/or hirsutism in conjunction with symptoms of oligomenorrhea. At year 30, participants completed cognitive testing, including the Montreal Cognitive Assessment, Rey Auditory Verbal Learning Test (RAVLT) (verbal learning and memory), Digit Symbol Substitution Test (processing speed and executive function), Stroop test (attention and cognitive control), and category and letter fluency tests (semantics and attention). A subset completed brain MRI to assess brain structure and white matter integrity. Multivariable linear regression models estimated the association between PCOS and outcomes, adjusting for age, race, education, and study center. Of the 1163 women in CWS, 907 completed cognitive testing, and of these, 66 (7.1%) met criteria for PCOS (age 54.7 years). Women with and without PCOS were similar for age, BMI, smoking/drinking status, and income. At year 30, participants with PCOS performed lower (mean z score; 95% CI) on Stroop (-0.323 (-0.69 to -7.37); p = 0.008), RAVLT (-0.254 (-0.473 to -0.034); p = 0.002), and category fluency (-0.267 (-0.480 to -0.040); p = 0.02) tests. Of the 291 participants with MRI, 25 (8.5%) met PCOS criteria and demonstrated lower total white matter fractional anisotropy, a measure of white matter integrity (coefficient (95% CI) -0.013 (-0.021 to -0.005); p = 0.002), though not abnormal white matter. Our results suggest that women with PCOS have lower cognitive performance and lower white matter integrity at midlife. Additional research is needed to confirm these findings and to determine potential mechanistic pathways including potential modifiable factors.

Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI.

There is inconsistent evidence for an association of obesity with white matter microstructural alterations. Such inconsistent findings may be related to the cumulative effects of obesity and alcohol dependence. This study aimed to investigate the possible interactions between alcohol dependence and overweight/obesity on white matter microstructure in the human brain. A total of 60 inpatients with alcohol dependence during early abstinence (44 normal weight and 16 overweight/obese) and 65 controls (42 normal weight and 23 overweight/obese) were included. The diffusion tensor imaging (DTI) measures [fractional anisotropy (FA) and radial diffusivity (RD)] of the white matter microstructure were compared between groups. We observed significant interactive effects between alcohol dependence and overweight/obesity on DTI measures in several tracts. The DTI measures were not significantly different between the overweight/obese and normal-weight groups (although widespread trends of increased FA and decreased RD were observed) among controls. However, among the alcohol-dependent patients, the overweight/obese group had widespread reductions in FA and widespread increases in RD, most of which significantly differed from the normal-weight group; among those with overweight/obesity, the alcohol-dependent group had widespread reductions in FA and widespread increases in RD, most of which were significantly different from the control group. This study found significant interactive effects between overweight/obesity and alcohol dependence on white matter microstructure, indicating that these two controllable factors may synergistically impact white matter microstructure and disrupt structural connectivity in the human brain.

TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance

We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise tissue microstructure measurements. By employing a point cloud representation, TractGeoNet can directly utilize tissue microstructure and positional information from all points within a fiber tract without the need to average or bin data along the streamline as traditionally required by dMRI tractometry methods. To improve regression performance, we propose a novel loss function, the Paired-Siamese Regression loss, which encourages the model to focus on accurately predicting the relative differences between regression label scores rather than just their absolute values. In addition, to gain insight into the brain regions that contribute most strongly to the prediction results, we propose a Critical Region Localization algorithm. This algorithm identifies highly predictive anatomical regions within the white matter fiber tracts for the regression task. We evaluate the effectiveness of the proposed method by predicting individual performance on two neuropsychological assessments of language using a dataset of 20 association white matter fiber tracts from 806 subjects from the Human Connectome Project Young Adult dataset. The results demonstrate superior prediction performance of TractGeoNet compared to several popular regression models that have been applied to predict individual cognitive performance based on neuroimaging features. Of the twenty tracts studied, we find that the left arcuate fasciculus tract is the most highly predictive of the two studied language performance assessments. Within each tract, we localize critical regions whose microstructure and point information are highly and consistently predictive of language performance across different subjects and across multiple independently trained models. These critical regions are widespread and distributed across both hemispheres and all cerebral lobes, including areas of the brain considered important for language function such as superior and anterior temporal regions, pars opercularis, and precentral gyrus. Overall, TractGeoNet demonstrates the potential of geometric deep learning to enhance the study of the brain's white matter fiber tracts and to relate their structure to human traits such as language performance.

Bridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people.

Portable low-field-strength magnetic resonance imaging (MRI) systems represent a promising alternative to traditional high-field-strength systems with the potential to make MR technology available at scale in low-resource settings. However, lower image quality and resolution may limit the research and clinical potential of these devices. We tested two super-resolution methods to enhance image quality in a low-field MR system and compared their correspondence with images acquired from a high-field system in a sample of young people. T1- and T2-weighted structural MR images were obtained from a low-field (64mT) Hyperfine and high-field (3T) Siemens system in N = 70 individuals (mean age = 20.39 years, range 9-26 years). We tested two super-resolution approaches to improve image correspondence between images acquired at high- and low-field: (1) processing via a convolutional neural network ('SynthSR'), and (2) multi-orientation image averaging. We extracted brain region volumes, cortical thickness, and cortical surface area estimates. We used Pearson correlations to test the correspondence between these measures, and Steiger Z tests to compare the difference in correspondence between standard imaging and super-resolution approaches. Single pairs of T1- and T2-weighted images acquired at low field showed high correspondence to high-field-strength images for estimates of total intracranial volume, surface area cortical volume, subcortical volume, and total brain volume (r range = 0.60-0.88). Correspondence was lower for cerebral white matter volume (r = 0.32, p = 0.007, q = 0.009) and non-significant for mean cortical thickness (r = -0.05, p = 0.664, q = 0.664). Processing images with SynthSR yielded significant improvements in correspondence for total brain volume, white matter volume, total surface area, subcortical volume, cortical volume, and total intracranial volume (r range = 0.85-0.97), with the exception of global mean cortical thickness (r = 0.14). An alternative multi-orientation image averaging approach improved correspondence for cerebral white matter and total brain volume. Processing with SynthSR also significantly improved correspondence across widespread regions for estimates of cortical volume, surface area and subcortical volume, as well as within isolated prefrontal and temporal regions for estimates of cortical thickness. Applying super-resolution approaches to low-field imaging improves regional brain volume and surface area accuracy in young people. Finer-scale brain measurements, such as cortical thickness, remain challenging with the limited resolution of low-field systems.

Deep learning-based, fully automated, pediatric brain segmentation.

The purpose of this study was to demonstrate the performance of a fully automated, deep learning-based brain segmentation (DLS) method in healthy controls and in patients with neurodevelopmental disorders, SCN1A mutation, under eleven. The whole, cortical, and subcortical volumes of previously enrolled 21 participants, under 11years of age, with a SCN1A mutation, and 42 healthy controls, were obtained using a DLS method, and compared to volumes measured by Freesurfer with manual correction. Additionally, the volumes which were calculated with the DLS method between the patients and the control group. The volumes of total brain gray and white matter using DLS method were consistent with that volume which were measured by Freesurfer with manual correction in healthy controls. Among 68 cortical parcellated volume analysis, the volumes of only 7 areas measured by DLS methods were significantly different from that measured by Freesurfer with manual correction, and the differences decreased with increasing age in the subgroup analysis. The subcortical volume measured by the DLS method was relatively smaller than that of the Freesurfer volume analysis. Further, the DLS method could perfectly detect the reduced volume identified by the Freesurfer software and manual correction in patients with SCN1A mutations, compared with healthy controls. In a pediatric population, this new, fully automated DLS method is compatible with the classic, volumetric analysis with Freesurfer software and manual correction, and it can also well detect brain morphological changes in children with a neurodevelopmental disorder.

Integration of diffusion tensor imaging parameters with mesh morphing for in-depth analysis of brain white matter fibre tracts.

Averaging is commonly used for data reduction/aggregation to analyse high-dimensional MRI data, but this often leads to information loss. To address this issue, we developed a novel technique that integrates diffusion tensor metrics along the whole volume of the fibre bundle using a 3D mesh-morphing technique coupled with principal component analysis for delineating case and control groups. Brain diffusion tensor MRI scans of high school rugby union players (n = 30, age 16-18) were acquired on a 3 T MRI before and after the sports season. A non-contact sport athlete cohort with matching demographics (n = 12) was also scanned. The utility of the new method in detecting differences in diffusion tensor metrics of the right corticospinal tract between contact and non-contact sport athletes was explored. The first step was to run automated tractography on each subject's native space. A template model of the right corticospinal tract was generated and morphed into each subject's native shape and space, matching individual geometry and diffusion metric distributions with minimal information loss. The common dimension of the 20 480 diffusion metrics allowed further data aggregation using principal component analysis to cluster the case and control groups as well as visualization of diffusion metric statistics (mean, ±2 SD). Our approach of analysing the whole volume of white matter tracts led to a clear delineation between the rugby and control cohort, which was not possible with the traditional averaging method. Moreover, our approach accounts for the individual subject's variations in diffusion tensor metrics to visualize group differences in quantitative MR data. This approach may benefit future prediction models based on other quantitative MRI methods.

Urban environment during pregnancy and childhood and white matter microstructure in preadolescence in two European birth cohorts

Growing evidence suggests that urban environment may influence cognition and behavior in children, but the underlying pollutant and neurobiological mechanisms are unclear. We evaluated the association of built environment and urban natural space indicators during pregnancy and childhood with brain white matter microstructure in preadolescents, and examined the potential mediating role of air pollution and road-traffic noise. We used data of the Generation R Study, a population-based birth cohort in Rotterdam, the Netherlands (n = 2725; 2002–2006) for the primary analyses. Replication of the main findings was attempted on an independent neuroimaging dataset from the PELAGIE birth cohort, France (n = 95; 2002–2006). We assessed exposures to 12 built environment and 4 urban natural spaces indicators from conception up to 9 years of age. We computed 2 white matter microstructure outcomes (i.e., average of fractional anisotropy (FA) and mean diffusivity (MD) from 12 white matte tracts) from diffusion tensor imaging data. Greater distance to the nearest major green space during pregnancy was associated with higher whole-brain FA (0.001 (95%CI 0.000; 0.002) per 7 m increase), and higher land use diversity during childhood was associated with lower whole-brain MD (−0.001 (95%CI -0.002; −0.000) per 0.12-point increase), with no evidence of mediation by air pollution nor road-traffic noise. Higher percentage of transport and lower surrounding greenness during pregnancy were associated with lower whole-brain FA, and road-traffic noise mediated 19% and 52% of these associations, respectively. We found estimates in the same direction in the PELAGIE cohort, although confidence intervals were larger and included the null. This study suggests an association between urban environment and white matter microstructure, mainly through road-traffic noise, indicating that greater access to green space nearby might promote white matter development.

Neuropathological characteristics of abnormal white matter functional signaling in adolescents with major depression.

Major depression disorder (MDD) constitutes a significant mental health concern. Epidemiological surveys indicate that the lifetime prevalence of depression in adolescents is much higher than that in adults, with a corresponding increased risk of suicide. In studying brain dysfunction associated with MDD in adole-scents, research on brain white matter (WM) is sparse. Some researchers even mistakenly regard the signals generated by the WM as noise points. In fact, studies have shown that WM exhibits similar blood oxygen level-dependent signal fluctuations. The alterations in WM signals and their relationship with disease severity in adolescents with MDD remain unclear. To explore potential abnormalities in WM functional signals in adolescents with MDD. This study involved 48 adolescent patients with MDD and 31 healthy controls (HC). All participants were assessed using the Patient Health Questionnaire-9 Scale and the mini international neuropsychiatric interview (MINI) suicide inventory. In addition, a Siemens Skyra 3.0T magnetic resonance scanner was used to obtain the subjects' image data. The DPABI software was utilized to calculate the WM signal of the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity, followed by a two-sample t-test between the MDD and HC groups. Independent component analysis (ICA) was also used to evaluate the WM functional signal. Pearson's correlation was performed to assess the relationship between statistical test results and clinical scales. Compared to HC, individuals with MDD demonstrated a decrease in the fALFF of WM in the corpus callosum body, left posterior limb of the internal capsule, right superior corona radiata, and bilateral posterior corona radiata [P < 0.001, family-wise error (FWE) voxel correction]. The regional homogeneity of WM increased in the right posterior limb of internal capsule and left superior corona radiata, and decreased in the left superior longitudinal fasciculus (P < 0.001, FWE voxel correction). The ICA results of WM overlapped with those of regional homo-geneity. The fALFF of WM signal in the left posterior limb of the internal capsule was negatively correlated with the MINI suicide scale (P = 0.026, r = -0.32), and the right posterior corona radiata was also negatively correlated with the MINI suicide scale (P = 0.047, r = -0.288). Adolescents with MDD involves changes in WM functional signals, and these differences in brain regions may increase the risk of suicide.

Diffusion kurtosis imaging of brain white matter alteration in patients with coronary artery disease based on the TBSS method.

The aim of our study was to examine the alterations in microstructure in patients with coronary artery disease (CAD) and cognitive impairment (CI) using diffusion kurtosis imaging (DKI). Additionally, we aimed to investigate the potential correlation between DKI parameters and cognitive function. A total of 28 CAD patients and 30 healthy controls (HC) were prospectively enrolled in our study. All participants underwent routine and diffusion sequences of head imaging. DKE software was utilized to generate various diffusion kurtosis imaging parameters (DKI), including kurtosis fractional anisotropy (KFA), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and mean diffusivity (MD). Nonparametric tests were conducted using tract-based spatial statistics (TBSS) to compare the parameter values between the two groups. The parameter values of the significantly different fiber tracts were extracted and correlated with the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Compared to the HC group, patients with coronary artery disease exhibited significant reductions in FA values in the bilateral Superior corona radiata, bilateral Anterior corona radiata, bilateral Posterior corona radiata, corpus callosum, left Posterior thalamic radiation, right Posterior limb of internal capsule, Anterior limb of internal capsule, and Cerebral peduncle, as well as in the left Superior longitudinal fasciculus. Additionally, KFA values decreased in the bilateral Anterior corona radiata, bilateral Anterior limb of internal capsule, and Genu of the corpus callosum. The MK values decreased in the right Posterior corona radiata, Retrolenticular part of the internal capsule, Posterior thalamic radiation (including optic radiation), Superior longitudinal fasciculus, and left Posterior thalamic radiation (including optic radiation). Moreover, the RK values decreased in the bilateral Retrolenticular part of the internal capsule, right Posterior thalamic radiation (including optic radiation), and Superior longitudinal fasciculus, as well as in the left Superior longitudinal fasciculus and Posterior thalamic radiation (including optic radiation) (p < 0.01, TFCE corrected), while no significant differences were observed in other parameter values (p > 0.01, TFCE corrected). The FA values of the right posterior limb of the internal capsule (r = 0.610, p = 0.001) and the right cerebral peduncle (r = 0.622, p < 0.001) were positively correlated with MMSE scores. Additionally, a significant correlation between kurtosis and diffusion coefficient parameters (FA and KFA) was observed. CAD patients showed radial shrinkage and complexity of brain white matter microstructure. Whole-brain white matter analysis based on TBSS DKI can objectively reflect the characteristics of white matter damage in CAD patients, providing a basis for the auxiliary diagnosis of CAD with CI.

Effects of α1-antitrypsin on motor function in mice with immature brain white matter injury

To investigate the effects of α1-antitrypsin (AAT) on motor function in adult mice with immature brain white matter injury. Five-day-old C57BL/6J mice were randomly assigned to the sham surgery group (n=27), hypoxia-ischemia (HI) + saline group (n=27), and HI+AAT group (n=27). The HI white matter injury mouse model was established using HI methods. The HI+AAT group received intraperitoneal injections of AAT (50 mg/kg) 24 hours before HI, immediately after HI, and 72 hours after HI; the HI+saline group received intraperitoneal injections of the same volume of saline at the corresponding time points. Brain T2-weighted magnetic resonance imaging scans were performed at 7 and 55 days after modeling. At 2 months of age, adult mice were evaluated for static, dynamic, and coordination parameters using the Catwalk gait analysis system. Compared to the sham surgery group, mice with HI injury showed high signal intensity on brain T2-weighted magnetic resonance imaging at 7 days after modeling, indicating significant white matter injury. The white matter injury persisted at 55 days after modeling. In comparison to the sham surgery group, the HI+saline group exhibited decreased paw print area, maximum contact area, average pressure, maximum pressure, paw print width, average velocity, body velocity, stride length, swing speed, percentage of gait pattern AA, and percentage of inter-limb coordination (left hind paw → left front paw) (P<0.05). The HI+saline group showed increased inter-paw distance, percentage of gait pattern AB, and percentage of phase lag (left front paw → left hind paw) compared to the sham surgery group (P<0.05). In comparison to the HI+saline group, the HI+AAT group showed increased average velocity, body velocity, stride length, and swing speed (right front paw) (P<0.05). The mice with immature brain white matter injury may exhibit significant motor dysfunction in adulthood, while the use of AAT can improve some aspects of their motor function.

Brain white matter microstructural alterations in patients with systemic lupus erythematosus: an automated fiber quantification study.

This study aimed to identify damaged segments of brain white matter fiber tracts in patients with systemic lupus erythematosus (SLE) using diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ), and analyze their relationship with cognitive impairment. Clinical and imaging data for 39 female patients with SLE and for 44 female healthy controls (HCs) were collected. AFQ was used to track whole-brain white matter tracts in each participant, and each tract was segmented into 100 equally spaced nodes. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated at each node. Correlations were also explored between DTI metrics in the damaged segments of white matter fiber tracts and neuropsychological test scores of patients with SLE. Compared with HCs, SLE patients exhibited significantly lower FA values, and significantly higher MD, AD, RD values in many white matter tracts (all P < 0.05, false discovery rate-corrected). FA values in nodes 97-100 of the left inferior fronto-occipital fasciculus (IFOF) positively correlated with the mini-mental state examination score. AFQ enables precise and accurate identification of damage to white matter fiber tracts in brains of patients with SLE. FA values in the left IFOF correlate with cognitive impairment in SLE.

Long-Term Brain Structure and Cognition Following Bariatric Surgery

Weight loss induced by bariatric surgery (BS) is associated with improved cognition and changed brain structure; however, previous studies on the association have used small cohorts and short follow-up periods, making it difficult to determine long-term neurological outcomes associated with BS. To investigate long-term associations of weight loss after BS with cognition and brain structure and perfusion. This cohort study included participants from the Bariatric Surgery Rijnstate and Radboudumc Neuroimaging and Cognition in Obesity study. Data from participants with severe obesity (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared] >40, or BMI >35 with comorbidities) eligible for Roux-en-Y gastric bypass and aged 35 to 55 years were enrolled from a hospital specialized in BS (Rijnstate Hospital, Arnhem, the Netherlands). Participants were recruited between September 2018 and December 2020 with follow-up till March 2023. Data were collected before BS and at 6 and 24 months after BS. Data were analyzed from March to November 2023. Roux-en-Y gastric bypass. Primary outcomes included body weight, BMI, waist circumference, blood pressure, medication use, cognitive performance (20% change index of compound z-score), brain volumes, cortical thickness, cerebral blood flow (CBF), and spatial coefficient of variation (sCOV). Secondary outcomes include cytokines, adipokines, depressive symptoms (assessed using the Beck Depression Inventory), and physical activity (assessed using the Baecke Questionnaire). A total of 133 participants (mean [SD] age, 46.8 [5.7] years; 112 [84.2%] female) were included. Global cognition was at least 20% higher in 52 participants (42.9%) at 24 months after BS. Compared with baseline, at 24 months, inflammatory markers were lower (mean [SD] high-sensitivity C-reactive protein: 4.77 [5.80] μg/mL vs 0.80 [1.09] μg/mL; P < .001), fewer patients used antihypertensives (48 patients [36.1%] vs 22 patients [16.7%]), and patients had lower depressive symptoms (median [IQR] BDI score: 9.0 [5.0-13.0] vs 3.0 [1.0-6.0]; P < .001) and greater physical activity (mean [SD] Baecke score: 7.64 [1.29] vs 8.19 [1.35]; P < .001). After BS, brain structure and perfusion were lower in most brain regions, while hippocampal and white matter volume remained stable. CBF and sCOV did not change in nucleus accumbens and parietal cortex. The temporal cortex showed a greater thickness (mean [SD] thickness: 2.724 [0.101] mm vs 2.761 [0.007] mm; P = .007) and lower sCOV (median [IQR] sCOV: 4.41% [3.83%-5.18%] vs 3.97% [3.71%-4.59%]; P = .02) after BS. These findings suggest that BS was associated with health benefits 2 years after surgery. BS was associated with improved cognition and general health and changed blood vessel efficiency and cortical thickness of the temporal cortex. These results may improve treatment options for patients with obesity and dementia.

Longitudinal enlargement of choroid plexus is associated with chronic lesion expansion and neurodegeneration in RRMS patients

Background and Objective: We explored dynamic changes in the choroid plexus (CP) in patients with relapsing-remitting multiple sclerosis (RRMS) and assessed its relationship with chronic lesion expansion and atrophy in various brain compartments. Methods: Fifty-seven RRMS patients were annually assessed for a minimum of 48 months with 3D FLAIR, pre- and post-contrast 3D T1 and diffusion-weighted magnetic resonance imaging (MRI). The CP was manually segmented at baseline and last follow-up. Results: The volume of CP significantly increased by 1.4% annually. However, the extent of CP enlargement varied considerably among individuals (ranging from −3.6 to 150.8 mm3 or −0.2% to 6.3%). The magnitude of CP enlargement significantly correlated with central (r = 0.70, p < 0.001) and total brain atrophy (r = −0.57, p < 0.001), white (r = −0.61, p < 0.001) and deep grey matter atrophy (r = −0.60, p < 0.001). Progressive CP enlargement was significantly associated with the volume and extent of chronic lesion expansion (r = 0.60, p < 0.001), but not with the number or volume of new lesions. Conclusion: This study provides evidence of progressive CP enlargement in patients with RRMS. Our findings also demonstrate that enlargement of the CP volume is linked to the expansion of chronic lesions and neurodegeneration of periventricular white and grey matter in RRMS patients.