Distinct patterns of white matter hyperintensity and cortical thickness of CSF1R-related leukoencephalopathy compared with subcortical ischemic vascular dementia.

BACKGROUND: CSF1R-related leukoencephalopathy is a type of autosomal dominant leukodystrophy caused by mutations in the colony stimulating factor 1 receptor (CSF1R) gene. Subcortical ischemic vascular dementia (SIVaD), which is caused by cerebral small vessel disease, is similar to CSF1R-related leukoencephalopathy in that it mainly affects subcortical white matter. In this study, we compared the patterns of white matter hyperintensity (WMH) and cortical thickness in CSF1R-related leukoencephalopathy with those in SIVaD. METHODS: Fourteen patients with CSF1R-related leukoencephalopathy and 129 with SIVaD were retrospectively recruited from three tertiary medical centers. We extracted and visualized WMH data using voxel-based morphometry to compare the WMH distributions between the two groups. Cortical thickness was measured using a surface-based method. Statistical maps of differences in cortical thickness between the two groups were generated using a surface model, with age, sex, education, and intracranial volume as covariates. RESULTS: Predominant distribution of WMH in the CSF1R-related leukoencephalopathy group was in the bilateral frontal and parietal areas, whereas the SIVaD group showed diffuse WMH involvement in the bilateral frontal, parietal, and temporal areas. Compared with the SIVaD group, the CSF1R-related leukoencephalopathy group showed more severe corpus callosum atrophy (CCA) and widespread cortical thinning. CONCLUSIONS: To our knowledge, this is the first study using the automated MR measurement to capture WMH, cortical thinning, and CCA with signal changes in CSF1R-related leukoencephalopathy. It provides new evidence regarding differences in the patterns of WMH distribution and cortical thinning between CSF1R-related leukoencephalopathy and SIVaD.

White Matter Hyperintensities and Cognitive Functions in People With the R544C Variant of the NOTCH3 Gene Without Stroke or Dementia.

BACKGROUND AND OBJECTIVES: NOTCH3 pathologic variants cause cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), which presents with stroke and dementia and is characterized by white matter hyperintensities (WMHs) on brain MRI. The R544C variant is a common pathologic variant in Taiwan, but not all carriers exhibit significant symptoms. We investigated whether WMHs occur before clinical symptoms in carriers with pathogenic variants, examined factors associated with WMHs, and explored their relationship with cognitive functions. METHODS: We enrolled 63 R544C carriers without overt clinical disease (WOCD) and 37 age-matched and sex-matched noncarriers as controls from the Taiwan Precision Medicine Initiative data set. All participants underwent clinical interviews, comprehensive neuropsychological assessments, and brain MRI. We calculated total and regional WMH volumes, determined the age at which WMHs began increasing in carriers, and examined the relationship between WMHs and neuropsychological performance. Factors associated with WMH volumes were analyzed using multivariable linear regression models. RESULTS: Compared with controls, R544C carriers WOCD had increased WMH volume, except in the occipital and midbrain areas, and showed a rapid increase in WMHs starting at age 48. They scored lower on the Mini-Mental State Examination (median = 28.4 vs 29.0, p = 0.048), Montreal Cognitive Assessment (MoCA) (median = 28.3 vs 29.0, p = 0.013), and memory and executive function tests than controls. After adjusting for age, sex, and education, MoCA scores were associated with whole-brain (r = -0.387, padj = 0.008) and regional WMHs (all padj < 0.05) except in the midbrain area. Age (ß = 0.034, 95% CI 0.021-0.046, p < 0.001), hypercholesterolemia (ß = 0.375, 95% CI 0.097-0.653, p = 0.009), and the vascular risk factor (VRF) index (ß = 0.132, 95% CI 0.032-0.242, p = 0.019) were associated with the WMH severity in carriers. DISCUSSION: Our study revealed that WMHs are extensively distributed in R544C carriers WOCD. They exhibited a rapid increase in WMHs beginning at age 48, approximately 7 years earlier than the reported age at symptomatic onset. Age was the strongest predictive factor of WMHs, and VRF, particularly hypercholesterolemia, might be modifying factors of WMHs.

Microangiopathy in temporal lobe epilepsy with diffusion MRI alterations and cognitive decline.

White matter microvascular alterations in temporal lobe epilepsy (TLE) may be relevant to acquired neurodegenerative processes and cognitive impairments associated with this condition. We quantified microvascular changes, myelin, axonal, glial and extracellular-matrix labelling in the gyral core and deep temporal lobe white matter regions in surgical resections from 44 TLE patients with or without hippocampal sclerosis. We compared this pathology data with in vivo pre-operative MRI diffusion measurements in co-registered regions and neuropsychological measures of cognitive impairment and decline. In resections, increased arteriolosclerosis was observed in TLE compared to non-epilepsy controls (greater sclerotic index, p < 0.001), independent of age. Microvascular changes included increased vascular densities in some regions but uniformly reduced mean vascular size (quantified with collagen-4, p < 0.05-0.0001), and increased pericyte coverage of small vessels and capillaries particularly in deep white matter (quantified with platelet-derived growth factor receptorß and smooth muscle actin, p < 0.01) which was more marked the longer the duration of epilepsy (p < 0.05). We noted increased glial numbers (Olig2, Iba1) but reduced myelin (MAG, PLP) in TLE compared to controls, particularly prominent in deep white matter. Gene expression analysis showed a greater reduction of myelination genes in HS than non-HS cases and with age and correlation with diffusion MRI alterations. Glial densities and vascular size were increased with increased MRI diffusivity and vascular density with white matter abnormality quantified using fixel-based analysis. Increased perivascular space was associated with reduced fractional anisotropy as well as age-accelerated cognitive decline prior to surgery (p < 0.05). In summary, likely acquired microangiopathic changes in TLE, including vascular sclerosis, increased pericyte coverage and reduced small vessel size, may indicate a functional alteration in contractility of small vessels and haemodynamics that could impact on tissue perfusion. These morphological features correlate with white matter diffusion MRI alterations and might explain cognitive decline in TLE.

Subtle motor signs in children with ADHD and their white matter correlates.

Subtle motor signs are a common feature in children with attention-deficit/hyperactivity disorder (ADHD). It has long been suggested that white matter abnormalities may be involved in their presentation, though no study has directly probed this question. The aim of this study was to investigate the relationship between white matter organization and the severity of subtle motor signs in children with and without ADHD. Participants were 92 children with ADHD aged between 8 and 12 years, and 185 typically developing controls. Subtle motor signs were examined using the Physical and Neurological Examination for Soft Signs (PANESS). Children completed diffusion MRI, and fixel-based analysis was performed after preprocessing. Tracts of interest were delineated using TractSeg including the corpus callosum (CC), the bilateral corticospinal tracts (CST), superior longitudinal fasciculus, and fronto-pontine tracts (FPT). Fiber cross-section (FC) was calculated for each tract. Across all participants, lower FC in the CST was associated with higher PANESS Total score (greater motor deficits). Within the PANESS, similar effects were observed for Timed Left and Right maneuvers of the hands and feet, with lower FC of the CST, CC, and FPT associated with poorer performance. No significant group differences were observed in FC in white matter regions associated with PANESS performance. Our data are consistent with theoretical accounts implicating white matter organization in the expression of motor signs in childhood. However, rather than contributing uniquely to the increased severity of soft motor signs in those with ADHD, white matter appears to contribute to these symptoms in childhood in general.

Examining relationships among NODDI indices of white matter structure in prefrontal cortical-thalamic-striatal circuitry and OCD symptomatology.

Obsessive-compulsive disorder is a psychiatric disorder characterized by intrusive thoughts and repetitive behaviors. There are two prominent features: Harm Avoidance (HA) and Incompleteness (INC). Previous resting-state studies reported abnormally elevated connectivity between prefrontal cortical (PFC) and subcortical regions (thalamus, striatum) in OCD participants. Yet, little is known about the white matter (WM) structural abnormalities in these connections. Using brain parcellation and segmentation, whole brain tractography, and Neurite Orientation Dispersion and Density Imaging (NODDI), we aimed to characterize WM structural abnormalities in OCD vs. healthy controls and determine the extent to which NODDI indices of these connections were associated with subthreshold-threshold HA, INC and overall OCD symptom severity across all participants. Four PFC regions were segmented: ventral medial (vmPFC), ventrolateral (vlPFC), dorsomedial (dmPFC), and dorsolateral (dlPFC). NODDI Neurite Density (NDI) and Orientation Dispersion (ODI) indices of WM structure were extracted from connections between these PFC regions and the thalamus (42 OCD, 44 healthy controls, mean age[SD] = 23.65[4.25]y, 63.9% female) and striatum (38 OCD, 41 healthy controls, mean age[SD] = 23.59[4.27]y, 64.5% female). Multivariate analyses of covariance revealed no between-group differences in these indices. Multivariate regression models revealed that greater NDI in vmPFC-thalamus, greater NDI and ODI in vmPFC-striatum, and greater NDI in dmPFC-thalamus connections were associated with greater INC severity (Q ≤ 0.032). These findings highlight the utility of NODDI in the examination of WM structure in OCD, provide valuable insights into specific WM alterations underlying dimensional INC, and can facilitate the development of customized treatments for OCD individuals with treatment-resistant symptoms.

Musical Sophistication and Multilingualism: Effects on Arcuate Fasciculus Characteristics.

The processing of auditory stimuli which are structured in time is thought to involve the arcuate fasciculus, the white matter tract which connects the temporal cortex and the inferior frontal gyrus. Research has indicated effects of both musical and language experience on the structural characteristics of the arcuate fasciculus. Here, we investigated in a sample of n = 84 young adults whether continuous conceptualizations of musical and multilingual experience related to structural characteristics of the arcuate fasciculus, measured using diffusion tensor imaging. Probabilistic tractography was used to identify the dorsal and ventral parts of the white matter tract. Linear regressions indicated that different aspects of musical sophistication related to the arcuate fasciculus' volume (emotional engagement with music), volumetric asymmetry (musical training and music perceptual abilities), and fractional anisotropy (music perceptual abilities). Our conceptualization of multilingual experience, accounting for participants' proficiency in reading, writing, understanding, and speaking different languages, was not related to the structural characteristics of the arcuate fasciculus. We discuss our results in the context of other research on hemispheric specializations and a dual-stream model of auditory processing.

Mendelian Randomization Analysis to Assess Whether Magnetic Resonance Imaging Signs of Cerebral Small Vessel Disease Can Cause Cognitive Decline and Dementia.

OBJECTIVE: Cognitive decline and dementia have been linked to cerebral small vessel disease, so we explored using Mendelian randomization whether cerebral small vessel disease visible as 10 neuroimaging signs may cause cognitive decline and dementia. METHODS: We analyzed publicly available data from genome-wide association studies using two-sample Mendelian randomization involving inverse variance weighting, weighted median, MR-Egger, and MR-PRESSO approaches. RESULTS: Mendelian randomization suggested that cognitive decline can be caused by lacunar stroke (inverse variance weighting, ß = -0.012, 95% CI -0.024 to -0.001, P = 0.033). Furthermore, an elevated burden of white matter hyperintensities was associated with an increased risk of Dementia due to Parkinson's disease (inverse variance weighting, OR 2.035, 95% CI 1.105 to 3.745, P = 0.023). Notably, no significant associations were observed between neuroimaging markers of Cerebral Small Vessel Disease and other types of dementia. CONCLUSION: This Mendelian randomization study provides evidence that lacunar stroke and white matter lesions can cause cognitive decline, and that white matter hyperintensity may increase risk of dementia due to Parkinson's disease. These results underscore the need for further investigations into the neurocognitive effects of cerebral small vessel disease.

Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder.

BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder associated with alterations in structural and functional coupling in gray matter. However, despite the detectability and modulation of brain signals in white matter, the structure-function coupling in white matter in autism remains less explored. METHODS: In this study, we investigated structural-functional coupling in white matter (WM) regions, by integrating diffusion tensor data that contain fiber orientation information from WM tracts, with functional connectivity tensor data that reflect local functional anisotropy information. Using functional and diffusion magnetic resonance images, we analyzed a cohort of 89 ASD and 63 typically developing (TD) individuals from the Autism Brain Imaging Data Exchange II (ABIDE-II). Subsequently, the associations between structural-functional coupling in WM regions and ASD severity symptoms assessed by Autism Diagnostic Observation Schedule-2 were examined via supervised machine learning in an independent test cohort of 29 ASD individuals. Furthermore, we also compared the performance of multi-model features (i.e. structural-functional coupling) with single-model features (i.e. functional or structural models alone). RESULTS: In the discovery cohort (ABIDE-II), individuals with ASD exhibited widespread reductions in structural-functional coupling in WM regions compared to TD individuals, particularly in commissural tracts (e.g. corpus callosum), association tracts (sagittal stratum), and projection tracts (e.g. internal capsule). Notably, supervised machine learning analysis in the independent test cohort revealed a significant correlation between these alterations in structural-functional coupling and ASD severity scores. Furthermore, compared to single-model features, the integration of multi-model features (i.e., structural-functional coupling) performed best in predicting ASD severity scores. CONCLUSION: This work provides novel evidence for atypical structural-functional coupling in ASD in white matter regions, further refining our understanding of the critical role of WM networks in the pathophysiology of ASD.

White matter disconnection impacts proprioception post-stroke.

Proprioceptive impairments occur in approximately 50-64% of people following stroke. While much is known about the grey matter structures underlying proprioception, our understanding of the white matter correlates of proprioceptive impairments is less well developed. It is recognised that behavioural impairments post-stroke are often the result of disconnection between wide-scale brain networks, however the disconnectome associated with proprioception post-stroke is unknown. In the current study, white matter disconnection was assessed in relation to performance on a robotic arm position matching (APM) task. Neuroimaging and robotic assessments of proprioception were collected for 203 stroke survivors, approximately 2-weeks post-stroke. The robotic assessment was performed in a KINARM Exoskeleton robotic device and consisted of a nine-target APM task. First, the relationship between white matter tract lesion load and performance on the APM task was assessed. Next, differences in the disconnectome between participants with and without impairments on the APM task were examined. Greater lesion load to the superior longitudinal fasciculus (SLF II and III), arcuate fasciculus (all segments) and fronto-insular tracts were associated with worse APM task performance. In those with APM task impairments, there was, additionally, disconnection of the posterior corpus callosum, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus and optic radiations. This study highlights an important perisylvian white matter network supporting proprioceptive processing in the human brain. It also identifies white matter tracts, important for relaying proprioceptive information from parietal and frontal brain regions, that are not traditionally considered proprioceptive in nature.

Atlas-based assessment of hypomyelination: Quantitative MRI in Pelizaeus-Merzbacher disease.

Pelizaeus-Merzbacher disease (PMD) is a rare childhood hypomyelinating leukodystrophy. Quantification of the pronounced myelin deficit and delineation of subtle myelination processes are of high clinical interest. Quantitative magnetic resonance imaging (qMRI) techniques can provide in vivo insights into myelination status, its spatial distribution, and dynamics during brain maturation. They may serve as potential biomarkers to assess the efficacy of myelin-modulating therapies. However, registration techniques for image quantification and statistical comparison of affected pediatric brains, especially those of low or deviant image tissue contrast, with healthy controls are not yet established. This study aimed first to develop and compare postprocessing pipelines for atlas-based quantification of qMRI data in pediatric patients with PMD and evaluate their registration accuracy. Second, to apply an optimized pipeline to investigate spatial myelin deficiency using myelin water imaging (MWI) data from patients with PMD and healthy controls. This retrospective single-center study included five patients with PMD (mean age, 6 years ± 3.8) who underwent conventional brain MRI and diffusion tensor imaging (DTI), with MWI data available for a subset of patients. Three methods of registering PMD images to a pediatric template were investigated. These were based on (a) T1-weighted (T1w) images, (b) fractional anisotropy (FA) maps, and (c) a combination of T1w, T2-weighted, and FA images in a multimodal approach. Registration accuracy was determined by visual inspection and calculated using the structural similarity index method (SSIM). SSIM values for the registration approaches were compared using a t test. Myelin water fraction (MWF) was quantified from MWI data as an assessment of relative myelination. Mean MWF was obtained from two PMDs (mean age, 3.1 years ± 0.3) within four major white matter (WM) pathways of a pediatric atlas and compared to seven healthy controls (mean age, 3 years ± 0.2) using a Mann-Whitney U test. Our results show that visual registration accuracy estimation and computed SSIM were highest for FA-based registration, followed by multimodal, and T1w-based registration (SSIMFA = 0.67 ± 0.04 vs. SSIMmultimodal = 0.60 ± 0.03 vs. SSIMT1 = 0.40 ± 0.14). Mean MWF of patients with PMD within the WM pathways was significantly lower than in healthy controls MWFPMD = 0.0267 ± 0.021 vs. MWFcontrols = 0.1299 ± 0.039. Specifically, MWF was measurable in brain structures known to be myelinated at birth (brainstem) or postnatally (projection fibers) but was scarcely detectable in other brain regions (commissural and association fibers). Taken together, our results indicate that registration accuracy was highest with an FA-based registration pipeline, providing an alternative to conventional T1w-based registration approaches in the case of hypomyelinating leukodystrophies missing normative intrinsic tissue contrasts. The applied atlas-based analysis of MWF data revealed that the extent of spatial myelin deficiency in patients with PMD was most pronounced in commissural and association and to a lesser degree in brainstem and projection pathways.

Abnormal multimodal neuroimaging patterns associated with social deficits in male autism spectrum disorder.

Atypical social impairments (i.e., impaired social cognition and social communication) are vital manifestations of autism spectrum disorder (ASD) patients, and the incidence rate of ASD is significantly higher in males than in females. Characterizing the atypical brain patterns underlying social deficits of ASD is significant for understanding the pathogenesis. However, there are no robust imaging biomarkers that are specific to ASD, which may be due to neurobiological complexity and limitations of single-modality research. To describe the multimodal brain patterns related to social deficits in ASD, we highlighted the potential functional role of white matter (WM) and incorporated WM functional activity and gray matter structure into multimodal fusion. Gray matter volume (GMV) and fractional amplitude of low-frequency fluctuations of WM (WM-fALFF) were combined by fusion analysis model adopting the social behavior. Our results revealed multimodal spatial patterns associated with Social Responsiveness Scale multiple scores in ASD. Specifically, GMV exhibited a consistent brain pattern, in which salience network and limbic system were commonly identified associated with all multiple social impairments. More divergent brain patterns in WM-fALFF were explored, suggesting that WM functional activity is more sensitive to ASD's complex social impairments. Moreover, brain regions related to social impairment may be potentially interconnected across modalities. Cross-site validation established the repeatability of our results. Our research findings contribute to understanding the neural mechanisms underlying social disorders in ASD and affirm the feasibility of identifying biomarkers from functional activity in WM.

White matter abnormalities in aneurysmal and angiographically negative subarachnoid hemorrhage: A diffusion kurtosis imaging study.

OBJECTIVE: Aneurysmal subarachnoid hemorrhage (aSAH) and angiographically negative subarachnoid hemorrhage (anSAH) cause an abrupt rise in intracranial pressure, resulting in shearing forces, causing damage to the white matter tracts. This study aims to investigate whole-brain white matter abnormalities with diffusion kurtosis imaging (DKI) after both aSAH and anSAH and explores whether these abnormalities are associated with impaired cognitive functioning. METHODS: Five months post-ictus, 34 patients with aSAH, 24 patients with anSAH and 17 healthy controls (HC) underwent DKI MRI scanning and neuropsychological assessment (measuring verbal memory, psychomotor speed, executive control, and social cognition). Differences in DKI measures (fractional anisotropy, mean diffusivity, axial diffusivity [AD], radial diffusivity, and mean kurtosis) were examined using tract-based spatial statistics. Significant voxel masks were then correlated with neuropsychological scores. RESULTS: All DKI measures differed significantly between patients with aSAH and HC, but no significant differences were found between patients with anSAH and HC. Although the two SAH groups did not differ significantly on all DKI parameters, effect sizes indicated that the anSAH group might be more similar to HC. Cognitive impairments were found for both SAH groups relative to HC. No significant associations were found between these impairments and white matter abnormalities in the aSAH group, but lower psychomotor speed scores were associated with higher AD values (r = -0.41, p = 0.04) in patients with anSAH. CONCLUSIONS: Patients with aSAH showed significant white matter diffusion abnormalities, while the anSAH group, despite cognitive deficits, did not. However, there were no significant differences between the SAH groups, and no correlations between DKI metrics and cognitive measures, except for one test on psychomotor speed in the anSAH group. Overall, this study suggests that while anSAH may not be as severe as aSAH, it is still not a benign condition. Further research with larger anSAH cohorts is necessary to gain a more precise understanding of white matter injuries, particularly regarding their prevalence.

Structural connectivity modifications following deep brain stimulation of the subcallosal cingulate and nucleus accumbens in severe anorexia nervosa.

PURPOSE: Anorexia nervosa (AN) is a mental health disorder characterized by significant weight loss and associated medical and psychological comorbidities. Conventional treatments for severe AN have shown limited effectiveness, leading to the exploration of novel interventional strategies, including deep brain stimulation (DBS). However, the neural mechanisms driving DBS interventions, particularly in psychiatric conditions, remain uncertain. This study aims to address this knowledge gap by examining changes in structural connectivity in patients with severe AN before and after DBS. METHODS: Sixteen participants, including eight patients with AN and eight controls, underwent baseline T1-weigthed and diffusion tensor imaging (DTI) acquisitions. Patients received DBS targeting either the subcallosal cingulate (DBS-SCC, N = 4) or the nucleus accumbens (DBS-NAcc, N = 4) based on psychiatric comorbidities and AN subtype. Post-DBS neuroimaging evaluation was conducted in four patients. Data analyses were performed to compare structural connectivity between patients and controls and to assess connectivity changes after DBS intervention. RESULTS: Baseline findings revealed that structural connectivity is significantly reduced in patients with AN compared to controls, mainly regarding callosal and subcallosal white matter (WM) tracts. Furthermore, pre- vs. post-DBS analyses in AN identified a specific increase after the intervention in two WM tracts: the anterior thalamic radiation and the superior longitudinal fasciculus-parietal bundle. CONCLUSIONS: This study supports that structural connectivity is highly compromised in severe AN. Moreover, this investigation preliminarily reveals that after DBS of the SCC and NAcc in severe AN, there are WM modifications. These microstructural plasticity adaptations may signify a mechanistic underpinning of DBS in this psychiatric disorder.

White matter microstructure and functional connectivity in the brains of infants with Turner syndrome.

Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome.

Impact of excessive abdominal obesity on brain microstructural abnormality in schizophrenia.

Significant evidence links obesity and schizophrenia (SZ), but the brain associations are still largely unclear. 48 people with SZ were divided into two subgroups: patients with lower waist circumference (SZ-LWC: n = 24) and patients with higher waist circumference (SZ-HWC: n = 24). Healthy controls (HC) were included for comparison (HC: n = 27). Using tract-based spatial statistics, we compared fractional anisotropy (FA) of the whole-brain white matter skeleton between these three groups (SZ-LWC, SZ-HWC, HC). Using Free Surfer, we compared whole-brain cortical thickness and the selected subcortical volumes between the three groups. FA of widespread white matter and the mean cortical thickness in the right temporal lobe and insular cortex were significantly lower in the SZ-HWC group than in the HC group. The FA of regional white matter was significantly lower in the SZ-LWC group than in the HC group. There were no significant differences in mean subcortical volumes between the groups. Additionally, the cognitive performances were worse in the SZ-HWC group, who had more severe triglycerides elevation. This study provides evidence for microstructural abnormalities of white matter, cortical thickness and neurocognitive deficits in SZ patients with excessive abdominal obesity.

No significant alteration in white matter microstructure in first-degree relatives of patients with obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is characterized by structural alteration within white matter tissues of cortico-striato-thalamo-cortical, temporal and occipital circuits. However, the presence of microstructural changes in the white matter tracts of unaffected first-degree relatives of patients with OCD as a vulnerability marker remains unclear. Therefore, here, diffusion-tensor magnetic resonance imaging (DTI) data were obtained from 29 first-degree relatives of patients with OCD and 59 healthy controls. We investigated the group differences in FA using whole-brain analysis (DTI analysis). For additional regions of interest (ROI) analysis, we focused on the posterior thalamic radiation and sagittal stratum, shown in recent meta-analysis of patients with OCD. In both whole-brain and ROI analyses, using a strict statistical threshold (family-wise error rate [FWE] corrected p<.05 for whole-brain analyses, and p<.0125 (0.05/4) with Bonferroni correction for ROI analyses), we found no significant group differences in FA. Subtle reductions were observed in the anterior corona radiata, forceps minor, cingulum bundle, and corpus callosum only when a lenient statistical was applied (FWE corrected p<.20). These findings suggest that alterations in the white matter microstructure of first-degree relatives, as potential vulnerability markers for OCD, are likely subtle.

Cluster-Based White Matter Signatures and the Risk of Dementia, Stroke, and Mortality in Community-Dwelling Adults.

BACKGROUND AND OBJECTIVES: Markers of white matter (WM) injury on brain MRI are important indicators of brain health. Different patterns of WM atrophy, WM hyperintensities (WMHs), and microstructural integrity could reflect distinct pathologies and disease risks, but large-scale imaging studies investigating WM signatures are lacking. This study aims to identify distinct WM signatures using brain MRI in community-dwelling adults, determine underlying risk factor profiles, and assess risks of dementia, stroke, and mortality associated with each signature. METHODS: Between 2005 and 2016, we measured WMH volume, WM volume, fractional anisotropy (FA), and mean diffusivity (MD) using automated pipelines on structural and diffusion MRI in community-dwelling adults aged older than 45 years of the Rotterdam study. Continuous surveillance was conducted for dementia, stroke, and mortality. We applied hierarchical clustering to identify separate WM injury clusters and Cox proportional hazard models to determine their risk of dementia, stroke, and mortality. RESULTS: We included 5,279 participants (mean age 65.0 years, 56.0% women) and identified 4 distinct data-driven WM signatures: (1) above-average microstructural integrity and little WM atrophy and WMH; (2) above-average microstructural integrity and little WMH, but substantial WM atrophy; (3) poor microstructural integrity and substantial WMH, but little WM atrophy; and (4) poor microstructural integrity with substantial WMH and WM atrophy. Prevalence of cardiovascular risk factors, lacunes, and cerebral microbleeds was higher in clusters 3 and 4 than in clusters 1 and 2. During a median 10.7 years of follow-up, 291 participants developed dementia, 220 had a stroke, and 910 died. Compared with cluster 1, dementia risk was increased for all clusters, notably cluster 3 (hazard ratio [HR] 3.06, 95% CI 2.12-4.42), followed by cluster 4 (HR 2.31, 95% CI 1.58-3.37) and cluster 2 (HR 1.67, 95% CI 1.17-2.38). Compared with cluster 1, risk of stroke was higher only for clusters 3 (HR 1.55, 95% CI 1.02-2.37) and 4 (HR 1.94, 95% CI 1.30-2.89), whereas mortality risk was increased in all clusters (cluster 2: HR 1.27, 95% CI 1.06-1.53, cluster 3: HR 1.65, 95% CI 1.35-2.03, cluster 4: HR 1.76, 95% CI 1.44-2.15), compared with cluster 1. Models including clusters instead of an individual imaging marker showed a superior goodness of fit for dementia and mortality, but not for stroke. DISCUSSION: Clustering can derive WM signatures that are differentially associated with dementia, stroke, and mortality risk. Future research should incorporate spatial information of imaging markers.

Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysis.

Intravital 2P-microscopy enables the longitudinal study of brain tumor biology in superficial mouse cortex layers. Intravital microscopy of the white matter, an important route of glioblastoma invasion and recurrence, has not been feasible, due to low signal-to-noise ratios and insufficient spatiotemporal resolution. Here, we present an intravital microscopy and artificial intelligence-based analysis workflow (Deep3P) that enables longitudinal deep imaging of glioblastoma up to a depth of 1.2 mm. We find that perivascular invasion is the preferred invasion route into the corpus callosum and uncover two vascular mechanisms of glioblastoma migration in the white matter. Furthermore, we observe morphological changes after white matter infiltration, a potential basis of an imaging biomarker during early glioblastoma colonization. Taken together, Deep3P allows for a non-invasive intravital investigation of brain tumor biology and its tumor microenvironment at subcortical depths explored, opening up opportunities for studying the neuroscience of brain tumors and other model systems.

In vivo spectrally unmixed multi-photon imaging of longitudinal axon-glia changes in injured spinal white matter.

Understanding the sequence of cellular responses and their contributions to pathomorphogical changes in spinal white matter injuries is a prerequisite for developing efficient therapeutic strategies for spinal cord injury (SCI) as well as neurodegenerative and inflammatory diseases of the spinal cord such as amyotrophic lateral sclerosis and multiple sclerosis. We have developed several types of surgical procedures suitable for acute one-time and chronic recurrent in vivo multiphoton microscopy of spinal white matter [1]. Sophisticated surgical procedures were combined with transgenic mouse technology to image spinal tissue labeled with up to four fluorescent proteins (FPs) in axons, astrocytes, microglia, and blood vessels. To clearly separate the simultaneously excited FPs, spectral unmixing including iterative procedures was performed after imaging the diversely labeled spinal white matter with a custom-made 4-channel two-photon laser-scanning microscope. In our longitudinal multicellular studies of injured spinal white matter, we imaged axonal dynamics and invasion of microglia and astrocytes for a time course of over 200 days after SCI. Our methods offer ideal platforms for investigating acute and chronic cellular dynamics, cell-cell interactions, and metabolite fluctuations in health and disease as well as pharmacological manipulations in vivo.

On the application of hybrid deep 3D convolutional neural network algorithms for predicting the micromechanics of brain white matter.

BACKGROUND: Material characterization of brain white matter (BWM) is difficult due to the anisotropy inherent to the three-dimensional microstructure and the various interactions between heterogeneous brain-tissue (axon, myelin, and glia). Developing full scale finite element models that accurately represent the relationship between the micro and macroscale BWM is however extremely challenging and computationally expensive. The anisotropic properties of the microstructure of BWM computed by building unit cells under frequency domain viscoelasticity comprises of 36 individual constants each, for the loss and storage moduli. Furthermore, the architecture of each unit cell is arbitrary in an infinite dataset. METHODS: In this study, we extend our previous work on developing representative volume elements (RVE) of the microstructure of the BWM in the frequency domain to develop 3D deep learning algorithms that can predict the anisotropic composite properties. The deep 3D convolutional neural network (CNN) algorithms utilizes a voxelization method to obtain geometry information from 3D RVEs. The architecture information encoded in the voxelized location is employed as input data while cross-referencing the RVEs' material properties (output data). We further develop methods by incorporating parallel pathways, Residual Neural Networks and inception modulus that improve the efficiency of deep learning algorithms. RESULTS: This paper presents different CNN algorithms in predicting the anisotropic composite properties of BWM. A quantitative analysis of the individual algorithms is presented with the view of identifying optimal strategies to interpret the combined measurements of brain MRE and DTI. SIGNIFICANCE: The proposed Multiscale 3D ResNet (M3DR) algorithm demonstrates high learning ability and performance over baseline CNN algorithms in predicting BWM tissue properties. The hybrid M3DR framework also overcomes the significant limitations encountered in modeling brain tissue using finite elements alone including those such as high computational cost, mesh and simulation failure. The proposed framework also provides an efficient and streamlined platform for implementing complex boundary conditions, modeling intrinsic material properties and imparting interfacial architecture information.