Altered associations between white matter structure and psychopathology in previously institutionalized adolescents.

Previously institutionalized adolescents show increased risk for psychopathology, though placement into high-quality foster care can partially mitigate this risk. White matter (WM) structure is associated with early institutional rearing and psychopathology in youth. Here we investigate associations between WM structure and psychopathology in previously institutionalized youth. Adolescent psychopathology data were collected using the MacArthur Health and Behavior Questionnaire. Participants underwent diffusion MRI, and data were processed using fixel-based analyses. General linear models investigated interactions between institutionalization groups and psychopathology on fixel metrics. Supplementary analyses also examined the main effects of psychopathology and institutionalization group on fixel metrics. Ever-Institutionalized children included 41 randomized to foster care (Mage=16.6), and 40 to care-as-usual (Mage=16.7)). In addition, 33 participants without a history of institutionalization were included as a reference group (Mage=16.9). Ever-Institutionalized adolescents displayed altered general psychopathology-fixel associations within the cerebellar peduncles, inferior longitudinal fasciculi, corticospinal tract, and corpus callosum, and altered externalizing-fixel associations within the cingulum and fornix. Our findings indicate brain-behavior associations reported in the literature may not be generalizable to all populations. Previously institutionalized youth may develop differential brain development, which in turn leads to altered neural correlates of psychopathology that are still apparent in adolescence.

Plastic reorganization of the topological asymmetry of hemispheric white matter networks induced by congenital visual experience deprivation.

Congenital blindness offers a unique opportunity to investigate human brain plasticity. The influence of congenital visual loss on the asymmetry of the structural network remains poorly understood. To address this question, we recruited 21 participants with congenital blindness (CB) and 21 age-matched sighted controls (SCs). Employing diffusion and structural magnetic resonance imaging, we constructed hemispheric white matter (WM) networks using deterministic fiber tractography and applied graph theory methodologies to assess topological efficiency (i.e., network global efficiency, network local efficiency, and nodal local efficiency) within these networks. Statistical analyses revealed a consistent leftward asymmetry in global efficiency across both groups. However, a different pattern emerged in network local efficiency, with the CB group exhibiting a symmetric state, while the SC group showed a leftward asymmetry. Specifically, compared to the SC group, the CB group exhibited a decrease in local efficiency in the left hemisphere, which was caused by a reduction in the nodal properties of some key regions mainly distributed in the left occipital lobe. Furthermore, interhemispheric tracts connecting these key regions exhibited significant structural changes primarily in the splenium of the corpus callosum. This result confirms the initial observation that the reorganization in asymmetry of the WM network following congenital visual loss is associated with structural changes in the corpus callosum. These findings provide novel insights into the neuroplasticity and adaptability of the brain, particularly at the network level.

Predictors of white matter hyperintensities in the elderly Congolese population.

Background: White matter hyperintensities (WMHs) are strongly linked to cardiovascular risk factors and other health conditions such as Alzheimer's disease. However, there is a dearth of research on this topic in low-income countries and underserved populations, especially in the Democratic Republic of Congo (DRC) where the population is aging rapidly with increasing cardiovascular risk factors and dementia-related diseases. This study evaluates health factors associated with WMH in the elderly Sub-Saharan Africa (SSA), specifically Congolese adults. Methods: In a cross-sectional study of 77 people from the DRC, participants underwent neuroimaging to analyze WMH volume and completed clinical evaluation, laboratory-based blood exams, self-reported questionnaires, and interviews. A simple linear regression model was conducted to test the association between WMH and potential predictors (neurological status, age, sex, hypertension, diabetes, tobacco abuse, stroke, high cholesterol, cardiovascular medication, and alcohol abuse). Stepwise selection and backward elimination analyses were performed to obtain the final model. Finally, a multiple linear regression model was conducted to assess the association between WMH and variables retained in the final model (neurological status, sex, and age). Results: Of the 77 individuals, 47 (61%) had dementia, 40 (52.6%) were males, and the mean age was 73 years (± 8.0 years standard deviation). In simple linear regression models, WMH was significantly associated with dementia (expß1=1.75, 95% CI=1.14 - 2.71, p-value=0.01) though it had a weak association with age (expß1=1.03, 95% CI=1.00 - 1.05, p-value=0.05) and sex (male) (expß1=0.66, 95% CI=0.43 - 1.01, p-value=0.05). In multiple linear regression models, WMH was statistically significantly associated with dementia (expß1=1.97, 95% CI=1.31 - 2.95, p-value =0.001), male sex (expß2=0.54, 95% CI=0.36 - 0.80, p-value=0.003), and age (expß3=1.03, 95% CI=1.00 - 1.06, p-value=0.03). However, WMH was not significantly associated with common cardiovascular risk factors, such as high blood pressure, diabetes, tobacco use, obesity, and high cholesterol levels. Conclusion: WMH is significantly associated with neurological status, sex, and age in the Congolese population. Understanding these predictors may improve our ability to diagnose, assess, and develop preventative treatments for white matter disease in SSA/DRC populations, where neuroimaging is difficult to obtain.

Metric comparison of connectome-based lesion-symptom mapping in post-stroke aphasia.

Connectome-based lesion-symptom mapping relates behavioural impairments to disruption of structural brain connectivity. Connectome-based lesion-symptom mapping can be based on different approaches (diffusion MRI versus lesion mask), network scales (whole brain versus regions of interest) and measure types (tract-based, parcel-based, or network-based metrics). We evaluated the similarity of different connectome-based lesion-symptom mapping processing choices and identified factors that influence the results using multiverse analysis-the strategy of conducting and displaying the results of all reasonable processing choices. Metrics derived from lesion masks and diffusion-weighted images were tested for association with Boston Naming Test and Token Test performance in a sample of 50 participants with aphasia following left hemispheric stroke. 'Direct' measures were derived from diffusion-weighted images. 'Indirect' measures were derived by overlaying lesion masks on a white matter atlas. Parcel-based connectomes were constructed for the whole brain and regions of interest (14 language-relevant parcels). Numerous tract-based and network-based metrics were calculated. There was a high discrepancy across processing approaches (diffusion-weighted images versus lesion masks), network scales (whole brain versus regions of interest) and metric types. Results indicate weak correlations and different connectome-based lesion-symptom mapping results across the processing choices. Substantial methodological work is needed to validate the various decision points that arise when conducting connectome-based lesion-symptom mapping analyses. Multiverse analysis is a useful strategy for evaluating the similarity across different processing choices in connectome-based lesion-symptom mapping.

Horizontal analysis and longitudinal cohort study of chronic renal failure correlates and cerebral small vessel disease relationship using peak width of skeletonized mean diffusivity.

Background and purpose: Peak width of skeletonized mean diffusivity (PSMD) is an MRI-based biomarker that may reflect white matter lesions (WML). PSMD is based on skeletonization of MR DTI data and histogram analysis. Both chronic renal failure (CRF) and WML may be affected by multisystemic small-vessel disorder. We aimed to explore the relationship between PSMD and estimated glomerular filtration rate (eGFR). Methods: Fifty followed-up CRF patients matched for age, sex, hypertension and smoking status were enrolled and classified into a progressive group (n = 16) and stable group (n = 34) based on eGFR levels. Longitudinal and horizontal differences of PSMD were compared between the progressive and stable groups at the initial and follow-up time points. Pearson's correlation was used for correlation of eGFR with PSMD and WML (per Fazekas scale score). ROC was used to measure the sensitivity of PSMD and WML score to changes of eGFR. Results: At the follow-up time point, PSMD of the progressive group was significantly higher than at the initial time point (p < 0.001), and PSMD of the progressive group was significantly higher than stable group (p < 0.001). PSMD and eGFR were significantly correlated. AUC curves explored that ΔPSMD (PSMD changes at the follow-up and initial time points) and follow-up PSMD was better for the classification of progressive and stable groups. Conclusion: PSMD has significant correlation with eGFR, PSMD can reveal a close relationship between WML and CRF.

White matter abnormalities in amino acid disorders and organic acidurias.

Inborn errors of metabolism (IEMs) are traditionally the domain of pediatricians and internists for metabolic diseases. In general, neurologists only become involved when these disorders are complicated by neurologic symptoms such as seizures, developmental delay, or motor problems. However, in recent years and mainly due to the successes of next-generation sequencing, the number of IEMs primarily presenting with neurologic symptoms and not detected by classic biochemical testing has grown significantly. This in particular relates to disorders in the biosynthesis of amino acids. Therefore, I will start by discussing defects in the synthesis pathways of the amino acids serine, glutamine, proline, and asparagine. In these disorders, the amino acid can be low in body fluids with biochemical testing, but more frequently are completely normal and although are in different metabolic pathways, they share many clinical features such as hypomyelination and white matter abnormalities. Next, I will discuss classic amino acid disorders and organic acid disorders due to defects in breakdown pathways characterized by elevations of key metabolites in body fluids and associated with neurologic abnormalities and white matter changes on MRI.

Disorders with prominent posterior fossa involvement.

Inherited white matter disorders include a wide range of disorders of various origins with distinct genetic, pathophysiologic, and metabolic backgrounds. Although most of these diseases have nonspecific clinical and radiologic features, some display distinct clinical and/or imaging (magnetic resonance imaging, MRI) characteristics that might suggest the causative gene. Recent advances in genetic testing allow assessing gene panels that include several hundred genes; however, an MRI-based diagnostic approach is important to narrow the choice of candidate genes, particularly in countries where these techniques are not available. Indeed, white matter disorders with prominent posterior fossa involvement present specific MRI (and clinical) phenotypes that can directly orient the diagnosis. This chapter describes the main genetic disorders with posterior fossa involvement and discusses diagnostic strategies.

Rare forms of hypomyelination and delayed myelination.

Hypomyelination is defined by the evidence of an unchanged pattern of deficient myelination on two MRIs performed at least 6 months apart in a child older than 1 year. When the temporal criteria are not fulfilled, and the follow-up MRI shows a progression of the myelination even if still not adequate for age, hypomyelination is excluded and the pattern is instead consistent with delayed myelination. This can be mild and nonspecific in some cases, while in other cases there is a severe delay that in the first disease stages could be difficult to differentiate from hypomyelination. In hypomyelinating leukodystrophies, hypomyelination is due to a primary impairment of myelin deposition, such as in Pelizaeus Merzabcher disease. Conversely, myelin lack is secondary, often to primary neuronal disorders, in delayed myelination and some condition with hypomyelination. Overall, the group of inherited white matter disorders with abnormal myelination has expanded significantly during the past 20 years. Many of these disorders have only recently been described, for many of them only a few patients have been reported and this contributes to make challenging the diagnostic process and the interpretation of Next Generation Sequencing results. In this chapter, we review the clinical and radiologic features of rare and lesser known forms of hypomyelination and delayed myelination not mentioned in other chapters of this handbook.

Familial cerebral amyloid disorders with prominent white matter involvement.

Familial cerebral amyloid disorders are characterized by the accumulation of fibrillar protein aggregates, which deposit in the parenchyma as plaques and in the vasculature as cerebral amyloid angiopathy (CAA). Amyloid ß (Aß) is the most common of these amyloid proteins, accumulating in familial and sporadic forms of Alzheimer's disease and CAA. However, there are also a number of rare, hereditary, non-Aß cerebral amyloidosis. The clinical manifestations of these familial cerebral amyloid disorders are diverse, including cognitive or neuropsychiatric presentations, intracerebral hemorrhage, seizures, myoclonus, headache, ataxia, and spasticity. Some mutations are associated with extensive white matter hyperintensities on imaging, which may or may not be accompanied by hemorrhagic imaging markers of CAA; others are associated with occipital calcification. We describe the clinical, imaging, and pathologic features of these disorders and discuss putative disease mechanisms. Familial disorders of cerebral amyloid accumulation offer unique insights into the contributions of vascular and parenchymal amyloid to pathogenesis and the pathways underlying white matter involvement in neurodegeneration. With Aß immunotherapies now entering the clinical realm, gaining a deeper understanding of these processes and the relationships between genotype and phenotype has never been more relevant.

MRI pattern recognition in white matter disease.

Magnetic resonance imaging (MRI) pattern recognition is a powerful tool for quick diagnosis of genetic and acquired white matter disorders. In many cases, distribution and character of white matter abnormalities directly point to a specific diagnosis and guide confirmatory testing. Knowledge of normal brain development is essential to interpret white matter changes in young children. MRI is also used for disease staging and treatment decisions in leukodystrophies and acquired disorders as multiple sclerosis, and as a biomarker to follow treatment effects.

Vanishing white matter.

"Vanishing white matter" (VWM) is a leukodystrophy caused by autosomal recessive pathogenic variants in the genes encoding the subunits of eukaryotic initiation factor 2B (eIF2B). Disease onset and disease course are extremely variable. Onset varies from the antenatal period until senescence. The age of onset is predictive of disease severity. VWM is characterized by chronic neurologic deterioration and, additionally, episodes of rapid and major neurologic decline, provoked by stresses such as febrile infections and minor head trauma. The disease is dominated by degeneration of the white matter of the central nervous system due to dysfunction of oligodendrocytes and in particular astrocytes. Organs other than the brain are rarely affected, with the exception of the ovaries. The reason for the selective vulnerability of the white matter of the central nervous system and, less consistently, the ovaries is poorly understood. eIF2B is a central regulatory factor in the integrated stress response (ISR). Genetic variants decrease eIF2B activity and thereby cause constitutive activation of the ISR downstream of eIF2B. Strikingly, the ISR is specifically activated in astrocytes. Modulation of eIF2B activity and ISR activation in VWM mouse models impacts disease severity, revealing eIF2B-regulated pathways as potential druggable targets.

White matter connectivity linked to novel word learning in children.

Children and adults are excellent word learners. Increasing evidence suggests that the neural mechanisms that allow us to learn words change with age. In a recent fMRI study from our group, several brain regions exhibited age-related differences when accessing newly learned words in a second language (L2; Takashima et al. Dev Cogn Neurosci 37, 2019). Namely, while the Teen group (aged 14-16 years) activated more left frontal and parietal regions, the Young group (aged 8-10 years) activated right frontal and parietal regions. In the current study we analyzed the structural connectivity data from the aforementioned study, examining the white matter connectivity of the regions that showed age-related functional activation differences. Age group differences in streamline density as well as correlations with L2 word learning success and their interaction were examined. The Teen group showed stronger connectivity than the Young group in the right arcuate fasciculus (AF). Furthermore, white matter connectivity and memory for L2 words across the two age groups correlated in the left AF and the right anterior thalamic radiation (ATR) such that higher connectivity in the left AF and lower connectivity in the right ATR was related to better memory for L2 words. Additionally, connectivity in the area of the right AF that exhibited age-related differences predicted word learning success. The finding that across the two age groups, stronger connectivity is related to better memory for words lends further support to the hypothesis that the prolonged maturation of the prefrontal cortex, here in the form of structural connectivity, plays an important role in the development of memory.

In Vivo visualization of white matter fiber tracts in the brainstem using low flip angle double echo 3D gradient echo imaging at 3T.

BACKGROUND: White matter (WM) fiber tracts in the brainstem communicate with various regions in the cerebrum, cerebellum, and spinal cord. Clinically, small lesions, malformations, or histopathological changes in the brainstem can cause severe neurological disorders. A direct and non-invasive assessment approach could bring valuable information about the intricate anatomical variations of the white matter fiber tracts and nuclei. Although tractography from diffusion tensor imaging has been commonly used to map the WM fiber tracts connectivity, it is difficult to differentiate the complex WM tracts anatomically. Both high field MRI methods and ultrahigh-field MRI methods at 7T and 11.7 T have been used to enhance the contrast of WM fiber tracts. Despite their promising results, it is still challenging to achieve wide clinical adoption at 3T. In this study, we explored a clinically feasible method using a proton density weighted (PDW) 3D gradient echo (GRE) sequence to directly image the WM fiber tracts in the brainstem at 3T in vivo. METHODS: We optimized a 3D high resolution, double echo, short TR, PDW GRE sequence on 5 healthy volunteers using a clinical 3T scanner to visualize the complicated anatomy of WM fiber tracts in the brain stem. Tissue properties including T1, proton density and T2* from in vivo quantitative MRI data were used for simulations to determine the optimal flip angle for the sequence. The visualization of multiple WM fiber tracts in the brainstem was assessed qualitatively and quantitatively using relative contrast and contrast-to-noise ratio (CNR). To improve the CNR, the final images were created by averaging over all echoes from two consecutive scans at the optimal flip angle. The results were compared to anatomical atlases and histology sections to identify the major fiber tracts. All the identified major fiber tracts were labeled on axial, sagittal and coronal slices. RESULTS: The WM fiber tracts were found to have distinct hypointense signal throughout the brainstem and most of the major WM fiber tracts, such as the corticospinal tract, medial lemniscus, medial longitudinal fasciculus, and central tegmental tract, in the brainstem up to and including the thalamus were identified in all subjects. Both qualitative and quantitative evaluations showed that the 3° scan offered the best contrast for WM fiber tracts for a TR of 20 ms. The average over the first two echo times and two consecutive 3° scans gave a CNR of 47.8 ± 6.2 for the pyramidal tracts in particular and CNRs values greater than 6.5 ± 2.4 for the rest of the fiber tracts. CONCLUSIONS: All the major fiber tracts in the brainstem could be visualized. Given the reasonably short scan time of 10 min at 3T, double echo PDW GRE sequence is a very practical approach for clinical adoption.

Quantitative MRI distinguishes different leukodystrophies and correlates with clinical measures.

OBJECTIVES: The leukodystrophy "vanishing white matter" (VWM) and "metachromatic leukodystrophy" (MLD) affect the brain's white matter, but have very different underlying pathology. We aim to determine whether quantitative MRI reflects known neuropathological differences and correlates with clinical scores in these leukodystrophies. METHODS: VWM and MLD patients and controls were prospectively included between 2020 and 2023. Clinical scores were recorded. MRI at 3 T included multi-compartment relaxometry diffusion-informed myelin water imaging (MCR-DIMWI) and multi-echo T2-relaxation imaging with compressed sensing (METRICS) to determine myelin water fractions (MWF). Multi-shell diffusion-weighted data were used for diffusion tensor imaging measures and neurite orientation dispersion and density imaging (NODDI) analysis, which estimates neurite density index, orientation dispersion index, and free water fraction. As quantitative MRI measures are age-dependent, ratios between actual and age-expected MRI measures were calculated. We performed the multilevel analysis with subsequent post-hoc and correlation tests to assess differences between groups and clinico-radiological correlations. RESULTS: Sixteen control (age range: 2.3-61.3 years, 8 male), 37 VWM (2.4-56.5 years, 20 male), and 14 MLD (2.2-41.7 years, 6 male) subjects were included. Neurite density index and MWF were lower in patients than in controls (p < 0.001). Free water fraction was highest in VWM (p = 0.01), but similar to controls in MLD (p = 0.99). Changes in diffusion tensor imaging measures relative to controls were generally more pronounced in VWM than in MLD. In both patient groups, MCR-DIMWI MWF correlated strongest with clinical measures. CONCLUSION: Quantitative MRI correlates to clinical measures and yields differential profiles in VWM and MLD, in line with differences in neuropathology. KEY POINTS: Question Can quantitative MRI reflect known neuropathological differences and correlate with clinical scores for these leukodystrophies? Finding Quantitative MRI measures, e.g., MWF, neurite density index, and free water fraction differ between leukodystrophies and controls, in correspondence to known histological differences. Clinical relevance MRI techniques producing quantitative, biologically-specific, measures regarding the health of myelin and axons deliver more comprehensive information regarding pathological changes in leukodystrophies than current approaches, and are thus viable tools for monitoring patients and providing clinical trial outcome measures.

Accelerating FLAIR imaging via deep learning reconstruction: potential for evaluating white matter hyperintensities.

PURPOSE: To evaluate deep learning-reconstructed (DLR)-fluid-attenuated inversion recovery (FLAIR) images generated from undersampled data, compare them with fully sampled and rapidly acquired FLAIR images, and assess their potential for white matter hyperintensity evaluation. MATERIALS AND METHODS: We examined 30 patients with white matter hyperintensities, obtaining fully sampled FLAIR images (standard FLAIR, std-FLAIR). We created accelerated FLAIR (acc-FLAIR) images using one-third of the fully sampled data and applied deep learning to generate DLR-FLAIR images. Three neuroradiologists assessed the quality (amount of noise and gray/white matter contrast) in all three image types. The reproducibility of hyperintensities was evaluated by comparing a subset of 100 hyperintensities in acc-FLAIR and DLR-FLAIR images with those in the std-FLAIR images. Quantitatively, similarities and errors of the entire image and the focused regions on white matter hyperintensities in acc-FLAIR and DLR-FLAIR images were measured against std-FLAIR images using structural similarity index measure (SSIM), regional SSIM, normalized root mean square error (NRMSE), and regional NRMSE values. RESULTS: All three neuroradiologists evaluated DLR-FLAIR as having significantly less noise and higher image quality scores compared with std-FLAIR and acc-FLAIR (p < 0.001). All three neuroradiologists assigned significantly higher frontal lobe gray/white matter visibility scores for DLR-FLAIR than for acc-FLAIR (p < 0.001); two neuroradiologists attributed significantly higher scores for DLR-FLAIR than for std-FLAIR (p < 0.05). Regarding white matter hyperintensities, all three neuroradiologists significantly preferred DLR-FLAIR (p < 0.0001). DLR-FLAIR exhibited higher similarity to std-FLAIR in terms of visibility of the hyperintensities, with 97% of the hyperintensities rated as nearly identical or equivalent. Quantitatively, DLR-FLAIR demonstrated significantly higher SSIM and regional SSIM values than acc-FLAIR, with significantly lower NRMSE and regional NRMSE values (p < 0.0001). CONCLUSIONS: DLR-FLAIR can reduce scan time and generate images of similar quality to std-FLAIR in patients with white matter hyperintensities. Therefore, DLR-FLAIR may serve as an effective method in traditional magnetic resonance imaging protocols.

Cognitive impairment mediates the white matter injury load and gait disorders in subcortical ischemic vascular disease.

Gait disorders are common in patients with subcortical ischemic vascular disease (SIVD). We aim to explore the impact of white matter (WM) damage on gait disorders in SIVD. 21 SIVD patients and 20 normal controls (NC) were included in the study. Montreal Cognitive Assessment (MoCA) was used to evaluate general cognition, while Speed-Accuracy Trade-Off (SAT) was used to assess executive function. Gait velocity, cadence, and stride length were measured. Diffusion Tensor Imaging (DTI) data were analyzed using Tract-Based Spatial Statistics (TBSS) and Peak Width of Skeletonized Mean Diffusivity (PSMD). The relationships among WM damage, gait disorders, and cognitive function were examined through mediation analysis. SIVD scored lower than NC in MoCA and SAT tests (P < 0.001). Gait velocity and stride length were decreased in SIVD. SIVD had lower PSMD (P < 0.001). PSMD correlated with gait parameters, which were totally mediated by MoCA and partially mediated by SAT. The fractional anisotropy (FA) and mean diffusivity (MD) of the genu of the corpus callosum (GCC) and body of CC (BCC) were correlated with gait parameters. The FA of the bilateral anterior corona radiata (ACR) was positively correlated with gait parameters, while the MD of the bilateral superior corona radiata (SCR), bilateral superior longitudinal fasciculus (SLF), and left external capsule (EC) were negatively correlated with them (P < 0.05). Gait impairments in SIVD were associated with cognitive deficits. Cognitive impairment mediated the WM damage and gait disorders. The microstructural alterations of CC, SLF, EC, and CR may be related to changes in gait.

Understanding the mechanisms of fatigue in multiple sclerosis: linking interoception, metacognition and white matter dysconnectivity.

One of the most prominent symptoms in multiple sclerosis is pathological fatigue, often described by sufferers as one of the most debilitating symptoms, affecting quality of life and employment. However, the mechanisms of both, physical and cognitive fatigue in multiple sclerosis remain elusive. Here, we use behavioural tasks and quantitative MRI to investigate the neural correlates of interoception (the ability to sense internal bodily signals) and metacognition (the ability of the brain to assess its own performance), in modulating cognitive fatigue. Assuming that structural damage caused by multiple sclerosis pathology might impair the neural pathways subtending interoception and/or metacognition, we considered three alternative hypotheses to explain fatigue as a consequence of, respectively: (i) reduced interoceptive accuracy, (ii) reduced interoceptive insight or (iii) reduced global metacognition. We then explored associations between these behavioural measures and white matter microstructure, assessed by diffusion and magnetisation transfer MRI. Seventy-one relapsing-remitting multiple sclerosis patients participated in this cross-sectional study (mean age 43, 62% female). Patient outcomes relevant for fatigue were measured, including disability, disease duration, depression, anxiety, sleepiness, cognitive function, disease modifying treatment and quality of life. Interoceptive and metacognitive parameters were measured using heartbeat tracking and discrimination tasks, and metacognitive visual and memory tasks. MRI was performed in 69 participants, including diffusion tensor MRI, neurite orientation dispersion and density imaging and quantitative magnetisation transfer. Associations between interoception and metacognition and the odds of high cognitive fatigue were tested by unconditional binomial logistic regression. The odds of cognitive fatigue were higher in the people with low interoceptive insight (P = 0.03), while no significant relationships were found between fatigue and other interoceptive or metacognitive parameters, suggesting a specific impairment in interoceptive metacognition, rather than interoception generally, or metacognition generally. Diffusion MRI-derived fractional anisotropy and neurite density index showed significant (P < 0.05) negative associations with cognitive fatigue in a widespread bilateral white matter network. Moreover, there was a significant (P < 0.05) interaction between cognitive fatigue and interoceptive insight, suggesting that the poorer the white matter structure, the lower the interoceptive insight, and the worse the fatigue. The results point towards metacognitive impairment confined to the interoceptive domain, in relapsing-remitting patients with cognitive fatigue. The neural basis of this impairment is supported by a widespread white matter network in which loss of neurite density plays a role.

Acute organic solvent toxic encephalopathy: A case report and literature review.

Organic solvents are a class of volatile, lipophilic substances that can easily enter the human body through skin and mucous membrane contact as well as air inhalation, and can lead to toxic encephalopathy (TE), especially after entering the lipid-rich nervous system. The present case reports a patient with acute organic solvent toxic encephalopathy (AOSTE), which may have been caused by occasional ink leakage from Xuzhou (Jiangsu, China). By summarizing the history the patient to exposure to organic solvents, clinical manifestations, radiology findings and relevant laboratory tests, we hypothesize that a history of ink exposure, brain magnetic resonance imaging findings and hippuric acid testing were indispensable factors in the diagnosis of AOSTE. After neurological treatment, the patient experienced notable improvement in symptoms. The present study reports on its clinical features, imaging features, treatment and follow-up, and review relevant literature to summarize its clinical experience, hoping to improve our understanding of AOSTE.

Association between fibrinogen and white matter lesions and cerebral atrophy in patients with acute ischemic stroke.

BACKGROUND: Inflammation is a potential mechanism underlying the development of white matter lesions (WMLs) and cerebral atrophy. We aimed to investigate the relationship of fibrinogen levels with WMLs and cerebral atrophy in patients with acute ischemic stroke (AIS). METHODS: A total of 701 AIS patients were enrolled. Participants were divided into four groups according to the quartiles of fibrinogen levels: Q1 < 2.58 g/L, Q2: 2.58-3.12 g/L, Q3: 3.12-3.67 g/L, Q4: ≥ 3.67 g/L. White matter hyperintensity (WMH), periventricular hyperintensity (PVH) and deep white matter hyperintensity (DWMH) were defined according to the Fazekas scale. Cerebral atrophy was defined according to global cortical atrophy scores. Univariate and multivariate logistic regression were used to explore the relationship of fibrinogen levels and WMHs, PVH, DWMH and cerebral atrophy. RESULTS: Among 701 AIS patients, 498 (71.0 %), 425 (60.6 %), 442 (63.1 %), and 560 (79.9 %) had WMHs, PVH, DWMH and cerebral atrophy, respectively. After adjustment for potential covariates, the highest fibrinogen quartiles were significantly associated with increased risk of WMHs (odds ratio [OR] 1.97, 95 % confidence intervals [CI] 1.10-3.50), PVH (OR 1.85, 95 % CI 1.08-3.16) and cerebral atrophy (OR 2.53, 95 % CI 1.19-5.40) but not DWMH (OR 1.37 95 % CI 0.81-2.31) compared with the lowest fibrinogen quartile. Moreover, the association between elevated fibrinogen levels and the risk of WMLs and cerebral atrophy remained significant as continuous variables. CONCLUSIONS: Increased baseline fibrinogen levels were independently associated with WMHs, PVH and cerebral atrophy in patients with ischemic stroke. Fibrinogen could be the potential blood biomarker of WMLs and cerebral atrophy.