Gray Matter Structures Research Articles

Comprehensive segmentation of gray matter structures on T1-weighted brain MRI: A Comparative Study of CNN, CNN hybrid-transformer or -Mamba architectures.

Recent advances in deep learning have shown promising results in medical image analysis and segmentation. However, most brain MRI segmentation models are limited by the size of their datasets and/or the number of structures they can identify. This study evaluates the performance of six advanced deep learning models in segmenting 122 brain structures from T1-weighted MRI scans, aiming to identify the most effective model for clinical and research applications. 1,510 T1-weighted MRIs were used to compare six deep-learning models for the segmentation of 122 distinct gray matter structures: nnU-Net, SegResNet, SwinUNETR, UNETR, U-Mamba_BOT and U-Mamba_ Enc. Each model was rigorously tested for accuracy using the Dice Similarity Coefficient (DSC) and the 95th percentile Hausdorff Distance (HD95). Additionally, the volume of each structure was calculated and compared between normal control (NC) and Alzheimer's Disease (AD) patients. U-Mamba_Bot achieved the highest performance with a median DSC of 0.9112 [IQR:0.8957, 0.9250]. nnU-Net achieved a median DSC of 0.9027 [IQR: 0.8847, 0.9205] and had the highest HD95 of 1.392[IQR: 1.174, 2.029]. The value of each HD95 (<3mm) indicates its superior capability in capturing detailed brain structures accurately. Following segmentation, volume calculations were performed, and the resultant volumes of normal controls and AD patients were compared. The volume changes observed in thirteen brain substructures were all consistent with those reported in existing literature, reinforcing the reliability of the segmentation outputs. This study underscores the efficacy of U-Mamba_Bot as a robust tool for detailed brain structure segmentation in T1-weighted MRI scans. The congruence of our volumetric analysis with the literature further validates the potential of advanced deep-learning models to enhance the understanding of neurodegenerative diseases such as AD. Future research should consider larger datasets to validate these findings further and explore the applicability of these models in other neurological conditions. AD = Alzheimer's Disease; ADNI = Alzheimer's Disease Neuroimaging Initiative; DSC = Dice Similarity Coefficient; HD95 = the 95th Percentile Hausdorff Distance; IQR = Interquartile Range; NC = Normal Control; SSMs = State-space Sequence Models.

Biophysical contrast sources for magnetic susceptibility and R2* mapping: A combined 7 Tesla, mass spectrometry and electron paramagnetic resonance study

Iron is the most abundant trace metal in the human brain and consistently shown elevated in prevalent neurological disorders. Because of its paramagnetism, brain iron can be assessed in vivo by quantitative MRI techniques such as R2* mapping and Quantitative Susceptibility Mapping (QSM). While Inductively Coupled Plasma Mass Spectrometry (ICP-MS) has demonstrated good correlations of the total iron content to MRI parameters in gray matter, the relationship to ferritin levels as assessed by Electron Paramagnetic Resonance (EPR) has not been systematically analyzed. Therefore, we included 15 postmortem subjects (age: 26–91 years) which underwent quantitative in-situ MRI at 7 Tesla within a post-mortem interval of 24 h after death. ICP-MS and EPR were used to measure the total iron and ferritin content in 8 selected gray matter (GM) structures and the correlations to R2* and QSM were calculated. We found that R2* and QSM in the iron rich basal ganglia and the red nucleus were highly correlated with iron (R² > 0.7) and ferritin (R² > 0.6), whereas those correlations were lost in cortical regions and the hippocampus. The neuromelanin-rich substantia nigra showed a different behavior with a correlation with total iron only (R² > 0.5) but not with ferritin. Although qualitative results were similar for both qMRI techniques the observed correlation was always stronger for QSM than R2*. This study demonstrated the quantitative correlations between R2*, QSM, total iron and ferritin levels in an in-situ MRI setup and therefore aids to understand how molecular forms of iron are responsible for MRI contrast generation.

Gray matter and cognitive alteration related to chronic obstructive pulmonary disease patients: combining ALE meta-analysis and MACM analysis.

Chronic obstructive pulmonary disease (COPD) is frequently comorbid with cognitive impairment, but it has not been paid enough attention, and its neuroanatomical characteristics have not been fully identified. Voxel-based morphometric (VBM) studies comparing gray matter (GM) abnormalities in COPD patients with healthy controls (HCs) were searched using 8 electronic databases from the inception to March 2023. Stereotactic data were extracted and tested for convergence and differences using the activation likelihood estimation (ALE) method. Moreover, based on the ALE results, a structural meta-analytic connectivity modeling (MACM) was conducted to explore the co-atrophy pattern in patients with COPD. Last, behavioral analysis was performed to assess the functional roles of the regions affected by COPD. In total, 11 studies on COPD with 949 participants were included. Voxel-based meta-analysis revealed significant GM abnormalities in the right postcentral gyrus (including inferior parietal lobule), left precentral gyrus, and left cingulate gyrus (including paracentral lobule) in patients with COPD compared with HCs. Further MACM analysis revealed a deeper co-atrophy pattern between the brain regions with abnormal GM structure and the insula in COPD patients. Behavioral analysis showed that the abnormal GM structure in the left cingulate gyrus (including paracentral lobule) was strongly associated with cognitive function, especially executive function. COPD comorbid with cognitive impairment has a specific neurostructural basis of GM structural abnormalities, which may also involve a deeper co-atrophy pattern between the insula. These findings enhance our understanding of the underlying neuropathogenesis and suggest potential imaging markers for cognitive impairment in COPD patients. PROSPERO registration number: CRD42022298722.

Mass spectrometry imaging of two neocortical areas reveals the histological selectivity of schizophrenia-associated lipid alterations

BACKGROUND: Schizophrenia is a psychiatric disorder known to affect brain structure and functionality. Structural changes in the brain at the level of gross anatomical structures have been fairly well studied, while microstructural changes, especially those associated with changes in the molecular composition of the brain, are still being investigated. Of special interest are lipids and metabolites, for which some previous studies have shown association with schizophrenia. AIM: To utilize a spatially resolved analysis of the brain lipidome composition to investigate the degree and nature of schizophrenia-associated lipidome alterations in the gray and white matter structures of two neocortical regions — the dorsolateral prefrontal cortex (Brodmann area 9, BA9) and the posterior part of the superior temporal gyrus (Brodmann area 22, posterior part, BA22p), as well compare the distribution of the changes between the two regions and tissue types. METHODS: We employed Matrix-Assisted Laser Desorption/Ionization Mass Spectrometric Imaging (MALDI-MSI), supplemented by a statistical analysis, to examine the lipid composition of brain sections. A total of 24 neocortical sections from schizophrenia patients (n=2) and a healthy control group (n=2), representing the two aforementioned neocortical areas, were studied, yielding data for 131 lipid compounds measured across more than a million MALDI-MSI pixels. RESULTS: Our findings revealed an uneven distribution of schizophrenia-related lipid alterations across the two neocortical regions. The BA22p showed double the differences in its subcortical white matter structures compared to BA9, while less bias was detected in the gray matter layers. While the schizophrenia-associated lipid differences generally showed good agreement between brain regions at the lipid class level for both gray and white matter, there were consistently more discrepancies for white matter structures. CONCLUSION: Our study found a consistent yet differential association of schizophrenia with the brain lipidome composition of distinct neocortical areas, particularly subcortical white matter. These findings highlight the need for broader brain coverage in future schizophrenia research and underscore the potential of spatially resolved molecular analysis methods in identifying structure-specific effects.

High-resolution 7T fMRI reveals the visual zone of the human claustrum

Abstract The claustrum is a thin grey matter structure located between the insular cortex and the putamen. The function of the claustrum is largely unknown with diverse hypotheses ranging from multisensory integration and consciousness to attention and cognitive control. Much research on the function of the claustrum relies on invasive techniques in animal models, as the claustrum’s uniquely thin shape makes it difficult to image non-invasively in human subjects. In the current proof-of-concept study, we used high-resolution ultra-high field (7 Tesla) functional magnetic resonance imaging (fMRI) to measure activity in the human claustrum during the processing of naturalistic stimuli. We presented short video clips as visual only, auditory only or audiovisual conditions while participants performed a central fixation task. We found distinct visual responses in both the left and the right claustrum at a consistent spatial location across participants, hemispheres and sessions. We also found deactivations in response to auditory stimulation. These deactivations were confined to the right claustrum and did not overlap with visual activity. The deactivation in response to auditory stimulation demonstrates the complexity of claustrum’s functional organization and suggests functional differentiation within the claustrum. This is the first study to demonstrate sensory-specific effects within the human claustrum. It opens the possibility for studying the claustrum’s role in higher-level aspects of sensory processing in humans.

Quantitative Susceptibility Mapping Values Quantification in Deep Gray Matter Structures for Relapsing-Remitting Multiple Sclerosis: A Systematic Review and Meta-Analysis.

This systematic review and meta-analysis aimed to investigate the role of magnetic susceptibility (χ) in deep gray matter (DGM) structures, including the putamen (PUT), globus pallidus (GP), caudate nucleus (CN), and thalamus, in the most common types of multiple sclerosis (MS) and relapsing-remitting MS (RRMS), using quantitative susceptibility mapping (QSM). The literature was systematically reviewed up to November 2023, adhering to PRISMA guidelines. This study was conducted using a random-effects model to calculate the standardized mean difference (SMD) in QSM values between patients with RRMS and healthy controls (HCs). Publication bias and risk of bias were also assessed. Nine studies involving 1074 RRMS patients with RRMS and 640 HCs were included in the meta-analysis. The results showed significantly higher QSM (χ) values in the PUT (SMD = 0.40, 95% confidence interval [CI] = 0.22-0.59, p =.000), GP (SMD = 0.60, 95% CI = 0.50-0.70, p =.00), and CN (SMD = 0.40, 95% CI = 0.15-0.66, p =.005) of RRMS patients compared to HCs. However, there were no significant differences in the QSM values in the thalamus between patients with RRMS and HCs (SMD = -0.33, 95% CI -0.67-0.01, p =.026). Age- and sex-based subgroup analysis demonstrated that younger patients (<40 years) in the PUT, GP, and CN groups and larger male populations (>25%) in the PUT and GP groups had more significant χ. Interestingly, thalamic QSM values were found to decrease in RRMS patients over 40 years of age and in higher male populations. Sex-based subgroup analysis indicated higher iron levels in the PUT and GP of RRMS patients regardless of sex. QSM values were higher in certain brain regions (PUT, GP, and CN) during the early stages (disease duration <9.6 years) of RRMS, but lower in the thalamus during the later stages (disease duration >9.6 years) than HCs. QSM may serve as a biomarker for understanding χ value alterations such as iron dysregulation and its contribution to neurodegeneration in RRMS, especially in the basal ganglia nuclei including PUT, GP, and CN.

A reassessment of spinal cord pathology in severe infantile spinal muscular atrophy: Reassessment of spinal cord pathology.

Spinal muscular atrophy (SMA) is a life-limiting paediatric motor neuron disease characterised by lower motor neuron loss, skeletal muscle atrophy and respiratory failure, if untreated. Revolutionary treatments now extend patient survival. However, a limited understanding of the foundational neuropathology challenges the evaluation of therapeutic success. As opportunities to study treatment-naïve tissue decrease, we have characterised spinal cord pathology in severe infantile SMA using gold-standard techniques, providing a baseline to measure treatment success and therapeutic limitations. Detailed histological analysis, stereology and transmission electron microscopy were applied to post-mortem spinal cord from severe infantile SMA patients to estimate neuron number at the end of life; characterise the morphology of ventral horn, lateral horn and Clarke's column neuron populations; assess cross-sectional spinal cord area; and observe myelinated white matter tracts in the clinically relevant thoracic spinal cord. Ventral horn neuron loss was substantial in all patients, even the youngest cases. The remaining ventral horn neurons were small with abnormal, occasionally chromatolytic morphology, indicating cellular damage. In addition to ventral horn pathology, Clarke's column sensory-associated neurons displayed morphological features of cellular injury, in contrast to the preserved sympathetic lateral horn neurons. Cellular changes were associated with aberrant development of grey and white matter structures that affected the overall dimensions of the spinal cord. We provide robust quantification of the neuronal deficit found at the end of life in SMA spinal cord. We question long-accepted dogmas of SMA pathogenesis and shed new light on SMA neuropathology out with the ventral horn, which must be considered in future therapeutic design.

Influence of intergenerational social mobility on brain structure and global cognition: findings from the Whitehall II study across 20years.

Whether changes in socioeconomic position (SEP) across generations, i.e. intergenerational social mobility, influence brain degeneration and cognition in later life is unclear. To examine the association of social mobility, brain grey matter structure and global cognition. We analysed T1 brain MRI data of 771 old adults (69.8 ± 5.2years) from the Whitehall II MRI substudy, with MRI data collected between 2012 and 2016. Social mobility was defined by SEP changes from their fathers' generation to mid-life status. Brain structural outcomes include grey matter (GM) volume and cortical thickness (CT) covering whole brain. Global cognition was measured by the Mini Mental State Examination. We firstly conducted analysis of covariance to identify regional difference of GM volume and cortical thickness across stable high/low and upward/downward mobility groups, followed with diagonal reference models studying the relationship between mobility and brain cognitive outcomes, apart from SEP origin and destination. We additionally conducted linear mixed models to check mobility interaction over time, where global cognition was derived from three phases across 2002 to 2017. Social mobility related to 48 out of the 136 GM volume regions and 4 out of the 68 CT regions. Declined volume was particularly seen in response to downward mobility, whereas no independent association of mobility with global cognition was observed. Despite no strong evidence supporting direct influence of mobility on global cognition in later life, imaging findings warranted a severe level of neurodegeneration due to downward mobility from their father's generation.

Altered structure and functional connection of subcortical gray matter in female patients with classical trigeminal neuralgia.

The etiology of classical trigeminal neuralgia (CTN) is still unclear. A better understanding of the cerebral structural and functional changes in female patients with CTN may provide important novel insights into the pathophysiologic mechanisms of female CTN. A total 37 female CTN patients were included and referred to MRI scans, comprising with 19 left CTN and 18 right CTN patients. We analyzed the volume and shape of subcortical gray matter (GM), and the functional connectivity (FC) between the accumbens nucleus (NAc) and whole brain in right and left CTN patients respectively. We found left CTN patients had a reduced right NAc volume compared to controls, similarly, the right CTN had the decreased volume in the left NAc. Vertex-wise shapes of right NAc in left CTN patients showed significant regional shape deformation on the anterior, medial and ventroposterior aspects, in contrast, left NAc of right CTN patients showed significant regional shape deformation on the anterior and posterior aspect. Furthermore, patients with left CTN showed significantly lower FC between the right NAc and right orbitofrontal cortex than control subjects. The volume of NAc in all CTN was significantly related to the perception of present pain intensity. The CTN might be majorly caused by volume reduction in NAc. A greater understanding of the neurobiological basis of pain-related changes in NAc will provide the knowledge for the development of novel NAc based therapeutic targets for pain management or even prevention in CTN patients.

Redefining the phenotype of alpha-methylacyl-CoA racemase (AMACR) deficiency

BackgroundAlpha-methylacyl-CoA racemase (AMACR) deficiency is a rare peroxisomal enzyme deficiency caused by biallelic variants in the AMACR gene. This deficiency leads to the accumulation of toxic bile acid intermediates (R)-trihydroxycholestenoic acid (THCA) and (R)-dihydroxycholestenoic acid (DHCA) and pristanic acid. With less than 20 patients described in literature, the phenotype of AMACR deficiency is poorly defined and no data on the natural history are available.ResultsHere we describe a cohort of 12 patients (9 adults and 3 children) with genetically confirmed AMACR deficiency (median age at diagnosis 56 years, range 3–69), followed for an average of 6 years (between 2015 and 2023). Five novel pathogenic variants are described. In 5/9 adult patients, retinitis pigmentosa was detected at a median age of 45 years (range 30–61). The median delay to diagnosis of AMACR deficiency after the diagnosis of retinitis pigmentosa was 24 years (range 0–33). All adult patients subsequently developed neurological signs and symptoms after the age of 40 years; most frequently neuropathy, ataxia and cognitive decline with prior normal cognitive functioning. One patient presented with a stroke-like episode. All adult patients showed a typical MRI pattern involving the thalami and gray matter structures of the pons and midbrain. One patient had a hepatocellular carcinoma at the time of the AMACR deficiency diagnosis and two patients suffered from gallstones. All three included children had elevated liver transaminases as single presenting sign and showed no brain MRI abnormalities.ConclusionAMACR deficiency can be considered as an adult slowly progressive disease with a predominant neurological phenotype. The main signs comprise retinitis pigmentosa, neuropathy, ataxia and cognitive decline; stroke-like episodes may occur. Recognition of typical MRI abnormalities may facilitate prompt diagnosis. In addition, there is a risk of liver fibrosis/cirrhosis and hepatocellular carcinoma in these patients, requiring active monitoring.

Causal relationships of grey matter structures in multiple sclerosis and neuromyelitis optica spectrum disorder: insights from Mendelian randomization.

Multiple sclerosis and neuromyelitis optica spectrum disorder are two debilitating inflammatory demyelinating diseases of the CNS. Although grey matter alterations have been linked to both multiple sclerosis and neuromyelitis optica spectrum disorder in observational studies, it is unclear whether these associations indicate causal relationships between these diseases and grey matter changes. Therefore, we conducted a bidirectional two-sample Mendelian randomization analysis to investigate the causal relationships between 202 grey matter imaging-derived phenotypes (33 224 individuals) and multiple sclerosis (47 429 cases and 68 374 controls) as well as neuromyelitis optica spectrum disorder (215 cases and 1244 controls). Our results suggested that genetically predicted multiple sclerosis was positively associated with the surface area of the left parahippocampal gyrus (β = 0.018, P = 2.383 × 10-4) and negatively associated with the volumes of the bilateral caudate (left: β = -0.020, P = 7.203 × 10-5; right: β = -0.021, P = 3.274 × 10-5) and putamen nuclei (left: β = -0.030, P = 2.175 × 10-8; right: β = -0.024, P = 1.047 × 10-5). In addition, increased neuromyelitis optica spectrum disorder risk was associated with an increased surface area of the left paracentral gyrus (β = 0.023, P = 1.025 × 10-4). Conversely, no evidence was found for the causal impact of grey matter imaging-derived phenotypes on disease risk in the opposite direction. We provide suggestive evidence that genetically predicted multiple sclerosis and neuromyelitis optica spectrum disorder are associated with increased cortical surface area and decreased subcortical volume in specific regions. Our findings shed light on the associations of grey matter alterations with the risk of multiple sclerosis and neuromyelitis optica spectrum disorder.

Axonal damage and inflammation response are biological correlates of decline in small-world values: a cohort study in autosomal dominant Alzheimer’s disease

Abstract The grey matter of the brain develops and declines in coordinated patterns during the lifespan. Such covariation patterns of grey matter structure can be quantified as grey matter networks, which can be measured with magnetic resonance imaging. In Alzheimer’s disease, the global organization of grey matter networks becomes more random, which is captured by a decline in the small-world coefficient. Such decline in the small-world value has been robustly associated with cognitive decline across clinical stages of Alzheimer’s disease. The biological mechanisms causing this decline in small-world values remain unknown. Cerebrospinal fluid (CSF) protein biomarkers are available for studying diverse pathological mechanisms in humans and can provide insight into decline. We investigated the relationships between 10 CSF proteins and small-world coefficient in mutation carriers (N = 219) and non-carriers (N = 136) of the Dominantly Inherited Alzheimer Network Observational study. Abnormalities in Amyloid beta, Tau, synaptic (Synaptosome associated protein-25, Neurogranin) and neuronal calcium-sensor protein (Visinin-like protein-1) preceded loss of small-world coefficient by several years, while increased levels in CSF markers for inflammation (Chitinase-3-like protein 1) and axonal injury (Neurofilament light) co-occurred with decreasing small-world values. This suggests that axonal loss and inflammation play a role in structural grey matter network changes.

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.

Detailed delineation of the fetal brain in diffusion MRI via multi-task learning.

Diffusion-weighted MRI is increasingly used to study the normal and abnormal development of fetal brain inutero. Recent studies have shown that dMRI can offer invaluable insights into the neurodevelopmental processes in the fetal stage. However, because of the low data quality and rapid brain development, reliable analysis of fetal dMRI data requires dedicated computational methods that are currently unavailable. The lack of automated methods for fast, accurate, and reproducible data analysis has seriously limited our ability to tap the potential of fetal brain dMRI for medical and scientific applications. In this work, we developed and validated a unified computational framework to (1) segment the brain tissue into white matter, cortical/subcortical gray matter, and cerebrospinal fluid, (2) segment 31 distinct white matter tracts, and (3) parcellate the brain's cortex and delineate the deep gray nuclei and white matter structures into 96 anatomically meaningful regions. We utilized a set of manual, semi-automatic, and automatic approaches to annotate 97 fetal brains. Using these labels, we developed and validated a multi-task deep learning method to perform the three computations. Our evaluations show that the new method can accurately carry out all three tasks, achieving a mean Dice similarity coefficient of 0.865 on tissue segmentation, 0.825 on white matter tract segmentation, and 0.819 on parcellation. The proposed method can greatly advance the field of fetal neuroimaging as it can lead to substantial improvements in fetal brain tractography, tract-specific analysis, and structural connectivity assessment.

Structural Development of Speech Networks in Young Children at Risk for Speech Disorder.

Characterizing the structural development of the neural speech network in early childhood is important for understanding speech acquisition. To investigate speech in the developing brain, 94 children aged 4-7-years-old at risk for early speech disorder were scanned using diffusion weighted imaging (DWI) magnetic resonance imaging (MRI). Additionally, each child completed the Syllable Repetition Task (SRT), a validated measure of phoneme articulation. The DWI data were modeled using multi-compartment restriction spectrum imaging (RSI) to measure restricted and hindered diffusion properties in both grey and white matter. Consequently, we analyzed the diffusion data using both whole brain analysis, and automated fiber quantification (AFQ) analysis to establish tract profiles for each of six fiber pathways thought to be important for supporting speech development. In the whole brain analysis, we found that SRT performance was associated with restricted diffusion in bilateral inferior frontal gyrus ( pars opercularis ), right pre-supplementary/ supplementary motor area (pre-SMA/SMA), and bilateral cerebellar grey matter ( p < .005). Age moderated these associations in left pars opercularis and frontal aslant tract (FAT). However, in both cases only the cerebellar findings survived a cluster correction. We also found associations between SRT performance and restricted diffusion in cortical association fiber pathways, especially left FAT, and in the cerebellar peduncles. Analyses using automatic fiber quantification (AFQ) highlighted differences in high and low performing children along specific tract profiles, most notably in left but not right FAT. These findings suggest that individual differences in speech performance are reflected in structural gray and white matter differences as measured by restricted and hindered diffusion metrics, and offer important insights into developing brain networks supporting speech in very young children.

Brain structural changes in diabetic retinopathy patients: a combined voxel-based morphometry and surface-based morphometry study.

The aim of this study was to investigate alterations in gray matter structure among individuals diagnosed with diabetic retinopathy (DR). This study included a cohort of 32 diabetic patients with retinopathy (DR group, n = 32) and 38 healthy adults (HC group, n = 38). Both cohorts underwent comprehensive psychological and cognitive assessments alongside structural magnetic resonance imaging. The brain's gray matter volume and morphology were analyzed using voxel-based morphometry (VBM) and surface-based morphometry (SBM). Partial correlation analysis was employed to investigate the associations between differences in gray matter volume (GMV) across diverse brain regions and the outcomes of cognitive psychological tests as well as clinical indicators. The VBM results revealed that, in comparison to the healthy control (HC) group, patients with diabetic retinopathy (DR) exhibited reduced gray matter volume (GMV) in the right fusiform gyrus, inferior frontal gyrus, opercular part, and left hippocampus; conversely, an increase in GMV was observed in the right thalamus. The SBM results indicated cortical thinning in the left caudal anterior cingulate cortex, left superior frontal gyrus, left parahippocampal gyrus, and bilateral lingual gyrus in the DR group. Sulcal depth (SD) exhibited increased values in the bilateral rostral middle frontal gyrus, superior frontal gyrus, frontal pole, left precentral gyrus, postcentral gyrus, lateral orbitofrontal gyrus, and right paracentral gyrus. Local gyrification indices (LGIs) decreased in the left caudal middle frontal gyrus and superior frontal gyrus. The fractal dimension (FD) decreased in the posterior cingulate gyrus and isthmus of the cingulate gyrus. The left hippocampal gray matter volume (GMV) in patients with diabetic retinopathy was negatively correlated with disease duration (r = -0.478, p = 0.008) and self-rating depression scale (SAS) score (r = -0.381, p = 0.038). The structural alterations in specific brain regions of individuals with DR, which may contribute to impairments in cognition, emotion, and behavior, provide valuable insights into the neurobiological basis underlying these dysfunctions.

Quantitative and Radiological Assessment of Post-cardiac-Arrest Comatose Patients with Diffusion-Weighted Magnetic Resonance Imaging.

Although magnetic resonance imaging, particularly diffusion-weighted imaging, has increasingly been used as part of a multimodal approach to prognostication in patients who are comatose after cardiac arrest, the performance of quantitative analysis of apparent diffusion coefficient (ADC) maps, as compared to standard radiologist impression, has not been well characterized. This retrospective study evaluated quantitative ADC analysis to the identification of anoxic brain injury by diffusion abnormalities on standard clinical magnetic resonance imaging reports. The cohort included 204 previously described comatose patients after cardiac arrest. Clinical outcome was assessed by (1) 3-6 month post-cardiac-arrest cerebral performance category and (2) coma recovery to following commands. Radiological evaluation was obtained from clinical reports and characterized as diffuse, cortex only, deep gray matter structures only, or no anoxic injury. Quantitative analyses of ADC maps were obtained in specific regions of interest (ROIs), whole cortex, and whole brain. A subgroup analysis of 172 was performed after eliminating images with artifacts and preexisting lesions. Radiological assessment outperformed quantitative assessment over all evaluated regions (area under the curve [AUC] 0.80 for radiological interpretation and 0.70 for the occipital region, the best performing ROI, p = 0.011); agreement was substantial for all regions. Radiological assessment still outperformed quantitative analysis in the subgroup analysis, though by smaller margins and with substantial to near-perfect agreement. When assessing for coma recovery only, the difference was no longer significant (AUC 0.83 vs. 0.81 for the occipital region, p = 0.70). Although quantitative analysis eliminates interrater differences in the interpretation of abnormal diffusion imaging and avoids bias from other prediction modalities, clinical radiologist interpretation has a higher predictive value for outcome. Agreement between radiological and quantitative analysis improved when using high-quality scans and when assessing for coma recovery using following commands. Quantitative assessment may thus be more subject to variability in both clinical management and scan quality than radiological assessment.

Gray matter volume of limbic brain structures during the development of chronic back pain: a longitudinal cohort study.

This study set out to investigate in a population-based longitudinal cohort, whether chronification of back pain (BP) is related to structural gray matter changes in corticolimbic brain structures. Gray matter volume (GMV) was measured in participants with chronic BP (CBP, n = 168) and controls without chronic pain (n = 323) at 2 time points with an interval of 7 years (baseline t1, follow-up t2). Over this time period, participants with CBP showed an increase of GMV in the left ventral striatum, whereas controls showed a decrease. By contrast, participants with CBP had a GMV decrease in the left parahippocampal gyrus. Within the CBP group, pain duration was negatively associated with GMV in the left caudate. Those with emerging CBP had less GMV in the right entorhinal area, right amygdala, and left medial frontal cortex. Additional variables differing between those who had BP at t1 and later developed CBP or not were pain intensity, body mass index, and depression score. In sum, these findings are in accordance with the notion that limbic brain properties are both predisposing risk factors and drivers of brain reorganization during the development of CBP.

Retigabine, a potassium channel opener, restores thalamocortical neuron functionality in a murine model of autoimmune encephalomyelitis

BackgroundMultiple Sclerosis (MS) is an autoimmune neurodegenerative disease, whose primary hallmark is the occurrence of inflammatory lesions in white and grey matter structures. Increasing evidence in MS patients and respective murine models reported an impaired ionic homeostasis driven by inflammatory-demyelination, thereby profoundly affecting signal propagation. However, the impact of a focal inflammatory lesion on single-cell and network functionality has hitherto not been fully elucidated. ObjectivesIn this study, we sought to determine the consequences of a localized cortical inflammatory lesion on the excitability and firing pattern of thalamic neurons in the auditory system. Moreover, we tested the neuroprotective effect of Retigabine (RTG), a specific Kv7 channel opener, on disease outcome. MethodsTo resemble the human disease, we focally administered pro-inflammatory cytokines, TNF-α and IFN-γ, in the primary auditory cortex (A1) of MOG35-55 immunized mice. Thereafter, we investigated the impact of the induced inflammatory milieu on afferent thalamocortical (TC) neurons, by performing ex vivo recordings. Moreover, we explored the effect of Kv7 channel modulation with RTG on auditory information processing, using in vivo electrophysiological approaches. ResultsOur results revealed that a cortical inflammatory lesion profoundly affected the excitability and firing pattern of neighboring TC neurons. Noteworthy, RTG restored control-like values and TC tonotopic mapping. ConclusionOur results suggest that RTG treatment might robustly mitigate inflammation-induced altered excitability and preserve ascending information processing.

Associations of Cerebral Blood Flow Patterns With Gray and White Matter Structure in Patients With Temporal Lobe Epilepsy.

Neuroimaging studies in patients with temporal lobe epilepsy (TLE) show widespread brain network alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. Here, we studied whole-brain perfusion and vascular network alterations in TLE and assessed its associations with gray and white matter compromises and various clinical variables. We included individuals with and without pharmaco-resistant TLE who underwent multimodal 3T MRI, including arterial spin labelling, structural, and diffusion-weighted imaging. Using surface-based MRI mapping, we generated individualized cortico-subcortical profiles of perfusion, morphology, and microstructure. Linear models compared regional CBF in patients with controls and related alterations to morphological and microstructural metrics. We further probed interregional vascular networks in TLE, using graph theoretical CBF covariance analysis. The effects of disease duration were explored to better understand the progressive changes in perfusion. We assessed the utility of perfusion in separating patients with TLE from controls using supervised machine learning. Compared with control participants (n = 38; mean ± SD age 34.8 ± 9.3 years; 20 females), patients with TLE (n = 24; mean ± SD age 35.8 ± 10.6 years; 12 females) showed widespread CBF reductions predominantly in fronto-temporal regions (Cohen d -0.69, 95% CI -1.21 to -0.16), consistent in a subgroup of patients who remained seizure-free after surgical resection of the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partially constrained by gray and white matter changes (8.11% reduction in Cohen d) and topologically segregated from whole-brain perfusion networks (area under the curve -0.17, p < 0.05). Negative effects of progressive disease duration further targeted regional CBF profiles in patients (r = -0.54, 95% CI -0.77 to -0.16). Perfusion-derived classifiers discriminated patients from controls with high accuracy (71% [70%-82%]). Findings were robust when controlling for several methodological confounds. Our multimodal findings provide insights into vascular contributions to TLE pathophysiology affecting and extending beyond mesiotemporal structures and highlight their clinical potential in epilepsy diagnosis. As our work was cross-sectional and based on a single site, it motivates future longitudinal studies to confirm progressive effects, ideally in a multicentric setting.