Eye tracking technology (ET) can objectively and noninvasively evaluate eye movements, and is closely related to cognitive dysfunction at early stage. This article reviews the research and application progress of eye tracking technology in memory, visual attention, visual search ability, executive ability, and social cognition of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI), and focuses on the potential application value of eye tracking technology combined with multimodal data in early diagnosis, disease monitoring and intervention measures of patients with Alzheimer's disease and mild cognitive impairment, so as to provide data support for the clinical application of eye tracking technology.

BackgroundAlzheimer's disease (AD) and mild cognitive impairment (MCI) cause progressive cognitive decline, with Western medicine only alleviating symptoms at present. Acupuncture shows potential for these disorders, but existing studies have inconsistent results.ObjectiveTo examine the effect of acupuncture on overall cognitive function in patients with AD and MCI via meta-analysis.MethodLiterature from six databases on acupuncture, AD, and MCI was searched. Meta-analyses and moderator analyses were performed using Comprehensive Meta Analysis V3.0.Results52 randomized controlled trials (RCTs) involving 3362 AD/MCI patients were included. Results showed that acupuncture alone outperformed blank or placebos (SMD=1.09, 95% CI = [0.60, 1.58], p < 0.001, I2 = 91.39%). In addition, acupuncture alone (SMD = 0.45, 95% CI = [0.22, 0.67], p < 0.001, I2 = 69.38%) and combined with Western medicine (SMD = 1.18, 95% CI = [0.92, 1.44], p < 0.001, I2 = 90.73%) were superior to Western medicine alone. Moderator analysis revealed significant effect of type of patients, showing larger effect in AD than MCI in acupuncture combined with Western medicine (Q = 10.20, p = 0.001). Regarding types of acupuncture, manual acupuncture (MA) and electroacupuncture (EA) showed no significant difference between them (alone: Q = 0.38, p = 0.536; combined with Western medicine: Q = 0.57, p = 0.449) and both outperformed Western medicine alone.ConclusionsAcupuncture could improve overall cognitive function in AD and MCI, with similar effects between MA and EA. Due to the heterogeneity and variable methodological quality of the studies included, our results must be interpreted with caution. Still, these results suggest acupuncture may be an adjuvant to Western medicine for eligible patients and a potential alternative for short-term cognitive improvement when Western medicine is contraindicated.

Quantitative MR relaxometry provides sensitive and reproducible measures of brain microstructure and is increasingly used in studies of ageing and neurodegenerative disease. However, normative brain atlases covering the adult lifespan remain scarce, especially from large, harmonized, multicenter datasets. This study aimed to establish lifespan-based normative T1 and T2 atlases to support individualized assessment and group-level comparisons. We retrospectively analyzed 947 healthy Han Chinese adults (421 males; median age 39 years; range 19-72) from 11 imaging centers in China. T1 and T2 maps were acquired with harmonized MP2RAGE and GRAPPATINI protocols, processed using a unified pipeline, and modeled with voxelwise mixed-effects regression including linear and quadratic age terms, sex, and random intercepts for site. Intersite reproducibility was further evaluated in three traveling subjects scanned at all centers. The atlases demonstrated region-specific age and sex effects in both white and gray matter. Intersite variability was minimal (intraclass correlation coefficients > 0.99 for T1 and > 0.90 for T2). Both T1 and T2 followed quadratic trajectories, decreasing in early adulthood, reaching minima in midlife, and increasing in later decades, with the strongest effects in cortical gray matter. Sex differences were most pronounced in parietal and callosal regions. These lifespan-based normative relaxometry atlases provide high-fidelity references for age- and sex-related microstructural changes in the healthy brain. They provide quantitative benchmarks for individualized profiling and group comparisons in Chinese adult populations, while validation in other ethnic populations remains necessary before broader application.

Cerebral asymmetry is a core principle of human brain organization, showing dynamic changes across the lifespan and alterations in brain disorders. However, it remains unclear whether lifespan trajectories of asymmetry differ across populations. We compared lifespan structural asymmetry normative charts of 221 cerebral imaging phenotypes from 43,037 Chinese and 56,339 Western participants aged 0–100 years. The two populations showed distinct lifespan asymmetry patterns in 26.2% of the phenotypes. Chinese-minus-Western asymmetry difference curves displayed distinct patterns across brain phenotypes: rightward (45.7%), leftward (26.2%), rightward-to-leftward (11.8%), leftward-to-rightward (10.0%), and unclassified (6.3%). Population-matched normative models outperformed population-unmatched normative models in capturing normal asymmetry variability among healthy individuals and in detecting abnormal asymmetry deviations in patients with Alzheimer’s disease, mild cognitive impairment, schizophrenia, and major depressive disorder. These findings indicate that population mismatch can bias chart-based individual-level asymmetry assessment and underscore the need for population-representative brain asymmetry normative charts.

BACKGROUND AND OBJECTIVE:Brain region volume from Structural Magnetic Resonance Imaging (sMRI) can directly reflect abnormal states in brain aging. While promising for clinical brain health assessment, existing volume-based brain age prediction methods fail to explore both linear and nonlinear relationships, resulting in weak representation and suboptimal estimates. METHODS:This paper proposes a brain age prediction method, RFBLSO, based on Random Forest (RF), Broad Learning System (BLS), and Leave-One-Out Cross Validation (LOO). Firstly, RF is used to eliminate redundant brain regions with low correlation to the target value. The objective function is constructed by integrating feature nodes, enhancement nodes, and optimal regularization parameters. Subsequently, the pseudo-inverse method is employed to solve for the output coefficients, which facilitates a more accurate representation of the linear and nonlinear relationships between volume features and brain age. RESULTS:Across various datasets, RFBLSO demonstrates the capability to formulate brain age prediction models, achieving a Mean Absolute Error (MAE) of 4.60 years within the Healthy Group and 4.98 years within the Chinese2020 dataset. In the Clinical Group, RFBLSO achieves measurement and effective differentiation among Healthy Controls (HC), Mild Cognitive Impairment (MCI), and Alzheimer's disease (AD) (MAE for HC, MCI, and AD: 4.46 years, 8.77 years, 13.67 years; the effect size η2 of the analysis of variance for AD/MCI vs. HC is 0.23; the effect sizes of post-hoc tests are Cohen's d = 0.74 (AD vs. MCI), 1.50 (AD vs. HC), 0.77 (MCI vs. HC)). Compared to other linear or nonlinear brain age prediction methods, RFBLSO offers more accurate measurements and effectively distinguishes between Clinical Groups. This is because RFBLSO can simultaneously explore both linear and nonlinear relationships between brain region volume and brain age. CONCLUSION:The proposed RFBLSO effectively represents both linear and nonlinear relationships between brain region volume and brain age, allowing for more accurate individual brain age estimation. This provides a feasible method for predicting the risk of neurodegenerative diseases.

PURPOSE:Imaging diagnosis of mild cognitive impairment (MCI) has garnered increasing attention due to its critical role in the early detection of Alzheimer's disease (AD) and other dementias. This study presents a bibliometric analysis to elucidate global research trends, key contributors, thematic clusters, and emerging topics within the field of MCI imaging diagnosis. METHOD:English-language publications related to MCI imaging were retrieved from the Web of Science Core Collection (WoSCC) from January 1999 to December 2024. Bibliometric analyses were performed using VOSviewer, CiteSpace, and R-bibliometrix to evaluate co-authorship networks, institutional collaborations, journal impact, keyword co-occurrence, and burst trends. FINDING:A total of 7,568 articles showed an average annual growth of 22.27%, with output surging after 2007 and peaking in 2024 (n = 762). The United States led in productivity and impact, ahead of China and Italy. Leading institutions were the University of California System, Vrije Universiteit Amsterdam, and the University of London, with key authors including Clifford R. Jack Jr., Ronald C. Petersen, and Philip Scheltens. Core journals were Neurology, Neuroimage, and Brain. Cluster analysis revealed four themes: functional and cognitive networks, biomarkers and pathology, structural imaging and computational diagnostics, and guidelines. Recent trendsc (AI) (e.g., machine learning, deep learning), while citation bursts indicate an evolution from early biomarker and imaging research toward current AI and multimodal imaging for improved diagnosis and risk prediction. CONCLUSION:This bibliometric analysis provides a comprehensive overview of the evolving research landscape in MCI imaging diagnosis. The integration of advanced computational methodologies, particularly AI-powered tools, is driving precision diagnostics and personalized medicine. These advancements hold significant potential to improve early detection, stratify risk, and inform therapeutic interventions, ultimately contributing to better outcomes for individuals with MCI.

BackgroundAcupuncture has been demonstrated to have a promising effect on Alzheimer’s disease (AD), but the underlying neural mechanisms remain unclear. The retrosplenial cortex (RSC) is one of the earliest brain regions affected in AD, and changes in its functional connectivity (FC) are reported to underlie disease-associated memory impairment. The aim of this study was to examine the effect of acupuncture on FC with the RSC in patients with AD.MethodsDemographic data, neuropsychological assessments, and resting-state functional magnetic resonance imaging (fMRI) data were collected from 14 AD patients and 14 normal controls (NCs) matched by age, sex, and educational level at baseline. After the baseline MRI scan, acupuncture stimulation on the Taichong (LIV3) and Hegu (LI4) points was performed for 3 min. Then, another 10 min of fMRI data were acquired after the needle was withdrawn. A dataset that included 100 healthy participants was also included to construct a reliable FC map of the RSC. Two sets of regions of interest (ROIs) in the RSC were selected to assess the sustained effect of acupuncture on FC with the RSC in AD patients and NCs.ResultsTwo sets of RSC ROI-based analyses demonstrated robust positive connectivity with the hippocampus (HPC). Furthermore, multiple brain regions, including the bilateral thalamus, bilateral posterior cingulate cortex (PCC), bilateral subcallosal cingulate gyrus (SCG), bilateral orbitofrontal cortex (OFC), and right precuneus, showed decreased FC with the RSC in the AD group and increased FC with the RSC in the NC group after acupuncture compared to that at baseline. Acupuncture also specifically elicited increased FC between the RSC and the HPC as well as between the RSC and the parahippocampal gyrus in AD patients and decreased FC between the RSC and the visual cortices in NCs. Additionally, diminished FC with the RSC was correlated with neuropsychological scale scores in the AD group before acupuncture treatment.ConclusionThese findings confirm and extend previous studies suggesting that acupuncture at Taichong (LIV3) and Hegu (LI4) can exert bidirectional and benign regulatory effects on RSC connectivity in AD patients.

Human brain charts provide unprecedented opportunities for decoding neurodevelopmental milestones and establishing clinical benchmarks for precision brain medicine 1-7. However, current lifespan brain charts are primarily derived from European and North American cohorts, with Asian populations severely underrepresented. Here, we present the first population-specific brain charts for China, developed through the Chinese Lifespan Brain Mapping Consortium (Phase I) using neuroimaging data from 43,037 participants (aged 0-100 years) across 384 sites nationwide. We establish the lifespan normative trajectories for 296 structural brain phenotypes, encompassing global, subcortical, and cortical measures. Cross-population comparisons with Western brain charts (based on data from 56,339 participants aged 0-100 years) reveal distinct neurodevelopmental patterns in the Chinese population, including prolonged cortical and subcortical maturation, accelerated cerebellar growth, and earlier development of sensorimotor regions relative to paralimbic regions. Crucially, these Chinese-specific charts outperform Western-derived models in predicting healthy brain phenotypes and detecting pathological deviations in Chinese clinical cohorts. These findings highlight the urgent need for diverse, population-representative brain charts to advance equitable precision neuroscience and improve clinical validity across populations.

Alzheimer’s dementia (AD) and mild cognitive impairment (MCI) are characterized by progressive cognitive decline. Repetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation technology, has been widely used to improve cognition in AD and MCI. However, the impact of rTMS on immediate and long-term cognitive functions in AD and MCI, as well as the optimal stimulating parameters, need further clarification. Thirty-one randomized controlled trials were included to examine the effects of rTMS on immediate cognition (post-treatment cognition), while nine trials were specifically used to assess its impact on long-term cognition (follow-up cognition). All participants were tested on at least one of the neuropsychological scales of the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Alzheimer’s disease Assessment Scale-Cognitive Section (ADAS-Cog) to evaluate global cognitive outcomes of rTMS. The study followed the guidelines for meta-analysis of intervention studies and assessed the risk of bias of the included studies. Moderator analysis was used to examine factors that might affect treatment effect. Sensitivity analysis was used to evaluate stability of results. Meta-regression analysis was used to assess the interpretability of heterogeneity. Begg’s and Egger’s test and funnel plot were applied to assess publication bias. The results demonstrated that rTMS significantly improved immediate cognition (SMD = 0.93, 95

Quantifying individual deviations in brain morphology from normative references is useful for understanding neurodiversity and facilitating personalized management of brain health. Here we report Chinese brain normative references using morphological imaging scans of 24,061 healthy volunteers from 105 sites, revealing later peak ages of lifespan neurodevelopmental milestones (1.2-8.9 years) than European/North American populations. We model individual brain deviation scores in 3,932 individuals with different neurological disorders from population references to evaluate three key aspects of brain health assessment using machine learning approaches: estimating disease propensity, predicting cognitive and physical outcomes and assessing treatment effects with distinct disability progression. The norm-deviation scores outperformed raw structural measures in these evaluations. Chinese-specific normative brain references may foster personalized diagnosis and prognosis in neurological diseases, enabling clinically applicable assessments of brain health.

BACKGROUND AND PURPOSE: The underlying transcriptomic signatures driving brain functional alterations in MS and neuromyelitis optica spectrum disorder (NMOSD) are still unclear. MATERIALS AND METHODS: Regional fractional amplitude of low-frequency fluctuation (fALFF) values were obtained and compared among 209 patients with MS, 90 patients with antiaquaporin-4 antibody (AQP4)+ NMOSD, 49 with AQP4- NMOSD, and 228 healthy controls from a discovery cohort. We used partial least squares (PLS) regression to identify the gene transcriptomic signatures associated with disease-related fALFF alterations. The biologic process and cell type-specific signature of the identified PLS genes were explored by enrichment analysis. The correlation between PLS genes and clinical variables was explored. A prospective independent cohort was used to validate the brain fALFF alterations and the repeatability of identified genes. RESULTS: MS, AQP4+ NMOSD, and AQP4- NMOSD showed decreased fALFF in cognition-related regions and deep gray matter, while NMOSD (both AQP4+ and AQP4-) additionally demonstrated lower fALFF in the visual region. The overlapping PLS1- genes (indicating that the genes were overexpressed as regional fALFF decreased) were enriched in response to regulation of the immune response in all diseases, and the PLS1- genes were specifically enriched in the epigenetics profile in MS, membrane disruption and cell adhesion in AQP4+ NMOSD, and leukocyte activation in AQP4- NMOSD. For the cell type transcriptional signature, microglia and astrocytes accounted for the decreased fALFF. The fALFF-associated PLS1- genes directly correlated with Expanded Disability Status Scale of MS and disease duration across disorders. CONCLUSIONS: We revealed the functional activity alterations and their underlying shared and specific gene transcriptional signatures in MS, AQP4+ NMOSD, and AQP4- NMOSD.

BackgroundAlthough right atrial (RA) myocardial deformation has important implications for patient diagnosis, prognosis, and risk stratification, its implementation in clinical practice has been hampered by limited normal reference values, especially in Asian populations.PurposeTo establish age‐ and sex‐specific reference values for RA strain, strain rate (SR), and displacement based on a large sample of healthy Chinese adults using MR‐feature tracking (MR‐FT).Study TypeRetrospective.Population524 healthy Chinese adults (287 male; mean age 43.7 ± 11.9 years).Field Strength/Sequence1.5T/balanced steady‐state free precession.AssessmentRA deformation parameters, including reservoir, conduit, and booster strain (εs, εe, and εa), peak positive, early negative, and late negative SR (SRs, SRe, and SRa), and total, passive, and active displacement (Ds, De, and Da), were assessed using MR‐FT.Statistical TestsStudent's t‐test, one‐way ANOVA, coefficients of determination (r2), intraclass correlation coefficients (ICC), and Bland–Altman plots. A P value <0.05 was considered significant.ResultsWomen demonstrated significantly greater magnitudes of RA deformation parameters than men: εs (57.4% ± 15.1% vs. 44.3% ± 12.6%), εe (37.5% ± 13.4% vs. 27.4% ± 10.9%), εa (19.9% ± 5.7% vs. 16.9% ± 5.0%), SRs (2.62 ± 0.88 sec−1 vs. 2.00 ± 0.63 sec−1), SRe (−2.98 ± 1.26 sec−1 vs. −2.16 ± 0.92 sec−1), SRa (−2.28 ± 0.75 sec−1 vs. −1.84 ± 0.62 sec−1), Ds (−7.80 ± 1.90 mm vs. −7.46 ± 1.70 mm), and De (−4.84 ± 1.31 mm vs. −4.49 ± 1.21 mm). For both sexes, aging was significantly associated with decreased RA reservoir and conduit function (εs, SRs, Ds, εe, SRe, and De), and with increased εa and Da. RA deformation measurements had good to excellent intraobserver and interobserver reproducibility, with ICCs ranging from to 0.790 to 0.972.Data ConclusionThis study provides age‐ and sex‐specific reference values of RA strain, SR, and displacement based on a large cohort of healthy Chinese adults using MR‐FT.Level of Evidence3Technical EfficacyStage 2

The insula, a crucial hub of the human brain network, can be divided into anterior and posterior regions. Previous studies have reported that different insula subregions play various roles in amnestic mild cognitive impairment (aMCI). However, the longitudinal changes in the functional connectivity (FC) of each insula subregion in aMCI patients over time remain unclear. Twenty aMCI patients and 20 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (fMRI) scans and neuropsychological assessments at baseline and at the 15-month follow-up. FMRI data were preprocessed using SPM 12 and the CONN toolbox. Two-way analysis of covariance was used to compare longitudinal changes in the FC of each insula subregion with covariates including sex, age, education, follow-up interval, volume of gray matter, and global correlation (GCOR). Pearson’s correlation was used to evaluate the relationship between insula subregional FC and neuropsychological performance in aMCI patients. In aMCI patients, the right anterior insula exhibited significantly increased FC with the left anterior cingulate cortex, whereas the left posterior insula exhibited decreased FC with the right precuneus compared with HCs. Furthermore, FC between the right anterior insula and left anterior cingulate cortex was significantly correlated with global cognition at follow-up. The current findings revealed different functional alterations in the insula subregions and provided new insights into the neurodegenerative process in aMCI patients.

Assessment of left atrial (LA) function and the left atrioventricular coupling index (LACI) have recently been increasingly recognized as important indices for cardiovascular diseases associated with the presence of prediabetes and diabetes. We aimed to evaluate LA function and the LACI in patients with prediabetes and diabetes via cardiac magnetic resonance (CMR). In this retrospective study, we included 35 patients with prediabetes, 32 patients with diabetes, and 84 healthy control participants. The LACI and LA total, passive, and active emptying fractions (LATEmF, LAPEmF, and LAAEmF, respectively) were calculated. The LA reservoir, conduit, and booster pump strains (εs, εe, and εa), and peak positive, peak early negative, and peak late negative strain rates (SRs, SRe, and SRa) were obtained via CMR-feature tracking (CMR-FT). For the statistical analyses, one-way analysis of variance, the Kruskal–Wallis test, and linear regression were conducted, and Pearson’s and interclass correlation coefficients were calculated. Compared with healthy control participants, patients with prediabetes or diabetes presented lower εs and εe values and a relatively preserved LACI. Patients with diabetes presented considerably reduced SRs, SRe, and LAPEmF. Elevated glycated haemoglobin (HbA1c) levels were independently associated with decreased magnitudes of εs, SRs, εe, and SRe. No significant associations were found between the LACI and the HbA1c or LA deformation parameters. We observed significant correlations between LATEmF and εs, LAPEmF and εe and between LAAEmF and εa. CMR-FT provides a potential noninvasive approach for the early detection of alterations in the LA reservoir and conduit function in individuals with prediabetes and diabetes.

Grey matter (GM) atrophies are observed in multiple sclerosis, neuromyelitis optica spectrum disorders [NMOSD; both anti-aquaporin-4 antibody-positive (AQP4+) and -negative (AQP4-) subtypes] and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Revealing the pathogenesis of brain atrophy in these disorders would help their differential diagnosis and guide therapeutic strategies.To determine the neurobiological underpinnings of GM atrophies in multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD and MOGAD, we conducted a virtual histology analysis that links T1-weighted image derived GM atrophy and gene expression using a multicentre cohort of 324 patients with multiple sclerosis, 197 patients with AQP4+ NMOSD, 75 patients with AQP4- NMOSD, 47 patients with MOGAD and 2169 healthy control subjects. First, interregional GM atrophy profiles across the cortical and subcortical regions were determined using Cohen's d between patients with multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD or MOGAD and healthy controls. The GM atrophy profiles were then spatially correlated with the gene expression levels extracted from the Allen Human Brain Atlas, respectively. Finally, we explored the virtual histology of clinical-feature relevant GM atrophy using a subgroup analysis that stratified by physical disability, disease duration, number of relapses, lesion burden and cognitive function.Multiple sclerosis showed a severe widespread GM atrophy pattern, mainly involving subcortical nuclei and brainstem. AQP4+ NMOSD showed an obvious widespread pattern of GM atrophy, predominately located in occipital cortex as well as cerebellum. AQP4- NMOSD showed a mild widespread GM atrophy pattern, mainly located in frontal and parietal cortices. MOGAD showed GM atrophy mainly involving the frontal and temporal cortices. High expression of genes specific to microglia, astrocytes, oligodendrocytes and endothelial cells in multiple sclerosis, S1 pyramidal cells in AQP4+ NMOSD, as well as S1 and CA1 pyramidal cells in MOGAD, had spatial correlations with GM atrophy profile, while no atrophy profile-related gene expression was found in AQP4- NMOSD. Virtual histology of clinical feature-relevant GM atrophy pointed mainly to the shared neuronal and endothelial cells, among the four neuroinflammatory diseases.The unique underlying virtual histology patterns were microglia, astrocytes and oligodendrocytes for multiple sclerosis; astrocytes for AQP4+ NMOSD; and oligodendrocytes for MOGAD. Neuronal and endothelial cells were shared potential targets across these neuroinflammatory diseases. These findings may help the differential diagnoses of these diseases and promote the use of optimal therapeutic strategies. Sun et al. use a virtual histology approach to assess the putative pathophysiological basis of interregional differences in grey matter atrophy patterns in patients with multiple sclerosis, AQP4+ and AQP4- subtypes of NMOSD, and MOGAD. The findings could aid differential diagnosis and identification of optimal therapeutic strategies.

We aimed to characterize the brain abnormalities that are associated with the cognitive and physical performance of patients with relapsing-remitting multiple sclerosis (RRMS) using a deep learning algorithm. Three-dimensional (3D) nnU-Net was employed to calculate a novel spatial abnormality map by T1-weighted images and 281 RRMS patients (Dataset-1, male/female = 101/180, median age [range] = 35.0 [17.0, 65.0] years) were categorized into subtypes. Comparison of clinical and MRI features between RRMS subtypes was conducted by Kruskal–Wallis test. Kaplan–Meier analysis was conducted to investigate disability progression in RRMS subtypes. Additional validation using two other RRMS datasets (Dataset-2, n = 33 and Dataset-3, n = 56) was conducted. Five RRMS subtypes were identified: (1) a Frontal-I subtype showing preserved cognitive performance and mild physical disability, and low risk of disability worsening; (2) a Frontal-II subtype showing low cognitive scores and severe physical disability with significant brain volume loss, and a high propensity for disability worsening; (3) a temporal-cerebellar subtype demonstrating lowest cognitive scores and severest physical disability among all subtypes but remaining relatively stable during follow-up; (4) an occipital subtype demonstrating similar clinical and imaging characteristics as the Frontal-II subtype, except a large number of relapses at baseline and preserved cognitive performance; and (5) a subcortical subtype showing preserved cognitive performance and low physical disability but a similar prognosis as the occipital and Frontal-II subtypes. Additional validation confirmed the above findings. Spatial abnormality maps can explain heterogeneity in cognitive and physical performance in RRMS and may contribute to stratified management. Question Can a deep learning algorithm characterize the brain abnormalities associated with the cognitive and physical performance of patients with RRMS? Findings Five RRMS subtypes were identified by the algorithm that demonstrated variable cognitive and physical performance. Clinical relevance The spatial abnormality maps derived RRMS subtypes had distinct cognitive and physical performances, which have a potential for individually tailored management.

ObjectivesPrevious studies have demonstrated that optic neuritis (ON) affects brain plasticity. However, whether ON affects the spinal cord remains unclear. We aimed to investigate the spinal cord changes in ON and their associations with disability.MethodsA total of 101 ON patients, and 41 healthy controls (HC) were retrospectively recruited. High-resolution imaging was conducted using a Magnetization Prepared Rapid Acquisition Gradient-Echo (MP-RAGE) sequence for T1-weighted images and an echo planar imaging (EPI) sequence for Diffusion Tensor Imaging (DTI) data collection. Additionally, patients' disability and cognitive impairment were evaluated using the Expanded Disability Status Scale (EDSS) and the Paced Auditory Serial Addition Test (PASAT), respectively. The quantitative spinal MRI was employed to examine the cross-sectional area (CSA) and diffusion indicators, with a specific focus on calculating the average values across the C2-C7 cervical spinal cord segments. CSA, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared between groups. Correlation analyses were performed between CSA, diffusion indicators, and clinical variables.ResultsNo significant differences were found in CSA between ON patients and HCs. MD (p = 0.007) and RD (p = 0.018) were increased in ON patients compared with HCs, and AD was decreased in ON (p = 0.013). The AD values of the ON patients were significantly positively correlated with PASAT scores (r = 0.37, p < 0.001).ConclusionsThis study provided imaging evidence for DTI abnormalities in patients with ON. Spinal cord DTI can improve our knowledge of the path physiology of ON, and clinical progression.

This study aims to investigate the brain gray matter volume (GMV) alterations of pediatric complete thoracolumbar spinal cord injury (SCI) without fracture or dislocation (SCIWOFD) using voxel-based morphometry (VBM) analysis and assess the sensitive neuroimaging biomarkers that may be surrogate targets to enhance brain plasticity. A total of 52 pediatric subjects (age range, 6-12 years), including 25 pediatric SCIWOFD patients and 27 typically developing (TD) children were recruited. An independent two-sample t test was performed to assess between-group differences of brain GMV. Partial correlation analyses were performed to explore the correlations between GMV values and The International Standards for Neurological Classification of Spinal Cord Injury scores, age at the time of injury, time after initial SCI. Receiver operating characteristic analysis was performed to compute the sensitivity and specificity of the imaging biomarkers for pediatric SCIWOFD diagnosis. As for the results, pediatric SCIWOFD patients showed significantly decreased GMV of bilateral cerebellum lobule VIII, right middle occipital gyrus and putamen (PUT), left pallidum (PAL) and thalamus, and increased GMV of vermis III, right cerebellum lobule VI, and supramarginal gyrus. In addition, GMV of left PAL and right PUT were negatively correlated with the pinprick/light touch sensory scores in pediatric SCIWOFD patients. Finally, when using the GMV values of left PAL and right PUT in combination as the predictor, area under the curve reached the highest-0.93. These findings provided evidence that the brain undergoes GMV changes after pediatric SCIWOFD, which may suggest important targets for functional remodeling after SCI in children and provide valuable information for the development of novel and effective rehabilitation therapies in the future.

本报告汇总了阿尔茨海默病及痴呆相关领域现有的最新数据，分析了我国阿尔茨海默病的流行病学、疾病负担、诊断治疗、风险因素、康复护理和疾病筛查等各方面的现状、问题以及趋势，针对目前中国民众和政策制定者最关心的问题，例如：阿尔茨海默病基本数据是怎样的？为什么知晓率相对提高，但是患者就诊愿望相对不高？如何采用有效的措施来应对，等等，提出了目前阿尔茨海默病的防控策略。特别强调了要大力开发经过验证的早期筛查和诊断工具，提供更有效治疗的创新药物，以及鼓励和建立全国性属地化社会互助支持网络。本报告期望能对医学专业人士、患者、家属和照护者、政府政策制定人员、养老机构等有所帮助，能为阿尔茨海默病的防治工作提供支撑，为相关卫生政策的制定提供依据和建议，有助于提高公众对阿尔茨海默病的认识，以期缓解我国阿尔茨海默病疾病的整体负担，推动我国健康老龄化的实现。

ObjectivesCardiovascular magnetic resonance-feature tracking (CMR-FT) enables quantification of myocardial deformation and may be used as an objective measure of myocardial involvement in ST-elevation myocardial infarction (STEMI). We sought to investigate the associations between myocardial dyssynchrony parameters and myocardium damage for STEMI.MethodsWe analyzed 65 patients (45–80 years old) with anterior STEMI after primary percutaneous coronary intervention during 3–7 days [observational (STEMI) group] and 60 healthy volunteers [normal control (NC) group]. Myocardial dyssynchrony parameters were derived, including global and regional strain, radial rebound stretch and displacement, systolic septal time delay, and circumferential stretch.ResultsCMR characteristics, including morphologic parameters such as left ventricular ejection fraction (LVEF) (45.3% ± 8.2%) and myocardium damage in late gadolinium enhancement (LGE) (19.4% ± 4.7% LV), were assessed in the observation group. The global radial strain (GRS) and global longitudinal strain (GLS) substantially decreased in anterior STEMI compared with the NC group (GRS: 19.4% ± 5.1% vs. 24.8% ± 4.0%, P < 0.05; GLS: −10.1% ± 1.7% vs. −13.7% ± 1.0%, P < 0.05). Among 362 infarcted segments, radial and circumferential peak strains of the infarcted zone were the lowest (14.4% ± 3.2% and −10.7% ± 1.6%, respectively). The radial peak displacement of the infarct zone significantly decreased (2.6 ± 0.4 mm) (P < 0.001) and manifested in the circumferential displacement (3.5° ± 0.7°) in the STEMI group (P < 0.01). As microvascular occlusion (MVO) was additionally present, some strain parameters were significantly impaired in LGE+/MVO+ segments (radial strain [RS]: 12.2% ± 2.1%, circumferential strain [CS]: −9.6% ± 0.7%, longitudinal strain [LS]: −6.8% ± 1.0%) compared to LGE+/MVO− (RS: 14.6% ± 3.2%, CS: −10.8% ± 1.8%, LS: −9.2% ± 1.3%) (P < 0.05). When the extent of transmural myocardial infarction is greater than 75%, the parameter of the systolic septal delay (mean, 148 ms) was significantly reduced compared to fewer degrees of infarction (P < 0.01).ConclusionIn anterior STEMI, the infarcted septum swings in a bimodal mode, and myocardial injury reduces the radial strain contractility. A more than 75% transmural degree was the septal strain-contraction reserve cut-off point.