Alterations of brain structural and functional connectivity networks topology and decoupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.

OBJECTIVE: To investigate the alteration in structural and functional connectivity networks (SCN and FCN) as well as their coupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and determine if these properties could serve as potential biomarkers for the disease. MATERIALS AND METHODS: In total of 32 children with MOGAD and 30 age- and sex-matched healthy controls (HC) were employed to construct the SCN and FCN, respectively. The graph-theoretical analyses of the global properties, node properties of the 90 brain nodes, and the structural-functional connectivity (SC-FC) coupling of the two networks were performed. The graph-theoretical properties that exhibited significant differences were analyzed using partial correlation analysis in conjunction with the clinical scales, including the expanded disability status scale (EDSS), modified Rankin scale (mRS), and pediatric cerebral performance category (PCPC) of the MOGAD group. Subsequently, a machine learning model was developed to discriminate between MOGAD and the HC group, aiming to explore the potential of these properties as biomarkers. RESULTS: The SCN of the MOGAD group exhibited aberrant global properties, including an increased characteristic path length (Lp) and a decreased global efficiency (Eg), along with reduced nodal properties such as degree centrality (Dc), nodal efficiency (Ne), and local efficiency in multiple nodes. The FCN of the MOGAD group only exhibited decreased Dc, Ne, and betweenness centrality in two nodes of nodal properties. Besides, MOGAD showed a significant decrease in SC-FC coupling compared to the HC group. The analysis of partial correlation revealed significant correlations between several properties and the scales of EDSS and mRS in the MOGAD group. The machine learning method was used to extract six features and establish the model, achieving a classification accuracy of 82.3% for MOGAD. CONCLUSIONS: Pediatric MOGAD showed a more pronounced impairment in the SCN along with decoupling of SC-FC. Both partial correlation analysis and discriminant modeling suggest that alterations in brain network properties have the potential as biomarkers for assessing brain damage in MOGAD.

Comparison of Doppler Imaging and Microvascular Imaging in Cervical Lymph Node Blood Flow Analysis.

Cervical lymph node metastasis is an important determinant of cancer stage and the selection of an appropriate treatment plan for patients with head and neck cancer. Therefore, metastatic cervical lymph nodes should be effectively differentiated from lymphoma, tuberculous lymphadenitis, and other benign lymphadenopathies. The aim of this work is to describe the performance of Doppler ultrasound and superb microvascular imaging (SMI) in evaluating blood flow information of cervical lymph nodes. In addition, the features of flow imaging in metastatic lymph nodes, lymphoma, and tuberculous lymphadenitis were described. Compared with Doppler ultrasound, SMI, the latest blood flow imaging technology, could detect more blood flow signals because the sensitivity, specificity, and accuracy of SMI in the diagnosis of cervical lymph node disease were higher. This article summarizes the value of Doppler ultrasound and SMI in evaluating cervical lymph node diseases and focuses on the diagnostic performance of SMI.

Structural or/and functional MRI-based machine learning techniques for attention-deficit/hyperactivity disorder diagnosis: A systematic review and meta-analysis.

BACKGROUND: The aim of this study was to investigate the diagnostic value of ML techniques based on sMRI or/and fMRI for ADHD. METHODS: We conducted a comprehensive search (from database creation date to March 2024) for relevant English articles on sMRI or/and fMRI-based ML techniques for diagnosing ADHD. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve and area under the curve (AUC) were calculated to assess the diagnostic value of sMRI or/and fMRI-based ML techniques. The I2 test was used to assess heterogeneity and the source of heterogeneity was investigated by performing a meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test. RESULTS: Forty-three studies were included in the systematic review, 27 of which were included in our meta-analysis. The pooled sensitivity and specificity of sMRI or/and fMRI-based ML techniques for the diagnosis of ADHD were 0.74 (95 % CI 0.65-0.81) and 0.75 (95 % CI 0.67-0.81), respectively. SROC curve showed that AUC was 0.81 (95 % CI 0.77-0.84). Based on these findings, the sMRI or/and fMRI-based ML techniques have relatively good diagnostic value for ADHD. LIMITATIONS: Our meta-analysis specifically focused on ML techniques based on sMRI or/and fMRI studies. Since EEG-based ML techniques are also used for diagnosing ADHD, further systematic analyses are necessary to explore ML methods based on multimodal medical data. CONCLUSION: sMRI or/and fMRI-based ML technique is a promising objective diagnostic method for ADHD.

Image-defined risk factors associated with MYCN oncogene amplification in neuroblastoma and their association with overall survival.

OBJECTIVE: The MYCN oncogene is a critical factor in the development and progression of neuroblastoma, and image-defined risk factors (IDRFs) are radiological findings used for the preoperative staging of neuroblastoma. This study aimed to investigate the specific categories of IDRFs associated with MYCN amplification in neuroblastoma and their association with overall survival. METHOD: A retrospective analysis was conducted on a cohort of 280 pediatric patients diagnosed with neuroblastoma, utilizing a combination of clinical and radiological data. MYCN amplification status was ascertained through molecular testing, and the assessment of IDRFs was conducted using either contrast-enhanced computed tomography or magnetic resonance imaging. The specific categories of IDRFs associated with MYCN amplification and their association with overall survival were analyzed. RESULTS: MYCN amplification was identified in 19.6% (55/280) of patients, with the majority of primary lesions located in the abdomen (53/55, 96.4%). Lesions accompanied by MYCN amplification exhibited significantly larger tumor volume and a greater number of IDRFs compared with those without MYCN amplification (P < 0.001). Both univariate and multivariate analyses revealed that coeliac axis/superior mesenteric artery encasement and infiltration of adjacent organs/structures were independently associated with MYCN amplification in abdominal neuroblastoma (P < 0.05). Patients presenting with more than four IDRFs experienced a worse prognosis (P = 0.017), and infiltration of adjacent organs/structures independently correlated with overall survival in abdominal neuroblastoma (P = 0.009). CONCLUSION: The IDRFs are closely correlated with the MYCN amplification status and overall survival in neuroblastoma.

Progression rate of radiation-induced carotid stenosis in head and neck cancer survivors after statin treatment: a retrospective cohort study.

BACKGROUND AND AIMS: Whether statin treatment is effective in retarding the progression of radiation-induced carotid stenosis (RICS) in head and neck cancer (HNC) survivors has not been well studied. The purpose of this study was to assess the association of statin treatment with RICS progression rate in HNC survivors after radiotherapy. METHODS: We conducted a retrospective cohort study at Sun Yat-sen Memorial Hospital, Sun Yat-sen University in Guangzhou, China. Between January 2010 and December 2021, we screened HNC survivors whose carotid ultrasound scans had shown stenosis of the common and/or internal carotid arteries. The primary outcome was the RICS progression rate. We compared eligible patients treated with statins with those who did not in multivariable Cox regression models. RESULTS: A total of 200 patients were included in this study, of whom 108 received statin treatment and 92 did not. Over a mean follow-up time of 1.5 years, 56 (28.0%) patients showed RICS progression, 24 (42.9%) and 32 (57.1%) in the statin and control groups, respectively. The statin group showed less RICS progression than the control group (adjusted-HR 0.49, 95% CI 0.30-0.80, P = 0.005). In the subgroup analysis, there was no significant interaction in the effect of statins on lowering RICS progression rate in the subgroups stratified by baseline low-density lipoprotein cholesterol (LDL-C) levels (P for interaction = 0.53) or baseline degrees of stenosis (P for interaction = 0.50). CONCLUSIONS: Statin treatment was associated with a lower risk of RICS progression in patients with HNC after radiotherapy, regardless of baseline LDL-C level and baseline stenosis degrees.

Aberrant white matter microstructure detected by automatic fiber quantification in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.

BACKGROUND AND OBJECTIVES: Myelin oligodendrocyte glycoprotein antibody-associated diseases (MOGAD) is an idiopathic inflammatory demyelinating disorder in children, for which the precise damage patterns of the white matter (WM) fibers remain unclear. Herein, we utilized diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ) to identify patterns of fiber damage and to investigate the clinical significance of MOGAD-affected fiber tracts. METHODS: A total of 28 children with MOGAD and 31 healthy controls were included in this study. The AFQ approach was employed to track WM fiber with 100 equidistant nodes defined along each tract for statistical analysis of DTI metrics in both the entire and nodal manner. The feature selection method was used to further screen significantly aberrant DTI metrics of the affected fiber tracts or segments for eight common machine learning (ML) to evaluate their potential in identifying MOGAD. These metrics were then correlated with clinical scales to assess their potential as imaging biomarkers. RESULTS: In the entire manner, significantly reduced fractional anisotropy (FA) was shown in the left anterior thalamic radiation, arcuate fasciculus, and the posterior and anterior forceps of corpus callosum in MOGAD (all p < 0.05). In the nodal manner, significant DTI metrics alterations were widely observed across 37 segments in 10 fiber tracts (all p < 0.05), mainly characterized by decreased FA and increased radial diffusivity (RD). Among them, 14 DTI metrics in seven fiber tracts were selected as important features to establish ML models, and satisfactory discrimination of MOGAD was obtained in all models (all AUC > 0.85), with the best performance in the logistic regression model (AUC = 0.952). For those features, the FA of left cingulum cingulate and the RD of right inferior frontal-occipital fasciculus were negatively and positively correlated with the expanded disability status scale (r = -0.54, p = 0.014; r = 0.43, p = 0.03), respectively. CONCLUSION: Pediatric MOGAD exhibits extensive WM fiber tract aberration detected by AFQ. Certain fiber tracts exhibit specific patterns of DTI metrics that hold promising potential as biomarkers.

Current progression in application of extracellular vesicles in central nervous system diseases.

Early diagnosis and pharmacological treatment of central nervous system (CNS) diseases has been a long-standing challenge for clinical research due to the presence of the blood-brain barrier. Specific proteins and RNAs in brain-derived extracellular vesicles (EVs) usually reflect the corresponding state of brain disease, and therefore, EVs can be used as diagnostic biomarkers for CNS diseases. In addition, EVs can be engineered and fused to target cells for delivery of cargo, demonstrating the great potential of EVs as a nanocarrier platform. We review the progress of EVs as markers and drug carriers in the diagnosis and treatment of neurological diseases. The main areas include visual imaging, biomarker diagnosis and drug loading therapy for different types of CNS diseases. It is hoped that increased knowledge of EVs will facilitate their clinical translation in CNS diseases.

Aberrant brain intra- and internetwork functional connectivity in children with Prader-Willi syndrome.

PURPOSE: Prader-Willi syndrome (PWS) suffers from brain functional reorganization and developmental delays during childhood, but the underlying neurodevelopmental mechanism is unclear. This paper aims to investigate the intra- and internetwork functional connectivity (FC) changes, and their relationships with developmental delays in PWS children. METHODS: Resting-state functional magnetic resonance imaging datasets of PWS children and healthy controls (HCs) were acquired. Independent component analysis was used to acquire core resting-state networks (RSNs). The intra- and internetwork FC patterns were then investigated. RESULTS: In terms of intranetwork FC, children with PWS had lower FC in the dorsal attention network, the auditory network, the medial visual network (VN) and the sensorimotor network (SMN) than HCs (FWE-corrected, p < 0.05). In terms of internetwork FC, PWS children had decreased FC between the following pairs of regions: posterior default mode network (DMN) and anterior DMN; posterior DMN and SMN; SMN and posterior VN and salience network and medial VN (FDR-corrected, p < 0.05). Partial correlation analyses revealed that the intranetwork FC patterns were positively correlated with developmental quotients in PWS children, while the internetwork FC patterns were completely opposite (p < 0.05). Intranetwork FC patterns showed an area under the receiver operating characteristic curve of 0.947, with a sensitivity of 96.15% and a specificity of 81.25% for differentiating between PWS and HCs. CONCLUSION: Impaired intra- and internetwork FC patterns in PWS children are associated with developmental delays, which may result from neural pathway dysfunctions. Intranetwork FC reorganization patterns can discriminate PWS children from HCs. REGISTRATION NUMBER ON THE CHINESE CLINICAL TRAIL REGISTRY: ChiCTR2100046551.

Cluster-based radiomics reveal spatial heterogeneity of bevacizumab response for treatment of radiotherapy-induced cerebral necrosis.

Background: Bevacizumab is used in the treatment of radiation necrosis (RN), which is a debilitating toxicity following head and neck radiotherapy. However, there is no biomarker to predict if a patient would respond to bevacizumab. Purpose: We aimed to develop a cluster-based radiomics approach to characterize the spatial heterogeneity of RN and map their responses to bevacizumab. Methods: 118 consecutive nasopharyngeal carcinoma patients diagnosed with RN were enrolled. We divided 152 lesions from the patients into 101 for training, and 51 for validation. We extracted voxel-level radiomics features from each lesion segmented on T1-weighted+contrast and T2 FLAIR sequences of pre- and post-bevacizumab magnetic resonance images, followed by a three-step analysis involving individual- and population-level clustering, before delta-radiomics to derive five radiomics clusters within the lesions. We tested the association of each cluster with response to bevacizumab and developed a clinico-radiomics model using clinical predictors and cluster-specific features. Results: 71 (70.3%) and 34 (66.7%) lesions had responded to bevacizumab in the training and validation datasets, respectively. Two radiomics clusters were spatially mapped to the edema region, and the volume changes were significantly associated with bevacizumab response (OR:11.12 [95% CI: 2.54-73.47], P = 0.004; and 1.63[1.07-2.78], P = 0.042). The combined clinico-radiomics model based on textural features extracted from the most significant cluster improved the prediction of bevacizumab response, compared with a clinical-only model (AUC:0.755 [0.645-0.865] to 0.852 [0.764-0.940], training; 0.708 [0.554-0.861] to 0.816 [0.699-0.933], validation). Conclusion: Our radiomics approach yielded intralesional resolution, enabling a more refined feature selection for predicting bevacizumab efficacy in the treatment of RN.

Development of a radiomics model to discriminate ammonium urate stones from uric acid stones in vivo: A remedy for the diagnostic pitfall of dual-energy computed tomography.

BACKGROUND: Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them. METHODS: This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated. RESULTS: When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899-0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796-0.995) and 0.870 (95% CI, 0.769-0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model. CONCLUSIONS: DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.

Classification of Myelin Oligodendrocyte Glycoprotein Antibody-Related Disease and Its Mimicking Acute Demyelinating Syndromes in Children Using MRI-Based Radiomics: From Lesion to Subject.

RATIONALE AND OBJECTIVES: To develop MRI-based radiomics models from the lesion level to the subject level and assess their value for differentiating myelin oligodendrocyte glycoprotein antibody-related disease (MOGAD) from non-MOGAD acute demyelinating syndromes in pediatrics. MATERIALS AND METHODS: 66 MOGAD and 66 non-MOGAD children were assigned to the training set (36/35), internal test set (14/16), and external test set (16/15), respectively. At the lesion level, five single-sequence models were developed alongside a fusion model (combining these five sequences). The radiomics features of each lesion were quantified as the lesion-level radscore (LRS) using the best-performing model. Subsequently, a lesion-typing function was employed to classify lesions into two types (MOGAD-like or non-MOGAD-like), and the average LRS of the predominant type lesions in each subject was considered as the subject-level radscore (SRS). Based on SRS, a subject-level model was established and compared to both clinical models and radiologists' assessments. RESULTS: At the lesion level, the fusion model outperformed the five single-sequence models in distinguishing MOGAD and non-MOGAD lesions (0.867 and 0.810 of area under the curve [AUC] in internal and external testing, respectively). At the subject level, the SRS model showed superior performance (0.844 and 0.846 of AUC in internal and external testing, respectively) compared to clinical models and radiologists' assessments for distinguishing MOGAD and non-MOGAD. CONCLUSION: MRI-based radiomics models have potential clinical value for identifying MOGAD from non-MOGAD. The fusion model and SRS model can distinguish between MOGAD and non-MOGAD at the lesion level and subject level, respectively, providing a differential diagnosis method for these two diseases.

Preoperative fluorescence in situ hybridization analysis as a predictor of tumor recurrence in patients with non-muscle invasive bladder cancer: a bi-institutional study.

BACKGROUND: Non-muscle invasive bladder cancer (NMIBC) is known for its elevated recurrence rate, necessitating an enhancement in the current risk stratification for recurrence. The urine-based fluorescence in situ hybridization (FISH) assay has emerged as a noninvasive auxiliary tool for detecting bladder cancer. The aim of this study was to explore the potential relationship between the preoperative FISH assay and recurrence, and to develop a FISH-clinical nomogram for predicting the recurrence-free survival (RFS) in NMIBC patients. METHODS: In total, 332 eligible patients were enrolled from two hospitals. The SYSMH cohort was randomly assigned to the training set (n = 168) and the validation set I (n = 72) at a ratio of 7:3, while the SYSUTH cohort was allocated to the validation set II (n = 92). The correlation between the preoperative FISH assay and recurrence was determined through the Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was used for model construction. The performance of the model was assessed by its discrimination, calibration, and clinical usefulness. RESULTS: We uncovered that chromosome 7 aneuploidy, p16 locus loss, number of the positive FISH sites, and the FISH test result were significantly associated with tumor recurrence. Then, a FISH-clinical nomogram incorporating the FISH test result, T stage, associated CIS, tumor grade, and tumor status was developed. It showed favorable calibration and discrimination with a C-index of 0.683 (95%CI, 0.611-0.756) in the training set, which was confirmed in the validation set I and validation set II with C-indexes of 0.665 (95%CI, 0.565-0.765) and 0.778 (95%CI, 0.665-0.891), respectively. Decision curve analysis revealed the clinical usefulness of the nomogram. Moreover, our proposed nomogram significantly outperformed the guideline-recommended EORTC and CUETO scoring models. CONCLUSION: Our study confirmed the prognostic value of the preoperative FISH assay and proposed a FISH-clinical nomogram to predict RFS in NMIBC patients. Our nomogram can serve as a more precise tool for recurrence risk stratification, which may optimize disease management in bladder cancer and improve patient prognosis.

Different types of milk consumption and the risk of dementia: Analysis from a large-scale cohort study.

BACKGROUND & AIMS: Previous studies have investigated whether milk consumption has a role in preventing the development of cognitive impairment, but the results were inconsistent. Importantly, most of them have disregarded the role of different types of milk. This study aimed to examine the associations between different types of milk consumption and the risk of dementia. METHODS: In this large-scale cohort study, participants without cognitive impairment at baseline were included from the UK Biobank. The type of milk mainly used was self-reported at baseline, including full-cream milk, skimmed-milk, soy milk, other milk, and no milk. The primary outcome was all-cause dementia. Secondary outcomes included Alzheimer's disease and vascular dementia. RESULTS: Of the 307,271 participants included in the study (mean age 56.3 [SD 8.1] years), 3789 (1.2%) incident all-cause dementia cases were observed over a median follow-up of 12.3 years. After adjustment for potential confounders, only soy milk consumers had a statistically significantly lower risk of all-cause dementia compared with no milk consumers (hazard ratio [HR], 0.69; 95% confidence interval [CI], 0.54 to 0.90). When compared with soy milk non-consumers consisting of full-cream milk, skimmed-milk, and other milk consumers, soy milk consumers still showed a lower risk of all-cause dementia (HR, 0.76; 95% CI, 0.63 to 0.92), and there was no significant interaction with genetic risk for dementia (P for interaction = 0.15). Soy milk consumers showed a lower risk of Alzheimer's disease (HR, 0.70; 95% CI, 0.51 to 0.94; P = 0.02), while the association was not significant for vascular dementia (HR, 0.72; 95% CI, 0.47 to 1.12; P = 0.14). CONCLUSIONS: The main consumption of soy milk was associated with a lower risk of dementia, particularly non-vascular dementia. Additional studies are needed to investigate how this association varies with the dose or frequency of the consumption of soy milk and to examine the generalizability of these findings in different populations.

The normal reference values and estimation formulae of renal structural parameters in Chinese children based on large-sample CT data.

Purpose: Our aim was to investigate the normal reference value and to establish an estimation formulae for renal structural parameters (RSPs) based on large-sample CT data of Chinese children, which can provide a data reference for the clinical assessment of kidney development and diseases in Chinese children. Materials and Methods: A total of 438 children aged 0-17 years with normal renal CT images and basic indices were continuously collected. The bilateral RSP, including renal length (RL), renal width (RW), renal thickness (RT), renal volume (RV), renal cortical thickness (RCT), renal artery diameter (RAD) and renal CT value, were measured. Kendall's rank correlation was used to analyze the correlation between RSP and sex. Pearson's correlation was used to analyze the correlation between RSP and age, height and weight. Differences in the RSP of bilateral kidneys were analyzed via a paired samples t-test. Multiple linear regression was used to analyze the multivariate relationships between RSP and basic indices and establish the estimation formula of RSP. Results: The RSP of normal kidneys showed a dynamic increasing trend with age, except for the CT values. The reference value ranges (95% confidence interval) of normal RSP for each age group were determined. Pearson correlation analysis demonstrated strong correlations between RSP (RL, RW, RT, RV, RCT and, RAD) and basic indices (age, height and, weight), with height exhibiting the greatest correlation coefficient, followed by age or weight. Kendall's analysis showed that none of the RSPs were correlated with sex. The RL, RW, RV and RAD of the left kidney were larger than those of the right kidney, and the RT and RCT of the right kidney exhibited opposite results. Multiple linear regression analysis demonstrated a significant linear relationship between the RSP (RL, RW, RT, RV and, RCT) and the variables of the basic indices. The estimation formulae for calculating the RSP were established. Conclusion: This is the first Chinese study to report of the trends, normal reference values and estimation formulae of normal RSP based on large-sample CT data. These results can provide data references for assessing adequate kidney growth or disease damage in Chinese children.

Association of earlier age at menopause with risk of incident dementia, brain structural indices and the potential mediators: a prospective community-based cohort study.

Background: To date, there is no homogeneous evidence of whether earlier age at menopause is associated with incident dementia. In addition, the underlying mechanism and driven mediators are largely unknown. We aimed to fill these knowledge gaps. Methods: This community-based cohort study included 154,549 postmenopausal women without dementia at enrolment (between 2006 and 2010) from the UK Biobank who were followed up until June 2021. We followed up until June 2021. Age at menopause was entered as a categorical variable (<40, 40-49, and ≥50 years) with ≥50 years taken as a reference. The primary outcome was all-cause dementia in a time-to-event analysis and the secondary outcomes included Alzheimer's disease, vascular dementia, and other types of dementia. In addition, we investigated the association between magnetic resonance (MR) brain structure indices with earlier menopause, and explored the potential underlying driven mediators on the relationship between earlier menopause and dementia. Findings: 2266 (1.47%) dementia cases were observed over a median follow-up period of 12.3 years. After adjusting for confounders, women with earlier menopause showed a higher risk of all-cause dementia compared with those ≥50 years (adjusted-HRs [95% CIs]: 1.21 [1.09-1.34] and 1.71 [1.38-2.11] in the 40-49 years and <40 years groups, respectively; P for trend <0.001). No significant interactions between earlier menopause and polygenic risk score, cardiometabolic factors, type of menopause, or hormone-replacement therapy strata were found. Earlier menopause was negatively associated with brain MR global and regional grey matter indices, and positively associated with white matter hyperintensity. The relationship between earlier menopause and dementia was partially mediated by menopause-related comorbidities including sleep disturbance, mental health disorder, frailty, chronic pain, and metabolic syndrome, with the proportion (95% CI) of mediation effect being 3.35% (2.18-5.40), 1.38% (1.05-3.20), 5.23% (3.12-7.83), 3.64% (2.88-5.62) and 3.01% (2.29-4.40), respectively. Multiple mediator analysis showed a combined effect being 13.21% (11.11-18.20). Interpretation: Earlier age at menopause was associated with risk of incident dementia and deteriorating brain health. Further studies are warranted to clarify the underlying mechanisms by which earlier age at menopause is linked to an increased risk of dementia, and to determine public health strategies to attenuate this association. Funding: National Natural Science Foundation of China, the Science and Technology Program of Guangzhou, the Key Area Research and Development Program of Guangdong Province, the China Postdoctoral Science Foundation, and the Guangdong Basic and Applied Basic Research Foundation.

A radiomics model for predicting the response to methylprednisolone in brain necrosis after radiotherapy for nasopharyngeal carcinoma.

BACKGROUND: Methylprednisolone is recommended as the front-line therapy for radiation-induced brain necrosis (RN) after radiotherapy for nasopharyngeal carcinoma. However, some patients fail to benefit from methylprednisolone or even progress. This study aimed to develop and validate a radiomic model to predict the response to methylprednisolone in RN. METHODS: Sixty-six patients receiving methylprednisolone were enrolled. In total, 961 radiomic features were extracted from the pre-treatment magnetic resonance imagings of the brain. Least absolute shrinkage and selection operator regression was then applied to construct the radiomics signature. Combined with independent clinical predictors, a radiomics model was built with multivariate logistic regression analysis. Discrimination, calibration and clinical usefulness of the model were assessed. The model was internally validated using 10-fold cross-validation. RESULTS: The radiomics signature consisted of 16 selected features and achieved favorable discrimination performance. The radiomics model incorporating the radiomics signature and the duration between radiotherapy and RN diagnosis, yielded an AUC of 0.966 and an optimism-corrected AUC of 0.967 via 10-fold cross-validation, which also revealed good discrimination. Calibration curves showed good agreement. Decision curve analysis confirmed the clinical utility of the model. CONCLUSIONS: The presented radiomics model can be conveniently used to facilitate individualized prediction of the response to methylprednisolone in patients with RN.

Progress in Brain Magnetic Resonance Imaging of Individuals with Prader-Willi Syndrome.

Prader-Willi syndrome (PWS), a rare epigenetic disease mapping the imprinted chromosomal domain of 15q11.2-q13.3, manifests a regular neurodevelopmental trajectory in different phases. The current multimodal magnetic resonance imaging (MRI) approach for PWS focues on morphological MRI (mMRI), diffusion MRI (dMRI) and functional MRI (fMRI) to uncover brain alterations. This technique offers another perspective to understand potential neurodevelopmental and neuropathological processes of PWS, in addition to specific molecular gene expression patterns, various clinical manifestations and metabolic phenotypes. Multimodal MRI studies of PWS patients demonstrated common brain changes in the volume of gray matter, the integrity of the fiber tracts and the activation and connectivity of some networks. These findings mainly showed that brain alterations in the frontal reward circuit and limbic system were related to molecular genetics and clinical manifestations (e.g., overwhelming eating, obsessive compulsive behaviors and skin picking). Further exploration using a large sample size and advanced MRI technologies, combined with artificial intelligence algorithms, will be the main research direction to study the structural and functional changes and potential pathogenesis of PWS.

A phase 2 study of thalidomide for the treatment of radiation-induced blood-brain barrier injury.

Radiation-induced brain injury (RIBI) is a debilitating sequela after radiotherapy to treat head and neck cancer, and 20 to 30% of patients with RIBI fail to respond to or have contraindications to the first-line treatments of bevacizumab and corticosteroids. Here, we reported a Simon's minmax two-stage, single-arm, phase 2 clinical trial (NCT03208413) to assess the efficacy of thalidomide in patients with RIBI who were unresponsive to or had contraindications to bevacizumab and corticosteroid therapies. The trial met its primary endpoint, with 27 of 58 patients enrolled showing ≥25% reduction in the volume of cerebral edema on fluid-attenuated inversion recovery-magnetic resonance imaging (FLAIR-MRI) after treatment (overall response rate, 46.6%; 95% CI, 33.3 to 60.1%). Twenty-five (43.1%) patients demonstrated a clinical improvement based on the Late Effects Normal Tissues-Subjective, Objective, Management, Analytic (LENT/SOMA) scale, and 36 (62.1%) experienced cognitive improvement based on the Montreal Cognitive Assessment (MoCA) scores. In a mouse model of RIBI, thalidomide restored the blood-brain barrier and cerebral perfusion, which were attributed to the functional rescue of pericytes secondary to elevation of platelet-derived growth factor receptor ß (PDGFRß) expression by thalidomide. Our data thus demonstrate the therapeutic potential of thalidomide for the treatment of radiation-induced cerebral vasculature impairment.

Microglia drive transient insult-induced brain injury by chemotactic recruitment of CD8+ T lymphocytes.

The crosstalk between the nervous and immune systems has gained increasing attention for its emerging role in neurological diseases. Radiation-induced brain injury (RIBI) remains the most common medical complication of cranial radiotherapy, and its pathological mechanisms have yet to be elucidated. Here, using single-cell RNA and T cell receptor sequencing, we found infiltration and clonal expansion of CD8+ T lymphocytes in the lesioned brain tissues of RIBI patients. Furthermore, by strategies of genetic or pharmacologic interruption, we identified a chemotactic action of microglia-derived CCL2/CCL8 chemokines in mediating the infiltration of CCR2+/CCR5+ CD8+ T cells and tissue damage in RIBI mice. Such a chemotactic axis also participated in the progression of cerebral infarction in the mouse model of ischemic injury. Our findings therefore highlight the critical role of microglia in mediating the dysregulation of adaptive immune responses and reveal a potential therapeutic strategy for non-infectious brain diseases.

Corpus Callosum Volumes in Children with Autism Spectrum Disorders: Sex-Associated Differences.

This study aimed to analyze the relationship between sex and corpus callosum (CC) volume in children with autism spectrum disorders (ASD) aged 2-4 years. This prospective study included 50 children with ASD and 50 typically developing (TD) children aged 2-4 years. Midsagittal slices of the CCs of the participants were divided into five subregions using FreeSurfer software. The PMCC, AMCC and TCC volumes were significantly higher in ASD participants than in TD participants, and results were significant in females with ASD rather than in males with ASD (all P < 0.05). In toddlers with ASD, the CC volumes were increased and more pronounced in females than in males. This could be due to overgrowth of axons or/and axonal pruning disorders.