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Despite advances in risk-stratified treatment strategies for children with medulloblastoma (MB), the prognosis for MB with short-term recurrence is extremely poor, and there is still a lack of evaluation of short-term recurrence risk or short-term survival. This study aimed to construct and validate a radiomics model for predicting the outcome of MB based on preoperative multiparametric magnetic resonance images (MRIs) and to provide an objective for clinical decision-making. The clinical and imaging data of 64 patients with MB admitted to Shenzhen Children's Hospital from December 2012 to December 2021 and confirmed by pathology were retrospectively collected. According to the 18-month progression-free survival, the cases were classified into a good prognosis group and a poor prognosis group, and all cases were divided into training group (70%) and validation group (30%) randomly. Radiomics features were extracted from MRI of each child. The consistency test, t -test, and the least absolute shrinkage and selection operator were used for feature selection. The support vector machine (SVM) and receiver operator characteristic were used to evaluate the distinguishing ability of the selected features to the prognostic groups. RAD score was calculated based on the selected features. The clinical characteristics and RAD score were included in the multivariate logistic regression, and prediction models were constructed by screening out independent influences. The radiomics nomogram was constructed, and its clinical significance was evaluated. A total of 1930 radiomic features were extracted from the images of each patient, and 11 features were included in the construction of radiomics score after selected. The area under the curve (AUC) values of the SVM model in the training and validation groups were 0.946 and 0.797, respectively. The radiomics nomogram was constructed based on the training cohort, and the AUC values in the training group and the validation group were 0.926 and 0.835, respectively. The results of clinical decision curve analysis showed that a good net benefit could be obtained from the nomogram. The radiomics nomogram established based on MRI can be used as a noninvasive predictive tool to evaluate the prognosis of children with MB, which is expected to help neurosurgeons better conduct preoperative planning and patient follow-up management. [ABSTRACT FROM AUTHOR]

• fALFF was first used to evaluate the brain function of ALL pre- and post-induction. • fALFF values decreased globally in the ALL pre-induction patients. • fALFF values normalized to baseline in the ALL after induction chemotherapy. Our previous study revealed altered resting-stated brain function in children with acute lymphoblastic leukemia (ALL) on new-onset stage. To investigate the effects after induction chemotherapy, a pilot self-contrast study was conducted to compare the difference in resting-stated brain function between pre- and post-induction chemotherapy of ALL. Fractional amplitude of low-frequency fluctuation (fALFF) was employed for fMRI data analysis. Clinical and resting state functional magnetic resonance imaging (RS-fMRI) data of 14 new-onset pediatric ALL patients were collected before and after 3 months of induction chemotherapy. Fourteen age- and gender-matched healthy controls (HCs) were recruited for comparison. Before induction chemotherapy, fALFF values of ALL patients decreased globally, especially in the default mode network (DMN), left frontal lobe, left occipital lobe, and bilateral postcentral gyri as compared to HCs. After induction chemotherapy, fALFF values of ALL patients decreased significantly in the bilateral cuneus, left lingual and calcarine gyri, and left mid frontal gyrus. Paired-sample t -tests and self-contrast analysis showed fALFF increased in the left precuneus, bilateral cuneus, left occipital lobe, bilateral frontal gyri, and bilateral temporal lobes, whereas fALFF in the bilateral precuneus decreased in the ALL patients after induction, which suggests potential side-effects of the treatment. The alteration of fALFF values suggested that resting brain function was impaired before induction chemotherapy and mostly recovered after treatment. This study suggested that fALFF is a reliable and feasible tool in detecting spontaneous brain activity to monitor early neurocognitive impairments in pediatric ALL to better understand the underlying neurobiological mechanisms of chemotherapy on the brain. [ABSTRACT FROM AUTHOR]

Infantile epileptic spasms syndrome (IESS) would accompany with severe neurological impairment. Our study aimed to explore the potential mechanism by employing voxel-based and surface-based morphometry to detect brain microwould accompany with severe neurological impairment. Our study aimed to explore the potential mechanism by employing voxel-based and surface-based morphometry to detect brain microanatomic structure alteration. The IESS group had 21 males and 13 females (mean age: 17.7 ± 15.6 months), whereas the healthy controls group had 22 males and 10 females (mean age: 29.4 ± 18.7 months). High-resolution 3D T1WI was performed. Computational Anatomy Toolbox implemented in Statistical Parametric Mapping 12 was used to measure the gray matter and white matter volume, and the cortical thickness separately. Independent sample t test was used to assess between-group differences. IESS group was assessed using the Bayley Scales of Infant Development. The IESS group showed a significantly decreased volume of gray matter in right middle temporal gyrus, inferior temporal gyrus, superior temporal gyrus, right fusiform, and bilateral precuneus (P < 0.001). There were no significant between-group differences with respect to white matter volume or cortical thickness (P > 0.001). The results of Bayley Scales of Infant Development showed that the Mental Development Index (MDI) and Psychomotor Development Index scores of children with IESS were almost concentrated in the range of <70. MDI score showed a positive correlation with gray matter reduction area in IESS group. Children with IESS had impaired cognitive and delayed motor development. And the decreased gray matter in the right temporal lobe, fusiform, and bilateral precuneus could be the potential anatomic basis for impaired function, such as hearing, visual, and language. [ABSTRACT FROM AUTHOR]

Pilocytic astrocytoma (PA) is the most common primary brain tumor in children and adolescents. Treatment strategy largely depends on its key genes and molecular mutations. This study aimed to identify potential biomarkers of PA closely related to its prognosis. The gene expression profiles (series numbers GSE50161, GSE66354, and GSE86574) of PA and normal brain tissues were downloaded from the Gene Expression Omnibus database. The Gene Expression Omnibus2R was used to identify differentially expressed genes. The overlapping differentially expressed genes were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. A protein-protein interaction network was constructed using Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. The Gene Expression Profiling Interactive Analysis 2 (GEPIA2) tool analyzed the impact of hub genes on PA prognosis based on the Kaplan–Meier curves. Compared with normal brain tissues (n = 36), a total of 37 upregulated and 144 downregulated genes were identified in PA (n = 40). In the protein-protein interaction network construction and GEPIA2 survival analysis, 2 of the top 10 hub genes were significantly associated with decreased overall survival of PA patients, namely Gamma-aminobutyric acid A receptor alpha 2 (hazard ratio = 2.8, P < 0.01) and regulating synaptic membrane exocytosis protein 1) (hazard ratio = 3.2, P < 0.01). This bioinformatics analysis reveals that low expression of Gamma-aminobutyric acid A receptor alpha 2 and regulating synaptic membrane exocytosis protein 1 is associated with a favorable prognosis for PA patients. These 2 hub genes could be novel biomarkers for prognosis assessment, furthermore a key element for treatment decisions in the future. [ABSTRACT FROM AUTHOR]

Cerebral palsy (CP) is a neurological disorder caused by cerebral ischemia and hypoxia during fetal brain development. Early intervention in CP patients has a favorable impact on medications and therapy; however, challenges are associated with early age development, potential recovery, and neuroimaging sensitivity. Previously, the main focus was given on early diagnosis, brain injury characterization, and neurodevelopmental outcomes in infants; however, it is inevitable to study the brain developmental patterns in health controls (HC) and CP children. This study elaborates on the effects of aging on the brains of infants with HC and CP, age ranging from a few months and 17 years using deep learning (DL). The introduced DL-based models, namely SCT-DL and MCT-DL, trained on single contrast MRI (SC-MRI) and coupling of multi-contrast (MC-MRI) to learn vulnerable brain regions associated to brain development. The proposed models are equipped with fully-convolutional-based attention mechanism leveraging average pooling operation, directly passing salient features, parallel partial computing unit, specialized parameter sharing module, fusion, and spatial-channel attention with traversal placement to learn and associate brain development accurately. In addition, the study reports optimal SC-MRI and MC-MRI deeply associated with CP vulnerabilities and association to brain development. The SCT-DL outperformed the counterpart models with accumulative MAE = 1.73 (C 1 1 C denotes HC and P denotes CP. = 1.61 and P = 1.63) underlying T1-w, where the MCT-DL is the improved version of SCT-DL and the prediction accuracy reached to MAE = 1.08 (C = 1.01 and P = 1.12) over the coupling of T1-w ⊕ Sagittal. The trained models result in unmatching and distinct learning patterns for healthy and CP patients. Notably, the age-wise brain development-based results deduce a significance in age association at an early age (around two years) and poor at a later age. The study findings will assist neurodevelopmental processing and clinical practices in radiomics without concerning infants' uncooperative movement or MRI artifacts. • Delving into the intricate process of brain age development in children. • Proposal of specialized DL models for learning brain age developmental process. • Selection of appropriate SC-MRI and coupling for brain age development. • Uncovering trends susceptible in children's brain development with CP. • Revealing the patterns that fluctuate mostly across different ages. [ABSTRACT FROM AUTHOR]

Benign childhood epilepsy with centrotemporal spikes (BECTS), a common pediatric epilepsy, may lead to cognitive decline when compounded by Electrical Status Epilepticus during Sleep (ESES). Emerging evidence suggests that disruptions in the Salience Network (SN) contribute significantly to the cognitive deficits observed in BECTS-ESES. Our study rigorously investigates the dynamic functional connectivity (dFC) within the SN and its correlation with cognitive impairments in BECTS-ESES, employing advanced neuroimaging and neuropsychological assessments. In this research, 45 patients diagnosed with BECTS-ESES and 55 age-matched healthy controls (HCs) participated. We utilized resting-state functional magnetic resonance imaging (fMRI) and Independent Component Analysis (ICA) to identify three fundamental SN nodes: the right Anterior Insula (rAI), left Anterior Insula (lAI), and the Anterior Cingulate Cortex (ACC). A two-sample t -test facilitated the comparison of dFC between these pivotal regions and other brain areas. Significantly, the BECTS-ESES group demonstrated increased dFC, particularly between the ACC and the right Middle Occipital Gyrus, and from the rAI to the right Superior Parietal Gyrus and Cerebellum, and from the lAI to the left Postcentral Gyrus. Such dFC augmentations provide neural insights potentially explaining the neuropsychological deficits in BECTS-ESES children. Employing comprehensive neuropsychological evaluations, we mapped these dFC disruptions to specific cognitive impairments encompassing memory, executive functioning, language, and attention. Through multiple regression analysis and path analysis, a preliminary but compelling association was discovered linking dFC disturbances directly to cognitive impairments. These findings underscore the critical role of SN disruptions in BECTS-ESES cognitive dysfunctions. Our cross-sectional design and analytic methods preclude definitive mediation models and causal inferences, leaving the precise nature of dFC's mediating role and its direct impact by BECTS-ESES partially unresolved. Future longitudinal and confirmatory studies are needed to comprehensively delineate these associations. Our study heralds dFC within the SN as a vital biomarker for cognitive impairment in pediatric epilepsy, advocating for targeted cognitive-specific interventions in managing BECTS-ESES. The preliminary nature of our findings invites further studies to substantiate these associations, offering profound implications for the prognosis and therapeutic strategies in BECTS-ESES, thereby underlining the importance of this research in the field of pediatric neurology and epilepsy management. • Utilized a cross-sectional case-control design to compare children diagnosed with BECTS-ESES to neurotypical HCs. • Help elucidate the complex relationships between the SN's dynamic functional interactions and the cognitive and behavioral profiles of affected children. [ABSTRACT FROM AUTHOR]

Objective Cognitive impairments had been reported in childhood acute lymphoblastic leukemia, what caused the impairments needed to be demonstrated, chemotherapy-related or the disease itself. The primary aim of this exploratory investigation was to determine if there were changes in brain function of children with acute lymphoblastic leukemia before chemotherapy. Methods In this study, we advanced a measure named regional homogeneity to evaluate the resting-state brain activities, intelligence quotient test was performed at same time. Using regional homogeneity, we first investigated the resting state brain function in patients with new onset childhood acute lymphoblastic leukemia before chemotherapy, healthy children as control. Results The decreased ReHo values were mainly founded in the default mode network and left frontal lobe, bilateral inferior parietal lobule, bilateral temporal lobe, bilateral occipital lobe, precentral gyrus, bilateral cerebellum in the newly diagnosed acute lymphoblastic leukemia patients compared with the healthy control. While in contrast, increased ReHo values were mainly shown in the right frontal lobe (language area), superior frontal gyrus-R, middle frontal gyrus-R and inferior parietal lobule-R for acute lymphoblastic leukemia patients group. There were no significant differences for intelligence quotient measurements between the acute lymphoblastic leukemia patient group and the healthy control in performance intelligence quotient, verbal intelligence quotient, total intelligence quotient. Conclusion The altered brain functions are associated with cognitive change and language, it is suggested that there may be cognition impairment before the chemotherapy. Regional homogeneity by functional magnetic resonance image is a sensitive way for early detection on brain damage in childhood acute lymphoblastic leukemia. [ABSTRACT FROM AUTHOR]