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Purpose: Diffuse gliomas present a significant challenge for healthcare systems globally. While brain MRI plays a vital role in diagnosis, prognosis, and treatment monitoring, accurately characterizing gliomas using conventional MRI techniques alone is challenging. In this study, we explored the potential of utilizing the amide proton transfer (APT) technique to predict tumor grade and type based on the WHO 2021 Classification of CNS Tumors. Methods: Forty-two adult patients with histopathologically confirmed brain gliomas were included in the study. They underwent 3T MRI imaging, which involved APT sequence. Multinomial and binary logistic regression models were employed to classify patients into clinically relevant groups based on MRI findings and demographic variables. Results: We found that the best model for tumor grade classification included patient age along with APT values. The highest sensitivity (88%) was observed for Grade 4 tumors, while Grade 3 tumors showed the highest specificity (79%). For tumor type classification, our model incorporated four predictors: APT values, patient's age, necrosis, and the presence of hemorrhage. The glioblastoma group had the highest sensitivity and specificity (87%), whereas balanced accuracy was the lowest for astrocytomas (0.73). Conclusion: The APT technique shows great potential for noninvasive evaluation of diffuse gliomas. The changes in the classification of gliomas as per the WHO 2021 version of the CNS Tumor Classification did not affect its usefulness in predicting tumor grade or type. [ABSTRACT FROM AUTHOR]

Brain gliomas, common in adults, pose significant diagnostic challenges. Accurate segmentation from multimodal magnetic resonance imaging (MRI) scans is critical for effective treatment planning. Traditional manual segmentation methods, labor‐intensive and error‐prone, often lead to inconsistent diagnoses. To overcome these limitations, our study presents a sophisticated framework for the automated segmentation of brain gliomas from multimodal MRI images. This framework consists of three integral components: a 3D UNet, a classifier, and a Classifier Weight Transformer (CWT). The 3D UNet, acting as both an encoder and decoder, is instrumental in extracting comprehensive features from MRI scans. The classifier, employing a streamlined 1 × 1 convolutional architecture, performs detailed pixel‐wise classification. The CWT integrates self‐attention mechanisms through three linear layers, a multihead attention module, and layer normalization, dynamically refining the classifier's parameters based on the features extracted by the 3D UNet, thereby improving segmentation accuracy. Our model underwent a two‐stage training process for maximum efficiency: in the first stage, supervised learning was used to pre‐train the encoder and decoder, focusing on robust feature representation. In the second stage, meta‐training was applied to the classifier, with the encoder and decoder remaining unchanged, ensuring precise fine‐tuning based on the initially developed features. Extensive evaluation of datasets such as BraTS2019, BraTS2020, BraTS2021, and a specialized private dataset (ZZU) underscored the robustness and clinical potential of our framework, highlighting its superiority and competitive advantage over several state‐of‐the‐art approaches across various segmentation metrics in training and validation sets. [ABSTRACT FROM AUTHOR]

To study the predictive value of Dynamic contrast-enhanced scanning-magnetic resonance examination(DCE-MRI) quantitative parameters combined with neutrophil-lymphocyte radio (NLR) and monocyte lymphocyte ratio (MLR) in theprognosis of brain glioma patients. 130 brain glioma patients who received treatment in our hospital from January 2020 to June2022 were selected as the observation objects. All patients were treated with radiotherapy after brain glioma resection. According to theprognosis evaluation, it was divided into good prognosis group (n=48) and poor prognosis group (n=82). Compare DCE-MRI quantitativeparameters, NLR and MLR in two groups; Unvariate and multivariate analysis of the factors affecting poor patient outcomes; The predictive value of the DCE-MRI quantitative parameters combined with NLR and MLR was analyzed using the receiver operating characteristic (ROC) curve. There was no loss to follow-up at 1 year, and the levels of transport constant (Ktrans), extravascular space vol-ume percentage (Ve), NLR and MLR in the poor prognosis group were significantly higher than those in the good prognosis group (P＜ 0.05). The proportion of age, tumor grade Ⅲ ~ Ⅳ, low differentiation and postoperative radiotherapy in the poor prognosis group werehigher than those in the good prognosis group (P＜0.05), and the Karnofsky Performance Status (KPS) score was lower than that in thegood prognosis group(P＜0.05). Univariate and multivariate Logistic regression analysis found that the factors associated with poor prognosis included Ktrans, Ve, NLR and MLR (P＜0.05). The ROC curve analysis found that found that DCE-MRI quantitative parameters Ktrans, Ve combined with NLR and MLR had the highest predictive value for patients with poor prognosis, the area under the curve(AUC) was 0.874, and the sensitivity was 95.21%, which was significantly higher than the results of other individual tests. NLR, MLLR and DCE-MRI quantitative parameters are abnormally elevated in glioma patients with poor prognosis, with three combinations can improve the predictive value in the prognosis of brain glioma patients, and it is worth promoting and applying in clinical diagnosis. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to investigate the activation of the C-X-C chemokine receptor type 4 (CXCR4)/Akt signaling pathway in the peripheral blood of individuals diagnosed with brain glioma and assess its potential as a predictive marker.

Background: Accurate segmentation of brain glioma is a critical prerequisite for clinical diagnosis, surgical planning and treatment evaluation. In current clinical workflow, physicians typically perform delineation of brain tumor subregions slice‐by‐slice, which is more susceptible to variabilities in raters and also time‐consuming. Besides, even though convolutional neural networks (CNNs) are driving progress, the performance of standard models still have some room for further improvement. Purpose: To deal with these issues, this paper proposes an attention‐guided multi‐scale context aggregation network (AMCA‐Net) for the accurate segmentation of brain glioma in the magnetic resonance imaging (MRI) images with multi‐modalities. Methods: AMCA‐Net extracts the multi‐scale features from the MRI images and fuses the extracted discriminative features via a self‐attention mechanism for brain glioma segmentation. The extraction is performed via a series of down‐sampling, convolution layers, and the global context information guidance (GCIG) modules are developed to fuse the features extracted for contextual features. At the end of the down‐sampling, a multi‐scale fusion (MSF) module is designed to exploit and combine all the extracted multi‐scale features. Each of the GCIG and MSF modules contain a channel attention (CA) module that can adaptively calibrate feature responses and emphasize the most relevant features. Finally, multiple predictions with different resolutions are fused through different weightings given by a multi‐resolution adaptation (MRA) module instead of the use of averaging or max‐pooling to improve the final segmentation results. Results: Datasets used in this paper are publicly accessible, that is, the Multimodal Brain Tumor Segmentation Challenges 2018 (BraTS2018) and 2019 (BraTS2019). BraTS2018 contains 285 patient cases and BraTS2019 contains 335 cases. Simulations show that the AMCA‐Net has better or comparable performance against that of the other state‐of‐the‐art models. In terms of the Dice score and Hausdorff 95 for the BraTS2018 dataset, 90.4% and 10.2 mm for the whole tumor region (WT), 83.9% and 7.4 mm for the tumor core region (TC), 80.2% and 4.3 mm for the enhancing tumor region (ET), whereas the Dice score and Hausdorff 95 for the BraTS2019 dataset, 91.0% and 10.7 mm for the WT, 84.2% and 8.4 mm for the TC, 80.1% and 4.8 mm for the ET. Conclusions: The proposed AMCA‐Net performs comparably well in comparison to several state‐of‐the‐art neural net models in identifying the areas involving the peritumoral edema, enhancing tumor, and necrotic and non‐enhancing tumor core of brain glioma, which has great potential for clinical practice. In future research, we will further explore the feasibility of applying AMCA‐Net to other similar segmentation tasks. [ABSTRACT FROM AUTHOR]

Brain glioma is a common gynecological tumor. MicroRNA (miRNA) plays a very important role in the pathogenesis and development of tumors. It was found that glycolysis played important regulatory roles in tumor growth. The present study aims to investigate the expression pattern of miR-21-5p in brain glioma cells. We examined miR-21-5p and PFKFB2 levels in brain glioma cells via qRT-PCR. Then we performed CCK-8 and Transwell migration assays and determined glucose uptake and lactose production to unveil the properties of miR-21-5p in invasion, cell viability, along with glycolysis in brain glioma cells. Luciferase activity assay was implemented to elucidate if PFKFB2 was a miR-21-5p target gene. Western blotting and qRT-PCR were executed to further validate that miR-21-5p targeted PFKFB2. We repeated these functional assays to observe whether miR-21-5p could impede the function of PFKFB2. qRT-PCR signified that miR-21-5p was elevated in brain glioma tissues in contrast to matching adjacent normal tissues. Functional assays disclosed that elevation of miR-21-5p promoted cell viability, invasion, together with glycolysis. Luciferase assay indicated that PFKFB2 was a miR-21-5p target gene. Moreover, miR-21-inhibit could hinder cell viability, invasion, and glycolysis triggered by overexpression of PFKFB2 in brain glioma cells. miR-21-5p level is elevated in brain glioma and can impede brain glioma cell growth via regulating the glycolysis mediated by PFKFB2, thus is a potential target of treating brain glioma. [ABSTRACT FROM AUTHOR]

Abstract Background Differentiation between the grades of brain gliomas is a crucial step in the management of patients. The gold standard technique for grading is biopsy but MR imaging may play a more substantial role as a non-invasive method by using promising molecular sequences. Our purpose was to assess the added value of the relative amide proton transfer signal [rAPT] to advanced multiparametric MRI protocol. Methods We enrolled a pathologically confirmed 102 patients with low-grade glioma [n = 38] and high-grade glioma [n = 64] who underwent advanced multiparametric MRI protocol on the same scanner. The protocol included anatomic, diffusion, MRS, and perfusion sequences. The newly added sequence was Amide proton transfer. The rAPT values of all lesions were investigated by two neuroradiologists to assess the inter-rater agreement of using interclass correlation coefficient [ICC]. HGGs demonstrated significantly higher mean values of relative cerebral blood volume (rCBV), choline to creatine ratio (Cho/cr), and rAPT with lower Apparent diffusion coefficient (ADC) values compared to LGGs. ROC analyses revealed medium to high diagnostic performance with an AUC of 0.941 for rAPT, 0.907 for mean ADC, and 0.906 for rCBV. Discriminant function analysis of two models, the first one included mean ADC, rCBV, and Cho/Cr, while in the second Model, we added rAPT to them. Model two demonstrated higher accuracy and a significant difference in the AUC after adding the rAPT. The inter-rater agreement was reasonable (ICC 0.61). Conclusions rAPT adds significant value to multiparametric MRI for distinguishing LGG from HGG.

Objective To explore the effect of magnetic resonance imaging （MRI） and contrast enhanced ultrasound （CEUS） in the grading diagnosis of glioma. MethodsA retrospective analysis was performed on the patients without glioma （control group, n=94） and with glioma （observation group, n=96） treated in No. 215 Hospital of Shaanxi Nuclear Industry from April 2017 to April 2022. All patients received CEUS and MRI examinations before surgery. Time to peak （TTP）, mean transit time （mTT）, pure water diffusion coefficient （D）, perfusion fraction （f） and quantitative indicators were compared between two groups. During six months after operation, 29 cases of residual tumor were found by histopathology examination. ResultsIn observation group, TTP, D, f were statistically higher than those in control group, mTT was lower than that in control group （P ＜ 0.05）. Compared with those in the patients with low-grade tumor, TTP, D and f increased significantly, and mTT decreased in the patients with high-grade tumor （P ＜ 0.05）. ROC curve analysis showed that the AUCs of TTP, mTT, D, f and joint prediction for glioma grading were 0.849, 0.839, 0.914, 0.893 and 0.971, respectively. ConclusionCEUS combined with MRI has a higher efficiency in predicting the grade of glioma and postoperative residual tumors, which can provide a scientific basis for prognosis evaluation.

Background: Differentiation between the grades of brain gliomas is a crucial step in the management of patients. The gold standard technique for grading is biopsy but MR imaging may play a more substantial role as a non-invasive method by using promising molecular sequences. Our purpose was to assess the added value of the relative amide proton transfer signal [rAPT] to advanced multiparametric MRI protocol. Methods: We enrolled a pathologically confirmed 102 patients with low-grade glioma [n = 38] and high-grade glioma [n = 64] who underwent advanced multiparametric MRI protocol on the same scanner. The protocol included anatomic, diffusion, MRS, and perfusion sequences. The newly added sequence was Amide proton transfer. The rAPT values of all lesions were investigated by two neuroradiologists to assess the inter-rater agreement of using interclass correlation coefficient [ICC]. HGGs demonstrated significantly higher mean values of relative cerebral blood volume (rCBV), choline to creatine ratio (Cho/cr), and rAPT with lower Apparent diffusion coefficient (ADC) values compared to LGGs. ROC analyses revealed medium to high diagnostic performance with an AUC of 0.941 for rAPT, 0.907 for mean ADC, and 0.906 for rCBV. Discriminant function analysis of two models, the first one included mean ADC, rCBV, and Cho/Cr, while in the second Model, we added rAPT to them. Model two demonstrated higher accuracy and a significant difference in the AUC after adding the rAPT. The inter-rater agreement was reasonable (ICC 0.61). Conclusions: rAPT adds significant value to multiparametric MRI for distinguishing LGG from HGG. [ABSTRACT FROM AUTHOR]

Understanding the key factors in the tumor microenvironment (TME) that affect the prognosis of gliomas is crucial. In this study, we sought to uncover the prognostic significance of immune cells and immune-related genes in the TME of gliomas. We incorporated data of 970 glioma patient samples from the Chinese Glioma Genome Atlas (CGGA) database as the training set, and an additional set of 666 samples from The Cancer Genome Atlas (TCGA) database served as the validation set. From our analysis, we identified 21 immune-related differentially expressed genes (DEGs) in the TME, which holds implications for glioma prognosis. Based on these genes, we constructed a prognostic risk model on the 21 genes. The prognostic risk model demonstrated robust performance with an area under the curve (AUC) value of 0.848. Notably, the risk score derived from the model emerged as an independent prognostic factor of gliomas, with high risk scores indicative of an unfavorable prognosis. Furthermore, we observed that high infiltration levels of certain immune cells, namely, activated dendritic cells, M0 macrophages, M2 macrophages, and regulatory T cells (Tregs), correlated with an unfavorable glioma prognosis. In conclusion, our findings suggested that the TME of gliomas harbored a distinct immune-associated signature, comprising 21 immune-related genes and specific immune cells. These elements significantly influence the prognosis and present potential as novel indicators in the clinical assessment of glioma patient outcomes. [ABSTRACT FROM AUTHOR]

Purpose The aim of this study was to evaluate the role of permeability surface area product in grading brain gliomas using computed tomography (CT) perfusion Materials and Methods CT perfusion was performed on 33 patients with brain glioma diagnosed on magnetic resonance imaging. Of these, 19 had high-grade glioma and 14 had low-grade glioma on histopathological follow-up. CT perfusion values were obtained and first compared between the tumor region and normal brain parenchyma. Then the relative values of perfusion parameters were compared between high- and low-grade gliomas. Cut-off values, sensitivity, specificity, and strength of agreement for each parameter were calculated and compared subsequently. A conjoint factor (permeability surface area product + cerebral blood volume) was also evaluated since permeability surface area product and cerebral blood volume are considered complimentary factors for tumor vascularity. Results All five perfusion parameters namely permeability surface area product, cerebral blood volume, cerebral blood flow, mean transit time, and time to peak were found significantly higher in the tumor region than normal brain parenchyma. Among these perfusion parameters, only relative permeability surface area product and relative cerebral blood volume were found significant in differentiating high- and low-grade glioma. Moreover, relative permeability surface area product was significantly better than all other perfusion parameters with highest sensitivity and specificity (97.74 and 100%, respectively, at a cut-off of 9.0065). Relative permeability surface area product had a very good agreement with the histopathology grade. The conjoint factor did not yield any significant diagnostic advantage over permeability surface area product. Conclusion Relative permeability surface area product and relative cerebral blood volume were helpful in differentiating high- and low-grade glioma; however, relative permeability surface area product was significantly better than all other perfusion parameters. Grading brain gliomas using relative permeability surface area product can add crucial value in their management and prognostication; hence, it should be evaluated in the routine CT perfusion imaging protocol. [ABSTRACT FROM AUTHOR]

To investigate the biodistribution and micro-PET imaging of 68Ga labeled fibroblast activation protein inhibitor (68Ga-FAPI-04) in normal mice and glioma nude mice, 68Ga-FAPI-04 was synthesized using DOTA-modified fibroblast activation protein inhibitor as precursor. The synthesis yield, radiochemical purity and in vitro stability were analyzed by radio-HPLC, and the hydrophilicity of 68Ga-FAPI-04 was evaluated by lipo-hydro partition coefficient. Twenty ICR mice were randomly divided into 5 groups. 3.7 MBq of 68Ga-FAPI-04 was injected by tail vein per mouse, then the mice were killed at 5, 15, 30, 60, 120 min post-injection(pi.). The main organs and tissues were collected and weighed, then the radioactivity was measured, and the uptake of each tissue or organ was calculated. The nude mice bearing U87MG glioma model were established, then the biodistribution study and micro-PET imaging were performed. The results indicate that the synthesis yield of 68Ga-FAPI-04 was (97.38±1.32)% (n=3), the radiochemical purity was 100%，and the in vitro stability and hydrophilicity were good. The biodistribution study of normal-ICR mice showed that 68Ga-FAPI-04 was cleared from blood rapidly and mainly excreted from kidneys, and the radioactivity uptake in brain was low. The biodistribution and micro-PET of U87MG tumor-bearing nude mice showed high radioactivity at the tumor targets. The uptake of 68Ga-FAPI-04 at the tumor targets reached (2.50±0.00)%ID/g at 90 min pi. The tumor-to-background ratios (TBRs) were（6.26±0.09）, （5.06±0.02）, （5.54±1.47） and （5.51±0.03） at 30, 60, 90 and 120 min pi., respectively. The preliminary studies indicate that 68Ga-FAPI-04 is synthesized easily with high yields, and is stable in vitro. The radiotracer was mainly excreted from kidneys, and targeting tumor targets with clear images in micro-PET of glioma models. Therefore, 68Ga-FAPI-04 might be a potential brain tumor imaging agent.

Liquid biopsy techniques based on deep sequencing of plasma cell‐free DNA (cfDNA) could detect the low‐frequency somatic mutations and provide an accurate diagnosis for many cancers. However, for brain gliomas, reliable performance of these techniques currently requires obtaining cfDNA from patients' cerebral spinal fluid, which is cumbersome and risky. Here we report a liquid biopsy method based on sequencing of plasma cfDNA fragments carrying 5‐hydroxymethylcytosine (5hmC) using selective chemical labeling (hMe‐Seal). We first constructed a dataset including 180 glioma patients and 229 non‐glioma controls. We found marked concordance between cfDNA hydroxymethylome and the aberrant transcriptome of the underlying gliomas. Functional analysis also revealed overrepresentation of the differentially hydroxymethylated genes (DhmGs) in oncogenic and neural pathways. After splitting our dataset into training and test cohort, we showed that a penalized logistic model constructed with training set DhmGs could distinguish glioma patients from healthy controls in both our test set (AUC = 0.962) and an independent dataset (AUC = 0.930) consisting of 111 gliomas and 111 controls. Additionally, the DhmGs between gliomas with mutant and wild‐type isocitrate dehydrogenase (IDH) could be used to train a cfDNA predictor of the IDH mutation status of the underlying tumor (AUC = 0.816), and patients with predicted IDH mutant gliomas had significantly better outcome (P =.01). These results indicate that our plasma cfDNA 5hmC sequencing method could obtain glioma‐specific signals, which may be used to noninvasively detect these patients and predict the aggressiveness of their tumors. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to investigate the impact of valproic acid (VPA) on survival and prognosis of patients with glioma who underwent postoperative radiotherapy. Methods: We obtained the case data with brain glioma who underwent postoperative radiotherapy from January 2012 to December 2019. This cohort was heterogeneous. We conducted single-factor analysis and multiple-factors analysis of the basic features, pathological classification, therapies of all 185 patients using Kaplan-Meier survival curve, log-rank survival significance test, and Cox regression analysis model. Results: By the end of the last follow-up, 94 patients had died and 96 had recurred in all 185 cases. The median follow-up time of this study was 47 months. The median overall survival (OS) and progression-free survival (PFS) times were 34 and 27 months, respectively. The 1-, 3-, and 5-year OS rates were 86.49%, 48.11%, and 14.60%, respectively. The 1-, 3-, and 5-year PFS rates were 80.00%, 43.78%, and 12.97%, respectively. Univariate analysis revealed that age, pathological grade, and VPA administration were all associated with patients' prognosis (p < 0.05). A Cox multivariate analysis revealed that being 47 years or older, having a high pathological grade (WHO grades III and IV), and not taking VPA were all adverse prognostic factors for OS and PFS in patients with glioma. Conclusion: Age, pathological grade, and VPA administration are the influencing factors for the prognosis of glioma patients with postoperative radiotherapy. Patients with glioma who received VPA had a more favorable prognosis and a lower recurrence rate. [ABSTRACT FROM AUTHOR]

The epidermal growth factor receptor (EGFR) plays a pivotal role in tumor progression and is an essential therapeutic target for treating malignant gliomas. Small interfering RNA (siRNA) has the potential to selectively degrade EGFR mRNA, yet its clinical utilization is impeded by various challenges, such as inefficient targeting and limited escape from lysosomes. Our research introduces polyethylene glycol (PEG) and endoplasmic reticulum membrane-coated siEGFR nanoplexes (PEhCv/siEGFR NPs) as an innovative approach to brain glioma therapy by overcoming several obstacles: 1) Tumor-derived endoplasmic reticulum membrane modifications provide a homing effect, facilitating targeted accumulation and cellular uptake; 2) Endoplasmic reticulum membrane proteins mediate a non-degradable "endosome-Golgi-endoplasmic reticulum" transport pathway, circumventing lysosomal degradation. These nanoplexes demonstrated significantly enhanced siEGFR gene silencing in both in vitro and in vivo U87 glioma models. The findings of this study pave the way for the advanced design and effective application of nucleic acid-based therapeutic nanocarriers. [Display omitted] • Polyethylene glycol and endoplasmic reticulum membrane-coated siEGFR nanoplexes-for brain glioma therapy. • A non-degradable "endosome-Golgi-Endoplasmic reticulum" transport pathway to evade the lysosomal degradation. • siEGFR downregulate EGFR protein to inhibit the growth of brain glioma. [ABSTRACT FROM AUTHOR]

Background: Most brain gliomas are high-grade and likely to spread locally. Consequently, these patients commonly have a poor prognosis. Accurate identification of the malignancy grade of brain glioma before treatment is of great clinical significance. Objectives: This study aimed to explore the correlation of diffusion tensor imaging (DTI) parameters, fractional anisotropy (FA), and apparent diffusion coefficient (ADC) with the pathological grade of brain glioma and expression of vascular endothelial growth factor (VEGF) and Ki-67. Patients and Methods: A total of 116 patients were selected for this study from January 2018 to December 2019. All the participants underwent magnetic resonance imaging (MRI) and DTI before surgery, and the FA and ADC values were measured for the regions of interest. Surgically resected tumor specimens were collected for immunohistochemical assay. Finally, the FA and ADC values and positive expression rates of VEGF and Ki-67 were compared. Results: A significantly higher FA, besides the positive expression of VEGF and Ki-67, was reported in the high-grade group, whereas a lower ADC was found in this group compared to the low-grade group (P < 0.05). Areas of normal white matter and peritumoral edema had higher FA values, whereas lower ADCs were measured in these areas compared to the cerebrospinal fluid (P < 0.05). The FA of tumor parenchymal area was positively correlated with theWorld Health Organization (WHO)WHOclass of tumors (r = 0.588, P = 0.028), and the expression of VEGF and Ki-67 was positively correlated with the WHO grade (r = 0.843, P = 0.002 and r = 0.743, P = 0.006, respectively). The FA of tumor parenchymal area was positively correlated with the expression of VEGF and Ki-67 (r = 0.654, P = 0.008 and r = 0.567, P = 0.012, respectively). However, the ADC of tumor parenchymal area was not significantly correlated with the WHO grade, VEGF expression, or Ki-67 expression (r = 0.143, P = 0.156, r = 0.232, P = 0.116, and r = 0.054, P = 0.179, respectively). Conclusion: The FA value, as a DTI parameter, is valuable for assessing the malignancy grade of tumor cells and can provide a proper reference for formulating treatment regimens for brain gliomas. [ABSTRACT FROM AUTHOR]

Purpose: Artificial intelligence (AI), in particular deep neural networks, has achieved remarkable results for medical image analysis in several applications. Yet the lack of explainability of deep neural models is considered the principal restriction before applying these methods in clinical practice. Methods: In this study, we propose a NeuroXAI framework for explainable AI of deep learning networks to increase the trust of medical experts. NeuroXAI implements seven state-of-the-art explanation methods providing visualization maps to help make deep learning models transparent. Results: NeuroXAI has been applied to two applications of the most widely investigated problems in brain imaging analysis, i.e., image classification and segmentation using magnetic resonance (MR) modality. Visual attention maps of multiple XAI methods have been generated and compared for both applications. Another experiment demonstrated that NeuroXAI can provide information flow visualization on internal layers of a segmentation CNN. Conclusion: Due to its open architecture, ease of implementation, and scalability to new XAI methods, NeuroXAI could be utilized to assist radiologists and medical professionals in the detection and diagnosis of brain tumors in the clinical routine of cancer patients. The code of NeuroXAI is publicly accessible at https://github.com/razeineldin/NeuroXAI. [ABSTRACT FROM AUTHOR]

In the field of histopathology, many studies on the classification of whole slide images (WSIs) using artificial intelligence (AI) technology have been reported. We have studied the disease progression assessment of glioma. Adult-type diffuse gliomas, a type of brain tumor, are classified into astrocytoma, oligodendroglioma, and glioblastoma. Astrocytoma and oligodendroglioma are also called low grade glioma (LGG), and glioblastoma is also called glioblastoma multiforme (GBM). LGG patients frequently have isocitrate dehydrogenase (IDH) mutations. Patients with IDH mutations have been reported to have a better prognosis than patients without IDH mutations. Therefore, IDH mutations are an essential indicator for the classification of glioma. That is why we focused on the IDH1 mutation. In this paper, we aimed to classify the presence or absence of the IDH1 mutation using WSIs and clinical data of glioma patients. Ensemble learning between the WSIs model and the clinical data model is used to classify the presence or absence of IDH1 mutation. By using slide level labels, we combined patch-based imaging information from hematoxylin and eosin (H & E) stained WSIs, along with clinical data using deep image feature extraction and machine learning classifier for predicting IDH1 gene mutation prediction versus wild-type across cohort of 546 patients. We experimented with different deep learning (DL) models including attention-based multiple instance learning (ABMIL) models on imaging data along with gradient boosting machine (LightGBM) for the clinical variables. Further, we used hyperparameter optimization to find the best overall model in terms of classification accuracy. We obtained the highest area under the curve (AUC) of 0.823 for WSIs, 0.782 for clinical data, and 0.852 for ensemble results using MaxViT and LightGBM combination, respectively. Our experimental results indicate that the overall accuracy of the AI models can be improved by using both clinical data and images., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Application of Bayesian recognition procedures to the analysis of inflammatory processes in gliomas is considered. Parameters of protein structures of blood plasma in gliomas, metastases, and concussion, obtained by a laser spectrograph, are analyzed. A comparative analysis is carried out for the results of recognition, on the basis of protein structures, by the measurements of surface plasmon resonance and modified erythrocyte sedimentation rate in gliomas. [ABSTRACT FROM AUTHOR]

Computed tomography (CT) images of the brain aid the radiotherapy of glioma. The identification and contouring of the gross tumor volume (GTV) are important for radiotherapy. However, manual segmenting GTV is time-consuming, exhausting, and subjective, and automated methods are desired. To overcome these shortcomings, a novel neural network framework based on multi-view fusion is proposed to segment GTV in brain glioma automatically. The multi-view image that includes the previous image, current image, and following image is inputted in this framework to abstract extra spatial features and then aggregated to segment the GTV. Compared with the 2D segmentation framework, the proposed framework retains more spatial information due to the multi-view image. Meanwhile, compared with the 3D segmentation framework, the proposed framework considers fewer images, which means the model has fewer parameters and is easier to train while retaining much useful spatial information. Moreover, the GliomaCT dataset, a large CT dataset collected from West China Hospital, is used to train, validate, and test the proposed method. The performance of the proposed method and other state-of-the-art methods are compared on this dataset. The high dice similarity coefficient achieved in the experiments demonstrates the effectiveness of the proposed method for segmenting the GTV in brain glioma. [ABSTRACT FROM AUTHOR]

Abstract Background Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted diagnosis for the brain tumor diagnosis is still the problem because the rough segmentation of the brain tumor makes the internal grade of the tumor incorrect. Methods In this paper, we proposed an Aggregation-and-Attention Network for brain tumor segmentation. The proposed network takes the U-Net as the backbone, aggregates multi-scale semantic information, and focuses on crucial information to perform brain tumor segmentation. To this end, we proposed an enhanced down-sampling module and Up-Sampling Layer to compensate for the information loss. The multi-scale connection module is to construct the multi-receptive semantic fusion between encoder and decoder. Furthermore, we designed a dual-attention fusion module that can extract and enhance the spatial relationship of magnetic resonance imaging and applied the strategy of deep supervision in different parts of the proposed network. Results Experimental results show that the performance of the proposed framework is the best on the BraTS2020 dataset, compared with the-state-of-art networks. The performance of the proposed framework surpasses all the comparison networks, and its average accuracies of the four indexes are 0.860, 0.885, 0.932, and 1.2325, respectively. Conclusions The framework and modules of the proposed framework are scientific and practical, which can extract and aggregate useful semantic information and enhance the ability of glioma segmentation.

Huang Y, Liu W, Gao F, Fang X, Chen Y. Int J Nanomedicine. 2016;11:1629–1641. The Editor and Publisher of the International Journal of Nanomedicine wish to retract the published article. Concerns were raised regarding the alleged duplication of an image in Figure 8B with the same image from Figure 10 in Chen et al, 2015 ‘The therapeutic effect of methotrexate-conjugated Pluronic-based polymeric micelles on the folate receptor-rich tumors treatment’ (https://doi.org/10.2147/IJN.S79045). Figure 8B, Heart, Saline appears to have been duplicated with the same image from Figure 10, Heart, F127/P105/MTX in Chen et al, 2015. The authors responded to our queries and explained that the animal experimental work for both studies was performed at the same time. It was possible an error was made during the arrangement of the H&E images for the respective figures from both articles. However, given the length of time that has passed since the completion of these studies the authors were no longer able to retrieve the original data. To help maintain the integrity of the scientific record the authors agreed with the decision to retract the article. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”.

• Multi-scale fusion gene identification network was first proposed to enhance the accuracy of IDH1 mutation prediction. • Different scales of histopathological images were fully exploited to extract context feature representation for accurate detection of IDH1 gene mutations. • The proposed MultiGeneNet significantly outperforms other single-scale methods on the clinical collection of H&E stained histopathological dataset. Mutations in isocitrate dehydrogenase 1 (IDH1) play a crucial role in the prognosis, diagnosis, and treatment of gliomas. However, current methods for determining its mutation status, such as immunohistochemistry and gene sequencing, are difficult to implement widely in routine clinical diagnosis. Recent studies have shown that using deep learning methods based on pathological images of glioma can predict the mutation status of the IDH1 gene. However, our research focuses on utilizing multi-scale information in pathological images to improve the accuracy of predicting IDH1 gene mutations, thereby providing an accurate and cost-effective prediction method for routine clinical diagnosis. In this paper, we propose a multi-scale fusion gene identification network (MultiGeneNet). The network first uses two feature extractors to obtain feature maps at different scale images, and then by employing a bilinear pooling layer based on Hadamard product to realize the fusion of multi-scale features. Through fully exploiting the complementarity among features at different scales, we are able to obtain a more comprehensive and rich representation of multi-scale features. Based on the Hematoxylin and Eosin stained pathological section dataset of 296 patients, our method achieved an accuracy of 83.575 % and an AUC of 0.886, thus significantly outperforming other single-scale methods. Our method can be deployed in medical aid systems at very low cost, serving as a diagnostic or prognostic tool for glioma patients in medically underserved areas. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To systematically evaluate the clinical efficacy of using fluorescein sodium injection to guide surgical resection of glioma. METHODS: PubMed, Embase, CNKI, VIP, CBM and Wanfang Data were retrieved to collect the randomized controlled trials(RCT) of efficacy of fluorescein sodium injection-guided surgical resection of glioma. The retrieval time was from the establishment of the database to Apr. 2021. Meta-analysis was performed on RCT that met the quality standards, and RevMan 5. 2 was used for statistical analysis. RESULTS: A total of 6 RCT with 333 patients were included. During the routine microsurgical resection of glioma in the observation group, the tumor tissue was stained by intravenous injection of sodium fluorescein injection, and the tumor boundary was judged according to the intensity of the fluorescent staining to perform tumor resection; the control group was resected by conventional microsurgery glioma. Meta-analysis showed that the total resection rate of glioma in the observation group was significantly higher than that in the control group ( OR = 5. 51, 95% CI = 3. 28-9. 24, P<0. 000 01), the recurrence rate of glioma in the observation group after surgery was significantly lower than that in the control group (OR = 0. 30,95%CI = 0. 15-0. 60,P = 0. 000 6), with statistically significant differences. There were no significant differences in the average duration of surgery and average length of stay between two groups (P>0. 05). CONCLUSIONS: Compared with conventional microsurgery, fluorescein sodium injection-guided surgical resection of glioma has a higher total tumor resection rate and a lower postoperative tumor recurrence rate. [ABSTRACT FROM AUTHOR]

Objective To study the effects of immunological markers glial fibrillary acidic protein (GFAP) and proliferation index (Ki67) on the results of immunohistochemical staining in glioma specimens due to different fixation times, and to explore the difference in the positive expression of GFAP and Ki67.The difference in the positive expression of GFAP and Ki67. Methods Seventy-one cases of brain glioma specimens with tumor diameter≥2 cm were collected during Jan 2018 to Dec 2019 in Jing’an District Central Hospital of Shanghai. Six tumor tissues of 1 cm×1 cm×0.2 cm were taken from each specimen.They were fixed in 4% formaldehyde for 4 hours, 24 hours, 48 hours, 96 hours, 7 days and 14 days. Immunohistochemical staining of GFAP and Ki67 was performed to compare the effects of different fixation time on the valid positive rates of GFAP and Ki67. Results After 4-hour, 24-hour, 48-hour, 96- hour, 7-day and 14-day fixation of glioma specimens, the valid positive rates of GFAP were 63.38%, 97.18%, 95.77%, 92.95%, 90.14% and 77.46% with the statistically significant difference（χ² =51.802, P<0.001), and the valid positive rates of Ki67 were 87.32%, 100%, 100%, 100%, 98.59% and 90.14% with the statistically significant difference（χ² =30.45, P<0.001). There was no significant difference in the valid positive rates of GFAP and Ki67 in the groups fixed for 24 hours, 48 hours, 96 hours and 7 days. Conclusion Fixation time had influence on the immunohistochemical staining results of GFAP and Ki67 in brain glioma specimens, and the staining results of fixation for 24 hours, 48 hours, 96 hours and 7 days were better than those for 4 hours and 14 days. [ABSTRACT FROM AUTHOR]

Objective: To study the relationship between serum hyalonectin (VTN), insulin-like growth factor binding protein (IGFBP), ubiquitin-coupled enzyme 2C (UBE2C) levels and clinicopathological characteristics and prognosis in patients with brain glioma. Methods: A total of 97 patients with glioma admitted to the first affiliated hospital of Xinjiang medical university from January 2019 to January 2020 were included as the study group, and 90 healthy volunteers who underwent physical examination in the hospital during the same period were included as the control group. In addition, all the study group researchers were followed up for 1 year, and they were divided into the death group (40 cases) and the survival group (57 cases) according to the difference in follow-up outcomes. Serum VTN, IGFBP and UBE2C levels were detected and compared in each group, and the relationship between serum VTN, IGFBP and UBE2C levels and clinicopathological features and prognosis of glioma patients was analyzed. The efficacy of serum VTN, IGFBP and UBE2C levels in predicting the death of glioma patients was analyzed by receiver operating characteristic (ROC) curve. Results: The serum VTN, IGFBP and UBE2C levels in the study group were higher than those in the control group (all P<0.05). Serum VTN and IGFBP levels in patients with brain glioma with tumor size ≥5 cm, world health organization (WHO) classification Ⅲ ~ Ⅳ grade and Karnofsky functional status (KPS) score < 70 scores were higher than those in patients with brain glioma with tumor size < 5 cm, WHO classification Ⅰ～Ⅱ grade and KPS score ≥70 scores (all P<0.05). The serum UBE2C level of patients with brain glioma with WHO classification Ⅲ～Ⅳ grade and KPS score < 70 scores were higher than that of patients with brain glioma with WHO classification Ⅰ～Ⅱ grade and KPS score ≥70 scores (all P<0.05). Serum VTN, IGFBP and UBE2C levels in the death group were higher than those in the survival group (all P<0.05). ROC curve analysis showed that the area under the curve, sensitivity, specificity and Youden index of the combined detection of serum VTN, IGFBP and UBE2C levels in predicting the death of patients with brain glioma were all higher than those of the above three indexes alone. Conclusion: There are abnormally high levels of SERUM VTN, IGFBP and UBE2C in glioma patients, which are related to the progression of tumor malignancies. Combined detection may be beneficial to predict the prognosis of patients. [ABSTRACT FROM AUTHOR]

Objective: Oncometabolite D-2-hydroxyglutarate (2HG) is pooled in isocitrate dehydrogenase (IDH)-mutant glioma cells. Detecting 2HG by MR spectroscopy (MRS) has been proven viable in the last decade but has not entirely found its way into the clinical routine. This study aimed to explore the adoption of 2HG MRS while acknowledging factors that influence its performance in the clinical environment. Methods: Thirty-nine MR spectra were acquired and reported prospectively in patients with suspected glioma using a 3 T system with Mescher–Garwood point-resolved spectroscopy (MEGA-PRESS) sequence utilizing averaged free induction decay (FID) signals. Postprocessing and evaluation of spectra were performed with jMRUI and LCModel. 2HG concentration estimates, 2HG/Cr ratio, together with quality measures, including Cramér–Rao lower bounds (CRLBs), full-width at half-maximum (FWHM) values, and signal-to-noise ratio (SNR) were calculated using LCModel. Immunohistochemistry and genomic analysis results used as a ground truth were available for 15 patients. Results: The threshold for test positivity was set according to the ROC curve at 1 mM. Calculated sensitivity was 57.14% (95% CI 0.20–0.88), specificity 87.5% (95% CI 0.46–0.99), positive predictive value 80%, and negative predictive value 70%. Overall diagnostic accuracy was 73.33% (95% CI 0.45–0.92). The 2HG/Cr ratio with the cutoff value 0.085 significantly improved sensitivity and overall diagnostic accuracy [85.71%, 95% CI 0.42–1.00 and 86.67%, (95% CI 0.60–0.98), respectively]. Conclusion: Multiple factors compromising spectral quality in the clinical adoption of edited 2HG MRS resulted in diminished sensitivity but clinically acceptable specificity. Furthermore, the 2HG/Cr ratio performs better than the sole 2HG concentration estimate in the pre-operative setting. [ABSTRACT FROM AUTHOR]

Robot-assisted brain tumor biopsy is becoming one of the most important innovative technologies in neurosurgical practice. The idea behind its engagement is to advance the safety and efficacy of the biopsy procedure, which is much in demand when planning the management of endocranial tumor pathology. Herein, we provide our earliest institutional experiences in utilizing this mesmerizing technology. Cranial robotic device was employed for stereotactic robot-assisted brain glioma biopsy in three consecutive patients from our series: an anaplastic isocitrate dehydrogenase (IDH) negative astrocytoma (WHO grade III) located in the right trigone region of the periventricular white matter; a low grade diffuse astrocytoma (WHO grade II) of bilateral thalamic region spreading into the right mesencephalic area; and an IDH-wildtype glioblastoma (WHO grade IV) of the right frontal lobe producing a contralateral midline shifting. Robot-assisted tumor biopsy was successfully performed to get tissue samples for histopathologic and immunohistochemical analysis. The adjacent tissue iatrogenic damage of the eloquent cortical areas was minimal, while the immediate postoperative recovery was satisfactory in all patients. In conclusion, considering the preliminary results of our early experiences, robot-assisted tumor biopsy was proven to be a feasible and accurate procedure when surgery for brain glioma was not an option. It may increase safety and precision, without expanding surgical time, being similarly effective when compared to standard stereotactic and manual biopsy. Using this method to provide accurate sampling for histopathologic and immunohistochemical analysis is a safe and easy way to determine management strategies and outcome of different types of brain glioma.

Brain glioma is the most common primary tumour of the central nervous system. Complete surgical removal of the brain glioma is virtually impossible. Chemotherapy is still an important treatment for brain glioma. However, blood–brain barrier (BBB) and vasculogenic mimicry (VM) channels remain two hindrances in regular treatments. Herein, we developed a novel nanoscaled dual targeting daunorubicin plus rofecoxib liposomes which could transport across the BBB, and eliminate brain glioma cells along with the VM channels. The liposomes were modified with two functional materials, and showed round in shape with a diameter about 120 nm. Evaluations were performed on human brain glioma U87MG cells in vitro and on intracranial brain glioma-bearing nude mice. The dual targeting liposomes demonstrated a long circulatory effect in the blood system, were able to transport across the BBB, and were accumulated into the brain. The results indicated that the dual targeting daunorubicin plus rofecoxib liposomes could inhibit the brain glioma VM channels and exhibited a significant efficacy in the treatment of intracranial glioma-bearing nude mice. The mechanisms are related to down regulations MMP-2, MMP-9, FAK and HIF-α. Hence, the established dual targeting liposomes could be a potential formulation to treat the brain glioma along with eliminating VM channels.

Objectives: To explore the effectiveness and safety of the combined application of sodium fluorescein and neuronavigation techniques in the resection of brain gliomas in different locations and patients of different ages. Methods: Fifty clinical cases of brain gliomas treated at the Department of Neurosurgery of Beijing Tiantan Hospital were collected from March 2014 to March 2019. These cases were divided into a supratentorial group (24 cases) and a brainstem group (26 cases) based on location and an adult group (28 cases) and a pediatric group (22 cases) based on age. Fluorescein-guided surgery was performed: the adult group received 5 mg/kg sodium fluorescein before opening the dura, while the pediatric group received 2.5 mg/kg during resection. Tumor visualization was evaluated by the enhancement of yellow fluorescein and considered "satisfactory" if the illumination demarcated the tumor boundary. Additionally, the consistency between fluorescein and neuronavigation was analyzed. The Karnofsky performance score (KPS) of all patients was recorded and assessed at admission, discharge, and the 6-month follow-up. Results: In the 28 adult cases, 4 were unsatisfactory, while in the 22 pediatric cases, 2 were unsatisfactory; in 7 cases, there was an inconsistency between yellow fluorescein enhancement and neuronavigation, 6 were in the supratentorial group, and 1 was in the brainstem group. Statistical analysis showed no significant differences in the satisfactory rate between the adult and pediatric groups (P = 0.575), whereas there were significant differences inconsistency between the supratentorial group and brainstem group (P = 0.031). The mean KPS at admission was between 70 and 100, which was not significantly different from that at discharge (P = 0.839), but the KPS at the 6-month follow-up was significantly higher than that at admission (P = 0.041). Conclusions: The consistency between sodium fluorescein and the neuronavigation system was higher in the brainstem group than in the supratentorial group; a half dose of sodium fluorescein (2.5 mg/kg) was sufficient for pediatric patients. The combined utilization of sodium fluorescein and neuronavigation techniques may confer glioma patients the opportunity to obtain better clinical outcomes after surgery. [ABSTRACT FROM AUTHOR]

Brain glioma is the most common primary tumour of the central nervous system. Complete surgical removal of the brain glioma is virtually impossible. Chemotherapy is still an important treatment for brain glioma. However, blood–brain barrier (BBB) and vasculogenic mimicry (VM) channels remain two hindrances in regular treatments. Herein, we developed a novel nanoscaled dual targeting daunorubicin plus rofecoxib liposomes which could transport across the BBB, and eliminate brain glioma cells along with the VM channels. The liposomes were modified with two functional materials, and showed round in shape with a diameter about 120 nm. Evaluations were performed on human brain glioma U87MG cells in vitro and on intracranial brain glioma-bearing nude mice. The dual targeting liposomes demonstrated a long circulatory effect in the blood system, were able to transport across the BBB, and were accumulated into the brain. The results indicated that the dual targeting daunorubicin plus rofecoxib liposomes could inhibit the brain glioma VM channels and exhibited a significant efficacy in the treatment of intracranial glioma-bearing nude mice. The mechanisms are related to down regulations MMP-2, MMP-9, FAK and HIF-α. Hence, the established dual targeting liposomes could be a potential formulation to treat the brain glioma along with eliminating VM channels. [ABSTRACT FROM AUTHOR]

Shanqiang Qu,1,* Shuting Li,2,* Zhicheng Hu3 1Department of Neurosurgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, People’s Republic of China; 2Department of Plastic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, People’s Republic of China; 3Department of Burn Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhicheng HuDepartment of Burn Surgery, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, People’s Republic of ChinaTel +86-20-87755766-8235Fax +86-20-87755766-8276Email huzhch5@mail.sysu.edu.cnShanqiang QuDepartment of Neurosurgery, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, People’s Republic of ChinaTel +86-20-87755766-8215Fax +86-20-87755766-8276Email qushq3@163.comPurpose: Previous study reported that Piezo1 was highly expressed in glioma and promoted the proliferation of glioma cells, suggesting that Piezo1 overexpression might contribute to the poor prognosis of patients. Thus, this study aimed to identify whether Piezo1 may become a new prognostic biomarker for glioma patients.Patients and Methods: Firstly, Piezo1 expression of gliomas was analyzed through GEO and Oncomine dataset, and verified by qRT-PCR and immunohistochemistry (IHC) methods. A total of 183 glioma patients were included in this study between January 2010 and December 2014. Kaplan-Meier survival analyses, Cox regression analyses and ROC curve analyses were performed to assess the diagnostic and prognostic values of Piezo1 in glioma patients.Results: In this study, Piezo1 was identified to be highly expressed in gliomas, and increased with WHO grade. Chi-square test results showed that Piezo1 expression was significantly related to age (P=0.00), WHO grade (P=0.00), Histopathology (P=0.00), IDH1 mutation (P=0.00) and chemotherapy (P=0.00). Kaplan-Meier analysis showed that the overall survival (OS) of patients with high Piezo1 expression was significantly worse than that of patients with low Piezo1 expression (HR=3.39, 95% CI=2.40– 4.81, P< 0.0001). A multivariate Cox regression analysis revealed that Piezo1 might be an independent prognostic factor for glioma patients (HR=1.34, 95% CI=1.23– 1.47, P=0.000). The area under the ROC curve (AUC) of 1-, 3-, and 5-year overall survival for Piezo1 overexpression was 0.820 (P=0.000), 0.849 (P=0.000), and 0.861 (P=0.000), respectively.Conclusion: Piezo1 was overexpressed in glioma samples. Piezo1 overexpression as an independent prognostic factor adversely affects the prognosis of patients, which could be a new novel prognostic indicator in glioma patients.Keywords: novel prognostic indicator, Piezo1, brain glioma

Background: Glioma a common type of the brain tumor, which originates in the glial cells that surround and support neurons in the brain, including astrocytes, oligodendrocytes and ependymalcells. Objectives: This study is aiming to investigate the role of MRS in patients in diagnosis of brain glioma. Patients and methods: The study was designed as a cross-sectional study recruit 30 patients, who were referred to the Radio-diagnosis Department of South Valley University Hospitals for suspected glioma from neurosurgery department during the period from February 2018 to Aug 2021 the study protocol was approved by the local ethics committee of South valley University hospitals (Ref No Code Ms-4–2018, Date of approval 10–02-2018). and it was approved by the local Research Ethics Committee of our hospital. Results: The study included 30 patients with age ranged from six to 72 years old. The lesions within the repetitive tumor group had essentially higher Cho/Cr ratios than those within the radiation damage group (p < 0.0001; SE, 0.18), and these, also, had vitally higher Cho/Cr proportions than the typical white matter of 6 patients (p = 0.0003; SE, 0.09). In differentiating tumor versus non-tumor lesions, the sensitivity and specificity of Cho/NAA ratio greater than 2.0 was 96% and 70%, respectively. For ratios higher than 2.5, the sensitivity and specificity to detect tumors was 97% and 86%, respectively. Conclusion: MRS examination was greatly beneficial in differentiating neoplastic from non-neoplastic lesions and decrease for stereotactic brain biopsy. However, further studies are required to confirm the current evidence.

The objective of the study was the analysis and evaluation of patients` intellectual and memory impairments before and after resection of brain gliomaMaterial and methods. We performed the study of 30 patients with brain glioma. The diagnosis of the studied patients was based on clinical and laboratory data, data of radiation and instrumental methods of research. The analysis of patients` intellectual and memory impairments was carried out in the preoperative and early, late postoperative periods. The patients` age ranged from 25 to 65 years; the median age was 56.5 year. In the present study, we used the following tests: intelligence tests – Amthauer test (for persons under 60 years), Raven test; memory tests – 10 word memorization test, Wechsler memory scale.Results. We revealed regression of various memory (from 100 to 96.7 %) and intellectual disorders (from 20 to 3.3 %; p

Objectives: To explore the effectiveness and safety of the combined application of sodium fluorescein and neuronavigation techniques in the resection of brain gliomas in different locations and patients of different ages.Methods: Fifty clinical cases of brain gliomas treated at the Department of Neurosurgery of Beijing Tiantan Hospital were collected from March 2014 to March 2019. These cases were divided into a supratentorial group (24 cases) and a brainstem group (26 cases) based on location and an adult group (28 cases) and a pediatric group (22 cases) based on age. Fluorescein-guided surgery was performed: the adult group received 5 mg/kg sodium fluorescein before opening the dura, while the pediatric group received 2.5 mg/kg during resection. Tumor visualization was evaluated by the enhancement of yellow fluorescein and considered “satisfactory” if the illumination demarcated the tumor boundary. Additionally, the consistency between fluorescein and neuronavigation was analyzed. The Karnofsky performance score (KPS) of all patients was recorded and assessed at admission, discharge, and the 6-month follow-up.Results: In the 28 adult cases, 4 were unsatisfactory, while in the 22 pediatric cases, 2 were unsatisfactory; in 7 cases, there was an inconsistency between yellow fluorescein enhancement and neuronavigation, 6 were in the supratentorial group, and 1 was in the brainstem group. Statistical analysis showed no significant differences in the satisfactory rate between the adult and pediatric groups (P = 0.575), whereas there were significant differences inconsistency between the supratentorial group and brainstem group (P = 0.031). The mean KPS at admission was between 70 and 100, which was not significantly different from that at discharge (P = 0.839), but the KPS at the 6-month follow-up was significantly higher than that at admission (P = 0.041).Conclusions: The consistency between sodium fluorescein and the neuronavigation system was higher in the brainstem group than in the supratentorial group; a half dose of sodium fluorescein (2.5 mg/kg) was sufficient for pediatric patients. The combined utilization of sodium fluorescein and neuronavigation techniques may confer glioma patients the opportunity to obtain better clinical outcomes after surgery.

The effectiveness of photodynamic therapy (PDT) in treating brain gliomas is limited by the solubility of photosensitizers and the production of reactive oxygen species (ROS), both of which are influenced by the concentration of photosensitizers and catalyst active sites. In this study, we developed a controllable surface hydroxyl concentration for the photosensitizer CN11 to address its poor water solubility issue and enhance PDT efficacy in tumor treatment. Compared to pure g-C 3 N 4 (CN), CN11 exhibited 4.6 times higher hydrogen peroxide production under visible light, increased incidence of the n → π* electron transition, and provided more available reaction sites for cytotoxic ROS generation. These findings resulted in a 2.43-fold increase in photodynamic treatment efficacy against brain glioma cells. Furthermore, in vivo experiments conducted on mice demonstrated that CN11 could be excreted through normal cell metabolism with low cytotoxicity and high biosafety, effectively achieving complete eradication of tumor cells.

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Objective: To investigate the relationship between the expression levels of microRNA (miR)-211, miR-374 and miR-510 in glioma tissues and their clinicopathological features and prognosis. Methods: 83 patients with glioma who were treated in our hospital from August 2013 to August 2015 were selected as study subjects, and the normal brain tissue samples resected in our hospital due to brain trauma during the same period were selected as control samples. Fluorescence quantitative PCR was used to detect the expression levels of miR-211, miR-374 and miR-510. Kaplan-Meier method was used for survival analysis. Cox proportional hazard regression model was used to analyze the prognosis influencing factors. Results: Compared with normal brain tissue, the expression levels of miR-211 and miR-374 in brain glioma tissue were significantly decreased, and the expression level of miR-510 was significantly increased (P<0.05). The expressions of miR-211, miR-374 and miR-510 in glioma tissues were all correlated with WHO grading and Karnofsky performance status (KPS) score (P<0.05). The 5-year overall survival rate of patients with low expression of miR-211 and miR-374 were significantly lower than thaose of patients with high expression, and the 5-year overall survival rate of patients with low expression of miR-510 was significantly higher than that of patients with high expression (P<0.05). WHO grading, KPS score, miR-211, miR-374 and miR-510 expression were the prognosis influencing factors of patients with glioma (P<0.05). Conclusion: The expressions of miR-211 and miR-374 in glioma tissues are down-regulated, while the expressions of miR-510 are up-regulated. The expressions of miR-211, miR-374 and miR-510 are all related to WHO grading, KPS score and prognosis, detection of miR-211, mir-374 and mir-51 has certain clinical significance in the diagnosis and treatment of glioma. [ABSTRACT FROM AUTHOR]

Background: Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted diagnosis for the brain tumor diagnosis is still the problem because the rough segmentation of the brain tumor makes the internal grade of the tumor incorrect. Methods: In this paper, we proposed an Aggregation-and-Attention Network for brain tumor segmentation. The proposed network takes the U-Net as the backbone, aggregates multi-scale semantic information, and focuses on crucial information to perform brain tumor segmentation. To this end, we proposed an enhanced down-sampling module and Up-Sampling Layer to compensate for the information loss. The multi-scale connection module is to construct the multi-receptive semantic fusion between encoder and decoder. Furthermore, we designed a dual-attention fusion module that can extract and enhance the spatial relationship of magnetic resonance imaging and applied the strategy of deep supervision in different parts of the proposed network. Results: Experimental results show that the performance of the proposed framework is the best on the BraTS2020 dataset, compared with the-state-of-art networks. The performance of the proposed framework surpasses all the comparison networks, and its average accuracies of the four indexes are 0.860, 0.885, 0.932, and 1.2325, respectively. Conclusions: The framework and modules of the proposed framework are scientific and practical, which can extract and aggregate useful semantic information and enhance the ability of glioma segmentation. [ABSTRACT FROM AUTHOR]

Automated segmentation of brain glioma plays an active role in diagnosis decision, progression monitoring and surgery planning. Based on deep neural networks, previous studies have shown promising technologies for brain glioma segmentation. However, these approaches lack powerful strategies to incorporate contextual information of tumor cells and their surrounding, which has been proven as a fundamental cue to deal with local ambiguity. In this work, we propose a novel approach named Context-Aware Network (CANet) for brain glioma segmentation. CANet captures high dimensional and discriminative features with contexts from both the convolutional space and feature interaction graphs. We further propose context guided attentive conditional random fields which can selectively aggregate features. We evaluate our method using publicly accessible brain glioma segmentation datasets BRATS2017, BRATS2018 and BRATS2019. The experimental results show that the proposed algorithm has better or competitive performance against several State-of-The-Art approaches under different segmentation metrics on the training and validation sets. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the correlation between quantitative dynamic contrast- enhanced magnetic resonance imaging (DCE-MRI) and the expression of serum interleukin-10 (IL-10) and interleukin-12 (IL-12) in patients with glioma. In this study, 150 patients with glioma were included as the observation group, including 68 cases of low-grade glioma and 82 cases of high-grade glioma, as well as 100 healthy patients as control group. The serum IL-10 and IL-12 levels of the two groups were detected, and the observation group was given MRI dynamic contrast enhancement scan. Serum IL-10 and IL-12 in the observation group were significantly higher than those in the control group (P<0.05). In the observation group, the volume transport constant (Ktrans), rate constant (Ke) and extracellular volume fraction (Ve) of high-grade glioma patients were significantly higher than those of low-grade glioma patients (P<0.05). The serum IL-10 and IL-12 levels of patients with high-grade glioma in the observation group were significantly higher than those of patients with low-grade glioma (P<0.05). Ktrans was positively correlated with IL-10 and IL-12 (P<0.05). The area under the high grade ROC curve of Ktrans, Ke, Ve combined with IL-10 and IL-12 glioma was 0.954, which was significantly higher than that of other indexes (P<0.05). MRI parameter Ktrans is positively correlated with serum IL-10 and IL-12 in patients with glioma, and has certain application value in differentiating low-grade and high-grade gliomas. [ABSTRACT FROM AUTHOR]

Wu Xu,1 Guo-Qing Hu,1 Clive Da Costa,2 Jun-Hai Tang,3 Qing-Rui Li,4 Lei Du,5 Ya-Wen Pan,6 Sheng-Qing Lv31Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, People’s Republic of China; 2Adult Stem Cell Laboratory, The Francis Crick Institute, London NW1 1AT, UK; 3Department of Neurosurgery, Xinqiao Hospital, Third Military Medical University, Chongqing 400037, People’s Republic of China; 4Biobank of Institute of Pathology, Southwest Hospital, Third Military Medical University, Chongqing 400037, People’s Republic of China; 5Department of Neurosurgery, The 42nd Hospital of the Chinese People‘s Liberation Army, Leshan City, Sichuan 614100, People’s Republic of China; 6Department of Neurosurgery, The Second Hospital of Lanzhou University, Lanzhou 730030, People’s Republic of ChinaIntroduction: Brain glioma is the most common type of primary malignancy in the central nervous system (CNS), with high recurrence and mortality rate, especially glioblastoma (GBM). Recent evidence suggests a role for many long noncoding RNAs (lncRNAs) in the pathogenesis, proliferation, apoptosis, metastasis, and chemotherapeutic resistance of cancer cells. Although the functions of some lncRNAs in the occurrence and development of gliomas have been confirmed, detailed mechanisms of action are lacking. Furthermore, the biological roles of many other lncRNAs in glioma have not been reported at all.Methods: In this study, we identified a novel lncRNA, UBE2R2-AS1, which was dramatically downregulated in glioma compared with normal tissue, by performing microarray detection of six pairs of glioma samples and adjacent normal tissues. In vitro experiments demonstrated that UBE2R2-AS1 regulated glioma cell proliferation, apoptosis, and migration.Results: UBE2R2-AS1 acted as a competing endogenous RNA (ceRNA) to target Toll-like receptor 4 (TLR4) mRNA by binding to miR-877-3p. Furthermore, lncRNA UBE2R2-AS1 suppressed glioblastoma cell growth, migration, and invasion, as well as promoting cell apoptosis by targeting miR-877-3p/TLR4 directly.Conclusion: This information regarding UBE2R2-AS1 and its glioma-related molecular mechanisms will aid the future identification of new lncRNA-directed diagnostics and drug-targeting therapies.Keywords: apoptosis, brain glioma, lncRNA, miR-877-3p/TLR4, UBE2R2-AS1

Introduction: Gliomas are tumors of the supporting cells of the central nervous system. They have great heterogeneity in their clinical and pathological features as well as prognosis. There is paucity of glioma epidemiology data in Zimbabwe. We carried out a study to determine the landscape, presentation, and characteristics of brain gliomas in Zimbabwe. Materials and Methods: A prospective cross-sectional study was conducted in Zimbabwe over a 2 years period to determine descriptive epidemiological data with regards to demographic distribution, presentation, and tumor characteristics. Consecutive patients from across the country with brain gliomas were recruited in the study. Results: A total of 112 brain tumors were diagnosed histologically. Of these 43.8% (n = 49) were gliomas and hence recruited in the study. The mean age of study participants was 40.3 years (standard deviation = 23.1 years), range 3–83 years. Male to female ratio (M:F) was 1:1. The study population consisted of 14% caucasians (n = 7), 83.7% black (n = 41), and 2% (n = 1) were of mixed race. Eighty-six percent (n = 42) of participants were from urban areas. The most common presenting complaint was headache in 87.8% (n = 43). The majority (61.2%) presented with a Karnofsky score ≥70%. Astrocytomas were the most common gliomas constituting 57.1% (n = 28), followed by ependymomas and oligodendrogliomas being 8.1% (n = 4) each. There was no statistical difference in the hemisphere of the brain involved (P = 0.475). Eight percent of the population were HIV positive (n = 4). Age above 60 years has an adjusted odds ratio of 13 for presenting with high-grade tumors. Conclusion: There is a disproportionately high number of gliomas among Caucasians, urban dwellers, and those gainfully employed. The prevalence of HIV in glioma patients is less than that of the general population. [ABSTRACT FROM AUTHOR]

The research work was intended to formulate teriflunomide (TFM) loaded nano lipid-based (TNLC) carbopol-gellan gum in situ gel (TNLCGHG) and to investigate its therapeutic efficacy against glioma, a brain and spine tumor. Nanoformulation was developed using gellan gum and carbopol 974P as gelling and mucoadhesive agents, respectively, Glyceryl di-behenate and Glyceryl mono-linoleate blend as lipids, and Gelucire 44/14: water blend as surfactant system. Globule size, PDI, zeta potential, encapsulation efficiency, mucoadhesive strength, and nasal permeation were found to be 117.80 nm, 0.56, −21.86 mV, 81.16%, 4.80 g, and 904 μg/cm2, respectively. Anticancer efficacy of TFM-loaded nano lipid-based carbopol-gellan gum in situ gel (TNLCGHG) was determined in human U-87MG glioma cell line. IC 50 was found 7.0 μg/mL for TNLCGHG, 4.8 μg/mL for pure TFM, and 78.5 μg/mL for TNLC, which approve the superiority of surfactant along with gellan gum as permeation enhancer. Brain C max for technetium (99mTC) labeled intranasal (i.n.) 99mTC-TNLCGHG was found 2-folds higher than 99mTC-TNLC (i.n.) and 99mTC-TNLC intravenous (i.v.) because the TNLCGHG formulation contains surfactant with natural gelling polymers, which promisingly improved drug permeability. Finally, this research revealed encouraging outcomes and successfully developed intranasal TNLCGHG nanoformulation as a novel tool for safe delivery of TFM in glioma patients. Unlabelled Image [ABSTRACT FROM AUTHOR]