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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.

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.

Objective: The aim of this study was to evaluate the efficacy of Gamma Knife radiosurgery (GKRS) as a salvage therapy for high-grade glioma in our center. Methods: A total of 167 patients with malignant glioma were treated with GKRS in our Gamma Knife Center between January 2013 and December 2017; 140 patients (85 males and 55 females) were followed up and enrolled in our study. A single lesion was found in 110 cases, and multiple lesions were found in 30 cases; 108 cases received a single therapy, and in 32 cases, at least 2 GKRSs were performed. The median tumor volume was 13.5 cm3. The mean radiation dosage was 14.35 Gy (range, 6–18 Gy). MRI was performed regularly. The RANO criteria and Cox analysis were used to evaluate the therapeutic efficiency. Results: Follow-up MRI showed the local control rate was 61.4% at 3 months after GKRS, 25.0% at 6 months, and 7.1% at 12 months. The mean and median progression-free survival (PFS) periods were 8.6 (95% CI, 6.3–11.0) and 4 (95% CI, 3.5–4.5) (range, 1–60) months, respectively. The overall survival (OS) after GKRS was 3–62 months, with a mean of 16.7 (95% CI, 14.6–18.9) months, and the median survival was 13 (95% CI, 12.1–13.9) months. The 1-, 2-, and 5-year survival rates were 51.4, 10.0, and 2.9%, respectively. No severe complications occurred. Cox regression showed that glioma pathology was closely related to prognosis (p < 0.05). The Karnofsky Performance Score had little influence on PFS (p > 0.05) but influenced OS significantly (p < 0.05). Conclusion: GKRS can be used to effectively treat malignant brain glioma and can therefore be used as an alternative treatment option.

In this paper, we propose a triple intersecting U-Nets (TIU-Nets) for brain glioma segmentation. First, the proposed TIU-Nets is composed of binary-class segmentation U-Net (BU-Net) and multi-class segmentation U-Net (MU-Net), in which MU-Net reuses multi-resolution features from BU-Net. Second, we introduce a segmentation soft-mask predicted by BU-Net, that is, candidate glioma region is generated by removing most of non-glioma backgrounds, which guides multi-category segmentation of MU-Net in a weighted manner. Third, an edge branch in MU-Net is leveraged to enhance boundary information of glioma substructure, which facilitates to locate glioma true boundaries and improve segmentation accuracy. Finally, we propose a sigmoid-evolution based polarized cross-entropy loss (S-CE) to resolve class unbalance problem, and apply S-CE loss to soft-mask prediction loss in BU-Net, multi-class segmentation loss in MU-Net and edge prediction loss in edge branch. Experimental results have demonstrated that the proposed 2D/3D TIU-Nets achieves a higher segmentation accuracy than corresponding 2D/3D state-of-the-art segmentation methods including FCN, U-Net, SegNet, CRDN, IVD-Net, FCDenseNet, DeepMedic, DMFNet, etc, evaluating on publicly available brain tumor segmentation challenge 2015 (BRATS2015) datasets. To show the universality of the proposed method, we also give a comparison of segmentation performance on BrainWeb dataset.

To investigate the magnetic resonance imaging (MRI) images of brain glioma before postoperative radiotherapy, and to provide reference for the delineation of postoperative radiotherapy target area. Retrospective analysis was performed on 106 cases of brain glioma confirmed by surgery and pathology in our hospital, including 70 cases of high-grade glioma (HGG) and 36 cases of low-grade glioma (LGG). The MRI images of the lesions within 1 month before and after surgery were analyzed, the apparent diffusion coefficient (ADC) values in the near and far tumor areas were measured, respectively, and the corresponding rADC values were calculated. The incidence of residual tumors of postoperative HGG and LGG was 0, 15.7% (0/36, 11/70), respectively. The incidence of postoperative reactive enhancement was 11.0% and 52.9% (4/36 and 37/70), respectively. About 30.6% and 81.4% (11/36 and 57/70) of patients with adjacent meningeal enhancement were found in the operative area. The MRI images of HGG and LGG before postoperative radiotherapy had certain characteristics, providing a favorable guidance for the delineation of the target area of radiotherapy and the formulation of treatment plan.

The study objectiveis to assess the possibilities of magnetic resonance imaging (MRI) in SWI (susceptibility weighted imaging) in the differential diagnosis of glial brain tumors and primary brain lymphomas.Materials and methods.Fifty-four patients with brain tumors were studied (men – 27 (50 %), women – 27 (50 %)). Average age 57.9 years. Histological examination of the surgical material revealed the glial nature of tumors in 41 patients (26 of them with glioblastoma, anaplastic astrocytomas – 15), primary brain lymphomas – in 13 patients. Brain MRI was performed using tomographs with a magnetic field of 3 and 1.5 T. A semi-quantitative assessment of the data obtained in the SWI mode based on the classification of ITSS (intratumoral susceptibility signals), reflecting the severity of interstitial vascular architectonics and microbleeding.Results.The degree of ITSS was 3 in glioblastomas (G4 ) in 26 (100 %) cases, in the structure of gliomas (G3 ) the ITSS values were 3 in 3 (20 %) cases, in the remaining 12 (80 %) cases – ITSS 2. In the group of primary brain lymphomas, the ITSS 1 was in 4 (30.7 %) cases, ITSS 0 was in 9 (69.3 %) cases.Conclusion.MRI in SWI mode is a promising technique that allows one to quantify the degree of pathological changes in tumor vascular architectonics and intratumoral hemorrhages and has shown high specificity in the differential diagnosis of malignant gliomas and lymphomas of the brain, accompanied by active accumulation of contrast medium.

Background MRI is successful in showing the anatomy of probable pathologies of the central nervous system. Although it may not be sufficient to reveal physiological and metabolic changes, advanced MRI techniques, such as perfusion and permeability MRI, are the key to overcoming these limitations. The aim of this study was to detect the efficacy of permeability and perfusion MRI techniques. Results The study included 38 patients with a pathology result of primary brain glioma. The permeability MRI (Ktrans, Ve), perfusion MRI values (CBV, CBF), and pathology results were evaluated. The high-grade group included 22 patients, and the low-grade group, 16 patients. Mean CBV and CBF, median Ktrans, and Ve values were higher in the high-grade group. All parameters tended to elevate with grade and had a positive correlation. CBV > 2.25, with sensitivity and specificity of 100%, CBF > 2.02, with sensitivity and specificity of 100%, Ktrans > 0.043, with sensitivity of 81.82% and specificity of 100%, and Ve > 0.255, with sensitivity and specificity of 100%, can predict high grade. Conclusion Perfusion and permeability MRI can be used safely for the differentiation of high- and low-grade gliomas and for the prediction of glioma grades.

Introduction Aberrant expression of long non-coding RNAs (lncRNAs) has been implicated in various diseases, including cancer. However, little is known about lncRNAs in human brain gliomas. Material and methods We examined lncRNA profiles from three glioma specimens using lncRNA expression profiling microarrays. Quantitative real-time RT-PCR was used to analyze the differential expression of raw intensities of lncRNA expression in glioma and peritumoral tissues. Results We found 4858 lncRNAs to be differentially expressed between tumor tissue and peritumoral tissue. Of these, 2845 lncRNAs were up-regulated (fold change > 3.0) and 2013 were down-regulated (fold change < 1/3). A total of 4084 messenger RNAs were also differentially expressed, including 2280 up-regulated transcripts (fold change > 3.0) and 1804 that were down-regulated (fold change < 1/3). Consistent with the microarray data, qPCR confirmed differential expression of these 6 lncRNAs (ak125809, ak098473, uc002ehu.1, bc043564, NR_027322, and uc003qmb.2) between tumor and peritumoral tissue. We next established co-expression networks of differentially expressed lncRNAs and mRNAs. Many mRNAs, such as LOC729991, NUDCD1, SHC3, PDGFA, and MDM2, and lncRNAs, such as ENST00000425922, ENST00000455568, uc002ukz.1, ENST00000502715, and NR_027873, have been shown to play important roles in glioma development. Consistent with this, pathway analysis revealed that “GLIOMA” (KEGG Pathway ID: hsa05214) was significantly enriched in tumor tissue. Conclusions Our data suggest that altered expression of lncRNAs may be a critical determinant of tumorigenesis in glioma patients.

Background. The analytic findings concerning 3-year cumulative survival of patients with malignant brain gliomas are presented, depending on IDH1 gene mutation status, tumor grade (Grade II) and patient’s age. Purpose. To study cumulative survival of patients with malignant brain gliomas depending on IDH1 gene mutation status, tumor grade (Grade II) and patient’s age for prediction of the disease course. Material and methods. The disease specific 3-year cumulative survival of 95 patients with malignant brain glioma treated at N.N. Alexandrov National cancer Centre in 2009–2014 was evaluated with the Kaplan-Meier method calculating standard error (Se). The age-related survival was assessed using univariate Cox proportional hazards regression. The data were processed in statistical R package, version 3.4.2 using Survival Library. Results: According to the analytic findings, the favourable prognostic factors in patients with malignant brain glioma are patient’s age younger than 45 years, low tumor grade (Grade II) and the presence of mutation in IDH1 gene. Conclusions. The factors influencing the survival of patients with malignant brain gliomas are the tumor grade (Grade), the mutational status of IDH1 gene, the patient’s age.

The objective of the study was the analysis and evaluation of patients` intellectual and memory impairments before and after resection of brain glioma Material 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

Background Glioma is the most common intracranial primary tumor of central nervous system (CNS) and accounts for about 70% of primary adult malignant brain tumors. The optimum therapeutic treatment and prognosis evaluation largely depends on the tumor pathological grades. Objective To evaluate the role of susceptibility weighted imaging (SWI) in grading of cerebral gliomas. The magnetic resonance imaging (MRI) results were compared and correlated to the pathology results to evaluate its role. The pathological grading of the glioma was done according to WHO 2007 classification system. Patients and Methods This was a retrospective study that included 35 adult patients, (11females & 24 males), their ages ranging from 18 years to 73 years. They were pathologically proven glioma patients ranging from grade I to grade IV. All the patients were referred from neurosurgeon to our radiology center (private center). This study was carried out during the period between January 2017 and November 2018. Results In our study, there were a strong positive correlation between both conventional imaging and pathological grading and between pathological and SWI grading. Using SWI sequence in grading of glioma will be very beneficial in patients with contraindication to contrast. Conclusion SWI using 3T MR system may provide quite useful information for preoperative glioma grading. There seems to be a strong positive correlation between pathological grading and SWI grading system for glioma. The main disadvantage for SWI is the extra time added to the usual time of routine MRI protocol used in cases of intra cranial space occupying lesions (SOL).

OBJECTIVE In this study, we analysed the results of magnetic resonance spectroscopy (MRS) in the patients with gliomas, including the error rate, MRS parameters variability, correlations with gene mutations and overall usefulness for clinical practice. MATERIAL AND METHODS Eighty patients with glial tumours were examined by multiparametric MRI completed with single voxel MRS, as one group, then as two separate groups according to progression of the disease after the initial surgery. The error rate between the groups, MRS parameters variability, hazard ratios and correlations between metabolites, genetic markers and tumour grade were all analysed. RESULTS Variability in Cho/Cr(h) was significantly higher in the group with a disease progression (p = 0.044). In the patients with a stable disease, strong significant negative correlations between Cho/Cr and Cho/NAA with p53 mutation (-0.945 and -0.812 respectively, p < 0.05) and between Cho/Cr and IDH1, 2 mutation (-0.796, p < 0.05) were found. In the patients with tumour progression, a significant positive correlation of NAA/Cr with 1p19q codeletion (0.486, p < 0.05) and of Cho/Cr and Cho/NAA values with p53 mutation (0.477 and 0.416, p < 0.05) were identified. Tumour grade positively correlated with Cho/Cr values (0.304, p = 0.02) in the whole patient group. CONCLUSION MRS brings an added value to multiparametric MRI evaluation of brain tumours in the patient follow-up after an initial surgery, especially in ambiguous findings (Tab. 5, Fig. 2, Ref. 29).

BackgroundGlioma 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.MethodsIn 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.ResultsExperimental 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.ConclusionsThe 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.

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., Robotom potpomognuta tumorska biopsija postaje jednom od najvažnijih inovativnih tehnologija u neurokirurškom radu. Razlog njezine uporabe nalazi se u daljnjem poboljšanju sigurnosti, učinkovitosti i preciznosti biopsijske metode koja je osobito značajna u planiranju opskrbe endokranijske tumorske patologije. Ovim radom donosimo prva institucijska iskustva u primjeni ove začudne tehnologije pri biopsiji gliomskih tumora mozga. Kranijski robotički uređaj korišten je pri stereotaksijskoj robotom potpomognutoj tumorskoj biopsiji u tri susljedna slučaja iz naše serije, koja je uspješno učinjena radi uzimanja uzorka tumorskoga tkiva za patohistološku i imunohistokemijsku dijagnostiku u bolesnice s anaplastičkim izocitrat dehidrogenaza (IDH) negativnim astrocitomom (SZO st. III.) smještenim u periventrukulskoj bijeloj tvari desnoga trigonuma, u bolesnika s difuznim astrocitomom niskoga stupnja malignosti (SZO st. II.) smještenim obostrano u talamičkom području sa širenjem u desni mezencefalon, kao i u bolesnika s IDH-wildtype glioblastomom (SZO st. IV.) desnog čeonog režnja s pomakom središnjih tvorba. Jatrogena lezija pripadajućeg elokventnog moždanog korteksa bila je minimalna, dok je neposredni poslijeoperacijski oporavak bio uspješan u svih bolesnika. Uzimajući u obzir preliminarne rezultate našega početnog iskustva, zaključujemo kako je robotom potpomognuta tumorska biopsija dokazano izvodljiva i primjerena metoda u kirurgiji gliomskih tumora mozga kojom se može poboljšati sigurnost i preciznost bez produljenja vremena operacije, a koja je podjednako učinkovita u usporedbi sa standardnom stereotaksijskom i manualnom biopsijom. Uporaba navedene metode omogućuje precizno uzorkovanje tumorskoga tkiva za patohistološku i imunohistokemijsku analizu na siguran i lak način, što doprinosi odabiru strategije liječenja i predviđanju ishoda različitih tipova gliomskih tumora mozga.

Purpose To evaluate the incidence and clinical importance of brain gliomas – optic pathway gliomas (OPGs) and especially gliomas outside the optic pathway (GOOP) for children with neurofibromatosis type 1 (NF1), additionally, to assess the causes of obstructive hydrocephalus in NF1 children with an emphasis on cases caused by idiopathic aqueduct stenosis. Subjects and methods We analysed data from 285 NF1 children followed up on our department from 1990 to 2010 by the same examination battery. Results We have found OPGs in 77/285 (27%) children and GOOPs in 29/285 (10,2%) of NF1 children, of who 19 had OPG and GOOP together, so the total number of brain glioma was 87/285 (30,5%). GOOPs were significantly more often treated than OPGs (p > 0.01). OPGs contain clinically important subgroup of 14/285 (4.9%) spreading to hypothalamus. Spontaneous regression was documented in 4/285 (1.4%) gliomas and the same number of NF1 children died due to gliomas. Obstructive hydrocephalus was found in 22/285 (7.7%) patients and 14/22 cases were due to glioma. Idiopathic aqueduct stenosis caused hydrocephalus in 6/22 cases and was found in 2.1% of NF1 children. Two had other cause. Conclusions The total brain glioma number (OPGs and only GOOPs together) better reflected the overall brain tumour risk for NF1 children. However, GOOPs occur less frequently than OPGs, they are more clinically relevant. The obstructive hydrocephalus was severe and featuring frequent complication, especially those with GOOP. Idiopathic aqueduct stenosis shows an unpredictable cause of hydrocephalus in comparison with glioma and is another reason for careful neurologic follow up.

Background Diffusion-tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that depicts the integrity of white matter (WM) tracts. This study was conducted to assess the utility of DTI tractography as an imaging technique in assessment of brain gliomas and planning of the surgical corridor. Results Twenty adult patients with brain gliomas were included. Neurological examination and conventional MRI and DTI scans were performed before and after surgery. Low-grade and high-grade tumors were found in 30% and 70% of patients, respectively. Preoperative DTI demonstrated five patterns of WM tract involvement: non-affected (10%), displaced (75%), edematous (55%), infiltrated (60%), and disrupted (20%). The obtained DTI scans were used for preoperative planning of the surgical corridor and extent of resection to achieve the maximum resection while preserving the WM tracts. Total resection was achieved in 40%, while 60% underwent subtotal resection. Postoperative neurological examination showed deterioration of cognitive function, motor power, and vision in 15%, 10%, and 5% of patients, respectively. Headache persisted in 15%, while motor power improved in 35% of patients. High-grade tumors were significantly associated with higher percentage of subtotal resection (p=0.018) and pattern IV (p=0.018). There was a significant association between the preoperative pattern of WM tract involvement and the postoperative DTI changes (p Conclusion DTI enables assessment of displaced and infiltrated WM tracts in the vicinity of brain tumors. Preoperative planning of tumor resection and surgical corridor should include DTI scan to achieve the balance between maximum resection of tumor and maximal preservation of function.

LS301 is a promising NIR fluorescence probe for targeting brain glioma cancer. The co-localization of LS31 and 5-ALA induced PpIX in vitro and in vivo enables LS301 to guide PpIX fluorescence image surgery. Moreover, LS301 showed no negative impact on 5-ALA-PpIX PDT outcome in brain glioma cells and mouse tumor model. Therefore, the implementation of LS301 and PpIX has potential to improve tumor resection surgery and PDT treatment for better tumor outcomes.

The incidence of glioma is increasing year by year, seriously endangering people’s health. Magnetic resonance imaging (MRI) can effectively provide intracranial images of brain tumors and provide strong support for the diagnosis and treatment of the disease. Accurate segmentation of brain glioma has positive significance in medicine. However, due to the strong variability of the size, shape, and location of glioma and the large differences between different cases, the recognition and segmentation of glioma images are very difficult. Traditional methods are time-consuming, labor-intensive, and inefficient, and single-modal MRI images cannot provide comprehensive information about gliomas. Therefore, it is necessary to synthesize multimodal MRI images to identify and segment glioma MRI images. This work is based on multimodal MRI images and based on deep learning technology to achieve automatic and efficient segmentation of gliomas. The main tasks are as follows. A deep learning model based on dense blocks of holes, 3D U-Net, is proposed. It can automatically segment multimodal MRI glioma images. U-Net network is often used in image segmentation and has good performance. However, due to the strong specificity of glioma, the U-Net model cannot effectively obtain more details. Therefore, the 3D U-Net model proposed in this paper can integrate hollow convolution and densely connected blocks. In addition, this paper also combines classification loss and cross-entropy loss as the loss function of the network to improve the problem of category imbalance in glioma image segmentation tasks. The algorithm proposed in this paper has been used to perform a lot of experiments on the BraTS2018 dataset, and the results prove that this model has good segmentation performance.

Brain gliomas require a deep knowledge of their effects on brain connectivity. Understanding the complex relationship between tumor and functional brain is the preliminary and fundamental step for the subsequent surgery. The extent of resection (EOR) is an independent variable of surgical effectiveness and it correlates with the overall survival. Until now, great efforts have been made to achieve gross total resection (GTR) as the standard of care of brain tumor patients. However, high and low-grade gliomas have an infiltrative behavior and peritumoral white matter is often infiltrated by tumoral cells. According to these evidences, many efforts have been made to push the boundary of the resection beyond the contrast-enhanced lesion core on T1w MRI, in the so called supratotal resection (SpTR). SpTR is aimed to maximize the extent of resection and thus the overall survival. SpTR of primary brain tumors is a feasible technique and its safety is improved by intraoperative neuromonitoring and advanced neuroimaging. Only transient cognitive impairments have been reported in SpTR patients compared to GTR patients. Moreover, SpTR is related to a longer overall and progression-free survival along with preserving neuro-cognitive functions and quality of life.

Gliomas are the most severe brain tumours with a poor prognosis. Although surgery, postoperative radiotherapy and chemotherapy can improve the survival rate of glioma patients, the prognosis of most glioma patients is still poor. In recent years, the influence of gene-targeted therapy on gliomas has been gradually discovered, and intervening the occurrence and development of brain gliomas from the perspective of the gene will significantly improve treatment prognosis. Protein Kinase C and Casein Kinase Substrate in Neurons 1 (PACSIN1) is a member of the conserved peripheral membrane protein family in eukaryotes. Improper expression of PACSIN1 can lead to neurological diseases such as Huntington’s disease and schizophrenia. However, its relationship with tumours or even gliomas has not been explored. The study aims to explore PACSIN1 as a prognostic factor that can predict overall survival (OS) for gliomas. We collected the data from CGGA, TCGA, GEO databases and the pathological glioma tissue specimens from 15 clinical glioma patients surgically resected. The differential expression of PACSIN1 in various clinical indicators, the genes related to PACSIN1 expression, the prognostic value of PACSIN1 and the functional annotations and pathway analysis of differently expressed genes (DEGs) were analysed. The results revealed that PACSIN1 had low expression levels in grade IV, IDH1 wild-type and 1p/19q non-codel group gliomas, and PACSIN1 was considered a mesenchymal molecular subtype marker. PACSIN1 expression is positively correlated with OS in all gliomas and it was found that PACSIN1 influenced the occurrence and development of gliomas through synaptic transmission. The PACSIN1 expression is negatively correlated with the malignant degree of gliomas and positively associated with the OS, indicating that PACSIN1 would play an essential role in the occurrence and development of gliomas and might be a potential new biomarker and targeted therapy site for gliomas.

To explore the application value of MRI in the diagnosis of brain glioma (BG), in the study, a deep learning-based multimodal feature fusion model was established, which was then applied in BG classification. 60 BG patients who came to our hospital for treatment were selected as research subjects. They all accepted the MRI scan and the enhanced scan, and the MRI results were compared with the pathological results. The results showed that the sensitivity of the algorithm was above 90%, and the sensitivity to diagnose grade IV glioma was as high as 98.28%; the specificity was above 78%, and the specificity to diagnose grade IV glioma was as high as 95.85%; the detection accuracy was above 95%. The relative fractional anisotropy (rFA) values of the tumor body were smaller than those of peritumoral edema in both the high-grade group and low-grade group, and the difference was notable P < 0.05 ; the relative apparent diffusion coefficients (rADC) values of the peritumoral edema were greater than those of tumor bodies of the same grade in both the high-grade group and the low-grade group, and the difference was notable P < 0.05 ; notable differences were noted in the rADC values of tumor bodies between the high-grade group and the low-grade group P < 0.05 and in the rADC values of the glioma peritumoral edema between the high-grade group and the low-grade group P < 0.05 . In summary, MRI based on deep learning raises the sensitivity, specificity, and accuracy to diagnose BG and can more accurately classify BG pathologically, providing reference for clinical treatment of BG.

Reading abilities and diffusion tensor imaging (DTI) parameters were retrospectively analyzed in a group of neurosurgical patients to investigate (Study 1) the role of white matter—in particular the arcuate fasciculus (AF)—in preserved vs. impaired reading; 4 months after surgery, we explored the plasticity processes (Study 2). Study 1 involved 40 patients with brain glioma (23 low-grade and 17 high-grade gliomas). We compared preoperative DTI parameters of language-related fascicles between patients who developed a reading impairment after surgery (n = 23) and patients with preserved reading (n = 17). Besides lower fractional anisotropy (FA), patients with impaired reading also displayed lower number and density of streamlines of a direct (i.e., directly connecting temporal and frontal lobes) AF segment. In Study 2, we longitudinally tested at follow-up-when reading performance had generally improved-13 patients diagnosed with low-grade glioma. The most relevant finding was a significant increase in length of streamlines of the direct AF segments in both hemispheres. From a neurosurgical perspective, our preliminary findings suggest the clinical importance of sparing direct AF segments for the involvement they showed in reading; however, the results also suggest the reorganization potential of these segments, possibly compensating of the right homologs as well.

High grade-gliomas are highly invasive and prone to metastasis, leading to poor survival and prognosis. Currently, we urgently need a new treatment strategy to effectively inhibit glioma. In this study, artemether and paclitaxel were used as two agents for tumour suppression. Two functional materials were synthesised and modified on the surface of the micelle as targeting molecules. The addition of two functional materials confers the ability of the micelles to effectively cross the blood-brain barrier (BBB) and then target the glioma cells. Thus, this dual-targeted delivery system allows the drug to play a better role in inhibiting tumour invasion and vasculogenic mimicry (VM) channels. In this paper, the anticancer effects of dual-targeted artemether plus paclitaxel micelles on glioma U87 cells were studied in three aspects: (I)

Objective To evaluate the application of laplacian-regularized mean apparent propagator (MAPL)-MRI to brain glioma-induced corticospinal tract (CST) injury. Materials and Methods This study included 20 patients with glioma adjacent to the CST pathway who had undergone structural and diffusion MRI. The entire CSTs of the affected and healthy sides were reconstructed, and the peritumoral CSTs were manually segmented. The morphological characteristics of the CST (track number, average length, volume, displacement of the affected CST) were examined and the diffusion parameter values, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean squared displacement (MSD), q-space inverse variance (QIV), return-to-origin probability (RTOP), return-to-axis probabilities (RTAP), and return-to-plane probabilities (RTPP) along the entire and peritumoral CSTs, were calculated. The entire and peritumoral CST characteristics of the affected and healthy sides as well as those relative CST characteristics of the patients with motor weakness and normal motor function were compared. Results The track number, volume, MD, RD, MSD, QIV, RTAP, RTOP, and RTPP of the entire and peritumoral CSTs changed significantly for the affected side, whereas the AD and FA changed significantly only in the peritumoral CST (p < 0.05). In patients with motor weakness, the relative MSD of the entire CST, QIV of the entire and peritumoral CSTs, and the AD, MD, RD of the peritumoral CST were significantly higher, whereas the RTPP of the entire and peritumoral CSTs and the RTOP of the peritumoral CST were significantly lower than those in patients with normal motor function (p < 0.05 for all). In contrast, no significant changes were found in the CST morphological characteristics, FA, or RTAP (p > 0.05 for all). Conclusion MAPL-MRI is an effective approach for evaluating microstructural changes after CST injury. Its sensitivity may improve when using the peritumoral CST features.

Background and objective:The manual segmentation, identification, and classification of brain tumor using magnetic resonance (MR) images are essential for making a correct diagnosis. It is, however, an exhausting and time consuming task performed by clinical experts and the accuracy of the results is subject to their point of view. Computer aided technology has therefore been developed to computerize these procedures. Methods:In order to improve the outcomes and decrease the complications involved in the process of analysing medical images, this study has investigated several methods. These include: a Local Difference in Intensity - Means (LDI-Means) based brain tumor segmentation, Mutual Information (MI) based feature selection, Singular Value Decomposition (SVD) based dimensionality reduction, and both Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) based brain tumor classification. Also, this study has presented a new method named Multiple Eigenvalues Selection (MES) to choose the most meaningful features as inputs to the classifiers. This combination between unsupervised and supervised techniques formed an effective system for the grading of brain glioma. Results:The experimental results of the proposed method showed an excellent performance in terms of accuracy, recall, specificity, precision, and error rate. They are 91.02%,86.52%, 94.26%, 87.07%, and 0.0897 respectively. Conclusion:The obtained results prove the significance and effectiveness of the proposed method in comparison to other state-of-the-art techniques and it can have in the contribution to an early diagnosis of brain glioma.

PURPOSE: To design a computational method for automatic brain glioma segmentation of multimodal MRI scans with high efficiency and accuracy. MATERIALS AND METHODS: The 2018 Multimodal Brain Tumor Segmentation Challenge (BraTS) dataset was used in this study, consisting of routine clinically acquired preoperative multimodal MRI scans. Three subregions of glioma—the necrotic and nonenhancing tumor core, the peritumoral edema, and the contrast-enhancing tumor—were manually labeled by experienced radiologists. Two-dimensional U-Net models were built using a three-plane–assembled approach to segment three subregions individually (three-region model) or to segment only the whole tumor (WT) region (WT-only model). The term three-plane–assembled means that coronal and sagittal images were generated by reformatting the original axial images. The model performance for each case was evaluated in three classes: enhancing tumor (ET), tumor core (TC), and WT. RESULTS: On the internal unseen testing dataset split from the 2018 BraTS training dataset, the proposed models achieved mean Sørensen–Dice scores of 0.80, 0.84, and 0.91, respectively, for ET, TC, and WT. On the BraTS validation dataset, the proposed models achieved mean 95% Hausdorff distances of 3.1 mm, 7.0 mm, and 5.0 mm, respectively, for ET, TC, and WT and mean Sørensen–Dice scores of 0.80, 0.83, and 0.91, respectively, for ET, TC, and WT. On the BraTS testing dataset, the proposed models ranked fourth out of 61 teams. The source code is available at https://github.com/GuanLab/Brain_Glioma. CONCLUSION: This deep learning method consistently segmented subregions of brain glioma with high accuracy, efficiency, reliability, and generalization ability on screening images from a large population, and it can be efficiently implemented in clinical practice to assist neuro-oncologists or radiologists. Supplemental material is available for this article. © RSNA, 2020

We analyze the different phases of glioma tumors treated with Photodynamic Therapy to obtain results that can help in diagnosing and treating this type of disease, generating a clinically predictive model.

Brain glioma segmentation using multi-parametric magnetic resonance (MR) imaging has significant clinical value. Although 3D convolutional neural networks (CNNs) have become increasingly prevalent in delivering this segmentation task, these models still suffer from an insufficient ability to high-resolution feature representation for small and irregular regions, limited local receptive fields, and poor long-range dependencies. In this paper, we propose a 3D High-resolution and Non-local Feature Network (HNF-Net) for brain glioma segmentation using multi-parametric MR imaging. We construct HNF-Net based mainly on the parallel multi-scale fusion (PMF) module, which helps produce strong high-resolution feature representation and aggregate multi-scale contextual information. We also introduce the expectation-maximization attention (EMA) module to HNF-Net, aiming to capture the long-range dependent contextual information and reduce the feature redundancy in a lightweight fashion. We evaluated our HNF-Net on the BraTS 2019 Challenge dataset against eight top-ranking methods listed on the challenge leaderboard. Our results suggest that the proposed HNF-Net achieves improved overall performance over these methods, and our ablation study demonstrates the effectiveness of the PMF module and EMA module.

The objective of this study is to perform brain glioma grade classification by identifying an optimal quantitative feature set from conventional magnetic resonance images. In this work, a hybrid fe...

Epithelial-mesenchymal transformation(EMT) is a coordinated process in which polarized epithelial cells are induced to lose adhesion from the basement membrane and obtain the properties of mesenchymal cells, including invasion and metastasis. It has been proved that EMT greatly contributes to the invasion and therapeutic resistance of various solid human cancers. However, the role of EMT in brain glioma has not yet been fully clarified. So in this review, we mainly elaborate the latest progression about the related regulatory transcription factors, key signaling pathways and microRNAs (miRNAs) of EMT in gliomas.

Background & objective Angiogenesis is an essential component of tumor growth. Expression of PSMA on the neo-vasculature of many solid tumors, including glioblastoma multi-form, has been determined. The pattern of expression suggests that PSMA may play a functional role in angiogenesis. Methods expression of PSMA in different grades of brain glioma was evaluated by the immunohistochemistry method to determine the probable usefulness of anti-PSMA antibody as complementary target therapy in different grades of glioma. Results Overall, 72 cases of low (grade I and II) and high (grade III and IV) grade gliomas were evaluated for expression of PSMA. Positive PSMA staining was observed in 12 (33.3%) of high grade and 3 (8.3%) of low grade gliomas. Although, high grade tumors more commonly had positive result for PSMA (P value=0.009), the intensity of staining was significantly stronger in low-grade tumors (P value=0.009). Conclusion Expression of PSMA in different grades of glioma might provide a basis for further investigations focusing on selective target therapy in combination with the current standard care in all glioma grades, to improve treatment efficacy.

Background: Gastrin-releasing peptide receptor is particularly expressed in gliomas, while the peptide bombesin [BBN(7-14)] has the complete C-terminal structure of human gastrin-releasing peptide. Glioma-specific imaging agents can therefore be constructed from BBN, for example 68Ga-NOTA-Aca-BBN(7-14). For consideration of the clinical translation of 68Ga-NOTA-Aca-BBN(7-14), an open-label dynamic whole-body positron emission tomography/computed tomography (PET/CT) study was designed to investigate the diagnostic effectiveness and safety of 68Ga-NOTA-Aca-BBN(7-14) in patients with brain gliomas. Methods/Design: This is an open-label single-arm clinical trial that will be conducted at Peking Union Medical College Hospital in Beijing, China. Thirty patients in suspicion of brain gliomas scheduled for surgical treatment will be recruited and subjected to PET/CT via intravenous injection of 68Ga-NOTA-Aca-BBN(7-14). The primary outcome measure will be the standardized uptake value of 68Ga-NOTA-Aca-BBN(7-14) in brain glioma at 30 minutes after injection. Secondary outcomes include the diagnostic accuracy rate of 68Ga-NOTA-Aca-BBN(7-14) PET/CT, and adverse events after injection. Discussion: Diagnostic performance and safety assessment of 68Ga-NOTA-Aca-BBN(7-14) in brain gliomas will provide new insights into the specific PET/CT diagnosis of brain gliomas. Trial registration: ClinicalTrials.gov identifier: NCT02520882, registered on 2 August 2015. Ethics: This study protocol has been approved by the Ethics Committee of Peking Union Medical College Hospital in China (approval No. S-714), and will be performed in accordance with the Declaration of Helsinki, formulated by the World Medical Association. Informed consent: An informed consent will be obtained from each patient or his/her guardian prior to participation in the study.

Gliomas are the most common primary brain tumours in children and adults, consisting of a heterogeneous group of neoplastic diseases arise from the supporting cells of the CNS (glial cells). Their histopathological and molecular characteristics vary considerably as do their management and prognosis. Conventional gadolinium-enhanced magnetic resonance imaging (MRI) is considered the primary imaging modality for initial work up and follow up of patients with gliomas, although it has some limitations, especially in differentiating high from low grade tumours and in distinguishing disease recurrence from post-therapy changes. Hybrid positron emission tomography (PET)/MRI is a relatively novel tool that combines MRI sequences with metabolic information from PET, and therefore different PET radiotracers, in a single scan. This article discusses the main advantages and disadvantages of combined PET/MRI compared to other conventional or more widely available imaging tools, such as MRI or combined positron emission tomography–computed tomography. The main uses of PET/MRI and the most commonly used PET radiotracers in providing diagnostic, prognostic and predictive information in patients with glioma are covered.

Demyelinating pseudotumor mainly attacks in teenagers and more commonly seen in female compared with male counterparts. Comprehensive understanding of medical history, clinical manifestations, imaging and pathological characteristics contribute to clinical diagnosis and management of demyelinating pseudotumor. Demyelinating pseudotumor in the central nervous system is mainly characterized as nerve fiber demyelination and inflammatory cell infiltration surrounding the minute vessels. However, the clinical and imaging characteristics of demyelinating pseudotumors mimic those of brain tumors, especially the brain glioma. It is likely to make a misdiagnosis of demyelinating pseudotumors. Herein, we reported one case of intracranial demyelinating pseudotumors and described the diagnosis and treatment of this patient in this study.

Maximal safe resection represents the gold standard for surgery of malignant brain tumors. As regards gross-total resection, accurate localization and precise delineation of the tumor margins are required. Intraoperative diagnostic imaging (Intra-Operative Magnetic Resonance-IOMR, Intra-Operative Computed Tomography-IOCT, Intra-Operative Ultrasound-IOUS) and dyes (fluorescence) have become relevant in brain tumor surgery, allowing for a more radical and safer tumor resection. IOUS guidance for brain tumor surgery is accurate in distinguishing tumor from normal parenchyma, and it allows a real-time intraoperative visualization. We aim to evaluate the role of IOUS in gliomas surgery and to outline specific strategies to maximize its efficacy. We performed a literature research through the Pubmed database by selecting each article which was focused on the use of IOUS in brain tumor surgery, and in particular in glioma surgery, published in the last 15 years (from 2003 to 2018). We selected 39 papers concerning the use of IOUS in brain tumor surgery, including gliomas. IOUS exerts a notable attraction due to its low cost, minimal interruption of the operational flow, and lack of radiation exposure. Our literature review shows that increasing the use of ultrasound in brain tumors allows more radical resections, thus giving rise to increases in survival.

// Ying Li 1 , Xuemin Zheng 2 , Min Gong 3, 4 , Jianning Zhang 1 1 Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China 2 Tianjin Institute of Pharmaceutical Research, Tianjin, China 3 School of Pharmacy, Tianjin Medical University, Tianjin, China 4 Department of Oncology, University of Oxford, Oxford, UK Correspondence to: Min Gong, email: kahongmg@163.com Jianning Zhang, email: liying11_@hotmail.com Keywords: blood brain barrier, low-density lipoprotein related protein-1, brain glioma, cell penetrating peptide, paclitaxel Received: August 08, 2016 Accepted: September 29, 2016 Published: October 17, 2016 ABSTRACT The challenge of effectively delivering therapeutic agents to the brain has created an entire field of active research devoted to overcoming the blood brain barrier (BBB) and efficiently delivering drugs to the brain. Angiopep-2 can trigger transcytosis and traverse the BBB by recognizing low-density lipoprotein related protein-1 (LRP-1) expressed on the brain capillary endothelial cells. Here, we designed a novel strategy for the delivery of drugs to the brain. The novel drug delivery system was a combination of a receptor-targeting ligand, such as low-density lipoprotein related protein 1, and a cell-penetrating peptide (CPP). It was hypothesized that this conjugate will enhance the delivery of associated therapeutic cargo across the BBB and increase the permeability of a solid tumor. Our findings indicate that the combination of these two agents in a delivery vehicle significantly improved translocation of small molecules (paclitaxel) into the brain compared to the vehicle treatment, which contained only receptor-targeting ligand. The application of this strategy could potentially expand the horizons for the treatment of central nervous system disorders.

Brain glioma is the most common primary intracranial tumor characterized by dismal prognosis and frequent recurrence, yet a real-time and reliable biological approach to monitor tumor response and progression is still lacking. Recently, few studies have reported that circulating tumor cells (CTCs) could be detected in glioblastoma multiform (GBM), providing the possibility of its application in brain glioma monitoring system. But its application limits still exist, because the detection rate of CTCs is still low and was exclusively limited to high- grade gliomas. Here, we adopted an advanced integrated cellular and molecular approach of SE-iFISH to detect CTCs in the peripheral blood (PB) of patients with 7 different subtypes of brain glioma, uncovering the direct evidences of glioma migration. We identified CTCs in the PB from 24 of 31 (77%) patients with glioma in all 7 subtypes. No statistical difference of CTC incidence and count was observed in different pathological subtypes or WHO grades of glioma. Clinical data revealed that CTCs, to some extent, was superior to MRI in monitoring the treatment response and differentiating radionecrosis from recurrence of glioma. Conclusively, CTCs is a common property of brain gliomas of various pathological subtypes, which has provided an ultimate paradox for the hypothesis “soil and seed”. It can be used to monitor the microenvironment of gliomas dynamically, which will be a meaningful complement to radiographic imaging.

Objectives The purpose of our study was to evaluate whether peritumoural perfusion weighted and proton spectroscopic magnetic resonance imaging can be used in differentiating between primary gliomas and solitary metastases. Methods Ten low-grade gliomas, eight high-grade gliomas and 10 metastases were prospectively evaluated with magnetic resonance imaging, dynamic susceptibility contrast enhanced perfusion imaging and single-voxel proton magnetic resonance spectroscopy before surgical resection or stereotactic biopsy. Maximal relative cerebral blood volume values were calculated drawing three regions of interest of 2 cm2 in the non-enhancing peritumoural areas. Maximal relative cerebral blood volume values were normalised to that of contralateral normal-appearing white matter. Maximal choline/creatine ratios were calculated from three voxels of 10 cm3 placed in the peritumoural areas defined as non-enhancing peritumoural white matter surrounding the tumour. The tumour grade presumed with these values was compared to histopathological grading. Differences in the study parameters between groups were assessed using the Mann–Whitney test. A receiver operating characteristic analysis was performed to determine cut-off values. Results A clear relative cerebral blood volume cut-off value of 1.88 was detected for differentiating low-grade gliomas from high-grade gliomas. A clear relative cerebral blood volume cut-off value of 1.20 was detected for differentiation of metastases from gliomas. The differences in the choline/creatine ratios in the peritumoural regions of high-grade gliomas and of solitary metastasis were statistically significant ( P Conclusion Our preliminary data support the hypothesis that peritumoural perfusion-weighted imaging can assist in preoperative differentiation between a glioma and a solitary metastasis.

INTRODUCTION The aim of this study was to determine the influence of the far upstream element binding protein 1 gene (FUBP1) on chemotherapy sensitivity in human U251 glioblastoma cells. MATERIAL AND METHODS Real-time polymerase chain reaction (PCR) was used to determine the expression of the FUBP1 gene in 43 cases of human brain gliomas. Western blot analysis was used to determine the inhibitory effect of RNA interference on FUBP1 gene expression. Methyl thiazolyl tetrazolium assay (MTT) and flow cytometry methods were used to determine the growth inhibitory rate and apoptosis rate of the U251 cells with FUBP1 silencing. The growth inhibitory rate and apoptosis rate were further determined after treatment of those U251 cells with cisplatin (DDP). RESULTS The expression of FUBP1 mRNA was up-regulated significantly in gliomas, 177.65% as much as in peri-cancerous tissues (p < 0.05). The expression of FUBP1 protein was inhibited significantly with siRNA-FUBP1 (p < 0.05). In FUBP1-silenced cells, the growth inhibitory rate increased from 1.4% to 29.5%, and the apoptosis rate increased from 2.68% to 5.84% (p < 0.05 for both). After treating with DDP at various concentrations (1, 3, 5 µg/ml), the growth inhibitory rate of FUBP1-silenced cells increased from 14.42%, 17.46% and 23.55% to 21.69%, 27.51% and 37.57%; the apoptosis rate increased from 8.85%, 14.37% and 18.21% to 13.25%, 18.46% and 26.52%. CONCLUSIONS The up-regulation of FUBP1 relates to the carcinogenesis of gliomas. FUBP1 silencing increases the growth inhibitory rate and apoptosis rate of the U251 cells, and enhances the chemotherapy sensitivity of U251 cells to DDP.

The vexing difficulty in distinguishing glioma from normal tissues is a major obstacle to prognosis. In an attempt to solve this problem, we used a joint strategy that combined targeted-cancer stem cells nanoparticles with precise photoacoustic and fluorescence navigation. We showed that traditional magnetic resonance imaging (MRI) did not represent the true morphology of tumors. Targeted nanoparticles specifically accumulated in the tumor area. Glioma was precisely revealed at the cellular level. Tumors could be non-invasively detected through the intact skull by fluorescence molecular imaging (FMI) and photoacoustic tomography (PAT). Moreover, PAT can be used to excise deep gliomas. Histological correlation confirmed that FMI imaging accurately delineated scattered tumor cells. The combination of optical PAT and FMI navigation fulfilled the promise of precise visual imaging in glioma detection and resection. This detection method was deeper and more intuitive than the current intraoperative pathology.

Positron emission tomography combined with computed tomography (PET/CT) enables assessment of not only anatomical and structural but also metabolic changes in tumor mass. 18F-fluoroethyl tyrosine (18F-FET) PET/CT is based on evaluation of transport of 18F-labeled tyrosine in tissues. We present a clinical case of a patient with a newly diagnosed brain tumor, demonstrating the capabilities of 18F-FET PET/CT in assessing the reliable volume and degree of tumor anaplasia, which is important when choosing the treatment approach for a patient.

Gliomas are the most common primary malignant brain tumours in adults, representing nearly 80%, with poor prognosis in their high-grade forms. Several variables positively affect the prognosis of patients with high-grade glioma: young age, tumour location, radiological features, recurrence, and the opportunity to perform post-operative adjuvant therapy. Low-grade gliomas are slow-growing brain neoplasms of adolescence and young-adulthood, preferentially involving functional areas, particularly the eloquent ones. It has been demonstrated that early surgery and higher extent rate ensure overall longer survival time regardless of tumour grading, but nowadays, functional preservation that is as complete as possible is imperative. To achieve the best surgical results, along with the best functional results, intraoperative mapping and monitoring of brain functions, as well as different anaesthesiology protocols for awake surgery are nowadays being widely adopted. We report on our experience at our institution with 28 patients affected by malignant brain tumours who underwent brain mapping-aided surgical resection of neoplasm: 20 patients underwent awake surgical resection and 8 patients underwent asleep surgical resection. An analysis of the results and a review of the literature has been performed.

Brain glioma is one of the most common and devastating intracranial malignancies with a high mortality. Chemotherapy for brain glioma is not ideal due to blood brain barrier (BBB) and multidrug resistance (MDR). The objectives of the present study were to develop a kind of RGD (Arg-Gly-Asp) tripeptide modified vinorelbine plus tetrandrine liposomes to achieve BBB transportation, MDR reversion and glioma cell targeting simultaneously. The studies were performed on glioma cells, resistant glioma cells and glioma-bearing mice. Results showed that the constructed liposomes with suitable physicochemical properties could significantly enhance the transport across BBB, obviously accumulate in glioma cells, and exhibit evident capabilities in diminishing brain glioma in mice. Action mechanism studies indicated that the enhanced anticancer efficacy could be attribute to the follows: prolonged elimination half-life (7.093 ± 1.311 h); increased AUC

For quantitative analysis of glioma, multimodal Magnetic Resonance Imaging (MRI) signals are required in combination to perform a complementary analysis of morphological, metabolic, and functional changes. Most of the morphological analyses are based on T1-weighted and T2-weighted signals, called traditional MRI. But more detailed information about tumorous tissues could not be explained. An information combination scheme of Diffusion-Weighted Imaging (DWI) and Blood-Oxygen-Level Dependent (BOLD) contrast Imaging is proposed in this paper. This is a non-model segmentation scheme of brain glioma tissues in a particular perspective of combining multi-parameters of DWI and BOLD contrast functional Magnetic Resonance Imaging (fMRI). Compared with traditional MRI, a promising advantage of our work is to provide an effective and adequate subdivision of the related pathological regions with glioma, by incorporating both knowledge of image graylevel and spatial structure. Furthermore, it is an automatic segmentation method without needs of parameter selection and model fitting for the extracted tissues. By the experiments in patients with glioma, the proposed method has achieved the average overlap ratios of 83.6% in the whole tumor region and 82.5% in the peritumoral edema region with the manual segmentation as "ground truth".