scholarly journals Brain Tumor Assortment into High Level and Low Level Gliomas

2021 ◽  
Vol 9 (12) ◽  
pp. 353-364
Author(s):  
Sanjeet Pandey
Keyword(s):  
Invasive Procedure ◽  
High Grade Glioma ◽  
Low Grade Glioma ◽  
World Health ◽  
Low Grade ◽  
High Grade ◽  
Learning Approaches ◽  
Sampling Errors ◽  
Promising Alternative ◽  
Glioma Grading

Abstract: Brain is recognized as one of the complex organ of the human body. Abnormal formation of cells may affect the normal functioning of the brain. These abnormal cells may belong to category of benign cells resulting in low grade glioma or malignant cells resulting in high grade glioma. The treatment plans vary according to grade of glioma detected. This results in need of precise glioma grading. As per World Health Organization, biopsy is considered to be gold standard in glioma grading. Biopsy is an invasive procedure which may contains sampling errors. Biopsy may also contain subjectivity errors. This motivated the clinician to look for other methods which may overcome the limitations of biopsy reports. Machine learning and deep learning approaches using MRI is considered to be most promising alternative approach reported by scientist in literature. The presented work were based on the concept of AdaBoost approach which is an ensemble learning approach. The developed model was optimized w.r.t to two hyper parameters i.e. no. of estimators and learning rate keeping the base model fixed. The decision tree was used as a base model. The proposed developed model was trained and validated on BraTS 2018 dataset. The developed optimized model achieves reasonable accuracy in carrying out classification task i.e. high grade glioma vs. low grade glioma. Keywords: High grade glioma, low grade glioma, AdaBoost, Texture Features,

Brain Tumor Classification into High Grade and Low Grade Gliomas

2019 ◽  
pp. 785-790
Author(s):  
Sanjeet Pandey ◽  
Brijesh Bharadwaj ◽  
Himanshu Pandey ◽  
Vineet Kr. Singh
Keyword(s):  
Invasive Procedure ◽  
High Grade Glioma ◽  
Low Grade Glioma ◽  
World Health ◽  
Low Grade ◽  
High Grade ◽  
Learning Approaches ◽  
Sampling Errors ◽  
Promising Alternative ◽  
Glioma Grading

Brain is recognized as one of the complex organ of the human body. Abnormal formation of cells may affect the normal functioning of the brain. These abnormal cells may belong to category of benign cells resulting in low grade glioma or malignant cells resulting in high grade glioma. The treatment plans vary according to grade of glioma detected. This results in need of precise glioma grading. As per World Health Organization, biopsy is considered to be gold standard in glioma grading. Biopsy is an invasive procedure which may contains sampling errors. Biopsy may also contain subjectivity errors. This motivated the clinician to look for other methods which may overcome the limitations of biopsy reports. Machine learning and deep learning approaches using MRI is considered to be most promising alternative approach reported by scientist in literature. The presented work were based on the concept of AdaBoost approach which is an ensemble learning approach. The developed model was optimized w.r.t to two hyper parameters i.e. no. of estimators and learning rate keeping the base model fixed. The decision tree was us ed as a base model. The proposed developed model was trained and validated on BraTS 2018 dataset. The developed optimized model achieves reasonable accuracy in carrying out classification task i.e. high grade glioma vs. low grade glioma.

scholarly journals Survival and low-grade glioma: the emergence of genetic information

2015 ◽  
Vol 38 (1) ◽  
pp. E6 ◽  
Author(s):  
Elizabeth B. Claus ◽  
Kyle M. Walsh ◽  
John K. Wiencke ◽  
Annette M. Molinaro ◽  
Joseph L. Wiemels ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Young Patients ◽  
High Grade Glioma ◽  
The United States ◽  
Low Grade Glioma ◽  
World Health ◽  
Low Grade ◽  
High Grade ◽  
Who Grade ◽  
Health Organization

Significant gaps exist in our understanding of the causes and clinical management of glioma. One of the biggest gaps is how best to manage low-grade (World Health Organization [WHO] Grade II) glioma. Low-grade glioma (LGG) is a uniformly fatal disease of young adults (mean age 41 years), with survival averaging approximately 7 years. Although LGG patients have better survival than patients with high-grade (WHO Grade III or IV) glioma, all LGGs eventually progress to high-grade glioma and death. Data from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute suggest that for the majority of LGG patients, overall survival has not significantly improved over the past 3 decades, highlighting the need for intensified study of this tumor. Recently published research suggests that historically used clinical variables are not sufficient (and are likely inferior) prognostic and predictive indicators relative to information provided by recently discovered tumor markers (e.g., 1p/19q deletion and IDH1 or IDH2 mutation status), tumor expression profiles (e.g., the proneural profile) and/or constitutive genotype (e.g., rs55705857 on 8q24.21). Discovery of such tumor and constitutive variation may identify variables needed to improve randomization in clinical trials as well as identify patients more sensitive to current treatments and targets for improved treatment in the future. This article reports on survival trends for patients diagnosed with LGG within the United States from 1973 through 2011 and reviews the emerging role of tumor and constitutive genetics in refining risk stratification, defining targeted therapy, and improving survival for this group of relatively young patients.

scholarly journals SURG-32. THE USE OF 5-AMINOLEVULINIC ACID IN LOW-GRADE GLIOMA RESECTION: A SYSTEMATIC REVIEW

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi246-vi246
Author(s):  
Ahmad Almekkawi ◽  
Tarek El Ahmadieh ◽  
Karl Abi-Aad ◽  
Salah Aoun ◽  
Najib EL Tecle ◽  
...  
Keyword(s):  
Systematic Review ◽  
Quality Index ◽  
Aminolevulinic Acid ◽  
High Grade Glioma ◽  
Extent Of Resection ◽  
Low Grade Glioma ◽  
Low Grade ◽  
High Grade ◽  
Visualization Technology ◽  
Glioma Resection

Abstract BACKGROUND 5-aminolevulinic acid is a reliable tool for optimizing high-grade glioma resection. However, its efficacy in low-grade glioma resection remains unclear. OBJECTIVE To study the role of 5-aminolevulinic acid in low-grade glioma resection and assess positive fluorescence rates and effect on the extent of resection. METHODS A systematic review of PubMed, Google Scholar, and Cochrane was performed from the date of inception to February 1, 2019. Studies that correlated 5-aminolevulinic acid fluorescence with low-grade glioma in the setting of operative resection were selected. Studies with biopsy only were excluded. Positive fluorescence rates were calculated. Quality index of the selected papers using the Downs and Black criteria checklist was provided. RESULTS Twelve articles met the selection criteria with 244 histologically-confirmed low-grade glioma patients who underwent microsurgical resection. All patients received 20 mg/kg body weight of 5-aminolevulinic acid. Only 60 patients (n=60/244; 24.5%) demonstrated visual intra-operative 5-aminolevulinic acid fluorescence. The extent of resection was reported in 4 studies, however, the data combined low- and high-grade tumors. Only 2 studies reported on tumor location. Only 3 studies reported on clinical outcomes. The Zeiss OPMI Pentero microscope was most commonly used across all studies. The average quality index was 14.58 (range: 10–17) which correlated with an overall good quality. CONCLUSION There is an overall low correlation between 5-aminolevulinic acid fluorescence and low-grade glioma. Advances in visualization technology and using standardized fluorescence quantification methods may further improve the visualization and reliability of 5-aminolevulinic acid fluorescence in low-grade glioma resection.

scholarly journals Homotopic functional connectivity disruptions in glioma patients are associated with tumor malignancy and overall survival

2021 ◽  
Author(s):  
Andy G S Daniel ◽  
Carl D Hacker ◽  
John J Lee ◽  
Donna Dierker ◽  
Joseph B Humphries ◽  
...  
Keyword(s):  
Overall Survival ◽  
Functional Connectivity ◽  
Healthy Subjects ◽  
High Grade Glioma ◽  
Tumor Grade ◽  
World Health ◽  
Low Grade ◽  
High Grade ◽  
Healthy Controls ◽  
Who Grade

Abstract Background Gliomas exhibit widespread bilateral functional connectivity (FC) alterations that may be associated with tumor grade. Limited studies have examined the connection-level mechanisms responsible for these effects. Given the typically strong FC observed between mirroring/homotopic brain regions in healthy subjects, we hypothesized that homotopic connectivity (HC) is altered in low-grade and high-grade glioma patients and the extent of disruption is associated with tumor grade and predictive of overall survival (OS) in a cohort of de novo high-grade glioma (World Health Organization [WHO] grade 4) patients. Methods We used a mirrored FC-derived cortical parcellation to extract blood-oxygen-level-dependent (BOLD) signals and to quantify FC differences between homotopic pairs in normal-appearing brain in a retrospective cohort of glioma patients and healthy controls. Results Fifty-nine glioma patients (WHO grade 2, n = 9; grade 4 = 50; mean age, 57.5 years) and thirty healthy subjects (mean age, 65.9 years) were analyzed. High-grade glioma patients showed lower HC compared to low-grade glioma patients and healthy controls across several cortical locations and resting-state networks. Connectivity disruptions were also strongly correlated with hemodynamic lags between homotopic regions. Finally, in high-grade glioma patients with known survival times (n = 42), HC in somatomotor and dorsal attention networks were significantly correlated with OS. Conclusions These findings demonstrate an association between tumor grade and HC alterations that may underlie global FC changes and provide prognostic information.

Diffusion Weighted Imaging of Brain Gliomas in the Differential Diagnosis Value

2020 ◽  
Author(s):  
Jian JIANG ◽  
Liangcai BAI ◽  
Xueling ZHANG ◽  
Jianli LIU ◽  
Junlin ZHOU
Keyword(s):  
Brain Metastases ◽  
Diffusion Weighted Imaging ◽  
High Grade Glioma ◽  
Low Grade Glioma ◽  
Control Group ◽  
Low Grade ◽  
High Grade ◽  
Imaging Data ◽  
Grade Group ◽  
Diffusion Weighted

Background: To evaluate the diagnostic value of diffusion weighted imaging (DWI) and apparent diffusion coefficient measurement (ADC) in glioma. cient measurement (ADC) in glioma. Methods: Thirty two low-grade glioma patients and 31 high-grade glioma patients who were confirmed by pathology in Lanzhou University Second Hospital, Lanzhou, China from February 2016 to January 2019 were selected. The other 30 patients with brain metastases were selected as a control group. DWI imaging data of the three groups were collected, and ADC, relative ADC (rADC) values in tumor parenchyma, peritumor edema area, and contralateral normal white matter area were measured, and the levels of n-acetyl aspartic acid (NAA), choline (Cho), creatine (Cr) of tumor metabolites were analyzed. Results: rADC values in the peri-tumor edema areas of the high-grade glioma group were significantly lower than those in the low-grade group and the metastatic group （P=0.011）, and the low-grade group was significantly lower than that in the metastatic group (P < 0.05). NAA/Cho and NAA/Cr in parenchymal and peritumor edema areas of patients in the advanced group were significantly lower than those in the metastatic group (P < 0.05), and Cho /Cr was significantly higher than those in the metastatic group (P < 0.05). Conclusion: the rADC value, NAA/Cho, NAA/Cr and Cho/Cr in parenchymal and peritumor edema areas of the tumor can help to distinguish high-grade glioma, low-grade glioma and brain metastases.

Long-term outcomes after irradiation (RT) for pediatric low-grade glioma.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 10549-10549
Author(s):  
Derek S. Tsang ◽  
Erin Sennett Murphy ◽  
Thomas E. Merchant
Keyword(s):  
Systemic Therapy ◽  
Cumulative Incidence ◽  
High Grade Glioma ◽  
Tumor Location ◽  
Low Grade Glioma ◽  
Low Grade ◽  
High Grade ◽  
Who Grade ◽  
Extent Of Surgery

10549 Background: Treatment for pediatric low-grade glioma (LGG) is variable, depending on age and tumor location. Systemic therapy (ST) is often used to delay RT, but ST does not result in durable local control. The goal of this study was to evaluate event-free survival (EFS) and toxicities for pediatric LGG treated with RT over a 30-year period. Methods: All patients age ≤21 with intracranial pediatric LGG (WHO grade I-II) treated with RT at a single institution since May 1986 were included in this retrospective review. Patients with metastatic disease (M+) received craniospinal irradiation (CSI); otherwise, RT was conformal. EFS and overall survival (OS) were measured from the first day of RT. Events included death, progression, or secondary high-grade glioma. Results: 221 patients were eligible. Median follow-up was 11.3 yrs (range, 0.1-30.5). Median RT dose was 54 Gy. 10-yr EFS and OS were 67.9% (95% CI 60.4-74.3) and 91.1% (95% CI 85.8-94.5) for non-metastatic patients, respectively. For 12 M+ patients treated with CSI, 10-yr EFS and OS were 58.9% (95% CI 23.4-82.5) and 70.0% (32.9-89.2), respectively. 28.6% developed pseudoprogression (PP) with median time to onset and resolution of 6.1 months (IQR 3.6-14.6) and 6.4 months (IQR 3.5-11.7), respectively. Patients with PP had improved 10-yr EFS (83.4% vs. 61.0%, HR 0.40, p = .006). Patients with grade II tumors and who received pre-RT ST had lower EFS (Table). Sex, NF-1, tumor location, extent of surgery and CSI were not independently associated with EFS. 10-yr cumulative incidence of grade ≥2 vasculopathy was 7.5% (95% CI 4.9-11.4). There were 12 cases of secondary high-grade glioma, with a 20-yr cumulative incidence of 5.5% (95% CI 2.6-11.4). Conclusions: Irradiation provides long-term control of pediatric LGG in a majority of patients. Receipt of pre-RT systemic therapy was associated with reduced EFS; this association requires further investigation. [Table: see text]

scholarly journals Using of Laplacian Re-decomposition image fusion algorithm for glioma grading with SWI, ADC, and FLAIR images

2021 ◽  
Vol 27 (4) ◽  
pp. 261-269
Author(s):  
Amir Khorasani ◽  
Mohamad Bagher Tavakoli ◽  
Masih Saboori
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
High Grade Glioma ◽  
Low Grade ◽  
High Grade ◽  
Fusion Algorithm ◽  
Medical Image Fusion ◽  
Glioma Grading ◽  
Adc Map ◽  
Glioma Differentiation

Abstract Introduction: Based on the tumor’s growth potential and aggressiveness, glioma is most often classified into low or high-grade groups. Traditionally, tissue sampling is used to determine the glioma grade. The aim of this study is to evaluate the efficiency of the Laplacian Re-decomposition (LRD) medical image fusion algorithm for glioma grading by advanced magnetic resonance imaging (MRI) images and introduce the best image combination for glioma grading. Material and methods: Sixty-one patients (17 low-grade and 44 high-grade) underwent Susceptibility-weighted image (SWI), apparent diffusion coefficient (ADC) map, and Fluid attenuated inversion recovery (FLAIR) MRI imaging. To fuse different MRI image, LRD medical image fusion algorithm was used. To evaluate the effectiveness of LRD in the classification of glioma grade, we compared the parameters of the receiver operating characteristic curve (ROC). Results: The average Relative Signal Contrast (RSC) of SWI and ADC maps in high-grade glioma are significantly lower than RSCs in low-grade glioma. No significant difference was detected between low and high-grade glioma on FLAIR images. In our study, the area under the curve (AUC) for low and high-grade glioma differentiation on SWI and ADC maps were calculated at 0.871 and 0.833, respectively. Conclusions: By fusing SWI and ADC map with LRD medical image fusion algorithm, we can increase AUC for low and high-grade glioma separation to 0.978. Our work has led us to conclude that, by fusing SWI and ADC map with LRD medical image fusion algorithm, we reach the highest diagnostic accuracy for low and high-grade glioma differentiation and we can use LRD medical fusion algorithm for glioma grading.

Temozolomide after Radiotherapy for Newly Diagnosed High-grade Glioma and Unfavorable Low-grade Glioma in Children

2005 ◽  
Vol 76 (3) ◽  
pp. 313-319 ◽  
Author(s):  
Alberto Broniscer ◽  
Murali Chintagumpala ◽  
Maryam Fouladi ◽  
Matthew J. Krasin ◽  
Mehmet Kocak ◽  
...  
Keyword(s):  
High Grade Glioma ◽  
Low Grade Glioma ◽  
Low Grade ◽  
High Grade ◽  
Newly Diagnosed
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