An application of neutrosophic hypersoft mapping to diagnose brain tumor and propose appropriate treatment

Brain tumors are one of the leading causes of death around the globe. More than 10 million people fall prey to it every year. This paper aims to characterize the discussions related to the diagnosis of tumors with their related problems. After examining the side effects of tumors, it encases similar indications, and it is hard to distinguish the precise type of tumors with their seriousness. Since in practical assessment, the indeterminacy and falsity parts are frequently dismissed, and because of this issue, it is hard to notice the precision in the patient’s progress history and cannot foresee the period of treatment. The Neutrosophic Hypersoft set (NHS) and the NHS mapping with its inverse mapping has been design to overcome this issue since it can deal with the parametric values of such disease in more detail considering the sub-parametric values; and their order and arrangement. These ideas are capable and essential to analyze the issue properly by interfacing it with scientific modeling. This investigation builds up a connection between symptoms and medicines, which diminishes the difficulty of the narrative. A table depending on a fuzzy interval between [0, 1] for the sorts of tumors is constructed. The calculation depends on NHS mapping to adequately recognize the disease and choose the best medication for each patient’s relating sickness. Finally, the generalized NHS mapping is presented, which will encourage a specialist to extricate the patient’s progress history and to foresee the time of treatment till the infection is relieved.

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Recent advancements in Fuzzy C-means based techniques for brain MRI Segmentation

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405616666210104111218 ◽

2021 ◽

Vol 16 ◽

Author(s):

Ghazanfar Latif ◽

Jaafar Alghazo ◽

Fadi N. Sibai ◽

D.N.F. Awang Iskandar ◽

Adil H. Khan

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Brain Mri ◽

Tumor Segmentation ◽

Brain Anatomy ◽

Mri Segmentation ◽

Brain Tumor Segmentation ◽

Brain Images ◽

Low Contrast ◽

Fuzzy C Means

Background: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques. Objective: In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review process, the concentration is on the use of FCM segmentation techniques for brain tumors. Brain tumor segmentation is a vital step in the process of automatically diagnosing brain tumors. Unlike segmentation of other types of images, brain tumor segmentation is a very challenging task due to the variations in brain anatomy. The low contrast of brain images further complicates this process. Early diagnosis of brain tumors is indeed beneficial to patients, doctors, and medical providers. Results: FCM segmentation works on images obtained from magnetic resonance imaging (MRI) scanners, requiring minor modifications to hospital operations to early diagnose tumors as most, if not all, hospitals rely on MRI machines for brain imaging. In this paper, we critically review and summarize FCM based techniques for brain MRI segmentation.

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Brain Tumor Detection via Asymmetry Quantification across Mid Sagittal Plane

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200831104047 ◽

2020 ◽

Vol 13 ◽

Author(s):

Shoaib Amin Banday ◽

Mohammad Khalid Pandit

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Sagittal Plane ◽

Early Stage ◽

Imaging Techniques ◽

Complex Structure ◽

Magnetic Resonance Images ◽

Absolute Difference ◽

Brain Hemispheres ◽

The Brain

Introduction: Brain tumor is among the major causes of morbidity and mortality rates worldwide. According to National Brain Tumor Foundation (NBTS), the death rate has nearly increased by as much as 300% over last couple of decades. Tumors can be categorized as benign (non-cancerous) and malignant (cancerous). The type of the brain tumor significantly depends on various factors like the site of its occurrence, its shape, the age of the subject etc. On the other hand, Computer Aided Detection (CAD) has been improving significantly in recent times. The concept, design and implementation of these systems ascend from fairly simple ones to computationally intense ones. For efficient and effective diagnosis and treatment plans in brain tumor studies, it is imperative that an abnormality is detected at an early stage as it provides a little more time for medical professionals to respond. The early detection of diseases has predominantly been possible because of medical imaging techniques developed from past many decades like CT, MRI, PET, SPECT, FMRI etc. The detection of brain tumors however, has always been a challenging task because of the complex structure of the brain, diverse tumor sizes and locations in the brain. Method: This paper proposes an algorithm that can detect the brain tumors in the presence of the Radio-Frequency (RF) inhomoginiety. The algorithm utilizes the Mid Sagittal Plane as a landmark point across which the asymmetry between the two brain hemispheres is estimated using various intensity and texture based parameters. Result: The results show the efficacy of the proposed method for the detection of the brain tumors with an acceptable detection rate. Conclusion: In this paper, we have calculated three textural features from the two hemispheres of the brain viz: Contrast (CON), Entropy (ENT) and Homogeneity (HOM) and three parameters viz: Root Mean Square Error (RMSE), Correlation Co-efficient (CC), and Integral of Absolute Difference (IAD) from the intensity distribution profiles of the two brain hemispheres to predict any presence of the pathology. First a Mid Sagittal Plane (MSP) is obtained on the Magnetic Resonance Images that virtually divides brain into two bilaterally symmetric hemispheres. The block wise texture asymmetry is estimated for these hemispheres using the above 6 parameters.

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Genetic variants and cognitive functions in patients with brain tumors

Neuro-Oncology ◽

10.1093/neuonc/noz094 ◽

2019 ◽

Vol 21 (10) ◽

pp. 1297-1309 ◽

Cited By ~ 5

Author(s):

Denise D Correa ◽

Jaya Satagopan ◽

Axel Martin ◽

Erica Braun ◽

Maria Kryza-Lacombe ◽

...

Keyword(s):

Oxidative Stress ◽

Cell Cycle ◽

Dna Repair ◽

Brain Tumor ◽

Brain Tumors ◽

Cell Cycle Regulation ◽

Cognitive Outcome ◽

Cholesterol Transport ◽

Tumor Patients ◽

Cycle Regulation

AbstractBackgroundPatients with brain tumors treated with radiotherapy (RT) and chemotherapy (CT) often experience cognitive dysfunction. We reported that single nucleotide polymorphisms (SNPs) in the APOE, COMT, and BDNF genes may influence cognition in brain tumor patients. In this study, we assessed whether genes associated with late-onset Alzheimer’s disease (LOAD), inflammation, cholesterol transport, dopamine and myelin regulation, and DNA repair may influence cognitive outcome in this population.MethodsOne hundred and fifty brain tumor patients treated with RT ± CT or CT alone completed a neurocognitive assessment and provided a blood sample for genotyping. We genotyped genes/SNPs in these pathways: (i) LOAD risk/inflammation/cholesterol transport, (ii) dopamine regulation, (iii) myelin regulation, (iv) DNA repair, (v) blood–brain barrier disruption, (vi) cell cycle regulation, and (vii) response to oxidative stress. White matter (WM) abnormalities were rated on brain MRIs.ResultsMultivariable linear regression analysis with Bayesian shrinkage estimation of SNP effects, adjusting for relevant demographic, disease, and treatment variables, indicated strong associations (posterior association summary [PAS] ≥ 0.95) among tests of attention, executive functions, and memory and 33 SNPs in genes involved in: LOAD/inflammation/cholesterol transport (eg, PDE7A, IL-6), dopamine regulation (eg, DRD1, COMT), myelin repair (eg, TCF4), DNA repair (eg, RAD51), cell cycle regulation (eg, SESN1), and response to oxidative stress (eg, GSTP1). The SNPs were not significantly associated with WM abnormalities.ConclusionThis novel study suggests that polymorphisms in genes involved in aging and inflammation, dopamine, myelin and cell cycle regulation, and DNA repair and response to oxidative stress may be associated with cognitive outcome in patients with brain tumors.

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Molecular Imaging of Brain Tumor-Associated Epilepsy

Diagnostics ◽

10.3390/diagnostics10121049 ◽

2020 ◽

Vol 10 (12) ◽

pp. 1049

Author(s):

Csaba Juhász ◽

Sandeep Mittal

Keyword(s):

Brain Tumor ◽

Amino Acid ◽

Brain Tumors ◽

Treatment Strategies ◽

Amino Acid Uptake ◽

Seizure Outcome ◽

Acid Uptake ◽

Positron Emission ◽

Oncology Practice ◽

Glioneuronal Tumors

Epilepsy is a common clinical manifestation and a source of significant morbidity in patients with brain tumors. Neuroimaging has a pivotal role in neuro-oncology practice, including tumor detection, differentiation, grading, treatment guidance, and posttreatment monitoring. In this review, we highlight studies demonstrating that imaging can also provide information about brain tumor-associated epileptogenicity and assist delineation of the peritumoral epileptic cortex to optimize postsurgical seizure outcome. Most studies focused on gliomas and glioneuronal tumors where positron emission tomography (PET) and advanced magnetic resonance imaging (MRI) techniques can detect metabolic and biochemical changes associated with altered amino acid transport and metabolism, neuroinflammation, and neurotransmitter abnormalities in and around epileptogenic tumors. PET imaging of amino acid uptake and metabolism as well as activated microglia can detect interictal or peri-ictal cortical increased uptake (as compared to non-epileptic cortex) associated with tumor-associated epilepsy. Metabolic tumor volumes may predict seizure outcome based on objective treatment response during glioma chemotherapy. Advanced MRI, especially glutamate imaging, can detect neurotransmitter changes around epileptogenic brain tumors. Recently, developed PET radiotracers targeting specific glutamate receptor types may also identify therapeutic targets for pharmacologic seizure control. Further studies with advanced multimodal imaging approaches may facilitate development of precision treatment strategies to control brain tumor-associated epilepsy.

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Is There a Relationship between the Elasticity of Brain Tumors, Changes in Diffusion Tensor Imaging, and Histological Findings? A Pilot Study Using Intraoperative Ultrasound Elastography

Brain Sciences ◽

10.3390/brainsci11020271 ◽

2021 ◽

Vol 11 (2) ◽

pp. 271

Author(s):

Santiago Cepeda ◽

Sergio García-García ◽

María Velasco-Casares ◽

Gabriel Fernández-Pérez ◽

Tomás Zamora ◽

...

Keyword(s):

Brain Tumor ◽

Diffusion Tensor Imaging ◽

Linear Regression ◽

Brain Tumors ◽

Diffusion Tensor ◽

Intraoperative Ultrasound ◽

Ultrasound Elastography ◽

Proliferation Index ◽

Strong Positive Correlation ◽

Non Linear

Intraoperative ultrasound elastography (IOUS-E) is a novel image modality applied in brain tumor assessment. However, the potential links between elastographic findings and other histological and neuroimaging features are unknown. This study aims to find associations between brain tumor elasticity, diffusion tensor imaging (DTI) metrics, and cell proliferation. A retrospective study was conducted to analyze consecutively admitted patients who underwent craniotomy for supratentorial brain tumors between March 2018 and February 2020. Patients evaluated by IOUS-E and preoperative DTI were included. A semi-quantitative analysis was performed to calculate the mean tissue elasticity (MTE). Diffusion coefficients and the tumor proliferation index by Ki-67 were registered. Relationships between the continuous variables were determined using the Spearman ρ test. A predictive model was developed based on non-linear regression using the MTE as the dependent variable. Forty patients were evaluated. The pathologic diagnoses were as follows: 21 high-grade gliomas (HGG); 9 low-grade gliomas (LGG); and 10 meningiomas. Cases with a proliferation index of less than 10% had significantly higher medians of MTE (110.34 vs. 79.99, p < 0.001) and fractional anisotropy (FA) (0.24 vs. 0.19, p = 0.020). We found a strong positive correlation between MTE and FA (rs (38) = 0.91, p < 0.001). A cubic spline non-linear regression model was obtained to predict tumoral MTE from FA (R2 = 0.78, p < 0.001). According to our results, tumor elasticity is associated with histopathological and DTI-derived metrics. These findings support the usefulness of IOUS-E as a complementary tool in brain tumor surgery.

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The Association of Human Herpesviruses with Malignant Brain Tumor Pathology and Therapy: Two Sides of a Coin

International Journal of Molecular Sciences ◽

10.3390/ijms22052250 ◽

2021 ◽

Vol 22 (5) ◽

pp. 2250

Author(s):

Evita Athanasiou ◽

Antonios N. Gargalionis ◽

Fotini Boufidou ◽

Athanassios Tsakris

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Comprehensive Evaluation ◽

Tumor Development ◽

Scientific Data ◽

Malignant Brain Tumor ◽

Direct Role ◽

Tumor Pathology ◽

Human Herpesviruses

The role of certain viruses in malignant brain tumor development remains controversial. Experimental data demonstrate that human herpesviruses (HHVs), particularly cytomegalovirus (CMV), Epstein–Barr virus (EBV) and human herpes virus 6 (HHV-6), are implicated in brain tumor pathology, although their direct role has not yet been proven. CMV is present in most gliomas and medulloblastomas and is known to facilitate oncomodulation and/or immunomodulation, thus promoting cancer cell proliferation, invasion, apoptosis, angiogenesis, and immunosuppression. EBV and HHV-6 have also been detected in brain tumors and high-grade gliomas, showing high rates of expression and an inflammatory potential. On the other hand, due to the neurotropic nature of HHVs, novel studies have highlighted the engagement of such viruses in the development of new immunotherapeutic approaches in the context of oncolytic viral treatment and vaccine-based strategies against brain tumors. This review provides a comprehensive evaluation of recent scientific data concerning the emerging dual role of HHVs in malignant brain pathology, either as potential causative agents or as immunotherapeutic tools in the fight against these devastating diseases.

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ETS-Domain Transcription Factor Elk-1 Regulates Stemness Genes in Brain Tumors and CD133+ BrainTumor-Initiating Cells

Journal of Personalized Medicine ◽

10.3390/jpm11020125 ◽

2021 ◽

Vol 11 (2) ◽

pp. 125

Author(s):

Melis Savasan Sogut ◽

Chitra Venugopal ◽

Basak Kandemir ◽

Ugur Dag ◽

Sujeivan Mahendram ◽

...

Keyword(s):

Transcription Factor ◽

Brain Tumor ◽

Brain Tumors ◽

System Development ◽

Nervous System Development ◽

Stem Cell Population ◽

Tumor Initiating Cells ◽

Specific Domain ◽

Brain Tumor Initiating Cells ◽

Ets Domain

Elk-1, a member of the ternary complex factors (TCFs) within the ETS (E26 transformation-specific) domain superfamily, is a transcription factor implicated in neuroprotection, neurodegeneration, and brain tumor proliferation. Except for known targets, c-fos and egr-1, few targets of Elk-1 have been identified. Interestingly, SMN, SOD1, and PSEN1 promoters were shown to be regulated by Elk-1. On the other hand, Elk-1 was shown to regulate the CD133 gene, which is highly expressed in brain-tumor-initiating cells (BTICs) and used as a marker for separating this cancer stem cell population. In this study, we have carried out microarray analysis in SH-SY5Y cells overexpressing Elk-1-VP16, which has revealed a large number of genes significantly regulated by Elk-1 that function in nervous system development, embryonic development, pluripotency, apoptosis, survival, and proliferation. Among these, we have shown that genes related to pluripotency, such as Sox2, Nanog, and Oct4, were indeed regulated by Elk-1, and in the context of brain tumors, we further showed that Elk-1 overexpression in CD133+ BTIC population results in the upregulation of these genes. When Elk-1 expression is silenced, the expression of these stemness genes is decreased. We propose that Elk-1 is a transcription factor upstream of these genes, regulating the self-renewal of CD133+ BTICs.

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Silencing ZEB2 Induces Apoptosis and Reduces Viability in Glioblastoma Cell Lines

Molecules ◽

10.3390/molecules26040901 ◽

2021 ◽

Vol 26 (4) ◽

pp. 901

Author(s):

Sahar Safaee ◽

Masoumeh Fardi ◽

Nima Hemmat ◽

Neda Khosravi ◽

Afshin Derakhshani ◽

...

Keyword(s):

Cell Cycle ◽

Brain Tumor ◽

Brain Tumors ◽

Cell Lines ◽

Scratch Test ◽

Cycle Arrest ◽

U373 Cell ◽

Brain Tumor Cell ◽

Induced Apoptosis ◽

Glioma Tumors

Background: Glioma is an aggressive type of brain tumor that originated from neuroglia cells, accounts for about 80% of all malignant brain tumors. Glioma aggressiveness has been associated with extreme cell proliferation, invasion of malignant cells, and resistance to chemotherapies. Due to resistance to common therapies, glioma affected patients’ survival has not been remarkably improved. ZEB2 (SIP1) is a critical transcriptional regulator with various functions during embryonic development and wound healing that has abnormal expression in different malignancies, including brain tumors. ZEB2 overexpression in brain tumors is attributed to an unfavorable state of the malignancy. Therefore, we aimed to investigate some functions of ZEB2 in two different glioblastoma U87 and U373 cell lines. Methods: In this study, we investigated the effect of ZEB2 knocking down on the apoptosis, cell cycle, cytotoxicity, scratch test of the two malignant brain tumor cell lines U87 and U373. Besides, we investigated possible proteins and microRNA, SMAD2, SMAD5, and miR-214, which interact with ZEB2 via in situ analysis. Then we evaluated candidate gene expression after ZEB2-specific knocking down. Results: We found that ZEB2 suppression induced apoptosis in U87 and U373 cell lines. Besides, it had cytotoxic effects on both cell lines and reduced cell migration. Cell cycle analysis showed cell cycle arrest in G0/G1 and apoptosis induction in U87 and U373 cell lines receptively. Also, we have found that SAMAD2/5 expression was reduced after ZEB2-siRNA transfection and miR-214 upregulated after transfection. Conclusions: In line with previous investigations, our results indicated a critical oncogenic role for ZEB2 overexpression in brain glioma tumors. These properties make ZEB2 an essential molecule for further studies in the treatment of glioma cancer.

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A pediatric brain tumor atlas of genes deregulated by somatic genomic rearrangement

Nature Communications ◽

10.1038/s41467-021-21081-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Yiqun Zhang ◽

Fengju Chen ◽

Lawrence A. Donehower ◽

Michael E. Scheurer ◽

Chad J. Creighton

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Tyrosine Kinases ◽

Pediatric Brain Tumor ◽

Pediatric Brain Tumors ◽

Altered Expression ◽

Critical Pathways ◽

Cis Regulation ◽

Or Gene ◽

Pediatric Brain

AbstractThe global impact of somatic structural variants (SSVs) on gene expression in pediatric brain tumors has not been thoroughly characterised. Here, using whole-genome and RNA sequencing from 854 tumors of more than 30 different types from the Children’s Brain Tumor Tissue Consortium, we report the altered expression of hundreds of genes in association with the presence of nearby SSV breakpoints. SSV-mediated expression changes involve gene fusions, altered cis-regulation, or gene disruption. SSVs considerably extend the numbers of patients with tumors somatically altered for critical pathways, including receptor tyrosine kinases (KRAS, MET, EGFR, NF1), Rb pathway (CDK4), TERT, MYC family (MYC, MYCN, MYB), and HIPPO (NF2). Compared to initial tumors, progressive or recurrent tumors involve a distinct set of SSV-gene associations. High overall SSV burden associates with TP53 mutations, histone H3.3 gene H3F3C mutations, and the transcription of DNA damage response genes. Compared to adult cancers, pediatric brain tumors would involve a different set of genes with SSV-altered cis-regulation. Our comprehensive and pan-histology genomic analyses reveal SSVs to play a major role in shaping the transcriptome of pediatric brain tumors.

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A Systems Approach to Brain Tumor Treatment

Cancers ◽

10.3390/cancers13133152 ◽

2021 ◽

Vol 13 (13) ◽

pp. 3152

Author(s):

James H. Park ◽

Adrian Lopez Garcia de Lomana ◽

Diego M. Marzese ◽

Tiffany Juarez ◽

Abdullah Feroze ◽

...

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Rational Design ◽

Clinical Medicine ◽

Systems Approach ◽

Therapy Resistance ◽

High Rate ◽

Intratumor Heterogeneity ◽

Primary Therapy ◽

Molecular Features

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood–brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice.

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