RESUMO
INTRODUCTION: The challenge of treating Glioblastoma (GBM) tumors is due to various mechanisms that make the tumor resistant to radiation therapy. One of these mechanisms is hypoxia, and therefore, determining the level of hypoxia can improve treatment planning and initial evaluation of its effectiveness in GBM. This study aimed to design an intelligent system to classify glioblastoma patients based on hypoxia levels obtained from magnetic resonance images with the help of an artificial neural network (ANN). MATERIAL AND METHOD: MR images and PET measurements were available for this study. MR images were downloaded from the Cancer Imaging Archive (TCIA) database to classify glioblastoma patients based on hypoxia. The images in this database were prepared from 27 patients with glioblastoma on T1W + Gd, T2W-FLAIR, and T2W. Our designed algorithm includes various parts of pre-processing, tumor segmentation, feature extraction from images, and matching these features with quantitative parameters related to hypoxia in PET images. The system's performance is evaluated by categorizing glioblastoma patients based on hypoxia. RESULTS: The results of classification with the artificial neural network (ANN) algorithm were as follows: the highest sensitivity, specificity, and accuracy were obtained at 86.71, 85.99 and 83.17%, respectively. The best specificity was related to the T2W-EDEMA image with the tumor to blood ratio (TBR) as a hypoxia parameter. T1W-NECROSIS image with the TBR parameter also showed the highest sensitivity and accuracy. CONCLUSION: The results of the present study can be used in clinical procedures before treating glioblastoma patients. Among these treatment approaches, we can mention the radiotherapy treatment design and the prescription of effective drugs for the treatment of hypoxic tumors.
Assuntos
Neoplasias Encefálicas , Glioblastoma , Imageamento por Ressonância Magnética , Redes Neurais de Computação , Humanos , Glioblastoma/diagnóstico por imagem , Glioblastoma/patologia , Imageamento por Ressonância Magnética/métodos , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Feminino , Masculino , Pessoa de Meia-Idade , Hipóxia/diagnóstico por imagem , Tomografia por Emissão de Pósitrons/métodos , Algoritmos , Idoso , AdultoRESUMO
PURPOSE: Glioblastoma (GBM) is considered the most common and lethal type of brain tumor with a poor prognosis. GBM treatment has challenges due to its aggressive nature, which often causes treatment failure and recurrence. Hypoxia is one of the characteristics of glioblastoma tumors that contribute to radioresistance and malignant phenotypes of GBM. In this study, we aimed to determine the effects of hypoxia on the radiosensitivity of U87 GBM cells by the hypoxia-mimicking model. METHODS: Following the treatment of cells with different concentrations of CoCl2, an MTT assay was used to evaluate the cytotoxicity of CoCl2. To understand the effects of Ionizing radiation on CoCl2-treated groups, cells were exposed to irradiation after pretreating with 100 µM CoCl2, and a clonogenic survival assay was performed to determine the radiosensitivity of U87 cells. Also, the intracellular Reactive oxygen level was measured by 2',7'-dichlorofluorescein diacetate (DCFDA) probe staining. Additionally, the expression of hypoxia-associated genes, including HIF-1α, HIF-2α, and their target genes (GLUT-1), was monitored by reverse transcription polymerase chain reaction (RT-PCR). RESULTS: Our study revealed that the cell viability of CoCl2-treated cells was decreased in a concentration-dependent manner. Also, CoCl2 did not cause any cytotoxicity on U87 cells at a concentration of 100 µM after treatment for 24 h. Colony formation assay showed that CoCl2 pretreatment induced radioresistance of tumor cells compared to non-treated cells. Also, CoCl2 can protect cells against irradiation by the clearance of ROS. Moreover, Real-time results showed that the mRNA expression of HIF-1α and GLUT-1 were significantly upregulated following hypoxia induction and/or irradiation condition. However, the level of HIF-2α mRNA did not change significantly in hypoxia or irradiation alone conditions, but it increased significantly only in hypoxia + irradiation conditions. CONCLUSION: Taken together, our results indicated that simulating hypoxia by CoCl2 can effectively increase hypoxia-associated genes, specially HIF-1α and GLUT-1, but did not affect HIF-2α gene expression. Also, it can increase the clearance of ROS, respectively, and it leads to inducing radioresistance of U87 cells.
Assuntos
Cobalto , Glioblastoma , Tolerância a Radiação , Humanos , Glioblastoma/metabolismo , Glioblastoma/radioterapia , Glioblastoma/genética , Glioblastoma/patologia , Cobalto/farmacologia , Tolerância a Radiação/efeitos dos fármacos , Linhagem Celular Tumoral , Espécies Reativas de Oxigênio/metabolismo , Sobrevivência Celular/efeitos dos fármacos , Sobrevivência Celular/efeitos da radiação , Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Subunidade alfa do Fator 1 Induzível por Hipóxia/genética , Hipóxia Celular/efeitos dos fármacos , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Regulação Neoplásica da Expressão Gênica/efeitos da radiação , Neoplasias Encefálicas/metabolismo , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/radioterapia , Neoplasias Encefálicas/patologia , Fatores de Transcrição Hélice-Alça-Hélice Básicos/metabolismo , Fatores de Transcrição Hélice-Alça-Hélice Básicos/genéticaRESUMO
Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders. Brain mapping has shown that functional brain connections are altered in autism. This study investigated the pattern of brain connection changes in autistic people compared to healthy people. This study aimed to analyze functional abnormalities within the brain due to ASD, using resting-state functional magnetic resonance imaging (fMRI). Resting-state functional magnetic resonance images of 26 individuals with ASD and 26 healthy controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. The DPARSF (data processing assistant for resting-state fMRI) toolbox was used for resting-state functional image processing, and features related to functional connections were extracted from these images. Then, the extracted features from both groups were compared using an Independent Two-Sample T Test, and the features with significant differences between the two groups were identified. Compared with healthy controls, individuals with ASD showed hyper-connectivity in the frontal lobe, anterior cingulum, parahippocampal, left precuneus, angular, caudate, superior temporal, and left pallidum, as well as hypo-connectivity in the precentral, left superior frontal, left middle orbitofrontal, right amygdala, and left posterior cingulum. Our findings show that abnormal functional connectivity exists in patients with ASD. This study makes an important advancement in our understanding of the abnormal neurocircuits causing autism.