Glioma Image Analysis to Accurately Classify Mgmt and Predict Drug Effectiveness

V. Mehta
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Abstract

Glioblastoma multiforme is a deadly brain cancer with a median patient survival time of 18-24 months. A single biopsy cannot provide complete assessment of the tumor’s microenvironment, making personalized care limited. 50% of the patients do not respond to the anti-cancer drug Temozolomide(TMZ) because of the over-expression of MGMT gene. Epigenetic silencing of the MGMT gene by methylation results in decreased MGMT expression, resulting in increased sensitivity to TMZ, and longer survival. The purpose of this research is to use artificial intelligence (AI) to design a low cost methodology to determine the MGMT’s methylation status and suggest non- invasive treatment plan
神经胶质瘤图像分析准确分类Mgmt和预测药物有效性
多形性胶质母细胞瘤是一种致命的脑癌,患者的中位生存时间为18-24个月。单个活检不能提供肿瘤微环境的完整评估,使得个性化护理受到限制。50%的患者对抗癌药物替莫唑胺(TMZ)无应答,原因是MGMT基因过表达。通过甲基化使MGMT基因表观遗传沉默导致MGMT表达减少,从而增加对TMZ的敏感性,延长生存期。本研究的目的是利用人工智能(AI)设计一种低成本的方法来确定MGMT的甲基化状态,并提出无创治疗方案
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