Hexem Eric, Taha Taha Abd-ElSalam Ashraf, Dhemesh Yaseen, Baqar Mohammad Aneel, Nada Ayman
University of Missouri-Columbia Diagnostic Radiology Department, Columbia, MO, United States.
Faculty of Medicine, Fayoum University, Egypt.
Curr Probl Cancer. 2025 Feb;54:101156. doi: 10.1016/j.currproblcancer.2024.101156. Epub 2024 Nov 11.
Glioblastoma, the most common primary malignant tumor of the central nervous system in adults, is also among the most lethal. Despite a comprehensive treatment approach which utilizes surgery and postoperative chemoradiation, prognosis typically remains dismal. However certain epigenetic modifications, such as methylation of the MGMT promoter, have been proven to correlate with improved post-treatment outcomes. The 2021 WHO classification emphasizes molecular characteristics, highlighting shared genomic alterations across different grades and positioning MGMT methylation as a key influencer of outcomes. A combined diagnostic approach involving current imaging technology and emerging radiomics and deep learning models may allow for timely and accurate prediction of MGMT methylation status and therefore earlier and more individualized treatment and prognostication. Though these advanced radiomics models are rapidly emerging, additional development, standardization, and implementation may lead to a higher and more individualized level of patient care. This review explores the potential of imaging features in predicting MGMT promoter methylation, a critical determinant of therapeutic response and patient outcomes.
胶质母细胞瘤是成人中枢神经系统最常见的原发性恶性肿瘤,也是最致命的肿瘤之一。尽管采用了包括手术及术后放化疗的综合治疗方法,但预后通常仍然很差。然而,某些表观遗传修饰,如MGMT启动子甲基化,已被证明与治疗后改善的结果相关。2021年世界卫生组织分类强调分子特征,突出了不同级别之间共享的基因组改变,并将MGMT甲基化定位为结果的关键影响因素。一种结合当前成像技术以及新兴的放射组学和深度学习模型的联合诊断方法,可能有助于及时、准确地预测MGMT甲基化状态,从而实现更早、更个性化的治疗和预后评估。尽管这些先进的放射组学模型正在迅速兴起,但进一步的开发、标准化和实施可能会带来更高水平、更个性化的患者护理。本综述探讨了成像特征在预测MGMT启动子甲基化方面的潜力,MGMT启动子甲基化是治疗反应和患者预后的关键决定因素。