——基于领域的放射组学与放射基因组学新前沿：2021年WHO CNS-5更新后分子诊断在中枢神经系统肿瘤分类和分级中的作用不断增强
-New frontiers in domain-inspired radiomics and radiogenomics: increasing role of molecular diagnostics in CNS tumor classification and grading following WHO CNS-5 updates
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影响因子:3.5
分区:医学2区 / 肿瘤学2区 核医学2区
发表日期:2024 Oct 07
作者:
Gagandeep Singh, Annie Singh, Joseph Bae, Sunil Manjila, Vadim Spektor, Prateek Prasanna, Angela Lignelli
DOI:
10.1186/s40644-024-00769-6
摘要
胶质瘤和胶质母细胞瘤占中枢神经系统（CNS）肿瘤的重要部分，伴随高死亡率和预后差异。2021年，世界卫生组织（WHO）更新了胶质瘤分类标准，特别引入了包括CDKN2A/B纯合缺失、TERT启动子突变、EGFR扩增、+ 7/-10染色体拷贝数变化等分子标志物，用于成人和儿童胶质瘤的分级与分类。这些标志物的引入以及新胶质瘤亚型的定义，使临床干预更加个性化，并激发了一波放射基因组学研究，旨在利用医学影像信息探索这些新型生物标志物的诊断和预后意义。放射组学、深度学习及多模态方法已开发出强大的计算工具，用于MRI分析，关联影像特征与整合到更新的WHO CNS-5指南中的多种分子生物标志物。最新研究利用这些方法，仅通过非侵入性MRI，精准分类胶质瘤，显示出放射基因组学工具的巨大潜力。本文综述了这些计算框架的优缺点，强调了近期研究在快速发展的分子基础胶质瘤亚型划分中的技术和临床创新。此外，还探讨了将这些工具融入常规放射学流程的潜在益处与挑战，以提升患者护理和优化中枢神经系统肿瘤管理的临床结果。
Abstract
Gliomas and Glioblastomas represent a significant portion of central nervous system (CNS) tumors associated with high mortality rates and variable prognosis. In 2021, the World Health Organization (WHO) updated its Glioma classification criteria, most notably incorporating molecular markers including CDKN2A/B homozygous deletion, TERT promoter mutation, EGFR amplification, + 7/-10 chromosome copy number changes, and others into the grading and classification of adult and pediatric Gliomas. The inclusion of these markers and the corresponding introduction of new Glioma subtypes has allowed for more specific tailoring of clinical interventions and has inspired a new wave of Radiogenomic studies seeking to leverage medical imaging information to explore the diagnostic and prognostic implications of these new biomarkers. Radiomics, deep learning, and combined approaches have enabled the development of powerful computational tools for MRI analysis correlating imaging characteristics with various molecular biomarkers integrated into the updated WHO CNS-5 guidelines. Recent studies have leveraged these methods to accurately classify Gliomas in accordance with these updated molecular-based criteria based solely on non-invasive MRI, demonstrating the great promise of Radiogenomic tools. In this review, we explore the relative benefits and drawbacks of these computational frameworks and highlight the technical and clinical innovations presented by recent studies in the landscape of fast evolving molecular-based Glioma subtyping. Furthermore, the potential benefits and challenges of incorporating these tools into routine radiological workflows, aiming to enhance patient care and optimize clinical outcomes in the evolving field of CNS tumor management, have been highlighted.