UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers (CVIB), David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA,
Curr Neurol Neurosci Rep. 2015 Jan;15(1):506. doi: 10.1007/s11910-014-0506-0.
Radiogenomics is a provocative new area of research based on decades of previous work examining the association between radiological and histological features. Many generalized associations have been established linking anatomical imaging traits with underlying histopathology, including associations between contrast-enhancing tumor and vascular and tumor cell proliferation, hypointensity on pre-contrast T1-weighted images and necrotic tissue, and associations between hyperintensity on T2-weighted images and edema or nonenhancing tumor. Additionally, tumor location, tumor size, composition, and descriptive features tend to show significant associations with molecular and genomic factors, likely related to the cell of origin and growth characteristics. Additionally, physiologic MRI techniques also show interesting correlations with underlying histology and genomic programs, including associations with gene expression signatures and histological subtypes. Future studies extending beyond simple radiology-histology associations are warranted in order to establish radiogenomic analyses as tools for prospectively identifying patient subtypes that may benefit from specific therapies.
放射组学是一个令人兴奋的新研究领域,其建立在几十年来对放射学和组织学特征之间关联的研究基础上。已经建立了许多与解剖成像特征与潜在组织病理学相关的普遍关联,包括增强肿瘤与血管和肿瘤细胞增殖之间的关联、增强前 T1 加权图像上的低信号与坏死组织之间的关联、T2 加权图像上的高信号与水肿或无强化肿瘤之间的关联。此外,肿瘤位置、肿瘤大小、成分和描述性特征往往与分子和基因组因素表现出显著的关联,这可能与起源细胞和生长特征有关。此外,生理 MRI 技术也与潜在的组织学和基因组程序显示出有趣的相关性,包括与基因表达特征和组织学亚型的关联。为了将放射基因组学分析确立为预测性识别可能受益于特定治疗的患者亚群的工具,需要进行超越简单放射学-组织学关联的未来研究。