Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Department of Diagnostic Imaging, The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Methods. 2021 Apr;188:84-97. doi: 10.1016/j.ymeth.2020.05.023. Epub 2020 Jun 1.
Lung cancer is the most common cancer, worldwide, and a major health issue with a remarkable mortality rate. 2-[F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[F]FDG PET/CT) plays an indispensable role in the management of lung cancer patients. Long-established quantitative parameters such as size, density, and metabolic activity have been and are being employed in the current practice to enhance interpretation and improve diagnostic and prognostic value. The introduction of radiomics analysis revolutionized the quantitative evaluation of medical imaging, revealing data within images beyond visual interpretation. The "big data" are extracted from high-quality images and are converted into information that correlates to relevant genetic, pathologic, clinical, or prognostic features. Technically advanced, diverse methods have been implemented in different studies. The standardization of image acquisition, segmentation and features analysis is still a debated issue. Importantly, a body of features has been extracted and employed for diagnosis, staging, risk stratification, prognostication, and therapeutic response. 2-[F]FDG PET/CT-derived features show promising value in non-invasively diagnosing the malignant nature of pulmonary nodules, differentiating lung cancer subtypes, and predicting response to different therapies as well as survival. In this review article, we aimed to provide an overview of the technical aspects used in radiomics analysis in non-small cell lung cancer (NSCLC) and elucidate the role of 2-[F]FDG PET/CT-derived radiomics in the diagnosis, prognostication, and therapeutic response.
肺癌是全球最常见的癌症,也是一个重大的健康问题,死亡率极高。2-[F]氟代-2-脱氧-D-葡萄糖正电子发射断层扫描/计算机断层扫描(2-[F]FDG PET/CT)在肺癌患者的管理中发挥着不可或缺的作用。长期以来,大小、密度和代谢活性等定量参数一直被用于当前的实践中,以增强解释并提高诊断和预后价值。放射组学分析的引入彻底改变了医学成像的定量评估,揭示了图像中超出视觉解释的数据。“大数据”从高质量的图像中提取出来,并转化为与相关遗传、病理、临床或预后特征相关的信息。不同的研究中已经实施了技术先进、多样化的方法。图像采集、分割和特征分析的标准化仍然是一个有争议的问题。重要的是,已经提取并用于诊断、分期、风险分层、预后和治疗反应的特征体已经被提取并应用。2-[F]FDG PET/CT 衍生的特征在非侵入性诊断肺结节的恶性性质、区分肺癌亚型以及预测对不同治疗方法的反应和生存方面显示出有希望的价值。在这篇综述文章中,我们旨在概述非小细胞肺癌(NSCLC)中放射组学分析中使用的技术方面,并阐明 2-[F]FDG PET/CT 衍生的放射组学在诊断、预后和治疗反应中的作用。