Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, No. 37, Guo Xue Xiang, Chengdu, Sichuan, 610041, China.
Radiat Oncol. 2017 Sep 15;12(1):154. doi: 10.1186/s13014-017-0885-x.
Since the discovery of X-rays at the end of the 19 century, medical imageology has progressed for 100 years, and medical imaging has become an important auxiliary tool for clinical diagnosis. With the launch of the human genome project (HGP) and the development of various high-throughput detection techniques, disease exploration in the post-genome era has extended beyond investigations of structural changes to in-depth analyses of molecular abnormalities in tissues, organs and cells, on the basis of gene expression and epigenetics. These techniques have given rise to genomics, proteomics, metabolomics and other systems biology subspecialties, including radiogenomics. Radiogenomics is an important revolution in the traditional visually identifiable imaging technology and constitutes a new branch, radiomics. Radiomics is aimed at extracting quantitative imaging features automatically and developing models to predict lesion phenotypes in a non-invasive manner. Here, we summarize the advent and development of radiomics, the basic process and challenges in clinical practice, with a focus on applications in pulmonary nodule evaluations, including diagnostics, pathological and molecular classifications, treatment response assessments and prognostic predictions, especially in radiotherapy.
自 19 世纪末发现 X 射线以来,医学影像学已经发展了 100 年,医学成像已成为临床诊断的重要辅助工具。随着人类基因组计划(HGP)的启动和各种高通量检测技术的发展,后基因组时代的疾病研究已经超越了对结构变化的探索,深入到组织、器官和细胞的分子异常分析,基于基因表达和表观遗传学。这些技术催生了基因组学、蛋白质组学、代谢组学等系统生物学分支,包括放射组学。放射组学是传统视觉可识别成像技术的重要革命,构成了一个新的分支,即放射组学。放射组学旨在自动提取定量成像特征,并开发模型以无创方式预测病变表型。在这里,我们总结了放射组学的出现和发展,以及其在临床实践中的基本过程和挑战,重点介绍了在肺结节评估中的应用,包括诊断、病理和分子分类、治疗反应评估和预后预测,特别是在放射治疗中。