Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research. Radiomic analysis exploits sophisticated image analysis tools and the rapid development and validation of medical imaging data that uses image-based signatures for precision diagnosis and treatment, providing a powerful tool in modern medicine. Herein, we describe the process of radiomics, its pitfalls, challenges, opportunities, and its capacity to improve clinical decision making, emphasizing the utility for patients with cancer. Currently, the field of radiomics lacks standardized evaluation of both the scientific integrity and the clinical relevance of the numerous published radiomics investigations resulting from the rapid growth of this area. Rigorous evaluation criteria and reporting guidelines need to be established in order for radiomics to mature as a discipline. Herein, we provide guidance for investigations to meet this urgent need in the field of radiomics.

Radiomics是一种高通量的，可以从照护标准医学影像中定量图像特征的挖掘方法，可以在临床决策支持系统中提取并应用数据，以改善诊断，预后和预测的准确性，在癌症研究中正变得越来越重要。放射分析利用先进的图像分析工具以及利用基于图像的签名进行精确诊断和治疗的医学成像数据的快速开发和验证，为现代医学提供了强大的工具。在这里，我们描述了放射学的过程，陷阱，挑战，机遇以及其改善临床决策的能力，强调了对癌症患者的效用。目前，由于该领域的迅速发展，放射线学领域缺乏对科学完整性和临床相关性的标准化评估，因为该领域已发表了许多已发表的放射线学研究。为了使放射线学成为一门学科，需要建立严格的评估标准和报告指南。在此，我们为满足放射线学领域这一迫切需求的研究提供指导。