Lambin et al. introduced the term radiomics in 2012 (1) to describe the extraction of biologically relevant quantitative features from radiological images. They suggested that radiomic features (RFs), the invisible tissue infrastructural components of the objects being imaged, might be a valuable way to study cancer using computed tomography (CT) and other modalities. Such imaging studies are easily repeated and provide in vivo visualization and quantitative analysis of RFs throughout an imaged mass. Thus, they could support a personalized precision medicine approach to cancer diagnosis and serial assessment and prediction of response to treatment. Even so, radiomics has not evolved into a widely used, reliable component of cancer evaluation. The complicated nature of radiomics and its validation have raised questions, as have the reproducibility and generalizability of texture analysis and other fundamental components of the radiomics signature (2). In this issue of the Journal, Dercle et al. (3) demonstrated progress in several aspects of cancer analysis by radiomics and provided insights into future validation work.

中文翻译：

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放射性化合物的发展状况。

Lambin等。介绍了术语radimics2012年（1）描述了从放射影像中提取生物学相关的定量特征。他们认为，放射学特征（RFs）是要成像的物体的不可见组织基础设施，可能是使用计算机断层扫描（CT）和其他方式研究癌症的一种有价值的方法。这种成像研究很容易重复，并且可以在整个成像过程中对RF进行体内可视化和定量分析。因此，他们可以支持个性化的精密医学方法来进行癌症诊断，系列评估以及对治疗反应的预测。即使这样，放射线学还没有发展成为癌症评估中广泛使用的可靠组件。放射性化合物的复杂性质及其验证提出了疑问，具有质构分析和放射性标记特征的其他基本组成部分的可重复性和通用性（2）。在本期杂志中，Dercle等人。（3）通过放射线学证明了癌症分析在多个方面的进展，并为以后的验证工作提供了见识。