Lubner Meghan G
Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Sciences Center, 600 Highland Avenue, Madison, WI 53792, USA.
Radiol Clin North Am. 2020 Sep;58(5):995-1008. doi: 10.1016/j.rcl.2020.06.001. Epub 2020 Jul 16.
Radiomics allows for high throughput extraction of quantitative data from images. This is an area of active research as groups try to capture and quantify imaging parameters and convert these into descriptive phenotypes of organs or tumors. Texture analysis is one radiomics tool that extracts information about heterogeneity within a given region of interest. This is used with or without associated machine learning classifiers or a deep learning approach is applied to similar types of data. These tools have shown utility in characterizing renal masses, renal cell carcinoma, and assessing response to targeted therapeutic agents in metastatic renal cell carcinoma.
放射组学能够从图像中高通量提取定量数据。这是一个活跃的研究领域，各研究团队试图捕捉并量化成像参数，并将其转化为器官或肿瘤的描述性表型。纹理分析是一种放射组学工具，可提取给定感兴趣区域内异质性的信息。该工具可单独使用，也可与相关机器学习分类器结合使用，或者对类似类型的数据应用深度学习方法。这些工具已显示出在表征肾肿块、肾细胞癌以及评估转移性肾细胞癌对靶向治疗药物反应方面的效用。
