van Rossum Peter S N, Xu Cai, Fried David V, Goense Lucas, Court Laurence E, Lin Steven H
Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston (Texas), USA.
Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
Transl Cancer Res. 2016 Aug;5(4):410-423. doi: 10.21037/tcr.2016.06.19.
'Radiomics' is the name given to the emerging field of extracting additional information from standard medical images using advanced feature analysis. This innovative form of quantitative image analysis appears to have future potential for clinical practice in patients with esophageal cancer by providing an additional layer of information to the standard imaging assessment. There is a growing body of evidence suggesting that radiomics may provide incremental value for staging, predicting treatment response, and predicting survival in esophageal cancer, for which the current work-up has substantial limitations. This review outlines the available evidence and future potential for the application of radiomics in the management of patients with esophageal cancer. In addition, an overview of the current evidence on the importance of reproducibility of image features and the substantial influence of varying smoothing scales, quantization levels, and segmentation methods is provided.
“放射组学”是指利用先进的特征分析从标准医学图像中提取额外信息的新兴领域。这种创新的定量图像分析形式,通过为标准成像评估提供额外的信息层,似乎在食管癌患者的临床实践中具有未来潜力。越来越多的证据表明,放射组学可能为食管癌的分期、预测治疗反应和预测生存提供增量价值,而目前的检查方法存在很大局限性。这篇综述概述了放射组学在食管癌患者管理中应用的现有证据和未来潜力。此外,还概述了关于图像特征可重复性的重要性以及不同平滑尺度、量化水平和分割方法的重大影响的当前证据。
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