Department of Nuclear Medicine, Centre Henri-Becquerel, France; LITIS EA4108, Normandie University, Rouen, France.
Department of Radiation Oncology, Centre Léon Bérard, France.
Crit Rev Oncol Hematol. 2019 Jun;138:44-50. doi: 10.1016/j.critrevonc.2019.03.015. Epub 2019 Mar 29.
Radiomics is defined as the extraction of a large quantity of quantitative image features. The different radiomic indexes that have been proposed in the literature are described as well as the various factors that have an impact on the robustness of these indexes. We will see that several hundred quantitative features can be extracted per lesion and imaging modality. The ever-growing number of features studied raises the question of the statistical method of analysis used. This review addresses the research supporting the clinical use of radiomics in oncology in the staging of disease, discrimination between healthy and pathological tissues, the identification of genetic features, the prediction of patient survival, the response to treatment, the recurrence after radiotherapy and chemoradiotherapy and the side effects. Based on the existing literature, it remains difficult to identify features that should be used for current clinical practice.
放射组学被定义为大量定量图像特征的提取。本文描述了文献中提出的不同放射组学指标,以及影响这些指标稳健性的各种因素。我们将看到,每个病变和成像方式可以提取几百个定量特征。研究的特征数量不断增加,这就提出了所使用的分析统计方法的问题。这篇综述讨论了放射组学在肿瘤学中的临床应用研究,包括疾病分期、健康组织和病变组织的区分、基因特征的识别、患者生存预测、治疗反应、放疗和放化疗后复发以及副作用。基于现有文献,仍然难以确定哪些特征应该用于当前的临床实践。
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