Granata Vincenza, Fusco Roberta, Barretta Maria Luisa, Picone Carmine, Avallone Antonio, Belli Andrea, Patrone Renato, Ferrante Marilina, Cozzi Diletta, Grassi Roberta, Grassi Roberto, Izzo Francesco, Petrillo Antonella
Radiology Division, "ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, Napoli, Italy", Via Mariano Semmola, Naples, Italy.
Abdominal Oncology Division, "ISTITUTO NAZIONALE TUMORI - IRCCS - FONDAZIONE G. PASCALE, NAPOLI, ITALIA", Via Mariano Semmola, Naples, Italy.
Infect Agent Cancer. 2021 Jun 2;16(1):39. doi: 10.1186/s13027-021-00379-y.
Radiomics is an emerging field and has a keen interest, especially in the oncology field. The process of a radiomics study consists of lesion segmentation, feature extraction, consistency analysis of features, feature selection, and model building. Manual segmentation is one of the most critical parts of radiomics. It can be time-consuming and suffers from variability in tumor delineation, which leads to the reproducibility problem of calculating parameters and assessing spatial tumor heterogeneity, particularly in large or multiple tumors. Radiomic features provides data on tumor phenotype as well as cancer microenvironment. Radiomics derived parameters, when associated with other pertinent data and correlated with outcomes data, can produce accurate robust evidence based clinical decision support systems. The principal challenge is the optimal collection and integration of diverse multimodal data sources in a quantitative manner that delivers unambiguous clinical predictions that accurately and robustly enable outcome prediction as a function of the impending decisions.
The search covered the years from January 2010 to January 2021. The inclusion criterion was: clinical study evaluating radiomics of liver colorectal metastases. Exclusion criteria were studies with no sufficient reported data, case report, review or editorial letter.
We recognized 38 studies that assessed radiomics in mCRC from January 2010 to January 2021. Twenty were on different tpics, 5 corresponded to most criteria; 3 are review, or letter to editors; so 10 articles were included.
In colorectal liver metastases radiomics should be a valid tool for the characterization of lesions, in the stratification of patients based on the risk of relapse after surgical treatment and in the prediction of response to chemotherapy treatment.
放射组学是一个新兴领域，尤其在肿瘤学领域备受关注。放射组学研究过程包括病变分割、特征提取、特征一致性分析、特征选择和模型构建。手动分割是放射组学最关键的部分之一。它可能耗时，且在肿瘤轮廓描绘方面存在变异性，这导致计算参数和评估肿瘤空间异质性时的可重复性问题，特别是在大肿瘤或多个肿瘤的情况下。放射组学特征提供了关于肿瘤表型以及癌症微环境的数据。当放射组学衍生参数与其他相关数据相关联并与结果数据相关时，可以产生基于准确可靠证据的临床决策支持系统。主要挑战是以定量方式最佳收集和整合各种多模态数据源，从而提供明确的临床预测，准确且可靠地根据即将做出的决策预测结果。
检索涵盖2010年1月至2021年1月期间的文献。纳入标准为：评估肝结直肠癌转移灶放射组学的临床研究。排除标准为数据报告不足的研究、病例报告、综述或编辑信件。
我们识别出2010年1月至2021年1月期间评估mCRC放射组学的38项研究。其中20项研究主题不同，5项符合大多数标准；3项为综述或给编辑的信件；因此纳入了10篇文章。
在结直肠癌肝转移中，放射组学应是用于病变特征描述、基于手术治疗后复发风险对患者进行分层以及预测化疗反应的有效工具。
