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原发性肝癌的放射组学技术进展

An update on radiomics techniques in primary liver cancers.

作者信息

Granata Vincenza, Fusco Roberta, Setola Sergio Venazio, Simonetti Igino, Cozzi Diletta, Grazzini Giulia, Grassi Francesca, Belli Andrea, Miele Vittorio, Izzo Francesco, Petrillo Antonella

机构信息

Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", Via Mariano Semmola 80131, Naples, Italy.

Medical Oncology Division, Igea SpA, Napoli, Italy.

出版信息

Infect Agent Cancer. 2022 Mar 4;17(1):6. doi: 10.1186/s13027-022-00422-6.

Abstract

BACKGROUND

Radiomics is a progressing field of research that deals with the extraction of quantitative metrics from medical images. Radiomic features detention indirectly tissue features such as heterogeneity and shape and can, alone or in combination with demographic, histological, genomic, or proteomic data, be used for decision support system in clinical setting.

METHODS

This article is a narrative review on Radiomics in Primary Liver Cancers. Particularly, limitations and future perspectives are discussed.

RESULTS

In oncology, assessment of tissue heterogeneity is of particular interest: genomic analysis have demonstrated that the degree of tumour heterogeneity is a prognostic determinant of survival and an obstacle to cancer control. Therefore, that Radiomics could support cancer detection, diagnosis, evaluation of prognosis and response to treatment, so as could supervise disease status in hepatocellular carcinoma (HCC) and Intrahepatic Cholangiocarcinoma (ICC) patients. Radiomic analysis is a convenient radiological image analysis technique used to support clinical decisions as it is able to provide prognostic and / or predictive biomarkers that allow a fast, objective and repeatable tool for disease monitoring.

CONCLUSIONS

Although several studies have shown that this analysis is very promising, there is little standardization and generalization of the results, which limits the translation of this method into the clinical context. The limitations are mainly related to the evaluation of data quality, repeatability, reproducibility, overfitting of the model.

TRIAL REGISTRATION

Not applicable.

摘要

背景

放射组学是一个不断发展的研究领域,涉及从医学图像中提取定量指标。放射组学特征间接反映组织特征,如异质性和形状,并且可以单独或与人口统计学、组织学、基因组学或蛋白质组学数据相结合,用于临床环境中的决策支持系统。

方法

本文是一篇关于原发性肝癌放射组学的叙述性综述。特别讨论了其局限性和未来展望。

结果

在肿瘤学中,组织异质性的评估尤为重要:基因组分析表明,肿瘤异质性程度是生存的预后决定因素,也是癌症控制的障碍。因此,放射组学可以支持癌症的检测、诊断、预后评估和治疗反应评估,从而可以监测肝细胞癌(HCC)和肝内胆管癌(ICC)患者的疾病状态。放射组学分析是一种便捷的放射影像分析技术,可用于支持临床决策,因为它能够提供预后和/或预测性生物标志物,为疾病监测提供快速、客观和可重复的工具。

结论

尽管多项研究表明这种分析很有前景,但结果的标准化和推广程度较低,这限制了该方法在临床中的应用。这些局限性主要与数据质量评估、可重复性、再现性以及模型的过拟合有关。

试验注册

不适用。

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