Radiomics in Antineoplastic Agents Development: Application and Challenge in Response Evaluation

Li Jiazheng; Tang Lei

doi:10.24920/003985

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Radiomics in Antineoplastic Agents Development: Application and Challenge in Response Evaluation

Chinese Medical Sciences Journal Vol. 36, Issue 3, Pages: 187-195(2021)

REVIEW | Updated：2024-04-10

- Radiomics in Antineoplastic Agents Development: Application and Challenge in Response Evaluation
- Affiliations：
  
  Department of Radiology, Peking University Cancer Hospital & Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing 100142, China
- Author bio：
  
  *E-mail: terrytang78@163.com
- Funds：
- DOI：10.24920/003985
  CLC：
- Received：19 August 2021，
  
  Accepted：2021-9-14，
  
  Published Online：21 September 2021，
  
  Published：21 September 2021
- Accepted：
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Li Jiazheng, Tang Lei. Radiomics in Antineoplastic Agents Development: Application and Challenge in Response Evaluation[J]. Chinese medical sciences journal, 2021, 36(3): 187-195.
DOI：

Li Jiazheng, Tang Lei. Radiomics in Antineoplastic Agents Development: Application and Challenge in Response Evaluation[J]. Chinese medical sciences journal, 2021, 36(3): 187-195. DOI： 10.24920/003985.

摘要

抗肿瘤药物的快速发展改善了恶性肿瘤患者预后。以CT、MRI和PET为代表的影像学手段作为重要的终点替代指标

在新药临床试验中发挥着越来越重要的作用。但因抗肿瘤药物作用靶点、应用线数等不同

治疗后影像学征象变化的个体差异较大

单用RECIST标准已无法满足个体化精准评效的需求。影像组学作为一种依托于新兴计算机技术的特征提取和模型构建手段

有望协助临床进行抗肿瘤药物治疗疗效的精准评估。本文介绍了影像组学的基本概念

回顾了影像组学在抗肿瘤药物疗效评价方面的最新进展

深入分析影像组学在预测肿瘤分子标志物、评价治疗疗效和预后预测方面的应用潜力

探讨了目前影像组学在抗肿瘤药物临床研究中存在的主要问题和未来发展方向。

Abstract

The recent spring up of the antineoplastic agents and the prolonged survival bring both challenge and chance to radiological practice. Radiological methods including CT

MRI and PET play an increasingly important role in evaluating the efficacy of these antineoplastic drugs. However

different antineoplastic agents potentially induce different radiological signs

making it a challenge for radiological response evaluation

which depends mainly on one-sided morphological response evaluation criteria in solid tumors (RECIST) in the status quo of clinical practice. This brings opportunities for the development of radiomics

which is promising to serve as a surrogate for response evaluations of anti-tumor treatments. In this article

we introduce the basic concepts of radiomics

review the state-of-art radiomics researches with highlights of radiomics application in predictions of molecular biomarkers

treatment response

and prognosis. We also provide in-depth analyses on major obstacles and future direction of this new technique in clinical investigations on new antineoplastic agents.

关键词

Keywords

references

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Multi-Omics and Its Clinical Application in Hepatocellular Carcinoma: Current Progress and Future Opportunities

Histopathological Diagnosis System for Gastritis Using Deep Learning Algorithm

Related Author

Ying An

Yu-Xia Guan

Jian-Xin Wang

Wei-Bai Pan

Feng-Yi Guo

Ziyang Wang

Yushan Lan

Zidu Xu

Related Institution

Big Data Institute, Central South University

Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University

Institute of Medical Information/Medical Library, Chinese Academy of Medical Science & Peking Union Medical College

Department of Radiology, Beijing United Family Hospital

PAII Inc., Bethesda

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