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基于医学大数据的现代放射治疗工作流程中的癌症风险评估

Cancer risk assessment in modern radiotherapy workflow with medical big data.

作者信息

Jin Fu, Luo Huan-Li, Zhou Juan, He Ya-Nan, Liu Xian-Feng, Zhong Ming-Song, Yang Han, Li Chao, Li Qi-Cheng, Huang Xia, Tian Xiu-Mei, Qiu Da, He Guang-Lei, Yin Li, Wang Ying

机构信息

Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing Cancer Institute, Chongqing Cancer Hospital, Chongqing, People's Republic of China.

Forensic Identification Center, College of Criminal Investigation, Southwest University of Political Science and Law, Chongqing, People's Republic of China.

出版信息

Cancer Manag Res. 2018 Jun 22;10:1665-1675. doi: 10.2147/CMAR.S164980. eCollection 2018.

DOI:10.2147/CMAR.S164980
PMID:29970965
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6021004/
Abstract

Modern radiotherapy (RT) is being enriched by big digital data and intensive technology. Multimodality image registration, intelligence-guided planning, real-time tracking, image-guided RT (IGRT), and automatic follow-up surveys are the products of the digital era. Enormous digital data are created in the process of treatment, including benefits and risks. Generally, decision making in RT tries to balance these two aspects, which is based on the archival and retrieving of data from various platforms. However, modern risk-based analysis shows that many errors that occur in radiation oncology are due to failures in workflow. These errors can lead to imbalance between benefits and risks. In addition, the exact mechanism and dose-response relationship for radiation-induced malignancy are not well understood. The cancer risk in modern RT workflow continues to be a problem. Therefore, in this review, we develop risk assessments based on our current knowledge of IGRT and provide strategies for cancer risk reduction. Artificial intelligence (AI) such as machine learning is also discussed because big data are transforming RT via AI.

摘要

现代放射治疗(RT)正因大量数字数据和密集技术而不断丰富。多模态图像配准、智能引导规划、实时跟踪、图像引导放射治疗(IGRT)以及自动随访调查都是数字时代的产物。在治疗过程中会产生大量数字数据,包括益处和风险。一般来说,放射治疗中的决策试图平衡这两个方面,这基于从各种平台存档和检索数据。然而,现代基于风险的分析表明,放射肿瘤学中出现的许多错误是由于工作流程失误。这些错误会导致益处与风险之间的失衡。此外,对于辐射诱发恶性肿瘤的确切机制和剂量反应关系尚未完全了解。现代放射治疗工作流程中的癌症风险仍然是一个问题。因此,在本综述中,我们基于对IGRT的现有知识开展风险评估,并提供降低癌症风险的策略。还讨论了诸如机器学习之类的人工智能(AI),因为大数据正在通过AI改变放射治疗。

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