Suppr超能文献

基于互联网的计算机技术在放射治疗中的应用

Internet-based computer technology on radiotherapy.

作者信息

Chow James C L

机构信息

Department of Radiation Oncology, University of Toronto and Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada.

出版信息

Rep Pract Oncol Radiother. 2017 Nov-Dec;22(6):455-462. doi: 10.1016/j.rpor.2017.08.005. Epub 2017 Sep 8.

Abstract

Recent rapid development of Internet-based computer technologies has made possible many novel applications in radiation dose delivery. However, translational speed of applying these new technologies in radiotherapy could hardly catch up due to the complex commissioning process and quality assurance protocol. Implementing novel Internet-based technology in radiotherapy requires corresponding design of algorithm and infrastructure of the application, set up of related clinical policies, purchase and development of software and hardware, computer programming and debugging, and national to international collaboration. Although such implementation processes are time consuming, some recent computer advancements in the radiation dose delivery are still noticeable. In this review, we will present the background and concept of some recent Internet-based computer technologies such as cloud computing, big data processing and machine learning, followed by their potential applications in radiotherapy, such as treatment planning and dose delivery. We will also discuss the current progress of these applications and their impacts on radiotherapy. We will explore and evaluate the expected benefits and challenges in implementation as well.

摘要

基于互联网的计算机技术最近的快速发展使得在放射剂量传递方面有了许多新颖的应用。然而,由于复杂的调试过程和质量保证协议,将这些新技术应用于放射治疗的转化速度很难跟上。在放射治疗中实施基于互联网的新技术需要对应用的算法和基础设施进行相应设计,制定相关临床政策,购买和开发软件硬件,进行计算机编程和调试,以及开展国内到国际的合作。尽管这样的实施过程很耗时,但最近在放射剂量传递方面的一些计算机进展仍然值得注意。在这篇综述中,我们将介绍一些最近基于互联网的计算机技术的背景和概念,如云计算、大数据处理和机器学习,随后阐述它们在放射治疗中的潜在应用,如治疗计划和剂量传递。我们还将讨论这些应用的当前进展及其对放射治疗的影响。我们也将探索和评估实施过程中预期的益处和挑战。

相似文献

1
Internet-based computer technology on radiotherapy.
Rep Pract Oncol Radiother. 2017 Nov-Dec;22(6):455-462. doi: 10.1016/j.rpor.2017.08.005. Epub 2017 Sep 8.
2
Radiotherapy Monte Carlo simulation using cloud computing technology.
Australas Phys Eng Sci Med. 2012 Dec;35(4):497-502. doi: 10.1007/s13246-012-0167-8. Epub 2012 Nov 28.
3
Toward a web-based real-time radiation treatment planning system in a cloud computing environment.
Phys Med Biol. 2013 Sep 21;58(18):6525-40. doi: 10.1088/0031-9155/58/18/6525. Epub 2013 Sep 3.
4
[Porting Radiotherapy Software of Varian to Cloud Platform].
Zhongguo Yi Liao Qi Xie Za Zhi. 2017 Sep 30;41(5):330-333. doi: 10.3969/j.issn.1671-7104.2017.05.005.
5
Big Data, Internet of Things and Cloud Convergence--An Architecture for Secure E-Health Applications.
J Med Syst. 2015 Nov;39(11):141. doi: 10.1007/s10916-015-0327-y. Epub 2015 Sep 7.
6
Web-based submission, archive, and review of radiotherapy data for clinical quality assurance: a new paradigm.
Int J Radiat Oncol Biol Phys. 2003 Dec 1;57(5):1427-36. doi: 10.1016/s0360-3016(03)01624-9.
8
VERIDOS: a new tool for quality assurance for intensity modulated radiotherapy.
Strahlenther Onkol. 2002 Dec;178(12):732-6. doi: 10.1007/s00066-002-0986-8.
9
Intensity-modulated radiotherapy: current status and issues of interest.
Int J Radiat Oncol Biol Phys. 2001 Nov 15;51(4):880-914. doi: 10.1016/s0360-3016(01)01749-7.
10

引用本文的文献

2
3
Synthesizing Efficiency Tools in Radiotherapy to Increase Patient Flow: A Comprehensive Literature Review.
Clin Med Insights Oncol. 2024 Dec 13;18:11795549241303606. doi: 10.1177/11795549241303606. eCollection 2024.
4
Use of social media in radiation oncology: multicenter data from the GOCO Group.
Rep Pract Oncol Radiother. 2024 Jun 6;29(2):236-244. doi: 10.5603/rpor.100386. eCollection 2024.
6
Value assessment of artificial intelligence in medical imaging: a scoping review.
BMC Med Imaging. 2022 Oct 31;22(1):187. doi: 10.1186/s12880-022-00918-y.

本文引用的文献

1
A machine learning tool for re-planning and adaptive RT: A multicenter cohort investigation.
Phys Med. 2016 Dec;32(12):1659-1666. doi: 10.1016/j.ejmp.2016.10.005. Epub 2016 Oct 17.
3
Big Data Analytics for Prostate Radiotherapy.
Front Oncol. 2016 Jun 14;6:149. doi: 10.3389/fonc.2016.00149. eCollection 2016.
4
A Systems Approach Using Big Data to Improve Safety and Quality in Radiation Oncology.
Int J Radiat Oncol Biol Phys. 2016 Jul 1;95(3):885-889. doi: 10.1016/j.ijrobp.2015.10.024. Epub 2015 Oct 21.
6
Introduction to Big Data in Radiation Oncology: Exploring Opportunities for Research, Quality Assessment, and Clinical Care.
Int J Radiat Oncol Biol Phys. 2016 Jul 1;95(3):871-872. doi: 10.1016/j.ijrobp.2015.12.358.
10
Some computer graphical user interfaces in radiation therapy.
World J Radiol. 2016 Mar 28;8(3):255-67. doi: 10.4329/wjr.v8.i3.255.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验