Unified risk analysis in radiation therapy

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Daniel Lohmann, Maya Shariff, Philipp Schubert, Tim Oliver Sauer, Rainer Fietkau, Christoph Bert
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引用次数: 0

Abstract

Purpose

The increasing complexity of new treatment methods as well as the Information Technology (IT) infrastructure within radiotherapy require new methods for risk analysis. This work presents a methodology on how to model the treatment process of radiotherapy in different levels. This subdivision makes it possible to perform workflow-specific risk analysis and to assess the impact of IT risks on the overall treatment workflow.

Methods

A Unified Modeling Language (UML) activity diagram is used to model the workflows. The subdivision of the workflows into different levels is done with the help of swim lanes. The model created in this way is exported in an xml-compatible format and stored in a database with the help of a Python program.

Results

Based on an existing risk analysis, the workflows CT Appointment, Glioblastoma Multiforme, and Deep Inspiration Breath Hold (DIBH) were modeled in detail. Part of the analysis are automatically generated workflow-specific risk matrices including risks of medical devices incorporated into a specific workflow. In addition, SQL queries allow to quickly retrieve e.g., the details of the medical device network installed in a department.

Conclusion

Activity diagrams of UML can be used to model workflows in radiotherapy. Through this, a connection between the different levels of the entire workflow can be established and workflow-specific risk analysis is possible.

放射治疗中的统一风险分析
目的新的治疗方法以及放疗中的信息技术(IT)基础设施日益复杂,需要新的风险分析方法。这项工作提出了一种方法,即如何在不同层次上对放射治疗的治疗过程进行建模。方法使用统一建模语言(UML)活动图为工作流建模。借助泳道将工作流程细分为不同层次。结果在现有风险分析的基础上,对 CT 预约、多形性胶质母细胞瘤和深吸气屏气(DIBH)的工作流程进行了详细建模。分析的一部分是自动生成的工作流程特定风险矩阵,包括纳入特定工作流程的医疗设备的风险。此外,还可通过 SQL 查询快速检索科室中安装的医疗设备网络的详细信息。通过这种方法,可以在整个工作流程的不同层次之间建立联系,并进行针对工作流程的风险分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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