Literature DB >> 18093042

Probabilistic fault tree analysis of a radiation treatment system.

Edidiong Ekaette1, Robert C Lee, David L Cooke, Sandra Iftody, Peter Craighead.   

Abstract

Inappropriate administration of radiation for cancer treatment can result in severe consequences such as premature death or appreciably impaired quality of life. There has been little study of vulnerable treatment process components and their contribution to the risk of radiation treatment (RT). In this article, we describe the application of probabilistic fault tree methods to assess the probability of radiation misadministration to patients at a large cancer treatment center. We conducted a systematic analysis of the RT process that identified four process domains: Assessment, Preparation, Treatment, and Follow-up. For the Preparation domain, we analyzed possible incident scenarios via fault trees. For each task, we also identified existing quality control measures. To populate the fault trees we used subjective probabilities from experts and compared results with incident report data. Both the fault tree and the incident report analysis revealed simulation tasks to be most prone to incidents, and the treatment prescription task to be least prone to incidents. The probability of a Preparation domain incident was estimated to be in the range of 0.1-0.7% based on incident reports, which is comparable to the mean value of 0.4% from the fault tree analysis using probabilities from the expert elicitation exercise. In conclusion, an analysis of part of the RT system using a fault tree populated with subjective probabilities from experts was useful in identifying vulnerable components of the system, and provided quantitative data for risk management.

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Year:  2007        PMID: 18093042     DOI: 10.1111/j.1539-6924.2007.00976.x

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  6 in total

1.  The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management.

Authors:  M Saiful Huq; Benedick A Fraass; Peter B Dunscombe; John P Gibbons; Geoffrey S Ibbott; Arno J Mundt; Sasa Mutic; Jatinder R Palta; Frank Rath; Bruce R Thomadsen; Jeffrey F Williamson; Ellen D Yorke
Journal:  Med Phys       Date:  2016-07       Impact factor: 4.071

2.  The Use of Expert Elicitation among Computational Modeling Studies in Health Research: A Systematic Review.

Authors:  Christopher J Cadham; Marie Knoll; Luz María Sánchez-Romero; K Michael Cummings; Clifford E Douglas; Alex Liber; David Mendez; Rafael Meza; Ritesh Mistry; Aylin Sertkaya; Nargiz Travis; David T Levy
Journal:  Med Decis Making       Date:  2021-10-25       Impact factor: 2.749

3.  Retrospective study on performance of constancy check device in Linac beam monitoring using Statistical Process Control.

Authors:  Bipasha Pal; Angshuman Pal; Suresh Das; Soura Palit; Papai Sarkar; Subhayan Mondal; Suman Mallik; Jyotirup Goswami; Sayan Das; Arijit Sen; Monidipa Mondol
Journal:  Rep Pract Oncol Radiother       Date:  2019-12-10

4.  Application of failure mode and effects analysis to treatment planning in scanned proton beam radiotherapy.

Authors:  Marie Claire Cantone; Mario Ciocca; Francesco Dionisi; Piero Fossati; Stefano Lorentini; Marco Krengli; Silvia Molinelli; Roberto Orecchia; Marco Schwarz; Ivan Veronese; Viviana Vitolo
Journal:  Radiat Oncol       Date:  2013-05-24       Impact factor: 3.481

5.  Retrospective analysis of linear accelerator output constancy checks using process control techniques.

Authors:  Taweap Sanghangthum; Sivalee Suriyapee; Somyot Srisatit; Todd Pawlicki
Journal:  J Appl Clin Med Phys       Date:  2013-01-07       Impact factor: 2.102

6.  Application of failure mode and effects analysis (FMEA) to pretreatment phases in tomotherapy.

Authors:  Sara Broggi; Marie Claire Cantone; Anna Chiara; Nadia Di Muzio; Barbara Longobardi; Paola Mangili; Ivan Veronese
Journal:  J Appl Clin Med Phys       Date:  2013-09-06       Impact factor: 2.102

  6 in total

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