Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

Hargrave, Catriona Elizabeth, Moores, Matthew T., Deegan, Timothy, Gibbs, Adrian, Poulsen, Michael, Harden, Fiona, & Mengersen, Kerrie (2014) Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network. Journal of Physics : Conference Series, 489(1), 012074 .

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Abstract

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

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ID Code: 67933
Item Type: Journal Article
Refereed: Yes
Keywords: Decision-making, Image-guided radiotherapy, Bayesian networks
DOI: 10.1088/1742-6596/489/1/012074
ISSN: 1742-6588
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Biostatistics (010402)
Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > ONCOLOGY AND CARCINOGENESIS (111200) > Radiation Therapy (111208)
Divisions: Current > Schools > School of Clinical Sciences
Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 The Author(s)
Copyright Statement: Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution
of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Published under licence by IOP Publishing Ltd
Deposited On: 03 Mar 2014 01:55
Last Modified: 07 Aug 2014 21:19

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