Evidence map›Paper›PMID 41451146›Full record

ArticlePhysics and imaging in radiation oncology2025

A proof of concept for improving comparability of dosimetry audits through centralised planning.

José Antonio Baeza-Ortega, Lauren May, Mohammad Hussein, Sarah Porter, Alisha Moore, Peter B Greer, Catharine H Clark, Joerg Lehmann

Abstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

José Antonio Baeza-OrtegaSchool of Information and Physical Sciences, University of Newcastle, Newcastle, Australia.
Lauren MaySchool of Information and Physical Sciences, University of Newcastle, Newcastle, Australia.
Mohammad HusseinRadiotherapy and Radiation Dosimetry, National Physical Laboratory, Teddington, United Kingdom.
Sarah PorterRadiation Therapy Quality Assurance, Trans-Tasman Radiation Oncology Group (TROG Cancer Research), Newcastle, Australia.
Alisha MooreRadiation Therapy Quality Assurance, Trans-Tasman Radiation Oncology Group (TROG Cancer Research), Newcastle, Australia.
Peter B GreerDepartment of Radiation Oncology, Calvary Mater Hospital, Newcastle, Australia.
Catharine H ClarkRadiotherapy and Radiation Dosimetry, National Physical Laboratory, Teddington, United Kingdom.
Joerg LehmannDepartment of Radiation Oncology, Calvary Mater Hospital, Newcastle, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: The role of dosimetry audits is well established in the development and verification of radiotherapy safety. Differences in planning and beam modelling make inter-centre comparisons challenging, which can be addressed through distribution of centrally created plans. This study developed a centralised planning approach applicable to multiple audit methodologies, using an example of remote patient specific quality assurance assessment, increasing the interpretability of results and facilitating automation and scalability. Material and methods: Starting with an established plan which met all clinical goals, a commercial dose mimicking algorithm was used to replicate this plan to be suitable for multiple treatment machines. Beam and machine limitation data were collected from participating centres to develop universally acceptable beam models. The influence of variation in beam modelling parameters among centres was assessed by creating additional models using the 2.5th, 25th, 75th and 97.5th percentiles of previously reported data. Multi-leaf collimator angle and leaf position, gantry angle and output deviations were then introduced into copies of these plans. Results: Introduced delivery errors caused consistent change in dose metrics across machine models (excluding outliers) with a median (range) standard deviation of 1.0 % (from 0.1 % to 1.7 %) demonstrating similar robustness. Beam model variation did not change whether simulated delivery errors were clinically impactful or not for 95 % of tested plans. Conclusion: This study lays the foundation for future standardised methodology for dosimetry audits by providing a centralised planning approach that allows a more consistent assessment of centres.

Indexed as

Patient specific quality assuranceQuality assuranceSEAFARERSensitivity

Identifiers

PMID41451146
PMCPMC12732305

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.