ARTEMIS®: A Web-based Orchestration System for Automating Radiotherapy Planning Workflows
Related Experiment Video
Updated: Nov 11, 2026
Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources
Published on: October 6, 2023
L Zheleva1, M Sundaram1, J Shenston1
1Clinical Scientific Computing, Medical Physics, University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD, UK.
Aims:
Modern radiotherapy departments operate across multiple digital systems, resulting in fragmented data, duplicated information, and repetitive manual tasks. This fragmentation reduces efficiency, limits pathway visibility, and contributes to workforce pressures. This study aimed to design, implement, and evaluate a vendor-neutral orchestration platform for workflow automation and centralised data management in radiotherapy treatment planning.
Materials And Methods:
ARTEMIS, a web-based orchestration platform, was developed in-house through a co-design process with clinical staff. The platform combines a centralised data hub, a Business Process Model and Notation (BPMN)-based workflow execution engine, and a modular automation plugin library. A structured four-environment deployment pipeline with independent validation at each stage governed clinical release. Service impact was evaluated using workflow throughput metrics, a workflow efficiency study, and an anonymous staff survey.
Results:
ARTEMIS was deployed clinically in September 2023 and supported 1800 workflow executions in its first year of operation. Monthly throughput increased from approximately 150 workflows during the v1.0 pilot to 350 workflows per month in v3.2. The plugin library expanded to 11 active plugins supporting workflow orchestration, clinical document management, and automated independent dose checking. User feedback (n = 11) indicated that 10 of 11 respondents spent less time on repetitive manual tasks, while all respondents believed further automation would improve service quality. Median planner interaction time for independent dose checking decreased from 5.2 min (interquartile range [IQR]: 4.83-6.00) to 3.0 min (IQR: 2.00-3.00), representing a 42% reduction (P < .001).
Conclusion:
ARTEMIS demonstrates the feasibility of a vendor-neutral, BPMN-driven orchestration platform for scalable workflow automation. By combining centralised data management, executable workflow modelling, and human-in-the-loop governance, ARTEMIS improved workflow throughput and reduced planner interaction time while maintaining clinical oversight. The implementation and validation methodology provides a transferable model for departments considering similar developments.
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