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Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources
Published on: October 6, 2023
Version upgrades in treatment planning Systems affect clinical application of a multi-Centre knowledge-based planning
Karen McGoldrick1,2, Colin Hornby1,3, Peter Griffin4
1Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia.
Summary
Software upgrades to the Eclipse treatment planning system can impact clinical plans. Re-training RapidPlan models after upgrades is crucial for maintaining optimal radiation therapy dosimetry.
Area of Science:
- Radiation Oncology
- Medical Physics
- Software Engineering
Background:
- Knowledge-based planning (KBP) models in radiation therapy are sensitive to software versions.
- Treatment planning system (TPS) software upgrades can alter treatment plan outcomes.
- Maintaining plan quality requires understanding the impact of TPS updates on KBP models.
Purpose of the Study:
- To assess the impact of Eclipse treatment planning system software version upgrades on clinical application of a RapidPlan knowledge-based model.
- To determine if re-training RapidPlan models is necessary after Eclipse software updates.
Main Methods:
- Retrospective analysis of 20 prostate cancer patient datasets.
- Planning on three Eclipse versions (Vn13.6, Vn15.6, Vn16.1) using a RapidPlan model built in Vn13.6.
- Re-training and re-planning with updated models in Vn15.6 and Vn16.1.
Main Results:
- Statistically significant differences in target and organ at risk (OAR) dose metrics were observed across versions.
- Re-trained models in Vn15.6 and Vn16.1 demonstrated improved target coverage and OAR dosimetry.
- Minor variations (≤1.4%) in some OAR metrics were noted with the Vn15.6 model.
Conclusions:
- Eclipse version upgrades affect treatment plans optimized by RapidPlan models.
- Re-extracting and re-training RapidPlan models is essential following Eclipse version upgrades to ensure optimal dosimetry.
- Vendor recommendations for re-training models post-upgrade should be followed.
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