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Updated: Feb 8, 2026

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
Personalized automated treatment planning for breast plus locoregional lymph nodes using Hybrid RapidArc
Mariët J van Duren-Koopman1, Jim P Tol1, Max Dahele1
1Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
Purpose:
Breast cancer patients who require locoregional lymph node (LLN) irradiation can be treated using a hybrid RapidArc technique combining 2 tangential and 3 RapidArc fields. Because the creation of hybrid RapidArc plans is complex and labor-intensive, we developed an automated treatment planning workflow using the scripting application programming interface of the Eclipse treatment planning system.
Methods And Materials:
Fifteen patients (5 right- and 10 left-sided) previously treated with breast + LLN radiation therapy were replanned using the script. The automated workflow included1 optimal placement of the tangential fields based on the planning target volume and organ-at-risk contours, followed by optimization of field weights and beam energy2; positioning of the RapidArc fields; and3 subsequent RapidArc optimization using the RapidPlan knowledge-based planning solution.
Results:
Average total planning times were 163 ± 97 and 33 ± 5 minutes for the manual and automated plans, respectively, with approximately 130 and 5 minutes of user interaction. Dosimetrically, both sets of plans were very similar, with comparable planning target volume dose homogeneity values and organ-at-risk mean dose differences of ≤1.9 Gy. In 14/15 patients, the physician judged that the automated plan was either preferred (n = 4) or equal (n = 10) to the manual plan.
Conclusions:
The complex hybrid RapidArc planning process for patients requiring breast + LLN irradiation was automated by optimizing the tangential field setup and integrating RapidPlan. The quality of the automated and manual plans was comparable, whereas automated planning times were substantially shorter. The principles described here could be used to automate other planning workflows.
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