Radiation planning assistant - a streamlined, fully automated radiotherapy treatment planning system
Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Visualized Experiments
Abstract
The Radiation Planning Assistant (RPA) is a system developed for the fully automated creation of radiotherapy treatment plans, including
volume-modulated arc therapy (VMAT) plans for patients with head/neck cancer and 4-field box plans for patients with cervical cancer. It is
a combination of specially developed in-house software that uses an application programming interface to communicate with a commercial
radiotherapy treatment planning system. It also interfaces with a commercial secondary dose verification software. The necessary inputs to the
system are a Treatment Plan Order, approved by the radiation oncologist, and a simulation computed tomography (CT) image, approved by
the radiographer. The RPA then generates a complete radiotherapy treatment plan. For the cervical cancer treatment plans, no additional user
intervention is necessary until the plan is complete. For head/neck treatment plans, after the normal tissue and some of the target structures
are automatically delineated on the CT image, the radiation oncologist must review the contours, making edits if necessary. They also delineate
the gross tumor volume. The RPA then completes the treatment planning process, creating a VMAT plan. Finally, the completed plan must be
reviewed by qualified clinical staff.
Description
CITATION: Court, L. E., et al. 2018. Radiation planning assistant - a streamlined, fully automated radiotherapy treatment planning system. Journal of Visualized Experiments, 134:e57411, doi:10.3791/57411 (2018).
The original publication is available at https://www.jove.com
The original publication is available at https://www.jove.com
Keywords
Radiotherapy, Automation
Citation
Court, L. E., et al. 2018. Radiation planning assistant - a streamlined, fully automated radiotherapy treatment planning system. Journal of Visualized Experiments, 134:e57411, doi:10.3791/57411 (2018)