Related Experiment Video
Updated: Aug 2, 2025

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
A novel automated planning approach for multi-anatomical sites cancer in Raystation treatment planning system
Zhaoyang Lou1, Chen Cheng1, Ronghu Mao1
1Department of Radiation Oncology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China.
Purpose:
To develop an automated planning approach in Raystation and evaluate its feasibility in multiple clinical application scenarios.
Methods:
An automated planning approach (Ruiplan) was developed by using the scripting platform of Raystation. Radiotherapy plans were re-generated both automatically by using Ruiplan and manually. 60 patients, including 20 patients with nasopharyngeal carcinoma (NPC), 20 patients with esophageal carcinoma (ESCA), and 20 patients with rectal cancer (RECA) were retrospectively enrolled in this study. Dosimetric and planning efficiency parameters of the automated plans (APs) and manual plans (MPs) were statistically compared.
Results:
For target coverage, APs yielded superior dose homogeneity in NPC and RECA, while maintaining similar dose conformity for all studied anatomical sites. For OARs sparing, APs led to significant improvement in most OARs sparing. The average planning time required for APs was reduced by more than 43% compared with MPs. Despite the increased monitor units (MUs) for NPC and RECA in APs, the beam-on time of APs and MPs had no statistical difference. Both the MUs and beam-on time of APs were significantly lower than that of MPs in ESCA.
Conclusions:
This study developed a new automated planning approach, Ruiplan, it is feasible for multi-treatment techniques and multi-anatomical sites cancer treatment planning. The dose distributions of targets and OARs in the APs were similar or better than those in the MPs, and the planning time of APs showed a sharp reduction compared with the MPs. Thus, Ruiplan provides a promising approach for realizing automated treatment planning in the future.
More Related Videos
05:18Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
Published on: October 6, 2023
07:57Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
Published on: March 24, 2022