A novel automated planning approach for multi-anatomical sites cancer in Raystation treatment planning system. (May 2023)

• Record Type: Journal Article
• Authors: Lou, Zhaoyang; Cheng, Chen; Mao, Ronghu; Li, Dingjie; Tian, Lingling; Li, Bing; Lei, Hongchang; Ge, Hong
• Is Part Of: Physica medica. Volume 109(2023)
• Publication Date: 2023-05
• Subjects: Automated planning -- Raystation -- Multi-anatomical sites cancer -- Scripting; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2023.102586
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: A fully automated planning algorithm for Raystation. Combines both benefits of atlas-based and template-based automated planning algorithm. With the functions of dose prediction and beam angle optimization. Feasible for multi-treatment techniques and multi-anatomical sites cancer. Similar or superior plan quality and higher efficiency compared to manual planning. Abstract: 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.