Rolling out RapidPlan: What we've learnt

• Published in: Journal of medical radiation sciences Vol. 67; no. 4; pp. 310 - 317
• Main Authors: Gysen, Kirsten, O'Toole, James, Le, Andrew, Wu, Kenny, Schuler, Thilo, Porter, Brian, Kipritidis, John, Atyeo, John, Brown, Chris, Eade, Thomas
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01-12-2020; John Wiley and Sons Inc
• Subjects: Dosimetry; Efficiency; Humans; Knowledge‐based planning; Objectives; Original; Prostate; Radiation therapy; Radiotherapy Planning, Computer-Assisted - methods; Rapid prototyping; RapidPlan; Success; Knowledge-based planning; RapidPlan; radiation therapy
• ISSN: 2051-3895; 2051-3909; 2051-3909
• DOI: 10.1002/jmrs.420

Introduction
RapidPlan (RP), a knowledge‐based planning system, aims to consistently improve plan quality and efficiency in radiotherapy. During the early stages of implementation, some of the challenges include knowing how to optimally train a model and how to integrate RP into a department. We discuss our experience with the implementation of RP into our institution.
Methods
We reviewed all patients planned using RP over a 7‐month period following inception in our department. Our primary outcome was clinically acceptable plans (used for treatment) with secondary outcomes including model performance and a comparison of efficiency and plan quality between RP and manual planning (MP).
Results
Between November 2017 and May 2018, 496 patients were simulated, of which 217 (43.8%) had an available model. RP successfully created a clinically acceptable plan in 87.2% of eligible patients. The individual success of the 24 models ranged from 50% to 100%, with more than 90% success in 15 (62.5%) of the models. In 40% of plans, success was achieved on the 1st optimisation. The overall planning time with RP was reduced by up to 95% compared with MP times. The quality of the RP plans was at least equivalent to historical MP plans in terms of target coverage and organ at risk constraints.
Conclusion
While initially time‐consuming and resource‐intensive to implement, plans optimised with RP demonstrate clinically acceptable plan quality, while significantly improving the efficiency of a department, suggesting RP and its application is a highly effective tool in clinical practice.
Knowledge‐based planning, RapidPlan (RP), aims to consistently improve plan quality and efficiency in a radiotherapy department. We discuss our experience with the implementation, validation and outcomes associated with the use of RP in a single institution. While initially time‐consuming and resource‐intensive to implement, plans optimised with RP demonstrate clinically acceptable plan quality, while significantly improving the efficiency of a department, suggesting RP and its application is a highly effective tool in clinical practice.