Related Experiment Video
Updated: Sep 16, 2026

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources
Published on: October 6, 2023
Automated planning architectures for online adaptive radiotherapy: A narrative review of the ethos and unity/Monaco
Songye Cui1,2, Maria F Chan1, Dandan Zheng2
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Abstract:
Online adaptive radiotherapy (OART) modifies treatment plans using anatomy-of-the-day imaging, but successful clinical implementation depends on automated planning strategies that can generate high-quality plans within the constraints of an online workflow. This narrative review compares the automated planning architectures of the Varian Ethos and Elekta Unity/Monaco systems using a targeted literature search through July 2026. Ethos generates a daily adapted plan through goal-prioritized supervisory optimization governed by an unchanged clinical directive. Unity/Monaco provides Adapt-to-Position (ATP) and Adapt-to-Shape (ATS) pathways, with methods ranging from reference-segment recalculation and refinement to full online replanning with newly optimized fluence and segments. Rather than representing opposing planning paradigms, these systems differ in how ordered clinical goals or reference-plan information guide a selected adaptation method and in the degrees of freedom available within that method. Representative workflow and implementation studies are reviewed to provide clinical context, but they do not support direct comparisons of platform performance or superiority. MRIdian is acknowledged as another established MR-guided adaptive platform, although its planning architecture is beyond the scope of this focused review. Accordingly, the comparison is best understood by asking what guides the selected adaptation method and which degrees of freedom that method permits, rather than as a binary distinction between flexible and reference-based planning. This framework provides a conceptual basis for interpreting current commercial OART systems and may help guide the future development and evaluation of automated adaptive planning technologies.

