Cyberorchestrator: A Unified Software Platform for Cyberknife Radiosurgery Workflow Management
Abstract
Purpose
To develop a unified software platform, CyberOrchestrator, for streamlining CyberKnife radiosurgery clinical workflows and managing clinical data in support of translational and clinical research.
Methods
CyberOrchestractor was developed in Python to interface with the Oncology Information System (OIS), treatment planning system (TPS), and record-and-verify (RV) system and relay critical clinical workflow information to the care team. CyberOrchestrator periodically queries the OIS for active workflow tasks (e.g., contouring, planning, plan review, approval) and automatically notifies assigned planners, physicians, and physicists based on task status and urgency. It also monitors TPS activity, performing automated plan checks when plans are marked ready for review, and generating plan 2nd check reports after plan approval. This automated QA includes approximately 20–25 checks spanning imaging integrity, plan deliverability, and plan quality metrics, supplemented by 5–8 manual checks. Approved plan metadata are written to a SQL database, and plan files are archived using a structured directory system. Upon treatment completion, delivery data are retrieved and stored, and an end-of-treatment summary is generated and distributed to the attending physician and chart-check physicist.
Results
Over the first three months of full clinical deployment at a single institution treating approximately 1,000 patients annually (~2 plans per patient), the platform generated QA documentation and archived data for 439 robotic radiosurgery plans. Automated workflows enabled timely identification and correction of imaging, deliverability, and plan quality issues. Anecdotally, automation reduced planner effort by approximately 10 minutes per plan and physicist QA time by approximately 20 minutes per plan, while improving consistency and completeness of QA documentation.
Conclusion
The CyberOrchestrator platform improves the efficiency and standardization of Cyberknife radiosurgery workflows while supporting reliable QA execution and structured data capture for clinical operations, quality improvement, and future research.