Towards a Feasible Offline Adaptive Planning Workflow with Halcyon Hypersight
Abstract
Purpose
Hypersight (Varian Medical Systems, Palo Alto, CA) captures clearer images than traditional on-board treatment imaging. The improved image quality and Hounsfield Unit accuracy supports adaptive radiotherapy workflows by enabling direct dose calculation on treatment CBCTs. This work aimed to develop and clinically implement a feasible and efficient routine offline adaptive workflow with Halcyon Hypersight imaging, thereby expanding access to the clinical benefits of treatment adaptation, including improved target coverage and organ-at-risk sparing.
Methods
Automation was leveraged where possible to achieve turnaround times approaching online adaptive planning. Hypersight iCBCT Acuros acquisitions (125 kVp, 470.35 mAs, 2 mm slice thickness) featuring noise reduction and scatter correction algorithms were used for plan optimisation and dose calculation. Target contours were propagated from the reference plan using image registration. Adapted plans were evaluated by the prescribing doctor against the reference simulation CT to confirm dosimetric improvement. Images with significant imaging artifacts likely to compromise dose accuracy were excluded.
Results
A clinically feasible offline adaptive workflow was demonstrated using Halcyon Hypersight CBCT. The integration of ESAPI scripting and AI contouring enabled a high degree of automation, reducing adaptive planning time and improving workflow efficiency. Comprehensive commissioning and reliable automated quality assurance workflows demonstrated seamless incorporation into routine clinical practice.
Conclusion
Offline adaptive radiotherapy using Halcyon Hypersight CBCT is feasible. Workflow efficiency is further improved by leveraging advanced technologies such as AI contouring and ESAPI scripting to automate adaptive planning where possible. Extending patient access to off-line adaptive planning can improve treatment quality without the additional resource burden of online adaptation. Future work will aim to further streamline this workflow and expand this work to other disease sites.