Spine SBRT With Halcyon™: Plan Quality, Modulation Complexity, Delivery Accuracy, and Speed.

Thumbnail Image




Petroccia, Heather M
Malajovich, Irina
Barsky, Andrew R
Ghiam, Alireza Fotouhi
Jones, Joshua
Wang, Chunhao
Zou, Wei
Teo, Boon-Keng Kevin
Dong, Lei
Metz, James M

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats


Citation Stats


Purpose: Spine SBRT requires treatment plans with steep dose gradients and tight limits to the cord maximal dose. A new dual-layer staggered 1-cm MLC in Halcyon™ treatment platform has improved leakage, speed, and DLG compared to 120-Millennium (0.5-cm) and High-Definition (0.25-cm) MLCs in the TrueBeam platform. Halcyon™ 2.0 with SX2 MLC modulates fluence with the upper and lower MLCs, while in Halcyon™ 1.0 with SX1 only the lower MLC modulates the fluence and the upper MLC functions as a back-up jaw. We investigated the effects of four MLC designs on plan quality for spine SBRT treatments. Methods: 15 patients previously treated at our institution were re-planned according to the NRG-BR-002 guidelines with a prescription of 3,000 cGy in 3 fractions, 6xFFF, 800 MU/min, and 3-arc VMAT technique. Planning objectives were adjusted manually by an experienced planner to generate optimal plans and kept the same for different MLCs within the same platform. Results: All treatment plans were able to achieve adequate target coverage while meeting NRG-BR002 dosimetric constraints. Planning parameters were evaluated including: conformity index, homogeneity index, gradient measure, and global point dose maximum. Delivery accuracy, modulation complexity, and delivery time were also analyzed for all MLCs. Conclusion: The Halcyon™ dual-layer MLC can generate comparable and clinically equivalent spine SBRT plans to TrueBeam plans with less rapid dose fall-off and lower conformity. MLC width leaf can impact maximum dose to organs at risk and plan quality, but does not cause limitations in achieving acceptable plans for spine SBRT treatments.





Published Version (Please cite this version)


Publication Info

Petroccia, Heather M, Irina Malajovich, Andrew R Barsky, Alireza Fotouhi Ghiam, Joshua Jones, Chunhao Wang, Wei Zou, Boon-Keng Kevin Teo, et al. (2019). Spine SBRT With Halcyon™: Plan Quality, Modulation Complexity, Delivery Accuracy, and Speed. Frontiers in Oncology, 9(APR). p. 319. 10.3389/fonc.2019.00319 Retrieved from https://hdl.handle.net/10161/20267.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.



Chunhao Wang

Assistant Professor of Radiation Oncology
  • Deep learning methods for image-based radiotherapy outcome prediction and assessment
  • Machine learning in outcome modelling
  • Automation in radiotherapy planning and delivery

Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.