Fast generation of lung SBRT plans with a knowledge-based planning model on ring-mounted Halcyon Linac

Area of Science:

• Radiation Oncology
• Medical Physics
• Cancer Treatment

Background:

• Stereotactic body radiation therapy (SBRT) is a precise radiation technique for treating tumors.
• Centrally located lung tumors present unique planning challenges.
• Adaptive radiotherapy aims to adjust treatment based on anatomical changes during treatment.

Purpose of the Study:

• To assess the feasibility of rapid treatment planning for lung SBRT using a knowledge-based planning (KBP) model on the Halcyon Linac.
• To support offline adaptive radiotherapy workflows.
• To evaluate the dosimetric and time efficiency of KBP-based Halcyon plans compared to traditional methods.

Main Methods:

• Twenty retrospective non-coplanar VMAT lung SBRT plans (50 Gy/5 fractions) were re-optimized for the Halcyon Linac.
• Plans were generated manually (m-Halcyon) and using a validated KBP model (k-Halcyon).
• Plans were compared against original c-Truebeam plans for target coverage, conformity, dose heterogeneity, OAR sparing, and planning time.

Main Results:

• k-Halcyon plans demonstrated dosimetric similarity or superiority to manual Halcyon and original c-Truebeam plans.
• Conformity index differences were insignificant for k-Halcyon and slightly higher for m-Halcyon.
• Gradient index was improved with k-Halcyon, while mean lung dose and bronchial tree dose were reduced.
• Planning time for k-Halcyon was significantly reduced to under 30 minutes compared to ~180 minutes for manual plans.

Conclusions:

• The KBP model on the Halcyon Linac enables rapid generation of high-quality SBRT plans for lung tumors.
• This approach is suitable for supporting adaptive radiotherapy and can facilitate high-volume patient throughput.
• The Halcyon Linac with KBP offers an efficient solution for lung SBRT expansion or patient transfer.