Evaluation of VMAT Fallback Planning for Tomotherapy Treatment Continuity
Abstract
Purpose
RayStation’s Fallback Planning (FBP) uses dose mimicking to automatically generate a new radiotherapy plan from an existing plan using a different treatment modality, technique, or unit. This facilitates contingency planning in the event of a non-paired treatment unit’s downtime if another delivery technique is available. This study evaluated the dosimetric quality and planning speed of fallback planning VMAT TrueBeam plans from Radixact tomotherapy plans.
Methods
Clinically acceptable tomotherapy plans were generated in RayStation (v.2023B) for 12 patients previously treated on a TrueBeam: four lung (60 Gy/30 fx), four pelvis (60 Gy/20 fx), and four liver SABR (45 Gy/3 fx, 45 Gy/5 fx, or 54 Gy/3 fx). VMAT fallback plans were automatically created (FBPoriginal) for each case. To simulate temporary Radixact unavailability, one (liver SABR) or two (lung and pelvis) FBPoriginal fractions were summed with the remaining tomotherapy fractions in the treatment course. If FBPoriginal failed to meet clinical goals, it was manually re-optimized (FBPmodified). The time for FBPoriginal generation and manual FBPmodified re-optimization was recorded.
Results
The average time for automatic generation of FBPoriginal was 191s. Ten of twelve FBPoriginal plans failed to meet clinical objectives. However, for all 8 high-fractionation lung and pelvis cases, objectives were met when FBPoriginal plans were used for only 2 fractions of a tomotherapy course. For all 4 low-fractionation liver SABR cases, at least one objective was not met if FBPoriginal plans were used for 1 fraction of a tomotherapy course. All FBPmodified plans met clinical criteria and required an additional mean optimization time of 457s.
Conclusion
FBP supports fast generation of contingency TrueBeam VMAT plans in the event of Radixact downtime. Long-course treatments may not require FBP modification if only used for a few fractions, while short-course treatments are likely to require additional post-FBP optimization.