Performance benchmarking of AAA, AXB, and CCC approaches against Monte Carlo standards in Halcyon-based radiotherapy
Source
Zhao, Y., Zhao, J., Ma, X., Jiang, Z., Sun, W., Zhang, Z. & Yin, Y. (2026). Performance benchmarking of AAA, AXB, and CCC approaches against Monte Carlo standards in Halcyon-based radiotherapy. Frontiers in Physics, 14. https://doi.org/10.3389/fphy.2026.1789216
Background
Accurate dose calculation is essential for radiotherapy. The present study benchmarks the performances of the anisotropic analytical algorithm (AAA), Acuros XB (AXB), and collapsed cone convolution (CCC) methods against the Monte Carlo (MC) standard for the Halcyon platform across diverse anatomical sites.
Methods
Sixty-five clinical Halcyon plans were anonymized and recalculated using the AAA, AXB, CCC, and MC approaches; the corresponding algorithmic performances were evaluated using gamma passing rates (GPRs) of 2% per 2 mm and dose–volume histograms (DVHs) with the MC standard as the reference.
Results
AXB achieved the highest GPRs across most tumor sites; however, for the lung cancer plans, the performance of CCC was comparable to that of AXB and superior to that of AAA. All algorithms exhibited systematic dose deviations by underestimating and overestimating doses in the lung tissues and planning target volumes (PTVs). The gamma failures increased in the high-Hounsfield-unit and high-dose regions.
Conclusion
Although AXB is generally found to be the most accurate algorithm, AAA is also recommended owing to its faster calculations while maintaining acceptable accuracy. However, CCC is more strongly recommended than AAA for lung cases owing to its superior performance. Thus, the present study highlights the necessity for secondary MC verifications and the application of compensatory strategies to effectively address the inherent inaccuracies of deterministic algorithms.