Performance Benchmarking of AAA, AXB, and CCC Algorithms Against Monte Carlo Standards

Sixty-five anonymized clinical radiotherapy plans were used to benchmark three dose calculation algorithms against a Monte Carlo standard. The study, authored by Yutong Zhao and last updated in May 2026, found AXB generally most accurate, while CCC performed comparably for lung cases. All deterministic algorithms exhibited systematic dose deviations in lung tissue and planning target volumes.

Use Cases

• Benchmarking dose calculation algorithm accuracy based on gamma passing rates and dose-volume histograms
• Evaluating algorithm performance for specific anatomical sites like lung cancer based on the described results
• Informing clinical protocol selection for the Halcyon radiotherapy platform based on the comparative findings
• Designing secondary verification strategies to address deterministic algorithm inaccuracies as highlighted in the conclusion

Strengths

• Benchmarking is based on 65 clinical Halcyon plans, providing a concrete sample size.
• Performance is evaluated using specific metrics: gamma passing rates of 2%/2mm and dose-volume histograms.
• The dataset is licensed under CC-BY-4.0, allowing for open sharing and reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (65.8 KB), indicating limited scope, likely containing summary results rather than raw plan data.

Provenance

Source

Yutong Zhao via figshare.

Collection Method

Sixty-five clinical Halcyon plans were anonymized and recalculated using AAA, AXB, CCC, and Monte Carlo approaches.

Freshness

Last updated 2026-05-15 04:27:26; freshness should be verified.