Beyond conventional bounds: Surpassing system limits for stereotactic ablative (SAbR) lung radiotherapy using...

Area of Science:

• Radiation Oncology
• Medical Physics
• Radiotherapy Planning

Background:

• Online adaptive radiotherapy requires automation for rapid treatment planning.
• The Varian Ethos intelligent optimization engine (IOE) needs specific guidance for lung SAbR.
• Mitigating inter-planner variability is crucial for meeting RTOG metrics in SAbR.

Purpose of the Study:

• To investigate the use of Ethos IOE with custom adaptive-specific optimization tuning structures.
• To reduce variability in meeting RTOG metrics for lung SAbR plans.
• To provide clear guidance for lung SAbR plans using Ethos IOE.

Main Methods:

• Developed an automated planning strategy for tuning structures and optimization.
• Validated the strategy on 35 lung SAbR cases (105 fractions).
• Compared plan quality with and without auto-generated tuning structures; analyzed ITV contour consistency.

Main Results:

• The strategy improved dose conformality by 2% and plan quality metrics (GI by 3.8%, CI by 1.7%).
• Adaptive plans achieved 100% PTV coverage compliance, significantly better than non-adaptive plans (37%).
• ITV size remained consistent between CT simulation and cone-beam CT (CBCT).

Conclusions:

• A robust, shareable planning strategy for adaptive lung SAbR on Ethos was developed.
• Automatic online re-optimization with adaptive tuning structures ensures consistent plan quality.
• The strategy enables highly ablative treatments on the Ethos system.