Introduce a rotational robust optimization framework for spot-scanning proton arc (SPArc) therapy

Area of Science:

• Medical Physics
• Radiation Oncology
• Radiotherapy Planning

Background:

• Patient setup errors, particularly in rotational directions, introduce dosimetric uncertainties in proton therapy.
• Advanced image-guided radiotherapy techniques still face challenges in mitigating these rotational uncertainties.

Purpose of the Study:

• To develop and evaluate a novel rotational robust optimization algorithm, SPArc_rot, for mitigating dosimetric impacts of rotational setup errors.
• To assess the effectiveness of SPArc_rot in reducing target and organ-at-risk (OAR) dose uncertainties compared to the original SPArc algorithm.

Main Methods:

• A new rotational robust optimization SPArc algorithm (SPArc_rot) was developed using a multi-CT robust optimization framework.
• Simulated rotational setup errors (±5° roll) and recalculated plans with varying rotational errors (±1° to ±5°).
• Evaluated dosimetric metrics including D98% of CTV and 3D gamma analysis (3%/3 mm) across five disease sites.

Main Results:

• SPArc_rot significantly reduced dosimetric changes in targets and uncertainties in maximum OAR doses (e.g., brainstem, spinal cord) compared to SPArc.
• Uncertainties in mean OAR doses (e.g., liver, parotid) were comparable between the two techniques.
• Gamma passing rates for the clinical target volume (CTV) were significantly improved with SPArc_rot.

Conclusions:

• Rotational setup errors are a significant source of dose perturbation in proton therapy.
• The SPArc_rot planning approach effectively mitigates dose uncertainties for targets and OARs by accounting for rotational errors.
• SPArc_rot offers improved precision and safety in image-guided proton radiotherapy.