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

Abstract Objective . Proton dosimetric uncertainties resulting from the patient’s daily setup errors in rotational directions exist even with advanced image-guided radiotherapy techniques. Thus, we developed a new rotational robust optimization SPArc algorithm (SPArc rot ) to mitigate the dosimetric impact of the rotational setup error in Raystation ver. 6.02 (RaySearch Laboratory AB, Stockholm, Sweden). Approach. The initial planning CT was rotated ±5° simulating the worst-case setup error in the roll direction. The SPArc rot uses a multi-CT robust optimization framework by taking into account of such rotational setup errors. Five cases representing different disease sites were evaluated. Both SPArc original and SPArc rot plans were generated using the same translational robust optimized parameters. To quantitatively investigate the mitigation effect from the rotational setup errors, all plans were recalculated using a series of pseudo-CT with rotational setup error (±1°/±2°/±3°/±5°). Dosimetric metrics such as D98% of CTV, and 3D gamma analysis were used to assess the dose distribution changes in the target and OARs. Main results. The magnitudes of dosimetric changes in the targets due to rotational setup error were significantly reduced by the SPArc rot compared to SPArc in all cases. The uncertainties of the max dose to the OARs, such as brainstem, spinal cord and esophagus were significantly reduced using SPArc rot . The uncertainties of the mean dose to the OARs such as liver and oral cavity, parotid were comparable between the two planning techniques. The gamma passing rate (3%/3 mm) was significantly improved for CTV of all tumor sites through SPArc rot . Significance. Rotational setup error is one of the major issues which could lead to significant dose perturbations. SPArc rot planning approach can consider such rotational error from patient setup or gantry rotation error by effectively mitigating the dose uncertainties to the target and in the adjunct series OARs.