Robust optimization of VMAT for lung cancer: Dosimetric implications of motion compensation techniques

Abstract

In inverse planning of lung radiotherapy, techniques are required to ensure dose coverage of target disease in the presence of tumor motion as a result of respiration. A range of published techniques for mitigating motion effects were compared for dose stability across 5 breath cycles of ±2 cm. Techniques included planning target volume ( PTV) expansions, internal target volumes with ( OITV) and without tissue override ( ITV), average dataset scans ( ADS), and mini‐max robust optimization. Volumetric arc therapy plans were created on a thorax phantom and verified with chamber and film measurements. Dose stability was compared by DVH analysis in calculations across all geometries. The lung override technique resulted in a substantial lack of dose coverage (−10%) to the tumor in the presence of large motion. PTV, ITV and ADS techniques resulted in substantial (up to 25%) maximum dose increases where solid tissue travelled into low density optimized regions. The results highlight the need for care in optimization of highly heterogeneous where density variations may occur with motion. Robust optimization was shown to provide greater stability in both maximum (<3%) and minimum dose variations (<2%) over all other techniques.