Dosimetric impact of knowledge-based automated planning using HyperArc for angiosarcoma of the scalp

This study aimed to automate and standardize treatment planning by comparing the dosimetric performance of conventional volumetric modulated arc therapy (C-VMAT) with that of HyperArc optimized using the knowledge-based RapidPlan model trained with the HyperArc plan (RP-HA) for total scalp irradiation (TSI) in the treatment of angiosarcoma of the scalp (AS). Additionally, this study compared the dosimetric performance of RP-HA with that of non-coplanar VMAT optimized using the same model (RP-NC-VMAT). From 40 patients with AS who had undergone TSI, 20 patients were selected for HyperArc planning and RapidPlan model training. The remaining 20 patients had treatment plans generated using three different methods (C-VMAT, RP-NC-VMAT, and RP-HA). The prescription doses were 70 and 56 Gy in 35 fractions of the target volumes, including gross tumor and whole scalp, respectively, using the simultaneous integrated boost technique. The dose distribution, dosimetric parameters, and dosimetric accuracy of each treatment plan were evaluated and compared between methods. None of the three methods exceeded the acceptable limits for all constraint parameters of the target and organs at risk. The RP-HA plan provided a significantly lower mean brain dose (10.96 ± 1.54 Gy) than the C-VMAT and RP-NC-VMAT plans (18.06 ± 2.17 Gy and 12.36 ± 2.12 Gy). The dose received by 0.1 cm³ of the hippocampus was significantly lower in the RP-NC-VMAT and RP-HA plans than in the C-VMAT plan. The RapidPlan model trained with the HyperArc plan can be helpful in automating and standardizing treatment planning in TSI for AS.