Session Item

Re-irradiation (reRT) for locoregional recurrence or second cancers after previous radiotherapy (RT) is a promising treatment technique, though anatomical changes between courses and radiobiologically-appropriate dose summation of multiple RT courses are recognised challenges. Optimally, reRT treatment planning should take the previously delivered dose into account. However, if traditional normal tissue threshold dose levels are already exceeded in previous treatments, regular optimization functions might cause suboptimal reRT plans. We propose a set of novel optimization functions designed for reRT treatment planning.

The standard physical optimization functions in RayStation that quadratically penalize voxel doses above a threshold dose level were adjusted to quadratically penalize the total equivalent dose in 2 Gy fractions (EQD2) above a threshold EQD2 level (EQD2_level). The EQD2_level was further adjusted in a voxelwise fashion to account for the accumulated delivered EQD2 and a selected minimum allowed reRT EQD2 (EQD2_{delivered+reRTmin}) as,

EQD2*_level[x] = max(EQD2_level[x], EQD2_{delivered+reRTmin}[x]),

where EQD2*_level[x] is the adapted EQD2_level for voxel x in a ROI. An α/β=3 Gy was used for all voxels in this study. To account for partial tissue recovery between the RT courses, a set of reRT scale factors ([0,1]) that scale the EQD2 for each previous RT course could be selected. These adjustments were implemented in a research version of RayStation 11A for the maximum EQD2/EUD/DVH functions and the EQD2 fall-off function (Fig. 1). To demonstrate proof of concept, reRT VMAT plans of 35 Gy in 5 fractions (EQD2=70 Gy) were optimized to fulfil D_95%≥95% and D_2%≤105% using standard and novel optimization functions (EQD2_reRTmin=1–2 Gy) for a spherical relapse (20 cc) in three positions (scenarios A, B and C) following a fictive pelvic treatment of 60 Gy in 20 fractions (EQD2=72 Gy) on a human phantom (CIRS 801-P) (Fig. 2). The homogeneity index (HI=EQD2_95%/EQD2_5%), EQD2 conformity index (CI=V_{target, 95%}/V_95%) and EQD2 gradient index (GI=[V_20%-V_80%]/V_target) were evaluated.

All reRT plans fulfilled D_95%≥95 % and D_2%≤105%. The EQD2 distributions in Fig. 2a and 2b resulted in 0.93, 0.91 and 8.54 (HI, CI, GI) using the standard functions compared with 0.95, 0.92 and 5.50 using the novel functions for scenario A. The corresponding values for scenario B were 0.90, 0.90 and 9.03 for the standard functions vs. 0.92, 0.96 and 6.81 for the novel functions, whereas for scenario C the standard functions resulted in 0.90, 0.70, 14.81 vs. 0.91, 0.98, 9.86 for the novel functions.

The novel optimization functions were well-suited for reRT with increased HI and CI as well as reduced GI compared to standard functions for all scenarios in this proof-of-concept study. These novel functions are being tested in the Support Tool for Re-Irradiation Decisions guided by Radiobiology (STRIDeR) project and have the potential to be instrumental in the future of reRT planning.