Brain Re-Irradiation Robustly Accounting for Previously Delivered Dose

Abstract

(1) Background: The STRIDeR (Support Tool for Re-Irradiation Decisions guided by Radiobiology) planning pathway aims to facilitate anatomically appropriate and radiobiologically meaningful re-irradiation (reRT). This work evaluated the STRIDeR pathway for robustness compared to a more conservative manual pathway. (2) Methods: For ten high-grade glioma reRT patient cases, uncertainties were applied and cumulative doses re-summed. Geometric uncertainties of 3, 6 and 9 mm were applied to the background dose, and LQ model robustness was tested using α/β variations (values 1, 2 and 5 Gy) and the linear quadratic linear (LQL) model δ variations (values 0.1 and 0.2). STRIDeR robust optimised plans, incorporating the geometric and α/β uncertainties during optimisation, were also generated. (3) Results: The STRIDeR and manual pathways both achieved clinically acceptable plans in 8/10 cases but with statistically significant improvements in the PTV D98% (p < 0.01) for STRIDeR. Geometric and LQ robustness tests showed comparable robustness within both pathways. STRIDeR plans generated to incorporate uncertainties during optimisation resulted in a superior plan robustness with a minimal impact on PTV dose benefits. (4) Conclusions: Our results indicate that STRIDeR pathway plans achieved a similar robustness to manual pathways with improved PTV doses. Geometric and LQ model uncertainties can be incorporated into the STRIDeR pathway to facilitate robust optimisation.

Technical note: Optimization functions for re‐irradiation treatment planning

“…Although some previous studies have reported similar approaches for the evaluation of re-irradiation treatments, 19,20 few have incorporated such functionalities into re-irradiation planning using commercially available software. [3][4][5] For the fictitious RI scenario in this study, the three re-planning strategies performed equally well (Table 2, Figure 2, Figure 3a,b), which was expected due to the large distances between PTV and relevant OARs associated with RI treatments. 1 However, note the slightly elongated EQD2 distribution for reRT reduce compared to F I G U R E 3 Dose-volume histograms (DVHs) using dose and total equivalent dose in 2-Gy fraction (EQD2 tot ) for the three relapse scenarios-repeat irradiation (RI), re-irradiation type 1 (RIT1) and type 2 (RIT2).…”

“…The use of EQD2 allows for dose summation of radiotherapy courses with different fractionation schedules and is often used for dose summations in re-irradiation treatments. 1,[3][4][5]10…”

“…The implementation here supports both rigid and DIR for dose mapping. [3][4][5] Note that the previously delivered dose from course j in Equation ( 2) can be estimated in various ways including the planned dose, dose-tracking on daily images, etc., and is always mapped to the re-irradiation CT before voxel-by-voxel conversion to EQD2 deliv, j with region of interest (ROI)-specific α/β ratios and ROI and treatment course specific recovery coefficients. Note also that the re-irradiation optimization function methodology presented in this study is conceptually invariant to the methodology used for dose accumulation.…”

“…These include the need to retrieve accurate image and dose data, handling of anatomical changes between the radiotherapy courses, integration of radiobiology when summing multiple radiotherapy courses, and deciding on clinically relevant dose constraints. [3][4][5][6][7][8] In contrast, almost no planning software specifically designed for re-irradiation exists, and even fewer efforts have been made on creating re-irradiation-specific optimization functions.Instead,various approaches requiring multiple manual steps for dose extraction and dose summation are often used. 4,7 Slightly more complex planning methods also exist where radiobiologically meaningful approaches are employed using, for example, the biological effective dose or the equivalent dose in 2-Gy fractions (EQD2).…”

“…9 Recent studies within the Support Tool for Re-Irradiation Decisions guided by Radiobiology (STRIDeR) project have, however, addressed some of these re-irradiation-specific planning issues including early versions of the optimization functions presented here, which act on the 3D distribution of the accumulated EQD2. [3][4][5] Beyond acting on radiobiologically meaningful doses, other key issues when using standard optimization functions in re-irradiation planning are the lack of accounting for tissue recovery between treatment courses, and the use of penalization dose levels without accounting for the estimated previously delivered EQD2 (EQD2 deliv ). In particular, the latter is an issue in situations where the previously delivered dose in a voxel is similar to or higher than the requested total EQD2 level, which might cause misbehavior in the optimization as very low, or even negative, voxel doses are requested.…”