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Using biologically based objectives to optimize boost intensity‐modulated radiation therapy planning for brainstem tumors in dogs
Authors:Valeria Meier  Jürgen Besserer  Carla Rohrer Bley
Abstract:Irradiated brain tumors commonly progress at the primary site, generating interest in focal dose escalation. The aim of this retrospective observational study was to use biological optimization objectives for a modeling exercise with simultaneously‐integrated boost IMRT (SIB‐IMRT) to generate a dose‐escalated protocol with acceptable late radiation toxicity risk estimate and improve tumor control for brainstem tumors in dogs safely. We re‐planned 20 dog brainstem tumor datasets with SIB‐IMRT, prescribing 20 × 2.81 Gy to the gross tumor volume (GTV) and 20 × 2.5 Gy to the planning target volume. During the optimization process, we used biologically equivalent generalized equivalent uniform doses (gEUD) as planning aids. These were derived from human data, calculated to adhere to normal tissue complication probability (NTCP) ≤5%, and converted to the herein used fractionation schedule. We extracted the absolute organ at risk dose‐volume histograms to calculate NTCP of each individual plan. For planning optimization, gEUD(a = 4) = 39.8 Gy for brain and gEUD(a = 6.3) = 43.8 Gy for brainstem were applied. Mean brain NTCP was low with 0.43% (SD ±0.49%, range 0.01‐2.04%); mean brainstem NTCP was higher with 7.18% (SD ±4.29%, range 2.87‐20.72%). Nevertheless, NTCP of < 10% in brainstem was achievable in 80% (16/20) of dogs. Spearman's correlation between relative GTV and NTCP was high (ρ = 0.798, P < .001), emphasizing increased risk with relative size even with subvolume‐boost. Including biologically based gEUD values into optimization allowed estimating NTCP during the planning process. In conclusion, gEUD‐based SIB‐IMRT planning resulted in dose‐escalated treatment plans with acceptable risk estimate of NTCP < 10% in the majority of dogs with brainstem tumors. Risk was correlated with relative tumor size.
Keywords:biologically based treatment planning  brain  gEUD  IMRT  SIB
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