SU‐E‐T‐651: Radiobiological Effect of Target Volume in SBRT of Lung Tumor: Comparison of Treatment Planning Algorithms Between Pencil Beam Algorithm and Monte Carlo Method

Abstract

Purpose: To use equivalent uniform dose (EUD) and tumor control probability (TCP) to retrospectively analyze the radiobiological effect of target volumes in patients with NSCLC planned and treated with Stereotactic Body Radiotherapy (SBRT). Methods: Eighty‐three stage I–II lung cancer patients with 86 lesions treated with SBRT were retrospectively analyzed. For each patient, a Pencil Beam (PB) algorithm‐based treatment plan with a dose regimen of 12 Gy/fraction in 4 fractions was generated. To overcome the known uncertainties of conventional PB algorithm in lung tissue, Monte Carlo (MC) treatment plans were also created in the iPlan (BrainLab) system using the same monitor units derived from the PB‐based plan. Niemierkoˈs EUD and TCP (Poisson model) were computed using different surviving fraction (SF) parameters for each dose calculation algorithm. The radiobiological effects of target volume were analyzed by correlating EUD and TCP with PTV volumes. Results: Mean PTV volume was 39.31 +/− 28.96 cc. The mean PB EUDs were 50.61, 50.60, 50.57 and 50.55 Gy for SF parameter values of 0.36, 0.34, 0.3 and 0.28, compared with MC EUDs 43.97, 43.84, 43.56 and 43.41 Gy. The mean PB TCP values were up to 18% higher than the mean MC TCP. EUDs calculated using both PB and MC were not sensitive to SF parameters, whereas they were for TCP calculation. Overall, MC EUDs were more sensitive to PTV volumes than PB EUDs, measured by Pearson correlation 0.46 vs. 0.07. Larger PTV volume decreased PB TCP values while this was not the case for MC TCP Conclusions: This work demonstrates encouraging evidence that radiobiological effect of target volume and dose calculation algorithm selection is significant in EUD and TCP estimations. Further studies confirming this relationship and relating to treatment outcomes are warranted.Work supported in part by NIH R01 CA106770