Assessment of RBE-Weighted Dose Models for Carbon Ion Therapy Toward Modernization of Clinical Practice at HIT: In Vitro, in Vivo, and in Patients

Purpose Present-day treatment planning in carbon ion therapy is conducted with assumptions for a limited number of tissue types and models for effective dose. Here, we comprehensively assess relative biological effectiveness (RBE) in carbon ion therapy and associated models toward the modernization of current clinical practice in effective dose calculation. Methods Using 2 human (A549, H460) and 2 mouse (B16, Renca) tumor cell lines, clonogenic cell survival assay was performed for examination of changes in RBE along the full range of clinical-like spread-out Bragg peak (SOBP) fields. Prediction power of the local effect model (LEM1 and LEM4) and the modified microdosimetric kinetic model (mMKM) was assessed. Experimentation and analysis were carried out in the frame of a multidimensional end point study for clinically relevant ranges of physical dose (D), dose-averaged linear energy transfer (LETd), and base-line photon radio-sensitivity (α/β)x. Additionally, predictions were compared against previously reported RBE measurements in vivo and surveyed in patient cases. Results RBE model prediction performance varied among the investigated perspectives, with mMKM prediction exhibiting superior agreement with measurements both in vitro and in vivo across the 3 investigated end points. LEM1 and LEM4 performed their best in the highest LET conditions but yielded overestimations and underestimations in low/midrange LET conditions, respectively, as demonstrated by comparison with measurements. Additionally, the analysis of patient treatment plans revealed substantial variability across the investigated models (±20%-30% uncertainty), largely dependent on the selected model and absolute values for input tissue parameters αx and βx. Conclusion RBE dependencies in vitro, in vivo, and in silico were investigated with respect to various clinically relevant end points in the context of tumor-specific tissue radio-sensitivity assignment and accurate RBE modeling. Discovered model trends and performances advocate upgrading current treatment planning schemes in carbon ion therapy and call for verification via clinical outcome analysis with large patient cohorts. Present-day treatment planning in carbon ion therapy is conducted with assumptions for a limited number of tissue types and models for effective dose. Here, we comprehensively assess relative biological effectiveness (RBE) in carbon ion therapy and associated models toward the modernization of current clinical practice in effective dose calculation. Using 2 human (A549, H460) and 2 mouse (B16, Renca) tumor cell lines, clonogenic cell survival assay was performed for examination of changes in RBE along the full range of clinical-like spread-out Bragg peak (SOBP) fields. Prediction power of the local effect model (LEM1 and LEM4) and the modified microdosimetric kinetic model (mMKM) was assessed. Experimentation and analysis were carried out in the frame of a multidimensional end point study for clinically relevant ranges of physical dose (D), dose-averaged linear energy transfer (LETd), and base-line photon radio-sensitivity (α/β)x. Additionally, predictions were compared against previously reported RBE measurements in vivo and surveyed in patient cases. RBE model prediction performance varied among the investigated perspectives, with mMKM prediction exhibiting superior agreement with measurements both in vitro and in vivo across the 3 investigated end points. LEM1 and LEM4 performed their best in the highest LET conditions but yielded overestimations and underestimations in low/midrange LET conditions, respectively, as demonstrated by comparison with measurements. Additionally, the analysis of patient treatment plans revealed substantial variability across the investigated models (±20%-30% uncertainty), largely dependent on the selected model and absolute values for input tissue parameters αx and βx. RBE dependencies in vitro, in vivo, and in silico were investigated with respect to various clinically relevant end points in the context of tumor-specific tissue radio-sensitivity assignment and accurate RBE modeling. Discovered model trends and performances advocate upgrading current treatment planning schemes in carbon ion therapy and call for verification via clinical outcome analysis with large patient cohorts.