Florian Kamp1, Gonzalo Cabal2, Andrea Mairani3, Katia Parodi2, Jan J Wilkens4, David J Carlson5. 1. Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut; Department of Radiation Oncology, Technische Universität München, Klinikum Rechts der Isar, München, Germany; Physik-Department, Technische Universität München, Garching, Germany. 2. Experimental Physics-Medical Physics, Ludwig Maximilians University Munich, Garching, Germany. 3. Medical Physics Unit, Centro Nazionale Adroterapia Oncologica (CNAO), Pavia, Italy; Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany. 4. Department of Radiation Oncology, Technische Universität München, Klinikum Rechts der Isar, München, Germany; Physik-Department, Technische Universität München, Garching, Germany. 5. Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut. Electronic address: david.j.carlson@yale.edu.
Abstract
PURPOSE: The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. METHODS AND MATERIALS: Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damage simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. RESULTS: We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β)X = 2 Gy. CONCLUSIONS: These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization.
PURPOSE: The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. METHODS AND MATERIALS: Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damage simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. RESULTS: We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β)X = 2 Gy. CONCLUSIONS: These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization.
Authors: Lawrence Bronk; Fada Guan; Darshana Patel; Duo Ma; Benjamin Kroger; Xiaochun Wang; Kevin Tran; Joycelyn Yiu; Clifford Stephan; Jürgen Debus; Amir Abdollahi; Oliver Jäkel; Radhe Mohan; Uwe Titt; David R Grosshans Journal: Cancers (Basel) Date: 2020-12-05 Impact factor: 6.639