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Predicting the Relative Biological Effectiveness of Carbon Ion Radiation Therapy Beams Using the Mechanistic Repair-Misrepair-Fixation (RMF) Model and Nuclear Fragment Spectra
Poster Viewing Abstracts S849
Volume 90 Number 1S Supplement 2014 error. These setup shifts were comparable for tumors of the trunk and extremity. While it is unknown whether such tumor misses translate to altered treatment efficacy or adverse effects, treatment conformity is a central principle in modern radiation therapy which is clearly undermined by interfractional setup variation, if not accounted for. Additionally, imaging provides early assessment of tumor (or surrounding soft-tissue) changes that may necessitate treatment replanning. We recommend imageguidance with setup corrections to minimize daily setup variations in the treatment of soft-tissue sarcomas. Author Disclosure: A.M. Monjazeb: None. N.K. Harandi: None. A.L. Michaud: None. R. Canter: None. J. Perks: None.
3625 Hypofractionated Liver Stereotactic Body Radiation Therapy: Biological Effective Dose Correlated Radiation-Induced Liver Disease A. Bergamo,1 K. Kaweloa,1 A.J. Patel,2 P. Mavroidis,3 N. Papanikolaou,4 S. Stathakis,5 and A.N. Gutierrez4; 1University of Texas Health Science Center at San Antonio, San Antonio, TX, 2University of Texas Health Science Center San Antonio, San Antonio, TX, 3University of Texas Health Sciences Center San Antonio, San Antonio, TX, 4Cancer Therapy & Research Center, San Antonio, TX, 5Cancer Therapy and Research Center, San Antonio, TX Purpose/Objective(s): To evaluate the correlation of physical and biological effective dose (BED) between SBRT fractionation schemes and radiation induced late disease seen in the Liver. Materials/Methods: A total of 23 patients (11 - 3Gy x 10fx, 7 - 10Gy x 5fx and 5 - 15Gy x 3fx) were selected. The physical dose distributions were converted to voxel based BED values using the linear quadratic (LQ) model and the linear-quadratic linear (LQ-L) model for doses per fraction larger than 6Gy. Dose comparisons were made between the LQ and LQ-L model predictions. The patients were graded using the RTOG Late Radiation Morbidity Scoring Schema associated with Radiation Induced Liver Disease (RILD) and compared against the current dose tolerance of V15Gy 700cc. A correlation between volumetric BED values and attributed acute or chronic RILD was made using a conservative BED converted dose constraint of V-30Gy3 700cc. Results were measured qualitatively using dose difference images and quantitatively using BED-DVH, Bland-Altman (BA) analysis, Pearson Correlation Coefficient (PCC) and Percent Error Volume Histograms (PEVH). Results: Linear regression fit of physical dose and BED against RILD grade yielded R2 values of 0.0923 and 0.0092, respectively. Mean Dose Tolerable to Normal Liver (MDTNL) against RILD grade resulted in an R2 value of 0.0057. Average values of Mean Dose- percent error and PCC for 3Gyx10Fx were 0% and 1.0 as control, 6.27% +/- 2.87% and 0.997 +/.0015 for 10Gyx5Fx and 17.92% +/- 2.39% with 0.987 +/- .0017 for 15Gyx3Fx. The average V15Gy and V-30Gy3 per grade plotted against RILD grade yielded R2 correlations of 0.535 and 0.7267, respectively. Conclusions: Increased doses per fraction yield an increase in deviation from the predictions of the LQ model however, regression analysis between physical dose, BED and RILD grade shows the same prediction of normal tissue toxicity will be reached by using either metric. MDTNL shows little to no direct correlation to RILD Grade. Although equivalent relationships are indicated, a larger patient sample population is needed to solidify correlations. Average BED per Grade exhibits a strong relationship to RILD Grade where physical dose shows only a moderate correlation. Author Disclosure: A. Bergamo: None. K. Kaweloa: None. A.J. Patel: None. P. Mavroidis: None. N. Papanikolaou: None. S. Stathakis: None. A.N. Gutierrez: None.
3626 Predicting the Relative Biological Effectiveness of Carbon Ion Radiation Therapy Beams Using the Mechanistic Repair-MisrepairFixation (RMF) Model and Nuclear Fragment Spectra F. Kamp,1,2 G. Cabal,3 A. Mairani,4,5 K. Parodi,3 J.J. Wilkens,2 and D.J. Carlson1; 1Department of Therapeutic Radiology, Yale University
School of Medicine, New Haven, CT, 2Department of Radiation Oncology, Technische Universita¨t Mu¨nchen, Klinikum rechts der Isar, Munich, Germany, 3 Ludwig Maximilians University (LMU) Munich, Experimental Physics Medical Physics, Munich, Germany, 4Medical Physics Unit CNAO Foundation, Pavia, Italy, 5Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany Purpose/Objective(s): The physical and biological advantages of carbon ion beams over conventional x-rays have not been fully exploited and may result in improvements in local tumor control and normal tissue sparing. Treatment planning must account for physical beam properties, such as absorbed dose, linear energy transfer, and the contribution of nuclear fragments, as well as differences in the relative biological effectiveness (RBE) of ions compared to photons. The purpose of this work is to use the mechanistic repair-misrepair-fixation (RMF) model in combination with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Materials/Methods: Relative changes in double strand break yields and intrinsic radiosensitivity parameters (aP, bP) with particle type and energy are predicted using the Monte Carlo Damage Simulation (MCDS) and the RMF model, respectively, to determine estimates of RBE values for primary carbon ions and secondary fragments (Z Z 1-5). Depth dependent energy spectra of these ions are generated with the Monte-Carlo code FLUKA for clinically-relevant initial carbon ion energies. Using the linearquadratic model, RBE is a function of dose averaged aP and bP, physical dose (dP), and reference radiosensitivity parameters (aX, bX). Predicted trends in RBE with particle energy and radiosensitivity are compared to recently published experimental data. Biological optimization for carbon ions was implemented in the 3D research treatment planning tool CERR. Results: We compare RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The dominant fragments are protons and helium ions, contributing up to 13% and 7% of the deposited dose, respectively. Inclusion of fragments in the simulations leads to smaller RBE predictions. For example, for a spread-out Bragg peak from 10 to 15 cm in water RBE decreases by 10-20% distally and 1-3% proximally, depending on dP. A validation of RMF against measured cell survival data reported in the literature shows excellent agreement. We calculate RWD distributions on 3D patient data, optimize the biological effect, and compare RMF predictions to other commonly used biological models. Conclusion: The reported studies provide new information to accurately quantify RBE for carbon ion therapy based on biophysical mechanisms. We have performed the first biological optimization of carbon ion radiation therapy beams on patient data using the RMF model. The presented method is advantageous for fast biological optimization in heavy ion radiation therapy. Acknowledgment: This project was partially supported by a fellowship from the German Academic Exchange Service (DAAD). Author Disclosure: F. Kamp: None. G. Cabal: None. A. Mairani: None. K. Parodi: A. Employee; Heidelberg University Hospital, LMU University Hospital. J.J. Wilkens: A. Employee; Klinikum rechts der Isar (University hospital). K. Advisory Board; Scientific Advisory Board of the Pro Health AG. S. Leadership; Associate Editor for the European Journal of Medical Physics. D.J. Carlson: A. Employee; Yale University School of Medicine, Yale-New Haven Hospital.
3627 A Novel Multi-Institutional Database for Tracking and Reporting Dose-Volume Data and Normal Tissue Effects D.R. Simpson,1 J.L. Ambite,2 R. Kosztyla,3 G. Kumaraguruparan,2 M. Liu,3 K.L. Moore,1 J.D. Murphy,1 J. Wu,3 and V. Moiseenko1; 1 University of California San Diego, La Jolla, CA, 2Information Sciences Institute, University of Southern California, Marina Del Rey, CA, 3 Vancouver Cancer Centre, Vancouver, BC, Canada Purpose/Objective(s): Understanding the interaction between normal tissue and radiation dose is crucial for predicting radiation toxicity and optimizing the therapeutic ratio between clinically effective radiation
Volume 90 Number 1S Supplement 2014 error. These setup shifts were comparable for tumors of the trunk and extremity. While it is unknown whether such tumor misses translate to altered treatment efficacy or adverse effects, treatment conformity is a central principle in modern radiation therapy which is clearly undermined by interfractional setup variation, if not accounted for. Additionally, imaging provides early assessment of tumor (or surrounding soft-tissue) changes that may necessitate treatment replanning. We recommend imageguidance with setup corrections to minimize daily setup variations in the treatment of soft-tissue sarcomas. Author Disclosure: A.M. Monjazeb: None. N.K. Harandi: None. A.L. Michaud: None. R. Canter: None. J. Perks: None.
3625 Hypofractionated Liver Stereotactic Body Radiation Therapy: Biological Effective Dose Correlated Radiation-Induced Liver Disease A. Bergamo,1 K. Kaweloa,1 A.J. Patel,2 P. Mavroidis,3 N. Papanikolaou,4 S. Stathakis,5 and A.N. Gutierrez4; 1University of Texas Health Science Center at San Antonio, San Antonio, TX, 2University of Texas Health Science Center San Antonio, San Antonio, TX, 3University of Texas Health Sciences Center San Antonio, San Antonio, TX, 4Cancer Therapy & Research Center, San Antonio, TX, 5Cancer Therapy and Research Center, San Antonio, TX Purpose/Objective(s): To evaluate the correlation of physical and biological effective dose (BED) between SBRT fractionation schemes and radiation induced late disease seen in the Liver. Materials/Methods: A total of 23 patients (11 - 3Gy x 10fx, 7 - 10Gy x 5fx and 5 - 15Gy x 3fx) were selected. The physical dose distributions were converted to voxel based BED values using the linear quadratic (LQ) model and the linear-quadratic linear (LQ-L) model for doses per fraction larger than 6Gy. Dose comparisons were made between the LQ and LQ-L model predictions. The patients were graded using the RTOG Late Radiation Morbidity Scoring Schema associated with Radiation Induced Liver Disease (RILD) and compared against the current dose tolerance of V15Gy 700cc. A correlation between volumetric BED values and attributed acute or chronic RILD was made using a conservative BED converted dose constraint of V-30Gy3 700cc. Results were measured qualitatively using dose difference images and quantitatively using BED-DVH, Bland-Altman (BA) analysis, Pearson Correlation Coefficient (PCC) and Percent Error Volume Histograms (PEVH). Results: Linear regression fit of physical dose and BED against RILD grade yielded R2 values of 0.0923 and 0.0092, respectively. Mean Dose Tolerable to Normal Liver (MDTNL) against RILD grade resulted in an R2 value of 0.0057. Average values of Mean Dose- percent error and PCC for 3Gyx10Fx were 0% and 1.0 as control, 6.27% +/- 2.87% and 0.997 +/.0015 for 10Gyx5Fx and 17.92% +/- 2.39% with 0.987 +/- .0017 for 15Gyx3Fx. The average V15Gy and V-30Gy3 per grade plotted against RILD grade yielded R2 correlations of 0.535 and 0.7267, respectively. Conclusions: Increased doses per fraction yield an increase in deviation from the predictions of the LQ model however, regression analysis between physical dose, BED and RILD grade shows the same prediction of normal tissue toxicity will be reached by using either metric. MDTNL shows little to no direct correlation to RILD Grade. Although equivalent relationships are indicated, a larger patient sample population is needed to solidify correlations. Average BED per Grade exhibits a strong relationship to RILD Grade where physical dose shows only a moderate correlation. Author Disclosure: A. Bergamo: None. K. Kaweloa: None. A.J. Patel: None. P. Mavroidis: None. N. Papanikolaou: None. S. Stathakis: None. A.N. Gutierrez: None.
3626 Predicting the Relative Biological Effectiveness of Carbon Ion Radiation Therapy Beams Using the Mechanistic Repair-MisrepairFixation (RMF) Model and Nuclear Fragment Spectra F. Kamp,1,2 G. Cabal,3 A. Mairani,4,5 K. Parodi,3 J.J. Wilkens,2 and D.J. Carlson1; 1Department of Therapeutic Radiology, Yale University
School of Medicine, New Haven, CT, 2Department of Radiation Oncology, Technische Universita¨t Mu¨nchen, Klinikum rechts der Isar, Munich, Germany, 3 Ludwig Maximilians University (LMU) Munich, Experimental Physics Medical Physics, Munich, Germany, 4Medical Physics Unit CNAO Foundation, Pavia, Italy, 5Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany Purpose/Objective(s): The physical and biological advantages of carbon ion beams over conventional x-rays have not been fully exploited and may result in improvements in local tumor control and normal tissue sparing. Treatment planning must account for physical beam properties, such as absorbed dose, linear energy transfer, and the contribution of nuclear fragments, as well as differences in the relative biological effectiveness (RBE) of ions compared to photons. The purpose of this work is to use the mechanistic repair-misrepair-fixation (RMF) model in combination with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Materials/Methods: Relative changes in double strand break yields and intrinsic radiosensitivity parameters (aP, bP) with particle type and energy are predicted using the Monte Carlo Damage Simulation (MCDS) and the RMF model, respectively, to determine estimates of RBE values for primary carbon ions and secondary fragments (Z Z 1-5). Depth dependent energy spectra of these ions are generated with the Monte-Carlo code FLUKA for clinically-relevant initial carbon ion energies. Using the linearquadratic model, RBE is a function of dose averaged aP and bP, physical dose (dP), and reference radiosensitivity parameters (aX, bX). Predicted trends in RBE with particle energy and radiosensitivity are compared to recently published experimental data. Biological optimization for carbon ions was implemented in the 3D research treatment planning tool CERR. Results: We compare RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The dominant fragments are protons and helium ions, contributing up to 13% and 7% of the deposited dose, respectively. Inclusion of fragments in the simulations leads to smaller RBE predictions. For example, for a spread-out Bragg peak from 10 to 15 cm in water RBE decreases by 10-20% distally and 1-3% proximally, depending on dP. A validation of RMF against measured cell survival data reported in the literature shows excellent agreement. We calculate RWD distributions on 3D patient data, optimize the biological effect, and compare RMF predictions to other commonly used biological models. Conclusion: The reported studies provide new information to accurately quantify RBE for carbon ion therapy based on biophysical mechanisms. We have performed the first biological optimization of carbon ion radiation therapy beams on patient data using the RMF model. The presented method is advantageous for fast biological optimization in heavy ion radiation therapy. Acknowledgment: This project was partially supported by a fellowship from the German Academic Exchange Service (DAAD). Author Disclosure: F. Kamp: None. G. Cabal: None. A. Mairani: None. K. Parodi: A. Employee; Heidelberg University Hospital, LMU University Hospital. J.J. Wilkens: A. Employee; Klinikum rechts der Isar (University hospital). K. Advisory Board; Scientific Advisory Board of the Pro Health AG. S. Leadership; Associate Editor for the European Journal of Medical Physics. D.J. Carlson: A. Employee; Yale University School of Medicine, Yale-New Haven Hospital.
3627 A Novel Multi-Institutional Database for Tracking and Reporting Dose-Volume Data and Normal Tissue Effects D.R. Simpson,1 J.L. Ambite,2 R. Kosztyla,3 G. Kumaraguruparan,2 M. Liu,3 K.L. Moore,1 J.D. Murphy,1 J. Wu,3 and V. Moiseenko1; 1 University of California San Diego, La Jolla, CA, 2Information Sciences Institute, University of Southern California, Marina Del Rey, CA, 3 Vancouver Cancer Centre, Vancouver, BC, Canada Purpose/Objective(s): Understanding the interaction between normal tissue and radiation dose is crucial for predicting radiation toxicity and optimizing the therapeutic ratio between clinically effective radiation