RBE and related modeling in carbon-ion therapy

Karger, Christian P.; Peschke, Peter

doi:10.1088/1361-6560/aa9102

Cited by 157 publications

(168 citation statements)

References 217 publications

(300 reference statements)

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“…The RBE is a nonlinear function of the physical dose and it is estimated by means of dedicated radiobiological models of the interaction between the particle beam and the irradiated system. 23 In this study, we validate the WED-space method for the estimation of motion-induced variations in the physical dose, which is independent of radiobiological modeling. We also provide a comparison between physical and biologically effective (i.e., RBE-weighted) dose variations due to respiratory motion, thus evaluating the feasibility of physical dose metrics to quantify the impact of organ motion in our context.…”

Section: Introductionmentioning

confidence: 76%

“…Nevertheless, the impact of respiratory motion on biologically effective dose distributions related to physical dose variations was investigated and resulted in an overall lower sensitivity, thus suggesting the feasibility of physical dose metrics for the WED‐space method validation. The integration of a radiobiological model will permit to obtain the missing information. Despite these limitations, this study showed that the WED‐space method is able to provide simulations of the dosimetric effect of irregular breathing when imaging data are lacking.…”

Section: Resultsmentioning

confidence: 99%

“…In carbon ion therapy, clinical dose distributions are evaluated in terms of relative biological effectiveness (RBE)‐weighted dose [Gy(RBE)]. The RBE is a nonlinear function of the physical dose and it is estimated by means of dedicated radiobiological models of the interaction between the particle beam and the irradiated system …”

Section: Introductionmentioning

confidence: 99%

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Validation of a model for physical dose variations in irregularly moving targets treated with carbon ion beams

et al. 2019

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Purpose In particle therapy, conventional treatment planning systems rely on an imaging representation of the irradiated region to compute the dose. For irregular breathing, when an imaging dataset describing the actual motion is not available, a different approach for dose estimation is needed. To this aim, we validate a method for the estimation of physical dose variations in gated carbon ion treatments, providing also a demonstration of the feasibility of physical dose metrics to assess the method performance. Finally, we describe a sample use case, in which this method is used to assess plan robustness with respect to undetected irregular tumor motion. Methods The method entails the definition of a patient‐ and beam‐specific water equivalent depth (WED) space, the simulation of motion as a translation equal to tumor displacement, and the reconstruction of the altered dose. We validated the approach using four‐dimensional computed tomographies (4DCTs) and clinical plans in 12 patients, treated with respiratory gated carbon ion beams at the National Centre for Oncological Hadrontherapy (Pavia, Italy). Using the end‐exhale CT and dose distribution as a reference, the physical dose delivered at the end‐inhale tumor position was estimated and compared to the ground‐truth dose recalculation on the end‐inhale CT. Biologically effective and physical dose variations between the plan and the recalculation were compared as well. As a use case, we evaluated dose changes caused by simulated irregular tumor motion, that is, linear and nonlinear baseline shifts and/or amplitude variations with hysteresis. Results The ratio between biologically effective and physical equivalent uniform dose (EUD) variations due to end‐exhale to end‐inhale motion was less than one for 96% of investigated structures. In the validation study, we found a median error corresponding to a 14% EUD overestimation for the tumor and 4% EUD underestimation for a subgroup of organs at risk, together with a high EUD variation due to motion [median 352% EUD variation between end‐exhale and end‐inhale doses in the planning tumor volume (PTV)]. Considering relevant dose‐volume histogram (DVH) metrics, the median difference between estimated and ground truth doses was ≤ 4%. Gamma analysis between estimated and recalculated dose distributions resulted in a pass rate > 80% for 83% of the target volumes. For the two patients selected for the sample use case, a patient‐specific assessment of the method performance was performed on the 4DCT and it was possible to relate EUD variations of both tumor and organs at risk to the simulated target motion. Conclusions The physical dose distribution was found to be more sensitive to motion with respect to the biologically effective one, suggesting the suitability of the physical dose metrics for the WED‐space method validation. We showed that the method can compensate for intra‐fractional tumor motion with proper accuracy in the selected patient group, although its use is recommended when limited deformations are expected....

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Section: Introductionmentioning

confidence: 76%

Section: Resultsmentioning

confidence: 99%

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Validation of a model for physical dose variations in irregularly moving targets treated with carbon ion beams

et al. 2019

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“…Because of the multitude of the factors and mechanisms of action underlying tumor and normal tissue responses to radiation therapy, particle RBE also depends on many biological, patient‐ and treatment‐specific factors, including the particle type, incident beam energy, and number and types of treatment fields . Because particle RBE is a ratio of the doses of radiations that produce the same biological effect, it is important to note that the biology and treatment factors (e.g., total dose and fraction size) used as low LET reference radiation are as important to accurate determinations of clinical RBE as particle beam biology and treatment factors.…”

Section: Introductionmentioning

confidence: 99%

“…32 Because of the multitude of the factors and mechanisms of action underlying tumor and normal tissue responses to radiation therapy, particle RBE also depends on many biological, patient-and treatment-specific factors, including the particle type, incident beam energy, and number and types of treatment fields. [33][34][35][36][37][38][39] Because particle RBE is a ratio of the doses of radiations that produce the same biological effect, it is important to note that the biology and treatment factors (e.g., total dose and fraction size) used as low LET reference radiation are as important to accurate determinations of clinical RBE as particle beam biology and treatment factors. For all of these reasons, mathematical models of particle RBE are essential for efforts to translate the results of in vitro and in vivo experiments probing mechanisms of action to the clinical setting, thus facilitating the optimization and personalization of hadron therapy treatment planning.…”

Section: Introductionmentioning

confidence: 99%

A comparison of mechanism‐inspired models for particle relative biological effectiveness (RBE)

et al. 2018

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Background and Significance The application of heavy ion beams in cancer therapy must account for the increasing relative biological effectiveness (RBE) with increasing penetration depth when determining dose prescriptions and organ at risk (OAR) constraints in treatment planning. Because RBE depends in a complex manner on factors such as the ion type, energy, cell and tissue radiosensitivity, physical dose, biological endpoint, and position within and outside treatment fields, biophysical models reflecting these dependencies are required for the personalization and optimization of treatment plans. Aim To review and compare three mechanism‐inspired models which predict the complexities of particle RBE for various ion types, energies, linear energy transfer (LET) values and tissue radiation sensitivities. Methods The review of models and mechanisms focuses on the Local Effect Model (LEM), the Microdosimetric‐Kinetic (MK) model, and the Repair‐Misrepair‐Fixation (RMF) model in combination with the Monte Carlo Damage Simulation (MCDS). These models relate the induction of potentially lethal double strand breaks (DSBs) to the subsequent interactions and biological processing of DSB into more lethal forms of damage. A key element to explain the increased biological effectiveness of high LET ions compared to MV x rays is the characterization of the number and local complexity (clustering) of the initial DSB produced within a cell. For high LET ions, the spatial density of DSB induction along an ion's trajectory is much greater than along the path of a low LET electron, such as the secondary electrons produced by the megavoltage (MV) x rays used in conventional radiation therapy. The main aspects of the three models are introduced and the conceptual similarities and differences are critiqued and highlighted. Model predictions are compared in terms of the RBE for DSB induction and for reproductive cell survival. Results and Conclusions Comparisons of the RBE for DSB induction and for cell survival are presented for proton (1H), helium (4He), and carbon (12C) ions for the therapeutically most relevant range of ion beam energies. The reviewed models embody mechanisms of action acting over the spatial scales underlying the biological processing of potentially lethal DSB into more lethal forms of damage. Differences among the number and types of input parameters, relevant biological targets, and the computational approaches among the LEM, MK and RMF models are summarized and critiqued. Potential experiments to test some of the seemingly contradictory aspects of the models are discussed.

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