Characterizing Radiation Effectiveness in Ion Beam Therapy Part I: Introduction and Biophysical Modeling of RBE Using the LEMIV

Scholz, M.; Friedrich, Thomas; Magrin, Giulio; Colautti, P.; Ristić-Fira, Aleksandra; Petrović, Ivana

doi:10.3389/fphy.2020.00272

Cited by 14 publications

(11 citation statements)

References 71 publications

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“…The investigations in this work demonstrate the universal applicability of the LEM IV concept for the simulation of various experimental scenarios, covering several ion species in a broad energy range. As shown in various publications before, the LEM IV is generally able to reproduce the characteristic shape of RBE as a function of LET 3,4,7–11 . Furthermore, due to the detailed quantitative comparison of simulation results to PIDE measurement data, previously reported model limitations could be confirmed.…”

Section: Discussionsupporting

confidence: 56%

“…As shown in various publications before, the LEM IV is generally able to reproduce the characteristic shape of RBE as a function of LET. 3,4,[7][8][9][10][11] Furthermore, due to the detailed quantitative comparison of simulation results to PIDE measurement data, previously reported model limitations could be confirmed. For lower LET values, the LEM IV tends to underestimate the RBE and the model accuracy decreases with increasing atomic number of the considered ion.…”

Section: Discussionmentioning

confidence: 88%

“…The LEM IV has shown good agreement with measurement data in several previous model applications. 3,4,[7][8][9][10][11] However, single comparisons of LEM IV predictions to measurement data already revealed a tendency toward an underestimation of RBE at higher ion energies for carbon ions. This was observed, for example, for V79 Chinese hamster cells in vitro 4 as well as for the tolerance of rat spinal cord in vivo.…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive comparison of local effect model IV predictions with the particle irradiation data ensemble

2021

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Purpose The increased relative biological effectiveness (RBE) of ions is one of the key benefits of ion radiotherapy compared to conventional radiotherapy with photons. To account for the increased RBE of ions during the process of ion radiotherapy treatment planning, a robust model for RBE predictions is indispensable. Currently, at several ion therapy centers the local effect model I (LEM I) is applied to predict the RBE, which varies with biological and physical impacting factors. After the introduction of LEM I, several model improvements were implemented, leading to the current version, LEM IV, which is systematically tested in this study. Methods As a comprehensive RBE model should give consistent results for a large variety of ion species and energies, the particle irradiation data ensemble (PIDE) is used to systematically validate the LEM IV. The database covers over 1100 photon and ion survival experiments in form of their linear‐quadratic parameters for a wide range of ion types and energies. This makes the database an optimal tool to challenge the systematic dependencies of the RBE model. After appropriate filtering of the database, 571 experiments were identified and used as test data. Results The study confirms that the LEM IV reflects the RBE systematics observed in measurements well. It is able to reproduce the dependence of RBE on the linear energy transfer (LET) as well as on the αγ/βγ ratio for several ion species in a wide energy range. Additionally, the systematic quantitative analysis revealed precision capabilities and limits of the model. At lower LET values, the LEM IV tends to underestimate the RBE with an increasing underestimation with increasing atomic number of the ion. At higher LET values, the LEM IV overestimates the RBE for protons or helium ions, whereas the predictions for heavier ions match experimental data well. Conclusions The LEM IV is able to predict general RBE characteristics for several ion species in a broad energy range. The accuracy of the predictions is reasonable considering the small number of input parameters needed by the model. The detailed quantification of possible systematic deviations, however, enables to identify not only strengths but also limitations of the model. The gained knowledge can be used to develop model adjustments to further improve the model accuracy, which is on the way.

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Section: Discussionsupporting

confidence: 56%

Section: Discussionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

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Comprehensive comparison of local effect model IV predictions with the particle irradiation data ensemble

2021

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“…A question could arise whether the LEM-IV model could be applied at such low energies, in particular for the heavier fragments. LEM-IV was indeed verified for a broad energy and LET range [ 16 , 55 ] including mixed field irradiations [ 56 ], considering also that every SOBP is a mixed field including stopping and more energetic particles. While it is true that uncertainties on LET and range arise at very low energies, the verification of LEM-IV with different experiments at high LET justify its application also in this case.…”

Section: Discussionmentioning

confidence: 95%

Biological Impact of Target Fragments on Proton Treatment Plans: An Analysis Based on the Current Cross-Section Data and a Full Mixed Field Approach

Bellinzona

Grzanka

Attili

et al. 2021

Cancers

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Clinical routine in proton therapy currently neglects the radiobiological impact of nuclear target fragments generated by proton beams. This is partially due to the difficult characterization of the irradiation field. The detection of low energetic fragments, secondary protons and fragments, is in fact challenging due to their very short range. However, considering their low residual energy and therefore high LET, the possible contribution of such heavy particles to the overall biological effect could be not negligible. In this context, we performed a systematic analysis aimed at an explicit assessment of the RBE (relative biological effectiveness, i.e., the ratio of photon to proton physical dose needed to achieve the same biological effect) contribution of target fragments in the biological dose calculations of proton fields. The TOPAS Monte Carlo code has been used to characterize the radiation field, i.e., for the scoring of primary protons and fragments in an exemplary water target. TRiP98, in combination with LEM IV RBE tables, was then employed to evaluate the RBE with a mixed field approach accounting for fragments’ contributions. The results were compared with that obtained by considering only primary protons for the pristine beam and spread out Bragg peak (SOBP) irradiations, in order to estimate the relative weight of target fragments to the overall RBE. A sensitivity analysis of the secondary particles production cross-sections to the biological dose has been also carried out in this study. Finally, our modeling approach was applied to the analysis of a selection of cell survival and RBE data extracted from published in vitro studies. Our results indicate that, for high energy proton beams, the main contribution to the biological effect due to the secondary particles can be attributed to secondary protons, while the contribution of heavier fragments is mainly due to helium. The impact of target fragments on the biological dose is maximized in the entrance channels and for small α/β values. When applied to the description of survival data, model predictions including all fragments allowed better agreement to experimental data at high energies, while a minor effect was observed in the peak region. An improved description was also obtained when including the fragments’ contribution to describe RBE data. Overall, this analysis indicates that a minor contribution can be expected to the overall RBE resulting from target fragments. However, considering the fragmentation effects can improve the agreement with experimental data for high energy proton beams.

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“…This work is the second of two parts focusing on characterizing radiation effectiveness in ion-beam therapy. The first part, on biophysical modeling of relative biological effectiveness (RBE), is published by Scholz et al [1]. It is cited in this work as "Part I."…”

Section: Introductionmentioning

confidence: 99%

Characterizing Radiation Effectiveness in Ion-Beam Therapy Part II: Microdosimetric Detectors

et al. 2020

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Characterizing Radiation Effectiveness in Ion Beam Therapy Part I: Introduction and Biophysical Modeling of RBE Using the LEMIV

Cited by 14 publications

References 71 publications

Comprehensive comparison of local effect model IV predictions with the particle irradiation data ensemble

Comprehensive comparison of local effect model IV predictions with the particle irradiation data ensemble

Biological Impact of Target Fragments on Proton Treatment Plans: An Analysis Based on the Current Cross-Section Data and a Full Mixed Field Approach

Characterizing Radiation Effectiveness in Ion-Beam Therapy Part II: Microdosimetric Detectors

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