Relative Biological Effect/Linear Energy Transfer in Proton Beam Therapy: A Primer

Gulliford, S. L., & Prise, K. M. (2019). Relative Biological Effect/Linear Energy Transfer in Proton Beam Therapy: A Primer. Clinical Oncology. https://doi.org/10.1016/j.clon.2019.06.009

Published in: Clinical Oncology

Document Version: Peer reviewed version

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Download date:02. Oct. 2021 Elsevier Editorial System(tm) for Clinical Oncology Manuscript Draft

Manuscript Number:

Title: RBE/LET in Proton Beam Therapy: A Primer.

Article Type: Editorial-commissioned

Keywords: Linear Energy Transfer (LET) Relative Biological Effect (RBE) Proton Beam Therapy

Corresponding Author: Dr. Sarah Gulliford, PhD

Corresponding Author's Institution: University College Hospital London

First Author: Sarah Gulliford, PhD

Order of Authors: Sarah Gulliford, PhD; Kevin M Prise, PhD

Manuscript Region of Origin: UNITED KINGDOM *Title Page

Title: RBE/LET in Proton Beam Therapy: A Primer

Sarah L Gulliford PhD [1] & Kevin M Prise PhD [2]

[1] Department of Radiotherapy

University College Hospitals London

250 Euston Road

London

NW1 2PG

[2] Centre for Cancer Research & Cell Biology

Queen’s University Belfast

Belfast

BT9 7AE,

Keywords

Linear Energy Transfer (LET)

Relative Biological Effect (RBE)

Proton Beam Therapy (PBT)

Acknowledgments

KMP acknowledges support from EPSRC (Ep/K022415/1). *Manuscript (without Author details)

1 2 RBE/LET in Proton Beam Therapy: A Primer 3 4 5 6 Keywords 7 8 9 10 Linear Energy Transfer (LET) 11 12 Relative Biological Effect (RBE) 13 14 Proton Beam Therapy 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

1 2 Introduction and aim of paper 3 4 Proton beam therapy is a rapidly developing tool in cancer treatment. This educational piece will 5 outline the key physical, biological and clinical parameters that give a basic understanding of the 6 radiobiology of proton therapy (Fig. 1). In particular it will focus on the important parameters of 7 8 linear energy transfer (LET) and relative biological effectiveness (RBE). 9 10 Proton vs. photon physical characteristics 11 12 Radiotherapy is based on the concept of delivering physical dose, in the form of ionizing radiation, to 13 cause a biological response. We know that the main target for damage is cellular DNA. High energy 14 photons are used globally for radiotherapy. They are indirectly ionizing particles which means that 15 16 the photons interact to produce secondary electrons which then impart dose to the medium. At the 17 photon energies used for external beam radiotherapy (≥6 MV) the dominant interaction is Compton 18 scattering where incoming photons eject an atomic electron [1]. In contrast, protons are directly 19 20 ionizing particles and predominantly interact with atomic electrons through multiple coulomb 21 scattering. The mass advantage of the protons means that little energy is lost by the proton during 22 23 an interaction but with the sheer number of interactions the proton loses energy with depth in the 24 patient [2]. As the energy decreases, the velocity of the proton decreases and the number of 25 interactions increases, consequently increasing the local dose deposition. The dose deposited 26 27 increases steeply in a short distance at the end of the protons range with a sharp fall off beyond the 28 peak. This dose distribution with depth is known as the Bragg curve. 29 30 Proton therapy is comparatively expensive to deliver relative to linac-based photons [3]; however 31 the difference in interactions results in a preferential dose-distribution which has the potential to 32 33 reduce the dose to normal tissues relative to optimal photon. We know that protons are 34 radiobiologically more effective than photons, however, quantification of this difference is a current 35 active area of research [4]. 36 37 38 Absorbed Dose 39 Absorbed Dose is defined as the mean energy imparted by ionising radiation to matter of mass m in 40 a finite volume v. The unit of absorbed dose is the gray (Gy) where 1 Gy is equivalent to 1 joule per 41 42 kilogram (J/kg). 43 44 Linear Energy Transfer 45 Linear Energy Transfer (LET) is defined as the average energy locally imparted to the absorbing 46 47 medium by a charged particle of specified energy traversing a given distance of the medium. Most 48 typically expressed in units of kiloelectronvolts per micrometre (keV/μm). As with dose, LET 49 increases with depth for protons with the maximum just beyond the Bragg peak. 50 51 52 Relative Biological Effectiveness (RBE) 53 RBE is the defined as the ratio of dose required to produce the same biological effect between a 54 radiation beam (often charged particles) and a reference radiation usually defined as 250 kVp X-rays 55 60 56 or a Co γ-rays (RBE=1). RBE depends on the conditions under which the effect is measured [5]. 57 58 Experimental evidence has shown that RBE is related to LET, increasing towards the end of the range 59 of a proton, in and just slightly beyond the Bragg peak. Although clinically, a constant value of 1.1 is 60 61 62 63 64 65 used to relate proton dosimetry to biological effect, this is an oversimplification for both tumour and 1 normal tissue responses [6]. 2 3 4 5 6 Photons vs. protons biological characteristics 7 The increased ionization density of particles relative to photons (i.e. increased LET), leads to more 8 9 densely ionizing clusters of energy interacting with cells and particular with the nuclear DNA leading 10 to a high probability of clusters of DNA damage being produced locally on the DNA. These can 11 consist of multiple DNA lesions, such as base damage, single-strand breaks, double-strand breaks 12 13 (dsb) and crosslinks as part of what is termed clustered (or complex) DNA damage [7]. This damage 14 is thought to be more difficult to repair and with increasing LET more DSB are left unrepaired and 15 have a higher probability to lead to cell death. This leads to an increased RBE for cell killing with 16 17 increasing LET, typically up to a maximum value (dependent on ion species) beyond which energy 18 then becomes wasted (overkill effect). RBE however is dependent on many additional factors, such 19 20 as dose, dose-rate and individual radiosensitivity. Oxygen is also a major modifier of response which 21 is LET dependent. For low LET radiations such as X-rays and γ-rays, regions of tumours which are 22 hypoxic (at reduced oxygen) are more radioresistant. Oxygen rapidly converts radicals produced 23 24 after irradiation to damaging peroxy-radicals which are the precursors of DNA damage. In the 25 absence of oxygen, cells are ~ 3 times more radioresistant. This is measured in clonogenic survival 26 assays as an Oxygen Enhancement Ratio (OER). This is defined as the ratio of the radiation dose 27 28 under anoxic conditions to produce a given effect relative to the radiation dose under fully 29 oxygenated conditions to produce the same effect. OER also decreases with increasing LET making 30 ion beams more effective against hypoxic tumours. 31 32 33 Calculating RBE - cell survival curve 34 RBE is found experimentally by plotting the cell survival curves for a single cell line comparing the 35 36 survival fraction using the reference beam and the particle beam. The dose required to produce a 37 specific survival is compared. These measurements are sensitive to a large number of experimental 38 factors including the choice of reference beam, the cell line, the choice of survival fraction, dose rate 39 [5]. 40 41 The review article by Paganetti which collated preclinical data found the RBE to be 1.1 at the 42 43 entrance of the beam, 1.3 at the distil edge and 1.7 in the distil fall off region. It also noted the large 44 variation in experimental setup and the large uncertainty in the derived values. 45 46 47 48 49 Current data for protons-models 50 Mathematical models relating physical dose to relative biological effect are numerous and remain 51 largely unvalidated. Models based on the Linear Quadratic model are widely cited when considering 52 53 proton beams [8] [9] [10] [11]. It is beyond the remit to describe in full each implementation but 54 generally each model requires the dose averaged LET and α/β value of the tissue (photons). The 55 models have been fitted to mostly pre-clinical data to derive the relevant parameter values. 56 57 Variation between models papers often present results for two or three models. 58 59 60 61 62 63 64 65 In general the models describe an increase in RBE with LET and an increase in RBE for low α/β 1 values. It should be noted that much of pre-clinical data does not include dose points in the range of 2 3 interest for clinical radiotherapy i.e. <=2Gy per fraction and rarely includes fractionated data. 4 5 Heavy ions 6 This article has considered the LET/RBE from the perspective of protons since they have now 7 12 8 become part of UK radiotherapy. However internationally heavier ions, most commonly C, have 9 been used, particularly in Japan and Germany [12]. In the case of heavy ions a variable RBE with 10 depth is included in treatment planning [13]. As such the physical dose is reduced in regions where 11 12 the RBE increases. Due to the higher LET than protons, significant biological advantages occur, 13 particularly for the treatment of radioresistant tumours. Given this importance of the underlying 14 15 biology, a range of mechanistic models have also been developed to define RBE relationships for 16 different ions (see [14] for a review). 17 18 Clinical Proton Beams 19 20 For the delivery of a clinical spot-scanning proton beams, overlapping Bragg Curves of different 21 energies (and hence range) are raster scanned into the patient to produce a spread-out-bragg-peak 22 (SOBP) covering the tumour volume at depth. The proton beam range has a small inherent 23 24 uncertainty resulting from the calibration curve required to translate CT Hounsfield Units to proton 25 stopping powers. Uncertainty in patient positioning and changes over the course of treatment will 26 further blur the dose distribution compared to the well-controlled pre-clinical environment. Since 27 28 individual organs are complex functional units of different cell types, the assays of individual cell 29 lines may not be relevant. Additionally dose distributions to OAR are intentionally heterogeneous 30 31 and therefore complex to characterize. The ability to calculate LET and RBE at a voxel-wise level is 32 emerging and subsequently the potential for LET-based treatment plan optimization. It has been 33 demonstrated that the distribution of high RBE regions may well be outside the CTV and within OAR. 34 35 However, despite the comprehensive data indicating that the RBE is variable, to date clinical practice 36 has steadfastly used the value of 1.1. This has been due to 1) uncertainty in knowing the correct 37 value to use in the clinical setting, 2) inability to include variable RBE in commercial treatment 38 39 planning systems and perhaps most influentially 3) limited clinical evidence of an enhanced RBE at 40 the distal edge of clinically delivered SOBP [15]. 41 42 The way forward is to consider the potential consequences of variable RBE whilst remaining mindful 43 44 of the uncertainties. AAPM released Task group report 256 earlier this year [4]. This report focusses 45 on how to move forward in the knowledge that a constant value of 1.1 may not be the optimal 46 approach but states that “it is premature to adopt and recommend a variable RBE model to use 47 48 clinically.” 49 50 51 52 Until LET and RBE information becomes available and is widely implemented in commercial 53 treatment planning systems it is important to consider the potential implications when designing 54 and reviewing proton therapy treatment plans. The most widely discussed scenario is where an 55 56 organ at risk abuts the target volume and a beam is placed so that the distil edge of the SOBP sits at 57 the border of the two. In an ideal case this situation would be avoided by considering alternative 58 59 beam placement but this is not always achievable for example where tumours are in close proximity 60 to the brainstem. If field specific optimization is used it may be possible to limit the weighting of 61 62 63 64 65 spots adjacent to or overlapping the OAR using additional structures defining the overlap region or 1 by decreasing the dosimetric constraint. Assessment of treatment plan robustness which is inherent 2 3 to the proton treatment planning process will indicate if the level of uncertainty in the physical dose 4 to the region of concern. 5 6 Summary 7 8 Understanding the relationship between LET and RBE is important for the delivery of improved 9 strategies of clinical delivery which can mitigate uncertainties with the use of proton and other ion 10 beams. 11 12

13 14 15 16 17 18 19 20 Bibliography 21 22 23 24 [1] E. B. Podgorsak, Radiation Oncology Physics: A Handbook for teachers and students, Vienna: 25 IAEA, 2005. 26 27 28 [2] A. Lühr, C. von Neubeck, J. Pawelke, A. Seidlitz, C. Peitzsch, S. Bentzen, T. Bortfeld, J. Debus, E. 29 Deutsch, J. Langendijk, J. Loeffler, R. Mohan, M. Scholz, B. Sørensen, D. Weber, M. Baumann 30 and M. Krause, ""Radiobiology of Proton Therapy": Results of an international expert 31 workshop.," Radiotherapy Oncology, pp. 56-67, 2018. 32 33 34 [3] National Cancer Research Institute Clinical and Translational Radiotherapy Research Working 35 Group (CTRad) Proton Beam Clinical Trial Strategy Group, "Proton Beam Therapy e the 36 Challenges of Delivering High-quality Evidence of Clinical Benefit," Clinical Oncology, pp. 280- 37 38 284, 2018. 39 40 [4] H. Paganetti, E. Blakely, A. Carabe-Fernandez, D. Carlson, I. Das, L. Dong, D. Grosshans, K. Held, 41 R. Mohan, V. Moiseenko, A. Niemierko, R. Stewart and H. Willers, "Report of the AAPM TG-256 42 on the relative biological effectiveness of proton beams in radiation therapy," Medical Physics, 43 44 pp. e53-e78, 2019. 45 46 [5] H. Paganetti, "Relative biological effectiveness (RBE) values for proton beam therapy. Variations 47 as a function of biological endpoint, dose, and linear energy transfer," Physics Medicine Biology, 48 pp. R419-72, 2014. 49 50 51 [6] B. Jones, S. McMahon and K. Prise, "The Radiobiology of Proton Therapy: Challenges and 52 Opportunities Around Relative Biological Effectiveness.," Clinical Oncology, vol. 30, no. 5, pp. 53 285-292, 2018. 54 55 56 [7] D. Goodhead, "Initial Events in the Cellular Effects of Ionizing-Radiations-Clustered Damage in 57 DNA.," International Journal Rdaiation Biology, pp. 7-17, 1994. 58 59 [8] M. Wedenberg, B. Lind and B. Hårdemark, "A model for the relative biologicaleffectiveness of 60 61 62 63 64 65 protons: the tissue specific parameter α / β of photons is a predictor for the sensitivity to LET 1 changes.," Acta Oncologica, vol. 52, no. 3, pp. 580-8, 2013. 2 3 4 [9] A. Carabe-Fernandez, R. Dale and B. Jones, "The incorporation of the concept of minimum RBE 5 (RbEmin) into the linear-quadratic model and the potential for improved radiobiological analysis 6 of high-LET treatments," International Journal of Radiation Biology , vol. 83, no. 1, pp. 27-39, 7 2007. 8 9 10 [10] A. McNamara, J. Schuemann and H. Paganetti, "A phenomenological relative biological 11 effectiveness (rbe) model for proton therapy based on all published in vitro cell survival data," 12 Physics Medicine Biology, vol. 60, no. 21, pp. 8399-416, 2015. 13 14 [11] J. Wilkens and U. Oelfke, "A phenomenological model for the relative biological effectiveness in 15 16 therapeutic proton beams," Physics Medicine and Biology, vol. 49, no. 13, pp. 2811-25, 2004. 17 18 [12] O. Mohamad, S. Yamada and M. Durante, "Clinical indications for Carbon Ion Radiotherapy," 19 Clinical Oncology, pp. 317-329, 2018. 20 21 [13] R. Stewart, D. Carlson, M. Butkus, R. Hawkins, T. Friedrich and M. Scholz, "A comparison of 22 23 mechanism-inspired models for particle relative biological effectiveness (RBE)," Medical Physics, 24 pp. e925-e952, 2018. 25 26 [14] S. McMahon and K. Prise, "Mechanistic Modelling of Radiation Responses.," Cancers (Basel), vol. 27 28 11, no. 2, 2019. 29 30 [15] D. Giantsoudi, R. Sethi, B. Yeap, B. Eaton, D. Ebb, P. Caruso, O. Rapalino, Y. Chen, J. Adams, T. 31 Yock, N. Tarbell, P. H. and S. MacDonald, "Incidence of CNS Injury for a Cohort of 111 Patients 32 Treated With Proton Therapy for Medulloblastoma: LET and RBE Associations for Areas of 33 34 Injury.," International Journal Radiation Oncology Biology Physics., vol. 95, no. 1, pp. 287-96, 35 2016. 36 37 38 39 40 41 42 43 44 45 Figure Legends 46 47 48 49 Figure 1. Schematic of key physical, biological and clinical issues associated with proton beam 50 51 therapy delivery. An idealized spread-out-Bragg-Peak is shown with an example of the difference 52 between physical and biological dose with depth. 53 54 55 56 57 58 59 60 61 62 63 64 65 *Declaration of Interest Statement

Declaration of interests

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

*ICMJE Form Click here to download ICMJE Form: Gulliford coi_disclosure (1).pdf

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*Author Contributions

Both authors were equally involved in writing this educational article

1 guarantor of integrity of the entire study KMP/SLG

2 study concepts and design KMP/SLG

3 literature research KMP/SLG

4 clinical studies NA

5 experimental studies / data analysis NA

6 statistical analysis NA

7 manuscript preparation KMP/SLG

8 manuscript editing KMP/SLG Illustrations

• Dose • Particle Type Physics • Energy/LET

Target Region OAR • RBE Particle SOBP Biological Dose • Repair/Survival Biology • Oxygen Therapy

SOBP Physical Dose Effect • Range Uncertainty • Macroscopic Clinical Biological response Depth • RBE models