Direct evaluation of radiobiological parameters from clinical data in the case of ion beam therapy: an alternative approach to the relative biological effectiveness

Treatment planning of carbon ion radiotherapy for prostate cancer based on cellular experiments with PC3 human prostate cancer cells

[Purpose] Treatment plans for carbon ion radiotherapy (CIRT) in Japan are designed to uniformly deliver the prescribed clinical dose based on the radiosensitivity of human salivary gland (HSG) cells to the planning target volume (PTV). However, sensitivity to carbon beams varies between cell lines, that is, it should be checked that the clinical dose distribution based on the cell radiosensitivity of the treatment site is uniform within the PTV. [Methods] We modeled the linear energy transfer (LET) dependence of the linear-quadratic (LQ) coefficients specific to prostate cancer, which accounts for the majority of CIRT. This was achieved by irradiating prostate cancer cells (PC3) with X-rays from a 4 MV-Linac and carbon beams with different LETs of 11.1-214.3 keV/μm. By using the radiosensitivity of PC3 cells derived from cellular experiments, we reconstructed prostate-cancer-specific clinical dose distributions on patient computed tomography (CT). [Results] The LQ coefficient, α, of PC3 cells was larger than that of HSG cells at low (<50 keV/μm) LET and smaller at high (>50 keV/μm) LET, which was validated by cellular experiments performed on rectangular SOBPs. The reconstructed dose distribution on patient CT was sloped when 1 fraction incident from the one side of the patient was considered, but remained uniform from the sum of 12 fractions of the left-right opposing beams (as is used in clinical practice). [Conclusion] Our study reveals the inhomogeneity of clinical doses in single-field plans calculated using the PC3 radiosensitivity data. However, this inhomogeneity is compensated by using the combination of left-right opposing beams.

Scripted spot removal in PBS proton therapy planning

Background

It is well known in proton therapy that the relative biological effectiveness (RBE) is not constant across the entire Bragg peak, with higher RBE at the distal end of the Bragg peak due to higher linear energy transfer (LET). Treatment planning systems are moving toward LET optimization to mitigate this potentially higher biological impact at a track end. However, using a simple script, proton users can begin to simulate this process by deleting spots from critical structures during optimization. In most cases, nominal target coverage and plan robustness remain satisfactory.

Methods

In our clinic, we developed a script that allows the user to delete spots in all organs at risk (OARs) of interest for one or more treatment beams. The purpose of this script is to potentially reduce side effects by eliminating Bragg peaks within OARs. The script was first used for prostate patients where spots in the rectum and sigmoid, outside of the overlap with the target, were deleted. We then began to use the script for head and neck (H&N) and breast/chestwall patients to reduce acute side effects of the skin by removing spots in a 0.5‐cm skin rind.

Conclusions

By utilizing a simple script for deleting spots in critical structures, we have seen excellent clinical results thus far. We have noted reduced skin reactions for nearly all H&N and breast patients.

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

Simple Summary

Proton therapy is now an established external radiotherapy modality for cancer treatment. Clinical routine currently neglects the radiobiological impact of nuclear target fragments even if experimental evidences show a significant enhancement in cell-killing effect due to secondary particles. This paper quantifies the contribution of proton target fragments of different charge in different irradiation scenarios and compares the computationally predicted corrections to the overall biological dose with experimental data.

Abstract

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.

Update of the particle irradiation data ensemble (PIDE) for cell survival

The particle irradiation data ensemble (PIDE) is the largest database of cell survival data measured after exposure to ion beams and photon reference radiation. We report here on the updated version of the PIDE database and demonstrate how to investigate generic properties of radiation dose response using these sets of raw data. The database now contains information of over 1100 pairs of photon and ion dose response curves. It provides the originally published raw data of cell survival in addition to given linear quadratic (LQ) model parameters. If available, the raw data were used to derive LQ model parameters in the same way for all experiments. To demonstrate the extent of the database and the variability among experiments we focus on the dose response curves after ion and photon radiation separately in a first step. Furthermore, we discuss the capability and the limitations of the database for analyzing properties of low and high linear energy transfer (LET) radiation response based on multiple experiments. PIDE is freely available to the research community under www.gsi.de/bio-pide.

The relative biological effectiveness of carbon ion radiation therapy for early stage lung cancer

BACKGROUND AND PURPOSE

Carbon ion radiation therapy (CIRT) is recognized as an effective alternative treatment modality for early stage lung cancer, but a quantitative understanding of relative biological effectiveness (RBE) compared to photon therapy is lacking. In this work, a mechanistic tumor response model previously validated for lung photon radiotherapy was used to estimate the RBE of CIRT compared to photon radiotherapy, as a function of dose and the fractionation schedule.

MATERIALS AND METHODS

Clinical outcome data of 9 patient cohorts (394 patients) treated with CIRT for early stage lung cancer, representing all published data, were included. Fractional dose, number of fractions, treatment schedule, and local control rates were used for model simulations relative to standard photon outcomes. Four parameters were fitted: α, α/β, and the oxygen enhancement ratios of cells either accessing only glucose, not oxygen (OER_I), or cells dying from starvation (OER_H). The resulting dose-response relationship of CIRT was compared with the previously determined dose-response relationship of photon radiotherapy for lung cancer, and an RBE of CIRT was derived.

RESULTS

Best-fit CIRT parameters were: α = 1.12 Gy^-1 [95%-CI: 0.97-1.26], α/β = 23.9 Gy [95%-CI: 8.9-38.9], and the oxygen induced radioresistance of hypoxic cell populations were characterized by OER_I = 1.08 [95%-CI: 1.00-1.41] (cells lacking oxygen but not glucose), and OER_H = 1.01 [95%-CI: 1.00-1.44] (cells lacking oxygen and glucose). Depending on dose and fractionation, the derived RBE ranges from 2.1 to 1.5, with decreasing values for larger fractional dose and fewer number of fractions.

CONCLUSION

Fitted radiobiological parameters were consistent with known carbon in vitro radiobiology, and the resulting dose-response curve well-fitted the reported data over a wide range of dose-fractionation schemes. The same model, with only a few fitted parameters of clear mechanistic meaning, thus synthesizes both photon radiotherapy and CIRT clinical experience with early stage lung tumors.

Biophysical modeling and experimental validation of relative biological effectiveness (RBE) for 4He ion beam therapy

BACKGROUND

Helium (4He) ion beam therapy provides favorable biophysical characteristics compared to currently administered particle therapies, i.e., reduced lateral scattering and enhanced biological damage to deep-seated tumors like heavier ions, while simultaneously lessened particle fragmentation in distal healthy tissues as observed with lighter protons. Despite these biophysical advantages, raster-scanning 4He ion therapy remains poorly explored e.g., clinical translational is hampered by the lack of reliable and robust estimation of physical and radiobiological uncertainties. Therefore, prior to the upcoming 4He ion therapy program at the Heidelberg Ion-beam Therapy Center (HIT), we aimed to characterize the biophysical phenomena of 4He ion beams and various aspects of the associated models for clinical integration.

METHODS

Characterization of biological effect for 4He ion beams was performed in both homogenous and patient-like treatment scenarios using innovative models for estimation of relative biological effectiveness (RBE) in silico and their experimental validation using clonogenic cell survival as the gold-standard surrogate. Towards translation of RBE models in patients, the first GPU-based treatment planning system (non-commercial) for raster-scanning 4He ion beams was devised in-house (FRoG).

RESULTS

Our data indicate clinically relevant uncertainty of ±5-10% across different model simulations, highlighting their distinct biological and computational methodologies. The in vitro surrogate for highly radio-resistant tissues presented large RBE variability and uncertainty within the clinical dose range.

CONCLUSIONS

Existing phenomenological and mechanistic/biophysical models were successfully integrated and validated in both Monte Carlo and GPU-accelerated analytical platforms against in vitro experiments, and tested using pristine peaks and clinical fields in highly radio-resistant tissues where models exhibit the greatest RBE uncertainty. Together, these efforts mark an important step towards clinical translation of raster-scanning 4He ion beam therapy to the clinic.

The Radiobiological Effects of Proton Beam Therapy: Impact on DNA Damage and Repair

Proton beam therapy (PBT) offers significant benefit over conventional (photon) radiotherapy for the treatment of a number of different human cancers, largely due to the physical characteristics. In particular, the low entrance dose and maximum energy deposition in depth at a well-defined region, the Bragg peak, can spare irradiation of proximal healthy tissues and organs at risk when compared to conventional radiotherapy using high-energy photons. However, there are still biological uncertainties reflected in the relative biological effectiveness that varies along the track of the proton beam as a consequence of the increases in linear energy transfer (LET). Furthermore, the spectrum of DNA damage induced by protons, particularly the generation of complex DNA damage (CDD) at high-LET regions of the distal edge of the Bragg peak, and the specific DNA repair pathways dependent on their repair are not entirely understood. This knowledge is essential in understanding the biological impact of protons on tumor cells, and ultimately in devising optimal therapeutic strategies employing PBT for greater clinical impact and patient benefit. Here, we provide an up-to-date review on the radiobiological effects of PBT versus photon radiotherapy in cells, particularly in the context of DNA damage. We also review the DNA repair pathways that are essential in the cellular response to PBT, with a specific focus on the signaling and processing of CDD induced by high-LET protons.

A new formalism for modelling parameters α and β of the linear-quadratic model of cell survival for hadron therapy

We propose a new formalism for calculating parameters α and β of the linear-quadratic model of cell survival. This formalism, primarily intended for calculating relative biological effectiveness (RBE) for treatment planning in hadron therapy, is based on a recently proposed microdosimetric revision of the single-target multi-hit model. The main advantage of our formalism is that it reliably produces α and β that have correct general properties with respect to their dependence on physical properties of the beam, including the asymptotic behavior for very low and high linear energy transfer (LET) beams. For example, in the case of monoenergetic beams, our formalism predicts that, as a function of LET, (a) α has a maximum and (b) the α/β ratio increases monotonically with increasing LET. No prior models reviewed in this study predict both properties (a) and (b) correctly, and therefore, these prior models are valid only within a limited LET range. We first present our formalism in a general form, for polyenergetic beams. A significant new result in this general case is that parameter β is represented as an average over the joint distribution of energies E 1 and E 2 of two particles in the beam. This result is consistent with the role of the quadratic term in the linear-quadratic model. It accounts for the two-track mechanism of cell kill, in which two particles, one after another, damage the same site in the cell nucleus. We then present simplified versions of the formalism, and discuss predicted properties of α and β. Finally, to demonstrate consistency of our formalism with experimental data, we apply it to fit two sets of experimental data: (1) α for heavy ions, covering a broad range of LETs, and (2) β for protons. In both cases, good agreement is achieved.

Towards Achieving the Full Clinical Potential of Proton Therapy by Inclusion of LET and RBE Models

Despite increasing use of proton therapy (PBT), several systematic literature reviews show limited gains in clinical outcomes, with publications mostly devoted to recent technical developments. The lack of randomised control studies has also hampered progress in the acceptance of PBT by many oncologists and policy makers. There remain two important uncertainties associated with PBT, namely: (1) accuracy and reproducibility of Bragg peak position (BPP); and (2) imprecise knowledge of the relative biological effect (RBE) for different tissues and tumours, and at different doses. Incorrect BPP will change dose, linear energy transfer (LET) and RBE, with risks of reduced tumour control and enhanced toxicity. These interrelationships are discussed qualitatively with respect to the ICRU target volume definitions. The internationally accepted proton RBE of 1.1 was based on assays and dose ranges unlikely to reveal the complete range of RBE in the human body. RBE values are not known for human (or animal) brain, spine, kidney, liver, intestine, etc. A simple efficiency model for estimating proton RBE values is described, based on data of Belli et al. and other authors, which allows linear increases in α and β with LET, with a gradient estimated using a saturation model from the low LET α and β radiosensitivity parameter input values, and decreasing RBE with increasing dose. To improve outcomes, 3-D dose-LET-RBE and bio-effectiveness maps are required. Validation experiments are indicated in relevant tissues. Randomised clinical studies that test the invariant 1.1 RBE allocation against higher values in late reacting tissues, and lower tumour RBE values in the case of radiosensitive tumours, are also indicated.