Toward A variable RBE for proton beam therapy

A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy

Objective.This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context.Approach.The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n= 151). The best-performing model was identified and externally validated on patients from a different center (n= 107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model.Main results.We found NNs based solely on the planned dose distribution, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24 keV µm-1, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points.Significance.The ability of NNs to predict LETdbased solely on planned dose distributions suggests a viable alternative to compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

NRG Oncology White Paper on the Relative Biological Effectiveness in Proton Therapy

This position paper, led by the NRG Oncology Particle Therapy Work Group, focuses on the concept of relative biologic effect (RBE) in clinical proton therapy (PT), with the goal of providing recommendations for the next-generation clinical trials with PT on the best practice of investigating and using RBE, which could deviate from the current standard proton RBE value of 1.1 relative to photons. In part 1, current clinical utilization and practice are reviewed, giving the context and history of RBE. Evidence for variation in RBE is presented along with the concept of linear energy transfer (LET). The intertwined nature of tumor radiobiology, normal tissue constraints, and treatment planning with LET and RBE considerations is then reviewed. Part 2 summarizes current and past clinical data and then suggests the next steps to explore and employ tools for improved dynamic models for RBE. In part 3, approaches and methods for the next generation of prospective clinical trials are explored, with the goal of optimizing RBE to be both more reflective of clinical reality and also deployable in trials to allow clinical validation and interpatient comparisons. These concepts provide the foundation for personalized biologic treatments reviewed in part 4. Finally, we conclude with a summary including short- and long-term scientific focus points for clinical PT. The practicalities and capacity to use RBE in treatment planning are reviewed and considered with more biological data in hand. The intermediate step of LET optimization is summarized and proposed as a potential bridge to the ultimate goal of case-specific RBE planning that can be achieved as a hypothesis-generating tool in near-term proton trials.

Impact on the Transcriptome of Proton Beam Irradiation Targeted at Healthy Cardiac Tissue of Mice

Proton beam therapy is considered a step forward with respect to electromagnetic radiation, thanks to the reduction in the dose delivered. Among unwanted effects to healthy tissue, cardiovascular complications are a known long-term radiotherapy complication. The transcriptional response of cardiac tissue from xenografted BALB/c nude mice obtained at 3 and 10 days after proton irradiation covering both the tumor region and the underlying healthy tissue was analyzed as a function of dose and time. Three doses were used: 2 Gy, 6 Gy, and 9 Gy. The intermediate dose had caused the greatest impact at 3 days after irradiation: at 2 Gy, 219 genes were differently expressed, many of them represented by zinc finger proteins; at 6 Gy, there were 1109, with a predominance of genes involved in energy metabolism and responses to stimuli; and at 9 Gy, there were 105, mainly represented by zinc finger proteins and molecules involved in the regulation of cardiac function. After 10 days, no significant effects were detected, suggesting that cellular repair mechanisms had defused the potential alterations in gene expression. The nonlinear dose-response curve indicates a need to update the models built on photons to improve accuracy in health risk prediction. Our data also suggest a possible role for zinc finger protein genes as markers of proton therapy efficacy.

Benchmarking proton RBE models

Objective.To biologically optimise proton therapy, models which can accurately predict variations in proton relative biological effectiveness (RBE) are essential. Current phenomenological models show large disagreements in RBE predictions, due to different model assumptions and differences in the data to which they were fit. In this work, thirteen RBE models were benchmarked against a comprehensive proton RBE dataset to evaluate predictions when all models are fit using the same data and fitting techniques, and to assess the statistical robustness of the models.Approach.Model performance was initially evaluated by fitting to the full dataset, and then a cross-validation approach was applied to assess model generalisability and robustness. The impact of weighting the fit and the choice of biological endpoint (either single or multiple survival levels) was also evaluated.Main results.Fitting the models to a common dataset reduced differences between their predictions, however significant disagreements remained due to different underlying assumptions. All models performed poorly under cross-validation in the weighted fits, suggesting that some uncertainties on the experimental data were significantly underestimated, resulting in over-fitting and poor performance on unseen data. The simplest model, which depends linearly on the LET but has no tissue or dose dependence, performed best for a single survival level. However, when fitting to multiple survival levels simultaneously, more complex models with tissue dependence performed better. All models had significant residual uncertainty in their predictions compared to experimental data.Significance.This analysis highlights that poor quality of error estimation on the dose response parameters introduces substantial uncertainty in model fitting. The significant residual error present in all approaches illustrates the challenges inherent in fitting to large, heterogeneous datasets and the importance of robust statistical validation of RBE models.

A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

Objective. While integration of variable relative biological effectiveness (RBE) has not reached full clinical implementation, the importance of having the ability to recalculate proton treatment plans in a flexible, dedicated Monte Carlo (MC) code cannot be understated . Here we provide a step-wise method for calibrating dose from a MC code to a treatment planning system (TPS), to obtain required parameters for calculating linear energy transfer (LET), variable RBE and in general enabling clinical realistic research studies beyond the capabilities of a TPS.Approach. Initially, Pristine Bragg peaks (PBP) were calculated in both the Eclipse TPS and the FLUKA MC code. A rearranged Bortfeld energy-range relation was applied to the initial energy of the beam to fine-tune the range of the MC code at 80% dose level distal to the PBP. The energy spread was adapted by dividing the TPS range by the MC range for dose level 80%-20% distal to the PBP. Density and relative proton stopping power were adjusted by comparing the TPS and MC for different Hounsfield units. To find the relationship of dose per primary particle from the MC to dose per monitor unit in the TPS, integration was applied to the area of the Bragg curve. The calibration was validated for spread-out Bragg peaks (SOBP) in water and patient treatment plans. Following the validation, variable RBE were calculated using established models.Main results.The PBPs ranges were within ±0.3mm threshold, and a maximum of 5.5% difference for the SOBPs was observed. The patient validation showed excellent dose agreement between the TPS and MC, with the greatest differences for the lung tumor patient.Significance. Aprocedure for calibrating a MC code to a TPS was developed and validated. The procedure enables MC-based calculation of dose, LET, variable RBE, advanced (secondary) particle tracking and more from treatment plans.

An experimental setup for proton irradiation of a murine leg model for radiobiological studies

BACKGROUND

The purpose of this study was to introduce an experimental radiobiological setup used for in vivo irradiation of a mouse leg target in multiple positions along a proton beam path to investigate normal tissue- and tumor models with varying linear energy transfer (LET). We describe the dosimetric characterizations and an acute- and late-effect assay for normal tissue damage.

METHODS

The experimental setup consists of a water phantom that allows the right hind leg of three to five mice to be irradiated at the same time. Absolute dosimetry using a thimble (Semiflex) and a plane parallel (Advanced Markus) ionization chamber and Monte Carlo simulations using Geant4 and SHIELD-HIT12A were applied for dosimetric validation of positioning along the spread-out Bragg peak (SOBP) and at the distal edge and dose fall-off. The mice were irradiated in the center of the SOBP delivered by a pencil beam scanning system. The SOBP was 2.8 cm wide, centered at 6.9 cm depth, with planned physical single doses from 22 to 46 Gy. The biological endpoint was acute skin damage and radiation-induced late damage (RILD) assessed in the mouse leg.

RESULTS

The dose-response curves illustrate the percentage of mice exhibiting acute skin damage, and at a later point, RILD as a function of physical doses (Gy). Each dose-response curve represents a specific severity score of each assay, demonstrating a higher ED50 (50% responders) as the score increases. Moreover, the results reveal the reversible nature of acute skin damage as a function of time and the irreversible nature of RILD as time progresses.

CONCLUSIONS

We want to encourage researchers to report all experimental details of their radiobiological setups, including experimental protocols and model descriptions, to facilitate transparency and reproducibility. Based on this study, more experiments are being performed to explore all possibilities this radiobiological experimental setup permits.

Plan robustness and RBE influence for proton dose painting by numbers for head and neck cancers

PURPOSE

To investigate the feasibility of dose painting by numbers (DPBN) with respect to robustness for proton therapy for head and neck cancers (HNC), and to study the influence of variable RBE on the TCP and OAR dose burden.

METHODS AND MATERIALS

Data for 19 patients who have been scanned pretreatment with PET-FDG and subsequently treated with photon therapy were used in the study. A dose response model developed for photon therapy was implemented in a TPS, allowing DPBN plans to be created. Conventional homogeneous dose and DPBN plans were created for each patient, optimized with either fixed RBE = 1.1 or a variable RBE model. Robust optimization was used to create clinically acceptable plans. To estimate the maximum potential loss in TCP due to actual SUV variations from the pre-treatment imaging, we applied a test case with randomized SUV distribution.

RESULTS

Regardless of the use of variable RBE for optimization or evaluation, a statistically significant increase (p < 0.001) in TCP was found for DPBN plans as compared to homogeneous dose plans. Randomizing the SUV distribution decreased the TCP for all plans. A correlation between TCP increase and variance of the SUV distribution and target volume was also found.

CONCLUSION

DPBN for protons and HNC is feasible and could lead to a TCP gain. Risks associated with the temporal variation of SUV distributions could be mitigated by imposing minimum doses to targets. The correlation found between TCP increase and SUV variance and target volume may be used for patient selection.

Mitigating Radiotoxicity in the Central Nervous System: Role of Proton Therapy

OPINION STATEMENT

Central nervous system (CNS) radiotoxicity remains a challenge in neuro-oncology. Dose distribution advantages of protons over photons have prompted increased use of brain-directed proton therapy. While well-recognized among pediatric populations, the benefit of proton therapy among adults with CNS malignancies remains controversial. We herein discuss the role of protons in mitigating late CNS radiotoxicities in adult patients. Despite limited clinical trials, evidence suggests toxicity profile advantages of protons over conventional radiotherapy, including retention of neurocognitive function and brain volume. Modelling studies predict superior dose conformality of protons versus state-of-the-art photon techniques reduces late radiogenic vasculopathies, endocrinopathies, and malignancies. Conversely, potentially higher brain tissue necrosis rates following proton therapy highlight a need to resolve uncertainties surrounding the impact of variable biological effectiveness of protons on dose distribution. Clinical trials comparing best photon and particle-based therapy are underway to establish whether protons substantially improve long-term treatment-related outcomes in adults with CNS malignancies.

Monte Carlo simulations of cell survival in proton SOBP

Objective. The objective of this study is to develop a multi-scale modeling approach that accurately predicts radiation-induced DNA damage and survival fraction in specific cell lines.Approach. A Monte Carlo based simulation framework was employed to make the predictions. The FLUKA Monte Carlo code was utilized to estimate absorbed doses and fluence energy spectra, which were then used in the Monte Carlo Damage Simulation code to compute DNA damage yields in Chinese hamster V79 cell lines. The outputs were converted into cell survival fractions using a previously published theoretical model. To reduce the uncertainties of the predictions, new values for the parameters of the theoretical model were computed, expanding the database of experimental points considered in the previous estimation. Simulated results were validated against experimental data, confirming the applicability of the framework for proton beams up to 230 MeV. Additionally, the impact of secondary particles on cell survival was estimated.Main results. The simulated survival fraction versus depth in a glycerol phantom is reported for eighteen different configurations. Two proton spread out Bragg peaks at several doses were simulated and compared with experimental data. In all cases, the simulations follow the experimental trends, demonstrating the accuracy of the predictions up to 230 MeV.Significance. This study holds significant importance as it contributes to the advancement of models for predicting biological responses to radiation, ultimately contributing to more effective cancer treatment in proton therapy.

Improving delivery efficiency using spots and energy layers reduction algorithms based on a large momentum acceptance beamline

BACKGROUND

Intensity-modulated proton therapy (IMPT) is a well-known delivery method of proton therapy. Besides higher plan quality, reducing the delivery time is also essential to IMPT plans. It can enhance patient comfort, reduce treatment costs, and improve delivery efficiency. From the perspective of treatment efficacy, it contributes to mitigating the intra-fractional motions and improving the accuracy of radiotherapy, especially for moving tumors.

PURPOSE

However, there is a tradeoff problem between the plan quality and delivery time. We consider the potential of a large momentum acceptance (LMA) beamline and apply the spots and energy layers reduction method to reduce the delivery time.

METHODS

The delivery time for each field consists of the energy layer switching time, spot traveling time, and dose delivery time. The larger momentum spread and higher intensity beam offered by the LMA beamline contribute to reducing the total delivery time compared to the conventional beamline. In addition to the dose fidelity term, an L1 and logarithm items were added to the objective function to increase the sparsity of the low-weighted spots and energy layers. After that, the low-weighted spots and layers were iteratively excluded in the reduced plan, which reduced the energy layer switching time and spot traveling time. We used the standard, reduced, and LMA-reduced plans to validate the proposed method and tested it on prostate and nasopharyngeal cases. Then, we compared and evaluated the plan quality, treatment time, and plan robustness against delivery uncertainty.

RESULTS

Compared with the standard plans, the number of spots in the LMA-reduced plans was on average reduced by 13 400 (95.6%) for prostate cases and by 48 300 (80.7%) for nasopharyngeal cases and the number of energy layers was on average reduced by 49 (61.3%) for prostate cases and by 97 (50.5%) for nasopharyngeal cases. And, the delivery time of the LMA-reduced plans was shortened from 34.5 to 8.6 s for prostate cases and from 163.8 to 53.6 s for nasopharyngeal cases. The LMA-reduced plans had comparable robustness to the spot monitor unit (MU) error compared with the standard plans, but the LMA-reduced plans became more sensitive to spot position uncertainty.

CONCLUSION

The delivery efficiency can be significantly improved using the LMA beamline and spots and energy layers reduction strategies. The method is promising to improve the efficiency of motion mitigation strategies for treating moving tumors.

Similar additive effects of doxorubicin in combination with photon or proton irradiation in soft tissue sarcoma models

High-precision radiotherapy with proton beams is frequently used in the management of aggressive soft tissue sarcoma (STS) and is often combined with doxorubicin (Dox), the first-line chemotherapy for STS. However, current treatment approaches continue to result in high local recurrence rates often occurring within the treatment field. This strongly indicates the need of optimized treatment protocols taking the vast heterogeneity of STS into account, thereby fostering personalized treatment approaches. Here, we used preclinical STS models to investigate the radiation response following photon (X) or proton (H) irradiation alone and in combination with different treatment schedules of Dox. As preclinical models, fibrosarcoma (HT-1080), undifferentiated pleiomorphic sarcoma (GCT), and embryonal rhabdomyosarcoma (RD) cell lines were used; the latter two are mutated for TP53. The cellular response regarding clonogenic survival, apoptosis, cell-cycle distribution, proliferation, viability, morphology, and motility was investigated. The different STS cell types revealed a dose-dependent radiation response with reduced survival, proliferation, viability, and motility whereas G2/M phase arrest as well as apoptosis were induced. RD cells showed the most radiosensitive phenotype; the linear quadratic model fit could not be applied. In combined treatment schedules, Dox showed the highest efficiency when applied after or before and after radiation; Dox treatment only before radiation was less efficient. GCT cells were the most chemoresistant cell line in this study most probably due to their TP53 mutation status. Interestingly, similar additive effects could be observed for X or H irradiation in combination with Dox treatment. However, the additive effects were determined more frequently for X than for H irradiation. Thus, further investigations are needed to specify alternative drug therapies that display superior efficacy when combined with H therapy.

Investigation of In-Field and Out-of-Field Radiation Quality With Microdosimetry and Its Impact on Relative Biological Effectiveness in Proton Therapy

PURPOSE

Using microdosimetry, this study investigated the relative biological effectiveness (RBE) and quality factor (Q¯) variations in field and out of field as a function of radiation quality for clinical protons.

METHODS AND MATERIALS

A water phantom with a spread-out Bragg peak (SOBP) was irradiated to acquire microdosimetric spectra at several distal and lateral depths with a tissue equivalent proportional counter. The measurements were used as inputs to microdosimetric kinetic and Loncol models to determine the RBE spatial distribution and compare it with predictions from the dose-averaged linear energy transfer-based McNamara model. Q¯ values and biological and dose equivalent values were also calculated.

RESULTS

The data demonstrated that radiation quality changed more rapidly with depth than lateral distance from the SOBP. In beam, y_D ranged from approximately 4 keV/μm at the entrance to 8 keV/μm at the SOBP far end, reaching approximately 15 keV/μm at the penumbra. Out of field, the overall highest value of 23 ± 2 keV/μm was observed at the beam-edge penumbra. Radiation quality changes caused RBE deviations from the clinical value of 1.1, whose extent depends on the approach used for assessing radiation quality as well as on the radiobiological model. For RBE₁₀, microdosimetry-based models appeared to better reproduce the radiobiological data than the dose-averaged linear energy transfer model. Out of field, both the RBE and Q¯ values appeared to have limitations in describing the radiation biological effectiveness. This research also presents a first comprehensive benchmark of TOPAS code against in-field and out-of-field microdosimetric spectra of therapeutic protons.

CONCLUSIONS

Further investigation will be necessary to evaluate the quantitative effects of RBE variations on treatment planning and assess the clinical consequences in terms of both tumor control and normal-tissue toxicity. The achievement of this goal calls for accurate radiobiological data to validate the RBE models.

Does particle radiation have superior radiobiological advantages for prostate cancer cells? A systematic review of in vitro studies

BACKGROUND

Charged particle beams from protons to carbon ions provide many significant physical benefits in radiation therapy. However, preclinical studies of charged particle therapy for prostate cancer are extremely limited. The aim of this study was to comprehensively investigate the biological effects of charged particles on prostate cancer from the perspective of in vitro studies.

METHODS

We conducted a systematic review by searching EMBASE (OVID), Medline (OVID), and Web of Science databases to identify the publications assessing the radiobiological effects of charged particle irradiation on prostate cancer cells. The data of relative biological effectiveness (RBE), surviving fraction (SF), standard enhancement ratio (SER) and oxygen enhancement ratio (OER) were extracted.

RESULTS

We found 12 studies met the eligible criteria. The relative biological effectiveness values of proton and carbon ion irradiation ranged from 0.94 to 1.52, and 1.67 to 3.7, respectively. Surviving fraction of 2 Gy were 0.17 ± 0.12, 0.55 ± 0.20 and 0.53 ± 0.16 in carbon ion, proton, and photon irradiation, respectively. PNKP inhibitor and gold nanoparticles were favorable sensitizing agents, while it was presented poorer performance in GANT61. The oxygen enhancement ratio values of photon and carbon ion irradiation were 2.32 ± 0.04, and 1.77 ± 0.13, respectively. Charged particle irradiation induced more G0-/G1- or G2-/M-phase arrest, more expression of γ-H2AX, more apoptosis, and lower motility and/or migration ability than photon irradiation.

CONCLUSIONS

Both carbon ion and proton irradiation have advantages over photon irradiation in radiobiological effects on prostate cancer cell lines. Carbon ion irradiation seems to have further advantages over proton irradiation.

Emodin coupled with high LET neutron beam-a novel approach to treat on glioblastoma

The primary motivation of this investigative study is trying to find an alternative treatment that can be used to slow down or treat glioblastoma due to the witnessed toxic side effects of the current drugs coupled with limited effectiveness in overall treatment. Consequently, a Chinese plant extract emodin proves to play a critical role in this investigative study since results from the Western blot and the other accompanying assays for anti-cancer effects indicate that it cannot work a lot to suppress cell migration and possible invasion, but rather emodin can be combined with radiation to give desired outcomes. Our result shows that the kind of radiation which acts well with emodin is neutron radiation rather than gamma radiation. Emodin significantly enhanced the radiosensitivity of LN18 and LN428 cells to γ-rays through MTT assay and cell counting. Accordingly, exposure to neutron radiation in the presence of emodin induced apoptotic cell death and autophagic cell death to a significantly higher extent, and suppressed cell migration and invasiveness more robustly. These effects are presumably due to the ability of emodin to amplify the effective dose from neutron radiation more efficiently. Thus, the study below is one such trial towards new interventional discovery and development in relation to glioblastoma treatment.

CONVERSION OF DOSE DISTRIBUTION TO CELL SURVIVAL FRACTION THROUGH DNA DAMAGE: A MONTE CARLO STUDY

Ionizing radiation plays an important role in cancer treatment. Radiation is able to damage the genetic material of cells, blocking their ability to divide and proliferate further. Since radiation affects both healthy and malignant tissues, for all radiation treatments, the design of an accurate treatment plan is fundamental. Usually, weight factors, such as the relative biological effectiveness, are applied to estimate the impact of the kind of radiation and the irradiated medium on the dose deposition. However, these factors can only provide a partial estimation of the real effect on tissues. In this work, a flexible system that is able to predict cell survival fractions according to the planned dose distribution is presented. Dose deposition and subsequent DNA damage were simulated with a multi-scale modeling approach by first applying the FLUKA Monte Carlo (MC) code to estimate the absorbed doses and fluence energy spectra and then using the MC Damage Simulation code to compute the DNA damage yields. Lastly, the results are converted into cell survival fraction using a theoretical model. The comparisons between the simulated survival fractions with experimental data are reported for a proton spread out Bragg peak at several doses. The presented approach helps to elucidate radiobiological responses along the Bragg curve and has the flexibility to be extended to a wide range of situations of clinical interest.

Roadmap: helium ion therapy

Helium ion beam therapy for the treatment of cancer was one of several developed and studied particle treatments in the 1950s, leading to clinical trials beginning in 1975 at the Lawrence Berkeley National Laboratory. The trial shutdown was followed by decades of research and clinical silence on the topic while proton and carbon ion therapy made debuts at research facilities and academic hospitals worldwide. The lack of progression in understanding the principle facets of helium ion beam therapy in terms of physics, biological and clinical findings persists today, mainly attributable to its highly limited availability. Despite this major setback, there is an increasing focus on evaluating and establishing clinical and research programs using helium ion beams, with both therapy and imaging initiatives to supplement the clinical palette of radiotherapy in the treatment of aggressive disease and sensitive clinical cases. Moreover, due its intermediate physical and radio-biological properties between proton and carbon ion beams, helium ions may provide a streamlined economic steppingstone towards an era of widespread use of different particle species in light and heavy ion therapy. With respect to the clinical proton beams, helium ions exhibit superior physical properties such as reduced lateral scattering and range straggling with higher relative biological effectiveness (RBE) and dose-weighted linear energy transfer (LET_d) ranging from ∼4 keVμm^-1to ∼40 keVμm^-1. In the frame of heavy ion therapy using carbon, oxygen or neon ions, where LET_dincreases beyond 100 keVμm^-1, helium ions exhibit similar physical attributes such as a sharp lateral penumbra, however, with reduced radio-biological uncertainties and without potentially spoiling dose distributions due to excess fragmentation of heavier ion beams, particularly for higher penetration depths. This roadmap presents an overview of the current state-of-the-art and future directions of helium ion therapy: understanding physics and improving modeling, understanding biology and improving modeling, imaging techniques using helium ions and refining and establishing clinical approaches and aims from learned experience with protons. These topics are organized and presented into three main sections, outlining current and future tasks in establishing clinical and research programs using helium ion beams-A. Physics B. Biological and C. Clinical Perspectives.

Particle Therapy for Breast Cancer

Particle therapy has received increasing attention in the treatment of breast cancer due to its unique physical properties that may enhance patient quality of life and reduce the late effects of therapy. In this review, we will examine the rationale for the use of proton and carbon therapy in the treatment of breast cancer and highlight their potential for sparing normal tissue injury. We will discuss the early dosimetric and clinical studies that have been pursued to date in this domain before focusing on the remaining open questions limiting the widespread adoption of particle therapy.

Comparative analysis of the immune responses in cancer cells irradiated with X-ray, proton and carbon-ion beams

Radiotherapy (RT) is an effective treatment option for cancer; however, its efficacy remains less than optimal in locally advanced cancer. Immune checkpoint inhibitor-based therapy, including the administration of anti-PD-L1 antibodies, is a promising approach that works synergistically with RT. Proton beam therapy and carbon-ion therapy are common options for patients with cancer. Proton and carbon ions are reported to induce an immune reaction in cancer cells; however, the underlying mechanisms remain unclear. Here, we aimed to compare the immune responses after irradiation (IR) with X-ray, protons, and carbon ions in an oesophageal cancer cell line and the underlying mechanisms. An oesophageal cancer cell line, KYSE450, was irradiated with 1 fraction/15 GyE (Gy equivalent) of X-ray, proton, or carbon-ion beams, and then, the cells were harvested for RNA sequencing and gene enrichment analysis. We also knocked out STING and STAT1 in the quest for mechanistic insights. RNA sequencing data revealed that gene expression signatures and biological processes were different in KYSE450 irradiated with X-ray, proton, and carbon-ion beams 6-24 h after IR. However, after 3 days, a common gene expression signature was detected, associated with biological pathways involved in innate immune responses. Gene knock-out experiments revealed that the STING-STAT1 axis underlies the immune reactions after IR. X-Ray, proton, and carbon-ion IRs induced similar immune responses, regulated by the STING-STAT1 axis.

In-vitro 3D modelling for charged particle therapy - Uncertainties and opportunities

Radiation therapy is a critical component of oncologic management, with more than half of all cancer patients requiring radiotherapy at some point during their disease course. Over the last decade, there has been increasing interest in charged particle therapy due to its advantageous physical and radiobiologic properties, with the therapeutic use of proton beam therapy (PBT) expanding worldwide. However, there remain large gaps in our knowledge of the radiobiologic mechanisms that underlie key aspects of PBT, such as variations in relative biologic effectiveness (RBE), radioresistance, DNA damage response and repair pathways, as well as immunologic effects. In addition, while the emerging technique of ultra-high dose rate or FLASH radiotherapy, with its potential to further reduce normal tissue toxicities, is an exciting development, in-depth study is needed into the postulated biochemical mechanisms that underpin the FLASH effect such as the oxygen depletion hypothesis as well as the relative contributions of immune responses and the tumor microenvironment. Further investigation is also required to ensure that the FLASH effect is not diminished or lost in PBT. Current methods to evaluate the biologic effects of charged particle therapy rely heavily on 2D cell culture systems and/or animal models. However, both of these methods have well-recognized limitations which limit translatability of findings from bench to bedside. The advent of novel three-dimensional in-vitro tumor models offers a more physiologically relevant and high throughput in-vitro system for the study of tumor development as well as novel therapeutic approaches such as PBT. Advances in 3D cell culture methods, together with knowledge of disease mechanism, biomarkers, and genomic data, can be used to design personalized 3D models that most closely recapitulate tumor microenvironmental factors promoting a particular disease phenotype, moving 3D models and PBT into the age of precision medicine.

Landscape of Carbon Ion Radiotherapy in Prostate Cancer: Clinical Application and Translational Research

Carbon ion radiotherapy (CIRT) is a useful and advanced technique for prostate cancer. This study sought to investigate the clinical efficacy and translational research for prostate cancer with carbon ion radiotherapy. We integrated the data from published articles, clinical trials websites, and our data. The efficacy of CIRT for prostate cancer was assessed in terms of overall survival, biochemical recurrence-free survival, and toxicity response. Up to now, clinical treatment of carbon ion radiotherapy has been carried in only five countries. We found that carbon ion radiotherapy induced little genitourinary and gastrointestinal toxicity when used for prostate cancer treatment. To some extent, it led to improved outcomes in overall survival, biochemical recurrence-free survival than conventional radiotherapy, especially for high-risk prostate cancer. Carbon ion radiotherapy brought clinical benefits for prostate cancer patients, and quality of life assessment indicated that CIRT affected patients to a lesser extent. Potential biomarkers from our omics-based study could be used to predict the efficacy of prostate cancer with CIRT. Carbon ion radiotherapy brought clinical benefits for prostate cancer patients. The omics-based translational research may provide insights into individualized therapy.

The Organ Sparing Potential of Different Biological Optimization Strategies in Proton Therapy

Purpose

Variable relative biological effectiveness (RBE) models allow for differences in linear energy transfer (LET), physical dose, and tissue type to be accounted for when quantifying and optimizing the biological damage of protons. These models are complex and fraught with uncertainties, and therefore, simpler RBE optimization strategies have also been suggested. Our aim was to compare several biological optimization strategies for proton therapy by evaluating their performance in different clinical cases.

Methods and Materials

Two different optimization strategies were compared: full variable RBE optimization and differential RBE optimization, which involve applying fixed RBE for the planning target volume (PTV) and variable RBE in organs at risk (OARs). The optimization strategies were coupled to 2 variable RBE models and 1 LET-weighted dose model, with performance demonstrated on 3 different clinical cases: brain, head and neck, and prostate tumors.

Results

In cases with low (α/β)x in the tumor, the full RBE optimization strategies had a large effect, with up to 10% reduction in RBE-weighted dose to the PTV and OARs compared with the reference plan, whereas smaller variations (<5%) were obtained with differential optimization. For tumors with high (α/β)x, the differential RBE optimization strategy showed a greater reduction in RBE-weighted dose to the OARs compared with the reference plan and the full RBE optimization strategy.

Conclusions

Differences between the optimization strategies varied across the studied cases, influenced by both biological and physical parameters. Whereas full RBE optimization showed greater OAR sparing, awareness of underdosage to the target must be carefully considered.

Cancer nanotechnology: current status and perspectives

Modern medicine has been waging a war on cancer for nearly a century with no tangible end in sight. Cancer treatments have significantly progressed, but the need to increase specificity and decrease systemic toxicities remains. Early diagnosis holds a key to improving prognostic outlook and patient quality of life, and diagnostic tools are on the cusp of a technological revolution. Nanotechnology has steadily expanded into the reaches of cancer chemotherapy, radiotherapy, diagnostics, and imaging, demonstrating the capacity to augment each and advance patient care. Nanomaterials provide an abundance of versatility, functionality, and applications to engineer specifically targeted cancer medicine, accurate early-detection devices, robust imaging modalities, and enhanced radiotherapy adjuvants. This review provides insights into the current clinical and pre-clinical nanotechnological applications for cancer drug therapy, diagnostics, imaging, and radiation therapy.

Combined DNA Damage Repair Interference and Ion Beam Therapy: Development, Benchmark, and Clinical Implications of a Mechanistic Biological Model

PURPOSE

Our purpose was to develop a mechanistic model that describes and predicts radiation response after combined DNA damage repair interference (DDRi) and particle radiation therapy.

METHODS AND MATERIALS

The heterogeneous dose distributions of protons and ⁴He ions were implemented into the "UNIfied and VERSatile bio-response Engine" (UNIVERSE). Predictions for monoenergetic and mixed fields over clinically relevant dose and linear energy transfer range were compared with experimental in vitro survival data measured in this work as well as data available in the literature, including different cell lines and DDR interferences. Ultimately, UNIVERSE predictions were investigated in a patient plan.

RESULTS

UNIVERSE accurately predicts survival of cell lines with and without DDRi in clinical settings of ion beam therapy based only on 3 parameters derived from photon data. With increasing dose or linear energy transfer, the radiosensitizing effect of DDRi decreases, resulting in diminished relative biological effect of ion beam radiation for cells subjected to DDRi in comparison to cells that are not. Similar trends were observed in patient plan recalculations; however, this analysis also suggests that DDRi + particle radiation therapy may better preserve the therapeutic window in comparison to DDRi + photon radiation therapy.

CONCLUSIONS

The presented framework represents the first mechanistic model of combined DDRi and particle radiation therapy comprehensively benchmarked in clinically relevant scenarios and a step toward more personalized treatment. It reveals potential differences between DDRi + photon radiation therapy versus DDRi + particle radiation therapy, which have not been described so far. UNIVERSE could aid in appraising the clinical viability of combined administration of radiosensitizing drugs and charged particle therapy, as well as the identification of patients with known DDR deficiencies in the tumor who might benefit from therapy with light ions, freeing limited space at heavy ion therapy centers.

Proton Therapy for Breast Cancer: A Consensus Statement From the Particle Therapy Cooperative Group Breast Cancer Subcommittee

Radiation therapy plays an important role in the multidisciplinary management of breast cancer. Recent years have seen improvements in breast cancer survival and a greater appreciation of potential long-term morbidity associated with the dose and volume of irradiated organs. Proton therapy reduces the dose to nontarget structures while optimizing target coverage. However, there remain additional financial costs associated with proton therapy, despite reductions over time, and studies have yet to demonstrate that protons improve upon the treatment outcomes achieved with photon radiation therapy. There remains considerable heterogeneity in proton patient selection and techniques, and the rapid technological advances in the field have the potential to affect evidence evaluation, given the long latency period for breast cancer radiation therapy recurrence and late effects. In this consensus statement, we assess the data available to the radiation oncology community of proton therapy for breast cancer, provide expert consensus recommendations on indications and technique, and highlight ongoing trials' cost-effectiveness analyses and key areas for future research.

Combining the past and present to advance immuno-radiotherapy of cancer

Since its first clinical application, 120 years ago, radiotherapy evolved into a major anti-cancer treatment modality, offering high cure rates in many human malignancies. During the past ten years, the establishment of immune checkpoint inhibitors (ICIs) in cancer therapeutics has vigorously reintroduced the immune system's role in the outcome of radiotherapy and, conversely, the role of radio-vaccination in the efficacy of immunotherapy. The knowledge and clinical experience that founded the current era of immuno-radiotherapy started alongside with the birth of radiotherapy, and evolved through exhaustive experimental work, clinical trials on active specific immunotherapy, frustrating attempts to validate the importance of cytokine administration with radiotherapy, and, finally, the encouraging ICI-based clinical trials that opened the door to a far more encouraging perspective; radio-vaccination, through its old and new methods, is rising as a research field that promises to cure, previously incurable, disease. In this critical review, we focus on the scientific knowledge gathered through more than a century of research on radiotherapy interactions with the immune system. Understanding the origins of this promising therapeutic approach will substantially contribute to developing new immuno-radiotherapy policies in the fight against cancer.

Normal Tissue Injury Induced by Photon and Proton Therapies: Gaps and Opportunities

Despite technological advances in radiation therapy (RT) and cancer treatment, patients still experience adverse effects. Proton therapy (PT) has emerged as a valuable RT modality that can improve treatment outcomes. Normal tissue injury is an important determinant of the outcome; therefore, for this review, we analyzed 2 databases: (1) clinical trials registered with ClinicalTrials.gov and (2) the literature on PT in PubMed, which shows a steady increase in the number of publications. Most studies in PT registered with ClinicalTrials.gov with results available are nonrandomized early phase studies with a relatively small number of patients enrolled. From the larger database of nonrandomized trials, we listed adverse events in specific organs/sites among patients with cancer who are treated with photons and protons to identify critical issues. The present data demonstrate dosimetric advantages of PT with favorable toxicity profiles and form the basis for comparative randomized prospective trials. A comparative analysis of 3 recently completed randomized trials for normal tissue toxicities suggests that for early stage non-small cell lung cancer, no meaningful comparison could be made between stereotactic body RT and stereotactic body PT due to low accrual (NCT01511081). In addition, for locally advanced non-small cell lung cancer, a comparison of intensity modulated RTwith passive scattering PT (now largely replaced by spot-scanned intensity modulated PT), PT did not provide any benefit in normal tissue toxicity or locoregional failure over photon therapy. Finally, for locally advanced esophageal cancer, proton beam therapy provided a lower total toxicity burden but did not improve progression-free survival and quality of life (NCT01512589). The purpose of this review is to inform the limitations of current trials looking at protons and photons, considering that advances in technology, physics, and biology are a continuum, and to advocate for future trials geared toward accurate precision RT that need to be viewed as an iterative process in a defined path toward delivering optimal radiation treatment. A foundational understanding of the radiobiologic differences between protons and photons in tumor and normal tissue responses is fundamental to, and necessary for, determining the suitability of a given type of biologically optimized RT to a patient or cohort.

Dosimetric Assessment of a High Precision System for Mouse Proton Irradiation to Assess Spinal Cord Toxicity

The uncertainty associated with the relative biological effectiveness (RBE) in proton therapy, particularly near the Bragg peak (BP), has led to the shift towards biological-based treatment planning. Proton RBE uncertainty has recently been reported as a possible cause for brainstem necrosis in pediatric patients treated with proton therapy. Despite this, in vivo studies have been limited due to the complexity of accurate delivery and absolute dosimetry. The purpose of this investigation was to create a precise and efficient method of treating the mouse spinal cord with various portions of the proton Bragg curve and to quantify associated uncertainties for the characterization of proton RBE. Mice were restrained in 3D printed acrylic boxes, shaped to their external contour, with a silicone insert extending down to mold around the mouse. Brass collimators were designed for parallel opposed beams to treat the spinal cord while shielding the brain and upper extremities of the animal. Up to six animals may be accommodated for simultaneous treatment within the restraint system. Two plans were generated targeting the cervical spinal cord, with either the entrance (ENT) or the BP portion of the beam. Dosimetric uncertainty was measured using EBT3 radiochromic film with a dose-averaged linear energy transfer (LETd) correction. Positional uncertainty was assessed by collecting a library of live mouse scans (n = 6 mice, two independent scans per mouse) and comparing the following dosimetric statistics from the mouse cervical spinal cord: Volume receiving 90% of the prescription dose (V90); mean dose to the spinal cord; and LETd. Film analysis results showed the dosimetric uncertainty to be ±1.2% and ±5.4% for the ENT and BP plans, respectively. Preliminary results from the mouse library showed the V90 to be 96.3 ± 4.8% for the BP plan. Positional uncertainty of the ENT plan was not measured due to the inherent robustness of that treatment plan. The proposed high-throughput mouse proton irradiation setup resulted in accurate dose delivery to mouse spinal cords positioned along the ENT and BP. Future directions include adapting the setup to account for weight fluctuations in mice undergoing fractionated irradiation.

Estimating the modulating effect of lung tissue in particle therapy using a clinical CT voxel histogram analysis

To treat lung tumours with particle therapy, different additional tasks and challenges in treatment planning and application have to be addressed thoroughly. One of these tasks is the quantification and consideration of the Bragg peak degradation due to lung tissue: As lung is an heterogeneous tissue, the Bragg peak is broadened when particles traverse the microscopic alveoli. These are not fully resolved in clinical CT images and thus, the effect is not considered in the dose calculation. In this work, a correlation between the CT histograms of heterogeneous material and the impact on the Bragg peak curve is presented. Different inorganic materials were scanned with a conventional CT scanner and additionally, the Bragg peak degradation was measured in a proton beam and was then quantified. A model is proposed that allows an estimation of the modulation power by performing a histogram analysis on the CT scan. To validate the model for organic samples, a second measurement series was performed with frozen porcine lunge samples. This allows to investigate the possible limits of the proposed model in a set-up closer to clinical conditions. For lung substitutes, the agreement between model and measurement is within ±0.05 mm and for the organic lung samples, within ±0.15 mm. This work presents a novel, simple and efficient method to estimate if and how much a material or a distinct region (within the lung) is degrading the Bragg peak on the basis of a common clinical CT image. Up until now, only a direct in-beam measurement of the region or material of interest could answer this question.

Double-strand breaks measured along a 160 MeV proton Bragg curve using a novel FIESTA-DNA probe in a cell-free environment

Proton radiotherapy treatment planning systems use a constant relative biological effectiveness (RBE) = 1.1 to convert proton absorbed dose into biologically equivalent high-energy photon dose. This method ignores linear energy transfer (LET) distributions, and RBE is known to change as a function of LET. Variable RBE approaches have been proposed for proton planning optimization. Experimental validation of models underlying these approaches is a pre-requisite for their clinical implementation. This validation has to probe every level in the evolution of radiation-induced biological damage leading to cell death, starting from DNA double-strand breaks (DSB). Using a novel FIESTA-DNA probe, we measured the probability of double-strand break (P _DSB) along a 160 MeV proton Bragg curve at two dose levels (30 and 60 Gy (RBE)) and compared it to measurements in a 6 MV photon beam. A machined setup that held an Advanced Markus parallel plate chamber for proton dose verification alongside the probes was fabricated. Each sample set consisted of five 10 μl probes suspended inside plastic microcapillary tubes. These were irradiated with protons to 30 Gy (RBE) at depths of 5-17.5 cm and 60 Gy (RBE) at depths of 10-17.2 cm with 1 mm resolution around Bragg peak. Sample sets were also irradiated using 6MV photons to 20, 40, 60, and 80 Gy. For the 30 Gy (RBE) measurements, increases in P _DSB/Gy were observed at 17.0 cm followed by decreases at larger depth. For the 60 Gy (RBE) measurements, no increase in P _DSB/Gy was observed, but there was a decrease after 17.0 cm. Dose-response for P _DSB between 30 and 60 Gy (RBE) showed less than doubling of P _DSB when dose was doubled. Proton RBE effect from DSB, RBE_P,DSB, was <1 except at the Bragg peak. The experiment showed that the novel probe can be used to perform DNA DSB measurements in a proton beam. To establish relevance to clinical environment, further investigation of the probe's chemical scavenging needs to be performed.

Targeting the DNA replication stress phenotype of KRAS mutant cancer cells

Mutant KRAS is a common tumor driver and frequently confers resistance to anti-cancer treatments such as radiation. DNA replication stress in these tumors may constitute a therapeutic liability but is poorly understood. Here, using single-molecule DNA fiber analysis, we first characterized baseline replication stress in a panel of unperturbed isogenic and non-isogenic cancer cell lines. Correlating with the observed enhanced replication stress we found increased levels of cytosolic double-stranded DNA in KRAS mutant compared to wild-type cells. Yet, despite this phenotype replication stress-inducing agents failed to selectively impact KRAS mutant cells, which were protected by CHK1. Similarly, most exogenous stressors studied did not differentially augment cytosolic DNA accumulation in KRAS mutant compared to wild-type cells. However, we found that proton radiation was able to slow fork progression and preferentially induce fork stalling in KRAS mutant cells. Proton treatment also partly reversed the radioresistance associated with mutant KRAS. The cellular effects of protons in the presence of KRAS mutation clearly contrasted that of other drugs affecting replication, highlighting the unique nature of the underlying DNA damage caused by protons. Taken together, our findings provide insight into the replication stress response associated with mutated KRAS, which may ultimately yield novel therapeutic opportunities.

Investigation of DNA Damage and Cell-Cycle Distribution in Human Peripheral Blood Lymphocytes under Exposure to High Doses of Proton Radiotherapy

This study systematically investigates how a single high-dose therapeutic proton beam versus X-rays influences cell-cycle phase distribution and DNA damage in human peripheral blood lymphocytes (HPBLs). Blood samples from ten volunteers (both male and female) were irradiated with doses of 8.00, 13.64, 15.00, and 20.00 Gy of 250 kV X-rays or 60 MeV protons. The dose-effect relations were calculated and distributed by plotting the frequencies of DNA damage of excess Premature Chromosome Condensation (PCC) fragments and rings in the G2/M phase, obtained via chemical induction with calyculin A. The Papworth's u test was used to evaluate the distribution of DNA damage. The study shows that high doses of protons induce HPBL DNA damage in the G2/M phase differently than X-rays do. The results indicate a different distribution of DNA damage following high doses of irradiation with protons versus photons between donors, types of radiation, and doses. The proliferation index confirms the impact of high doses of mitosis and the influence of radiotherapy type on the different HPBL response. The results illuminate the cellular and molecular mechanisms that underlie differences in the distribution of DNA damage and cell-cycle phases; these findings may yield an improvement in the efficacy of the radiotherapies used.

Clinical Progress in Proton Radiotherapy: Biological Unknowns

Simple Summary

Proton radiation therapy is a more recent type of radiotherapy that uses proton beams instead of classical photon or X-rays beams. The clinical benefit of proton therapy is that it allows to treat tumors more precisely. As a result, proton radiotherapy induces less toxicity to healthy tissue near the tumor site. Despite the experience in the clinical use of protons, the response of cells to proton radiation, the radiobiology, is less understood. In this review, we describe the current knowledge about proton radiobiology.

Abstract

Clinical use of proton radiation has massively increased over the past years. The main reason for this is the beneficial depth-dose distribution of protons that allows to reduce toxicity to normal tissues surrounding the tumor. Despite the experience in the clinical use of protons, the radiobiology after proton irradiation compared to photon irradiation remains to be completely elucidated. Proton radiation may lead to differential damages and activation of biological processes. Here, we will review the current knowledge of proton radiobiology in terms of induction of reactive oxygen species, hypoxia, DNA damage response, as well as cell death after proton irradiation and radioresistance.

Combined effects of cisplatin and photon or proton irradiation in cultured cells: radiosensitization, patterns of cell death and cell cycle distribution

The purpose of the current study was to investigate the biological effects of protons and photons in combination with cisplatin in cultured cells and elucidate the mechanisms responsible for their combined effects. To evaluate the sensitizing effects of cisplatin against X-rays and proton beams in HSG, EMT6 and V79 cells, the combination index, a simple measure for quantifying synergism, was estimated from cell survival curves using software capable of performing the Monte Carlo calculation. Cell death and apoptosis were assessed using live cell fluorescence imaging. HeLa and HSG cells expressing the fluorescent ubiquitination-based cell cycle indicator system (Fucci) were irradiated with X-rays and protons with cisplatin. Red and green fluorescence in the G1 and S/G2/M phases, respectively, were evaluated and changes in the cell cycle were assessed. The sensitizing effects of ≥1.5 μM cisplatin were observed for both X-ray and proton irradiation (P < 0.05). In the three cell lines, the average combination index was 0.82-1.00 for X-rays and 0.73-0.89 for protons, indicating stronger effects for protons. In time-lapse imaging, apoptosis markedly increased in the groups receiving ≥1.5 μM cisplatin + protons. The percentage of green S/G2/M phase cells at that time was higher when cisplatin was combined with proton beams than with X-rays (P < 0.05), suggesting more significant G2 arrest. Proton therapy plus ≥1.5 μM cisplatin is considered to be very effective. When combined with cisplatin, proton therapy appeared to induce greater apoptotic cell death and G2 arrest, which may partly account for the difference observed in the combined effects.

Assessing the Need for Adjusted Organ-at-Risk Planning Goals for Patients Undergoing Adjuvant Radiation Therapy for Locally Advanced Breast Cancer with Proton Radiation

PURPOSE

Locally advanced breast cancer requires surgical management via lumpectomy or mastectomy with or without systemic therapy followed by chest wall or breast (CW) and comprehensive nodal irradiation (CNI). Radiation (RT) dose constraints for the heart and ipsilateral lung have been developed based on photon RT. Proton therapy (PBT) can deliver significantly lower doses of RT to these organs-at-risk (OARs) and may warrant adjustments to OAR planning goals.

METHODS AND MATERIALS

The RT plans of consecutive patients undergoing adjuvant CW-CNI RT with PBT within a single center were reviewed. A inital treatment volume, comprised of CW/intact breast + CNI (CTV_init) structure, including the CW and CNI but excluding any boost plans was analyzed. Frequency distributions were generated based on doses received by the heart, lungs, and esophagus for validated dosimetric parameters. Frequency distributions were generated and then stratified by laterality and compared using the Kruskal-Wallis H test. The 75th, 85th, and 95th percentiles for each dosimetric parameter were calculated, overall and by laterality. The 75th percentile (Q3), was used as a suggested primary goal, and the 95th percentile was used as a suggested secondary goal.

RESULTS

One hundred and seventy-two plans were analyzed. Forty-nine plans were right-sided, 107 were left-sided, and 16 were bilateral. The overall Q3 of the mean and V25 of the heart were 1.5 Gy and 1.7%, respectively. The mean and V25 to the heart differed significantly by laterality. Pulmonary values were similar to current recommendations. For all lateralites, the median volume of the esophagus receiving 70% prescription dose was ≤1 cm³.

CONCLUSIONS

We present the first dosimetric study providing complete OAR dose-volume histograms data for patients undergoing adjuvant pencil-beam scanning-PBT for locally advanced breast cancer, with detailed information on central tendencies, ranges and distributions of data. We have provided suggested planning goals and metrics for the lungs, heart, and esophagus; the latter 2 differing significantly from current Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) constraints and classical photon goals.

RBE for proton radiation therapy - a Nordic view in the international perspective

BACKGROUND

This paper presents an insight into the critical discussions and the current strategies of the Nordic countries for handling the variable proton relative biological effectiveness (RBE) as presented at The Nordic Collaborative Workshop for Particle Therapy that took place at the Skandion Clinic on 14th and 15th of November 2019.

MATERIAL AND METHODS

In the current clinical practice at the two proton centres in operation at the date, Skandion Clinic, and the Danish Centre for Particle Therapy, a constant proton RBE of 1.1 is applied. The potentially increased effectiveness at the end of the particle range is however considered at the stage of treatment planning at both places based on empirical observations and knowledge. More elaborated strategies to evaluate the plans and mitigate the problem are intensely investigated internationally as well at the two centres. They involve the calculation of the dose-averaged linear energy transfer (LET_d) values and the assessment of their distributions corroborated with the distribution of the dose and the location of the critical clinical structures.

RESULTS

Methods and tools for LET_d calculations are under different stages of development as well as models to account for the variation of the RBE with LET_d, dose per fraction, and type of tissue. The way they are currently used for evaluation and optimisation of the plans and their robustness are summarised. A critical but not exhaustive discussion of their potential future implementation in the clinical practice is also presented.

CONCLUSIONS

The need for collaboration between the clinical proton centres in establishing common platforms and perspectives for treatment planning evaluation and optimisation is highlighted as well as the need of close interaction with the research academic groups that could offer a complementary perspective and actively help developing methods and tools for clinical implementation of the more complex metrics for considering the variable effectiveness of the proton beams.

Combined radiation strategies for novel and enhanced cancer treatment

Numerous studies focus on cancer therapy worldwide, and although many advances have been recorded, the complexity of the disease dictates thinking out of the box to confront it. This study reviews some of the currently available ionizing (IR) and non-ionizing radiation (NIR)-based treatment methods and explores their possible combinations that lead to synergistic, multimodal approaches with promising therapeutic outcomes. Traditional techniques, like radiotherapy (RT) show decent results, although they cannot spare 100% the healthy tissues neighboring with the cancer ones. Targeted therapies, such as proton and photodynamic therapy (PT and PDT, respectively) present adequate outcomes, even though each one has its own drawbacks. To overcome these limitations, the combination of therapeutic modalities has been proposed and has already been showing promising results. At the same time, the recent advances in nanotechnology in the form of nanoparticles enhance cancer therapy, making multimodal treatments worthy of exploring and studying. The combination of RT and PDT has reached the level of clinical trials and is showing promising results. Moreover, in vitro and in vivo studies of nanoparticles with PDT have also provided beneficial results concerning enhanced radiation treatments. In any case, novel and multimodal approaches have to be adopted to achieve personalized, enhanced and effective cancer treatment.

Applying Tissue Slice Culture in Cancer Research-Insights from Preclinical Proton Radiotherapy

A challenge in cancer research is the definition of reproducible, reliable, and practical models, which reflect the effects of complex treatment modalities and the heterogeneous response of patients. Proton beam radiotherapy (PBRT), relative to conventional photon-based radiotherapy, offers the potential for iso-effective tumor control, while protecting the normal tissue surrounding the tumor. However, the effects of PBRT on the tumor microenvironment and the interplay with newly developed chemo- and immunotherapeutic approaches are still open for investigation. This work evaluated thin-cut tumor slice cultures (TSC) of head and neck cancer and organotypic brain slice cultures (OBSC) of adult mice brain, regarding their relevance for translational radiooncology research. TSC and OBSC were treated with PBRT and investigated for cell survival with a lactate dehydrogenase (LDH) assay, DNA repair via the DNA double strand break marker γH2AX, as well as histology with regards to morphology. Adult OBSC failed to be an appropriate model for radiobiological research questions. However, histological analysis of TSC showed DNA damage and tumor morphological results, comparable to known in vivo and in vitro data, making them a promising model to study novel treatment approaches in patient-derived xenografts or primary tumor material.

Assessment of RBE-Weighted Dose Models for Carbon Ion Therapy Toward Modernization of Clinical Practice at HIT: In Vitro, in Vivo, and in Patients

PURPOSE

Present-day treatment planning in carbon ion therapy is conducted with assumptions for a limited number of tissue types and models for effective dose. Here, we comprehensively assess relative biological effectiveness (RBE) in carbon ion therapy and associated models toward the modernization of current clinical practice in effective dose calculation.

METHODS

Using 2 human (A549, H460) and 2 mouse (B16, Renca) tumor cell lines, clonogenic cell survival assay was performed for examination of changes in RBE along the full range of clinical-like spread-out Bragg peak (SOBP) fields. Prediction power of the local effect model (LEM1 and LEM4) and the modified microdosimetric kinetic model (mMKM) was assessed. Experimentation and analysis were carried out in the frame of a multidimensional end point study for clinically relevant ranges of physical dose (D), dose-averaged linear energy transfer (LET_d), and base-line photon radio-sensitivity (α/β)_x. Additionally, predictions were compared against previously reported RBE measurements in vivo and surveyed in patient cases.

RESULTS

RBE model prediction performance varied among the investigated perspectives, with mMKM prediction exhibiting superior agreement with measurements both in vitro and in vivo across the 3 investigated end points. LEM1 and LEM4 performed their best in the highest LET conditions but yielded overestimations and underestimations in low/midrange LET conditions, respectively, as demonstrated by comparison with measurements. Additionally, the analysis of patient treatment plans revealed substantial variability across the investigated models (±20%-30% uncertainty), largely dependent on the selected model and absolute values for input tissue parameters α_x and β_x.

CONCLUSION

RBE dependencies in vitro, in vivo, and in silico were investigated with respect to various clinically relevant end points in the context of tumor-specific tissue radio-sensitivity assignment and accurate RBE modeling. Discovered model trends and performances advocate upgrading current treatment planning schemes in carbon ion therapy and call for verification via clinical outcome analysis with large patient cohorts.

Evaluation of proton beam radiation-induced skin injury in a murine model using a clinical SOBP

The purpose of this paper is to characterize the skin deterministic damage due to the effect of proton beam irradiation in mice occurred during a long-term observational experiment. This study was initially defined to evaluate the insurgence of myelopathy irradiating spinal cords with the distal part of a Spread-out Bragg peak (SOBP). To the best of our knowledge, no study has been conducted highlighting high grades of skin injury at the dose used in this paper. Nevertheless these effects occurred. In this regard, the experimental evidence of significant insurgence of skin injury induced by protons using a SOBP configuration will be shown. Skin damages were classified into six scores (from 0 to 5) according to the severity of the injuries and correlated to ED50 (i.e. the radiation dose at which 50% of animals show a specific score) at 40 days post-irradiation (d.p.i.). The effects of radiation on the overall animal wellbeing have been also monitored and the severity of radiation-induced skin injuries was observed and quantified up to 40 d.p.i.

Multi-modality bedding platform for combined imaging and irradiation of mice

Preclinical imaging and irradiation yields valuable insights into clinically relevant research topics. While complementary imaging methods such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) can be combined within single devices, this is technically demanding and cost-intensive. Similarly, bedding and setup solutions are often specific to certain devices and research questions. We present a bedding platform for mice that is compatible with various preclinical imaging modalities (combined PET/MRI, cone beam CT) and irradiation with photons and protons. It consists of a 3D-printed bedding unit (acrylonitrile butadiene styrene, ABS) holding the animal and features an inhalation anesthesia mask, jaw fixation, ear pins, and immobilization for the hind leg. It can be embedded on mounting adaptors for multi-modal imaging and into a transport box (polymethyl methacrylate, PMMA) for experiments outside dedicated animal facilities while maintaining the animal's hygiene status. A vital support unit provides heating, inhalation anesthesia, and a respiration monitor. We dosimetrically evaluated used materials in order to assess their interaction with incident irradiation. Proof-of-concept multi-modal imaging protocols were used on phantoms and mice. The measured attenuation of the bedding unit for 40/60/80/200 kV X-rays was less than 3%. The measured stopping-power-ratio of ABS was 0.951, the combined water-equivalent thickness of bedding unit and transport box was 4.2 mm for proton energies of 150 MeV and 200 MeV. Proof-of-concept imaging showed no loss of image quality. Imaging data of individual mice from different imaging modalities could be aligned rigidly. The presented bed aims to provide a platform for experiments related to both multi-modal imaging and irradiation, thus offering the possibility for image-guided irradiation which relies on precise imaging and positioning. The usage as a self-contained, stand-alone unit outside dedicated animal facilities represents an advantage over setups designed for specific devices.

Inter-patient variations in relative biological effectiveness for cranio-spinal irradiation with protons

Cranio-spinal irradiation (CSI) using protons has dosimetric advantages compared to photons and is expected to reduce risk of adverse effects. The proton relative biological effectiveness (RBE) varies with linear energy transfer (LET), tissue type and dose, but a variable RBE has not replaced the constant RBE of 1.1 in clinical treatment planning. We examined inter-patient variations in RBE for ten proton CSI patients. Variable RBE models were used to obtain RBE and RBE-weighted doses. RBE was quantified in terms of dose weighted organ-mean RBE ([Formula: see text] = mean RBE-weighted dose/mean physical dose) and effective RBE of the near maximum dose (D2%), i.e. RBED2% = [Formula: see text], where subscripts RBE and phys indicate that the D2% is calculated based on an RBE model and the physical dose, respectively. Compared to the median [Formula: see text] of the patient population, differences up to 15% were observed for the individual [Formula: see text] values found for the thyroid, while more modest variations were seen for the heart (6%), lungs (2%) and brainstem (<1%). Large inter-patient variation in RBE could be correlated to large spread in LET and dose for these organs at risk (OARs). For OARs with small inter-patient variations, the results show that applying a population based RBE in treatment planning may be a step forward compared to using RBE of 1.1. OARs with large inter-patient RBE variations should ideally be selected for patient-specific biological or RBE robustness analysis if the physical doses are close to known dose thresholds.

Proton Irradiation Increases the Necessity for Homologous Recombination Repair Along with the Indispensability of Non-Homologous End Joining

Technical improvements in clinical radiotherapy for maximizing cytotoxicity to the tumor while limiting negative impact on co-irradiated healthy tissues include the increasing use of particle therapy (e.g., proton therapy) worldwide. Yet potential differences in the biology of DNA damage induction and repair between irradiation with X-ray photons and protons remain elusive. We compared the differences in DNA double strand break (DSB) repair and survival of cells compromised in non-homologous end joining (NHEJ), homologous recombination repair (HRR) or both, after irradiation with an equal dose of X-ray photons, entrance plateau (EP) protons, and mid spread-out Bragg peak (SOBP) protons. We used super-resolution microscopy to investigate potential differences in spatial distribution of DNA damage foci upon irradiation. While DNA damage foci were equally distributed throughout the nucleus after X-ray photon irradiation, we observed more clustered DNA damage foci upon proton irradiation. Furthermore, deficiency in essential NHEJ proteins delayed DNA repair kinetics and sensitized cells to both, X-ray photon and proton irradiation, whereas deficiency in HRR proteins sensitized cells only to proton irradiation. We assume that NHEJ is indispensable for processing DNA DSB independent of the irradiation source, whereas the importance of HRR rises with increasing energy of applied irradiation.

Late Contrast Enhancing Brain Lesions in Proton-Treated Patients With Low-Grade Glioma: Clinical Evidence for Increased Periventricular Sensitivity and Variable RBE

PURPOSE

Late radiation-induced contrast-enhancing brain lesions (CEBLs) on magnetic resonance imaging (MRI) after proton therapy of brain tumors have been observed to occur frequently in regions of high linear energy transfer (LET) and in proximity to the ventricular system. We analyzed 110 patients with low-grade glioma treated with proton therapy to determine whether the risk for CEBLs is increased in proximity to the ventricular system and if there is a relationship between relative biological effectiveness (RBE) and LET.

METHODS AND MATERIALS

We contoured CEBLs identified on follow-up T1-MRI scans and computed dose and dose-averaged LET (LET_d) distributions for all patients using the Monte Carlo method. We then performed cross-validated voxel-level logistic regression to predict local risks for image change and to extract model parameters, such as the RBE. From the voxel-level model, we derived a model for patient-level risk prediction based on the treatment plan.

RESULTS

Of 110 patients, 23 exhibited 1 or several CEBLs on follow-up MRI scans. The voxel-level logistic model has an accuracy as follows: area under the curve of 0.94 and Brier score of 2.6 × 10^-5. Model predictions are a 3-fold increased risk in the 4 mm region around the ventricular system and an LET_d-dependent RBE of, for example, 1.20 for LET_d = 2 keV/μm and 1.50 for LET_d = 5 keV/μm. The patient-level risk model has an accuracy as follows: area under the curve of 0.78 and Brier score of 0.13.

CONCLUSIONS

Our findings present clinical evidence for an increased risk in ventricular proximity and for a proton RBE that increases significantly with increasing LET. We present a voxel-level model that accurately predicts the localization of late MRI contrast change and extrapolate a patient-level model that allows treatment plan-based risk prediction.

Modelling variable proton relative biological effectiveness for treatment planning

Dose in proton radiotherapy is generally prescribed by scaling the physical proton dose by a constant value of 1.1. Relative biological effectiveness (RBE) is defined as the ratio of doses required by two radiation modalities to cause the same level of biological effect. The adoption of an RBE of 1.1. assumes that the biological efficacy of protons is similar to photons, allowing decades of clinical dose prescriptions from photon treatments and protocols to be utilized in proton therapy. There is, however, emerging experimental evidence that indicates that proton RBE varies based on technical, tissue and patient factors. The notion that a single scaling factor may be used to equate the effects of photons and protons across all biological endpoints and doses is too simplistic and raises concern for treatment planning decisions. Here, we review the models that have been developed to better predict RBE variations in tissue based on experimental data as well as using a mechanistic approach.