Dose or 'LET' painting--What is optimal in particle therapy of hypoxic tumors?

Investigation on the physical dose filtered by linear energy transfer for treatment plan evaluation in carbon ion therapy

BACKGROUND

Large tumor size has been reported as a predicting factor for inferior clinical outcome in carbon ion radiotherapy (CIRT). Besides the clinical factors accompanied with such tumors, larger tumors receive typically more low linear energy transfer (LET) contributions than small ones which may be the underlying physical cause. Although dose averaged LET is often used as a single parameter descriptor to quantify the beam quality, there is no evidence that this parameter is the optimal clinical predictor for the complex mixed radiation fields in CIRT.

PURPOSE

Purpose of this study was to investigate on a novel dosimetric quantity, namely high-LET-dose (D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the physical dose filtered based on an LET threshold) as a single parameter estimator to differentiate between carbon ion treatment plans (cTP) with a small and large tumor volume.

METHODS

Ten cTPs with a planning target volume,PTV ≥ 500 cm 3 $\mathrm{PTV}\ge {500}\,{{\rm cm}^{3}}$ (large) and nine with aPTV < 500 cm 3 $\mathrm{PTV}<{500}\,{{\rm cm}^{3}}$ (small) were selected for this study. To find a reasonable LET threshold (L thr $\textrm {L}_{\textrm {thr}}$ ) that results in a significant difference in terms ofD > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the voxel based normalized high-LET-dose (D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) distribution in the clinical target volume (CTV) was studied on a subset (12 out of 19 cTPs) for 18 LET thresholds, using standard distribution descriptors (mean, variance and skewness). The classical dose volume histogram concept was used to evaluate theD > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ andD ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ distributions within the target of all 19 cTPs at the before determinedL thr $\textrm {L}_{\textrm {thr}}$ . Statistical significance of the difference between the two groups in terms of meanD > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ andD ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ volume histogram parameters was evaluated by means of (two-sided) t-test or Mann-Whitney-U-test. In addition, the minimum target coverage at the above determinedL thr $\textrm {L}_{\textrm {thr}}$ was compared and validated against three other thresholds to verify its potential in differentiation between small and large volume tumors.

RESULTS

AnL thr $\textrm {L}_{\textrm {thr}}$ of approximately30 keV / μ m ${30}\,{\rm keV/}\umu {\rm m}$ was found to be a reasonable threshold to classify the two groups. At this threshold, theD > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ andD ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ were significantly larger (p < 0.05 $p<0.05$ ) in small CTVs. For the small tumor group, the near-minimum and medianD > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (andD ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) in the CTV were in average9.3 ± 1.5 Gy $9.3\pm {1.5}\,{\rm Gy}$ (0.31 ± 0.08) and13.6 ± 1.6 Gy $13.6\pm {1.6}\,{\rm Gy}$ (0.46 ± 0.06), respectively. For the large tumors, these parameters were6.6 ± 0.2 Gy $6.6\pm {0.2}\,{\rm Gy}$ (0.20 ± 0.01) and8.6 ± 0.4 Gy $8.6\pm {0.4}\,{\rm Gy}$ (0.28 ± 0.02). The difference between the two groups in terms of mean near-minimum and medianD > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) was 2.7 Gy (11%) and 5.0 Gy (18%), respectively.

CONCLUSIONS

The feasibility of high-LET-dose based evaluation was shown in this study where a lowerD > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ was found in cTPs with a large tumor size. Further investigation is needed to draw clinical conclusions. The proposed methodology in this work can be utilized for future high-LET-dose based studies.

The LET trilemma: Conflicts between robust target coverage, uniform dose, and dose-averaged LET in carbon therapy

BACKGROUND

Linear energy transfer (LET) is closely related to the biological effect of ionizing radiation. Increasing the dose-averaged LET (LETd ) within the target volume has been proposed as a means to improve clinical outcome for hypoxic tumors. However, doing so can lead to reduced robustness to range uncertainty.

PURPOSE

To quantify the relationship between robust target coverage, target dose uniformity, and LETd , we employ robust optimization using dose-based and LETd -based functions and allow varying amounts of target non-uniformity.

METHODS AND MATERIALS

Robust carbon therapy optimization is used to create plans for phantom cases with increasing target sizes (radii 1, 3, and 5 cm). First, the influence of respectively range and setup uncertainty on the LETd in the target is studied. Second, we employ strategies allowing overdosage in the clinical target volume (CTV) or gross tumor volume (GTV), which enable increased LETd in the target. The relationship between robust target coverage and LETd in the target is illustrated by tradeoff curves generated by optimization using varying weights for the LETd -based functions.

RESULTS

As the range uncertainty used in the robust optimization increased from 0% to 5%, the near-minimum nominal LETd decreased by 17%-29% (9-21 keV/µm) for the different target sizes. The effect of increasing setup uncertainty was marginal. Allowing 10% overdosage in the CTV enabled 9%-29% (6-12 keV/µm) increased near-minimum worst case LETd for the different target sizes, compared to uniform dose plans. When 10% overdosage was allowed in the GTV only, the increase was 1%-20% (1-8 keV/µm).

CONCLUSIONS

There is an inherent conflict between range uncertainty robustness and high LETd in the target, which is aggravated with increasing target size. For large tumors, it is possible to simultaneously achieve two of the three qualities range robustness, uniform dose, and high LETd in the target.

Carbon Ions for Hypoxic Tumors: Are We Making the Most of Them?

Hypoxia, which is associated with abnormal vessel growth, is a characteristic feature of many solid tumors that increases their metastatic potential and resistance to radiotherapy. Carbon-ion radiation therapy, either alone or in combination with other treatments, is one of the most promising treatments for hypoxic tumors because the oxygen enhancement ratio decreases with increasing particle LET. Nevertheless, current clinical practice does not yet fully benefit from the use of carbon ions to tackle hypoxia. Here, we provide an overview of the existing experimental and clinical evidence supporting the efficacy of C-ion radiotherapy in overcoming hypoxia-induced radioresistance, followed by a discussion of the strategies proposed to enhance it, including different approaches to maximize LET in the tumors.

Combined RBE and OER optimization in proton therapy with FLUKA based on EF5-PET

INTRODUCTION

Tumor hypoxia is associated with poor treatment outcome. Hypoxic regions are more radioresistant than well-oxygenated regions, as quantified by the oxygen enhancement ratio (OER). In optimization of proton therapy, including OER in addition to the relative biological effectiveness (RBE) could therefore be used to adapt to patient-specific radioresistance governed by intrinsic radiosensitivity and hypoxia.

METHODS

A combined RBE and OER weighted dose (ROWD) calculation method was implemented in a FLUKA Monte Carlo (MC) based treatment planning tool. The method is based on the linear quadratic model, with α and β parameters as a function of the OER, and therefore a function of the linear energy transfer (LET) and partial oxygen pressure (pO2 ). Proton therapy plans for two head and neck cancer (HNC) patients were optimized with pO2 estimated from [18 F]-EF5 positron emission tomography (PET) images. For the ROWD calculations, an RBE of 1.1 (RBE1.1,OER ) and two variable RBE models, Rørvik (ROR) and McNamara (MCN), were used, alongside a reference plan without incorporation of OER (RBE1.1 ).

RESULTS

For the HNC patients, treatment plans in line with the prescription dose and with acceptable target ROWD could be generated with the established tool. The physical dose was the main factor modulated in the ROWD. The impact of incorporating OER during optimization of HNC patients was demonstrated by the substantial difference found between ROWD and physical dose in the hypoxic tumor region. The largest physical dose differences between the ROWD optimized plans and the reference plan was 12.2 Gy.

CONCLUSION

The FLUKA MC based tool was able to optimize proton treatment plans taking the tumor pO2 distribution from hypoxia PET images into account. Independent of RBE-model, both elevated LET and physical dose were found in the hypoxic regions, which shows the potential to increase the tumor control compared to a conventional optimization approach.

A Systematic Review of LET-Guided Treatment Plan Optimisation in Proton Therapy: Identifying the Current State and Future Needs

The well-known clinical benefits of proton therapy are achieved through higher target-conformality and normal tissue sparing than conventional radiotherapy. However, there is an increased sensitivity to uncertainties in patient motion/setup, proton range and radiobiological effect. Although recent efforts have mitigated some uncertainties, radiobiological effect remains unresolved due to a lack of clinical data for relevant endpoints. Therefore, RBE optimisations may be currently unsuitable for clinical treatment planning. LET optimisation is a novel method that substitutes RBE with LET, shifting LET hotspots outside critical structures. This review outlines the current status of LET optimisation in proton therapy, highlighting knowledge gaps and possible future research. Following the PRISMA 2020 guidelines, a search of the MEDLINE® and Scopus databases was performed in July 2023, identifying 70 relevant articles. Generally, LET optimisation methods achieved their treatment objectives; however, clinical benefit is patient-dependent. Inconsistencies in the reported data suggest further testing is required to identify therapeutically favourable methods. We discuss the methods which are suitable for near-future clinical deployment, with fast computation times and compatibility with existing treatment protocols. Although there is some clinical evidence of a correlation between high LET and adverse effects, further developments are needed to inform future patient selection protocols for widespread application of LET optimisation in proton therapy.

Hypoxia-Targeted Dose Painting in Radiotherapy

Hypoxia (oxygen deprivation) occurs in most solid malignancies, albeit with considerable heterogeneity. Hypoxia is associated with an aggressive cancer phenotype by promotion of genomic instability, evasion of anti-cancer therapies including radiotherapy and enhancement of metastatic risk. Therefore, hypoxia results in poor cancer outcomes. Targeting hypoxia to improve cancer outcomes is an attractive therapeutic strategy. Hypoxia-targeted dose painting escalates radiotherapy dose to hypoxic sub-volumes, as quantified and spatially mapped using hypoxia imaging. This therapeutic approach could overcome hypoxia-induced radioresistance and improve patient outcomes without the need for hypoxia-targeted drugs. This article will review the premise and underpinning evidence for personalized hypoxia-targeted dose painting. It will present data on relevant hypoxia imaging biomarkers, highlight the challenges and potential benefit of this approach and provide recommendations for future research priorities in this field. Personalized hypoxia-based radiotherapy de-escalation strategies will also be addressed.

Technical note: In silico benchmarking of the linear energy transfer-based functionalities for carbon ion beams in a commercial treatment planning system

BACKGROUND

The increasing number of studies dealing with linear energy transfer (LET)-based evaluation and optimization in the field of carbon ion radiotherapy (CIRT) indicates the rising demand for LET implementation in commercial treatment planning systems (TPS). Benchmarking studies could play a key role in detecting (and thus preventing) computation errors prior implementing such functionalities in a TPS.

PURPOSE

This in silico study was conducted to benchmark the following two LET-related functionalities in a commercial TPS against Monte Carlo simulations: (1) dose averaged LET (LET_d ) scoring and (2) physical dose filtration based on LET for future LET-based treatment plan evaluation and optimization studies.

METHODS

The LET_d scoring and LET-based dose filtering (in which the deposited dose can be separated into the dose below and above the user specified LET threshold) functionalities for carbon ions in the research version RayStation (RS) 9A-IonPG TPS (RaySearch Laboratories, Sweden) were benchmarked against GATE/Geant4 simulations. Pristine Bragg peaks (BPs) and cuboid targets, positioned at different depths in a homogeneous water phantom and a setup with heterogeneity were used for this study.

RESULTS

For all setups (homogeneous and heterogeneous), the mean absolute (and relative) LET_d difference was less than 1 keV/ μ $\umu$ m (3.5%) in the plateau and target and less than 2 keV/ μ $\umu$ m (8.3%) in the fragmentation tail. The maximum local differences were 4 and 6 keV/ μ $\umu$ m, respectively. The mean absolute (and relative) physical dose differences for both low- and high-LET doses were less than 1 cGy (1.5%) in the plateau, target and tail with a maximum absolute difference of 2 cGy.

CONCLUSIONS

No computation error was found in the tested functionalities except for LET_d in lateral direction outside the target, showing the limitation of the implemented monochrome model in the tested TPS version.

Potential benefits of using radioactive ion beams for range margin reduction in carbon ion therapy

Sharp dose gradients and high biological effectiveness make ions such as ¹²C an ideal tool to treat deep-seated tumors, however, at the same time, sensitive to errors in the range prediction. Tumor safety margins mitigate these uncertainties, but during the irradiation they lead to unavoidable damage to the surrounding healthy tissue. To fully exploit the Bragg peak benefits, a large effort is put into establishing precise range verification methods. Despite positron emission tomography being widely in use for this purpose in ¹²C therapy, the low count rates, biological washout, and broad activity distribution still limit its precision. Instead, radioactive beams used directly for treatment would yield an improved signal and a closer match with the dose fall-off, potentially enabling precise in vivo beam range monitoring. We have performed a treatment planning study to estimate the possible impact of the reduced range uncertainties, enabled by radioactive ¹¹C ions treatments, on sparing critical organs in tumor proximity. Compared to ¹²C treatments, (i) annihilation maps for ¹¹C ions can reflect sub- millimeter shifts in dose distributions in the patient, (ii) outcomes of treatment planning with ¹¹C significantly improve and (iii) less severe toxicities for serial and parallel critical organs can be expected.

Development of a portable hypoxia chamber for ultra-high dose rate laser-driven proton radiobiology applications

Background

There is currently significant interest in assessing the role of oxygen in the radiobiological effects at ultra-high dose rates. Oxygen modulation is postulated to play a role in the enhanced sparing effect observed in FLASH radiotherapy, where particles are delivered at 40–1000 Gy/s. Furthermore, the development of laser-driven accelerators now enables radiobiology experiments in extreme regimes where dose rates can exceed 10⁹ Gy/s, and predicted oxygen depletion effects on cellular response can be tested. Access to appropriate experimental enviroments, allowing measurements under controlled oxygenation conditions, is a key requirement for these studies. We report on the development and application of a bespoke portable hypoxia chamber specifically designed for experiments employing laser-driven sources, but also suitable for comparator studies under FLASH and conventional irradiation conditions.

Materials and methods

We used oxygen concentration measurements to test the induction of hypoxia and the maintenance capacity of the chambers. Cellular hypoxia induction was verified using hypoxia inducible factor-1α immunostaining. Calibrated radiochromic films and GEANT-4 simulations verified the dosimetry variations inside and outside the chambers. We irradiated hypoxic human skin fibroblasts (AG01522B) cells with laser-driven protons, conventional protons and reference 225 kVp X-rays to quantify DNA DSB damage and repair under hypoxia. We further measured the oxygen enhancement ratio for cell survival after X-ray exposure in normal fibroblast and radioresistant patient- derived GBM stem cells.

Results

Oxygen measurements showed that our chambers maintained a radiobiological hypoxic environment for at least 45 min and pathological hypoxia for up to 24 h after disconnecting the chambers from the gas supply. We observed a significant reduction in the 53BP1 foci induced by laser-driven protons, conventional protons and X-rays in the hypoxic cells compared to normoxic cells at 30 min post-irradiation. Under hypoxic irradiations, the Laser-driven protons induced significant residual DNA DSB damage in hypoxic AG01522B cells compared to the conventional dose rate protons suggesting an important impact of these extremely high dose-rate exposures. We obtained an oxygen enhancement ratio (OER) of 2.1 ± 0.1 and 2.5 ± 0.1 respectively for the AG01522B and patient-derived GBM stem cells for X-ray irradiation using our hypoxia chambers.

Conclusion

We demonstrated the design and application of portable hypoxia chambers for studying cellular radiobiological endpoints after exposure to laser-driven protons at ultra-high dose, conventional protons and X-rays. Suitable levels of reduced oxygen concentration could be maintained in the absence of external gassing to quantify hypoxic effects. The data obtained provided indication of an enhanced residual DNA DSB damage under hypoxic conditions at ultra-high dose rate compared to the conventional protons or X-rays.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02024-3.

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.

Histosurgical mapping of endoscopic endonasal surgery of sinonasal tumours to improve radiotherapy guidance

PURPOSE

Endoscopic endonasal surgery (EES) is becoming a standard for most malignant sinonasal tumours. Margin analysis after piecemeal resection is complex and optimally relies on accurate histosurgical mapping. Postoperative radiotherapy may be adapted based on margin assessment mapping to reduce the dose to some sinonasal subvolumes. We assessed the use of histosurgical mapping by radiation oncologists (RO).

MATERIAL AND METHODS

A French practice survey was performed across 29 ENT expert RO (2 did not answer) regarding integration of information on EES, as well as quality of operative and pathology reportsto refine radiotherapy planning after EES. This was assessed through an electronic questionnaire.

RESULTS

EES was ubiquitously performed in France. Operative and pathology reports yielded accurate description of EES samples according to 66.7% of interviewed RO. Accuracy of margin assessment was however insufficient according to more than 40.0% of RO. Additional margins/biopsies of the operative bed were available in 55.2% (16/29) of the centres. In the absence of additional margins, quality of resection after EES was considered as microscopically incomplete in 48.3% or dubious in 48.3% of RO. As performed, histosurgical mapping allowed radiotherapy dose and volumes adaptation according to 26.3% of RO only.

CONCLUSIONS

Standardized histosurgical mapping with margin and additional margin analysis could be more systematic. Advantages of accurate EES reporting could be dose painting radiotherapy to further decrease morbidity in sinonasal tumours.

Spot-Scanning Hadron Arc (SHArc) Therapy: A Study With Light and Heavy Ions

PURPOSE

To evaluate the clinical potential of spot-scanning hadron arc (SHArc) therapy with a heavy-ion gantry.

METHODS AND MATERIALS

A series of in silico studies was conducted via treatment plan optimization in FRoG and the RayStation TPS to compare SHArc therapy against reference plans using conventional techniques with single, parallel-opposed, and 3-field configurations for 3 clinical particle beams (protons [p], helium [4He], and carbon [12C] ions). Tests were performed on water-equivalent cylindrical phantoms for simple targets and clinical-like scenarios with an organ-at-risk in proximity of the target. Effective dose and dose-averaged linear energy transfer (LETD) distributions for SHArc were evaluated against conventional planning techniques applying the modified microdosimetric kinetic model for considering bio-effect with (α/β)x = 2 Gy. A model for hypoxia-induced tumor radio-resistance was developed for particle therapy with dependence on oxygen concentration and particle species/energy (Zeff/β)2 to investigate the impact on effective dose.

RESULTS

SHArc plans exhibited similar target coverage with unique treatment attributes and distributions compared with conventional planning, with carbon ions demonstrating the greatest potential for tumor control and normal tissue sparing among the arc techniques. All SHArc plans exhibited a low-dose bath outside the target volume with a reduced maximum dose in normal tissues compared with single, parallel-opposed, and 3-field configuration plans. Moreover, favorable LETD distributions were made possible using the SHArc approach, with maximum LETD in the r = 5 mm tumor core (~8 keVμm-1, ~30 keVμm-1, and ~150 keVμm-1 for p, 4He, and 12C ions, respectively) and reductions of high-LET regions in normal tissues and organs-at-risk compared with static treatment beam delivery.

CONCLUSION

SHArc therapy offers potential treatment benefits such as increased normal tissue sparing. Without explicit consideration of oxygen concentration during treatment planning and optimization, SHArc-C may mitigate tumor hypoxia-induced loss of efficacy. Findings justify further development of robust SHArc treatment planning toward potential clinical translation.

The FLUKA Monte Carlo code coupled with an OER model for biologically weighted dose calculations in proton therapy of hypoxic tumors

INTRODUCTION

The increased radioresistance of hypoxic cells compared to well-oxygenated cells is quantified by the oxygen enhancement ratio (OER). In this study we created a FLUKA Monte Carlo based tool for inclusion of both OER and relative biological effectiveness (RBE) in biologically weighted dose (ROWD) calculations in proton therapy and applied this to explore the impact of hypoxia.

METHODS

The RBE-weighted dose was adapted for hypoxia by making RBE model parameters dependent on the OER, in addition to the linear energy transfer (LET). The OER depends on the partial oxygen pressure (pO₂) and LET. To demonstrate model performance, calculations were done with spread-out Bragg peaks (SOBP) in water phantoms with pO₂ ranging from strongly hypoxic to normoxic (0.01-30 mmHg) and with a head and neck cancer proton plan optimized with an RBE of 1.1 and pO₂ estimated voxel-by-voxel using [¹⁸F]-EF5 PET. An RBE of 1.1 and the Rørvik RBE model were used for the ROWD calculations.

RESULTS

The SOBP in water had decreasing ROWD with decreasing pO₂. In the plans accounting for oxygenation, the median target doses were approximately a factor 1.1 lower than the corresponding plans which did not consider the OER. Hypoxia adapted target ROWDs were considerably more heterogeneous than the RBE_1.1-weighted doses.

CONCLUSION

We realized a Monte Carlo based tool for calculating the ROWD. Read-in of patient pO₂ and estimation of ROWD with flexibility in choice of RBE model was achieved, giving a tool that may be useful in future clinical applications of hypoxia-guided particle therapy.

Combination Therapy With Charged Particles and Molecular Targeting: A Promising Avenue to Overcome Radioresistance

Radiotherapy plays a central role in the treatment of cancer patients. Over the past decades, remarkable technological progress has been made in the field of conventional radiotherapy. In addition, the use of charged particles (e.g., protons and carbon ions) makes it possible to further improve dose deposition to the tumor, while sparing the surrounding healthy tissues. Despite these improvements, radioresistance and tumor recurrence are still observed. Although the mechanisms underlying resistance to conventional radiotherapy are well-studied, scientific evidence on the impact of charged particle therapy on cancer cell radioresistance is restricted. The purpose of this review is to discuss the potential role that charged particles could play to overcome radioresistance. This review will focus on hypoxia, cancer stem cells, and specific signaling pathways of EGFR, NFκB, and Hedgehog as well as DNA damage signaling involving PARP, as mechanisms of radioresistance for which pharmacological targets have been identified. Finally, new lines of future research will be proposed, with a focus on novel molecular inhibitors that could be used in combination with charged particle therapy as a novel treatment option for radioresistant tumors.

Experimental study on monitoring system of clinical beam purity in multiple-ion beam operation for heavy-ion radiotherapy

The National Institute of Radiological Sciences has investigated multiple-ion therapy using energetic beams of helium, carbon, oxygen, and neon ions, to improve treatment outcomes of refractory cancer. For this therapy, it is necessary to ensure the helium-ion beam purity to avoid irradiation by unwanted ions. Here, we develop a measurement method for monitoring beam purity. This method can measure the charge number of the ions in a high-purity beam using an ionization chamber and Faraday cup. In addition, it can be used to detect the contamination of the clinical helium-ion beam. We perform beam experiments to evaluate our beam-purity monitoring method and predict that our method is capable of detecting contamination below 1%.

Optimization of treatment planning for hypoxic tumours and re-modulation of radiation intensity in heavy-ion radiotherapy

Aim

The purpose of this study is to optimize treatment planning in carbon ion radiotherapy, taking into account the effect of tumour hypoxia.

Background

In conventional hadron therapy, the goal is to create a homogenous dose in the tumour area and, thus, achieve a uniform cell survival level. Since the induction of a specific damage to cells is directly influenced by the level of hypoxia in the tissue, the varying oxygen pressure in the different regions of hypoxic tumours would disrupt the uniformity of the cell survival level.

Materials and methods

Using the Geant4 Monte Carlo Code, the physical dose profile and dose-averaged linear energy transfer were calculated in the tumour. Then, the oxygen enhancement ratio in different areas of the tumour were compared with different pressures.

Results

Modulations of radiation intensities as well as energies of ion beams were calculated, both considering and disregarding the effect of hypoxia, and the required dose profiles were compared with each other. Cell survival levels were also compared between the two methods. An equation was obtained for re-modulating the beams in the presence of hypoxia, and radiation weighting factors were extracted for the beam intensities.

Conclusion

The results show that taking the effect of hypoxia into account would cause the reduction of average doses delivered to the tumour tissues up to 1.54 times. In this regard, the required dose is reduced by 1.63 times in the healthy tissues before the tumour. This will result in an effective protection of healthy tissues around the tumour.

Hadrontherapy Interactions in Molecular and Cellular Biology

The resistance of cancer cells to radiotherapy is a major issue in the curative treatment of cancer patients. This resistance can be intrinsic or acquired after irradiation and has various definitions, depending on the endpoint that is chosen in assessing the response to radiation. This phenomenon might be strengthened by the radiosensitivity of surrounding healthy tissues. Sensitive organs near the tumor that is to be treated can be affected by direct irradiation or experience nontargeted reactions, leading to early or late effects that disrupt the quality of life of patients. For several decades, new modalities of irradiation that involve accelerated particles have been available, such as proton therapy and carbon therapy, raising the possibility of specifically targeting the tumor volume. The goal of this review is to examine the up-to-date radiobiological and clinical aspects of hadrontherapy, a discipline that is maturing, with promising applications. We first describe the physical and biological advantages of particles and their application in cancer treatment. The contribution of the microenvironment and surrounding healthy tissues to tumor radioresistance is then discussed, in relation to imaging and accurate visualization of potentially resistant hypoxic areas using dedicated markers, to identify patients and tumors that could benefit from hadrontherapy over conventional irradiation. Finally, we consider combined treatment strategies to improve the particle therapy of radioresistant cancers.

Kill painting of hypoxic tumors with multiple ion beams

We report on a novel method for simultaneous biological optimization of treatment plans for hypoxic tumors using multiple ion species. Our previously introduced kill painting approach, where the overall cell killing is optimized on biologically heterogeneous targets, was expanded with the capability of handling different ion beams simultaneously. The current version (MIBO) of the research treatment planning system TRiP98 has now been augmented to handle 3D (voxel-by-voxel) target oxygenation data. We present a case of idealized geometries where this method can identify optimal combinations leading to an improved peak-to-entrance effective dose ratio. This is achieved by the redistribution of particle fluences, when the heavier ions are preferentially forwarded to hypoxic target areas, while the lighter ions deliver the remaining dose to its normoxic regions. Finally, we present an in silico skull base chordoma patient case study with a combination of ⁴He and ¹⁶O beams, demonstrating specific indications for its potential clinical application. In this particular case, the mean dose, received by the brainstem, was reduced by 3%-5% and by 10%-12% as compared to the pure ⁴He and ¹⁶O plans, respectively. The new method allows a full biological optimization of different ion beams, exploiting the capabilities of actively scanned ion beams of modern particle therapy centers. The possible experimental verification of the present approach at ion beam facilities disposing of fast ion switch is presented and discussed.

Radiobiological issues in prospective carbon ion therapy trials

Carbon ion radiotherapy (CIRT) is developing toward a versatile tool in radiotherapy; however, the increased relative biological effectiveness (RBE) of carbon ions in tumors and normal tissues with respect to photon irradiation has to be considered by mathematical models in treatment planning. As a consequence, dose prescription and definition of dose constraints are performed in terms of RBE weighted rather than absorbed dose. The RBE is a complex quantity, which depends on physical variables, such as dose and beam quality as well as on normal tissue- or tumor-specific factors. At present, three RBE models are employed in CIRT: (a) the mixed-beam model, (b) the Microdosimetric Kinetic Model (MKM), and (c) the local effect model. While the LEM is used in Europe, the other two models are employed in Japan, and unfortunately, the concepts of how the nominal RBE-weighted dose is determined and prescribed differ significantly between the European and Japanese centers complicating the comparison, transfer, and reproduction of clinical results. This has severe impact on the way treatments should be prescribed, recorded, and reported. This contribution reviews the concept of the clinical application of the different RBE models and the ongoing clinical CIRT trials in Japan and Europe. Limitations of the RBE models and the resulting radiobiological issues in clinical CIRT trials are discussed in the context of current clinical evidence and future challenges.

Computational models and tools

In this chapter, we describe two different methods, analytical (pencil beam) algorithms and Monte Carlo simulations, used to obtain the intended dose distributions in patients and evaluate their strengths and shortcomings. We discuss the difference between the prescribed physical dose and the biologically effective dose, the relative biological effectiveness (RBE) between ions and photons and the dependence of RBE on the linear energy transfer (LET). Lastly, we show how LET- or RBE-based optimization can be used to improve treatment plans and explore how the availability of multimodality ion beam facilities can be used to design a tumor-specific optimal treatment.

Radiobiological issues in proton therapy

BACKGROUND

The relative biological effectiveness (RBE) for particle therapy is a complex function of particle type, radiation dose, linear energy transfer (LET), cell type, endpoint, etc. In the clinical practice of proton therapy, the RBE is assumed to have a fixed value of 1.1. This assumption, along with the effects of physical uncertainties, may mean that the biologically effective dose distributions received by the patient may be significantly different from what is seen on treatment plans. This may contribute to unforeseen toxicities and/or failure to control the disease. Variability of Proton RBE: It has been shown experimentally that proton RBE varies significantly along the beam path, especially near the end of the particle range. While there is now an increasing acceptance that proton RBE is variable, there is an ongoing debate about whether to change the current clinical practice. Clinical Evidence: A rationale against the change is the uncertainty in the models of variable RBE. Secondly, so far there is no clear clinical evidence of the harm of assuming proton RBE to be 1.1. It is conceivable, however, that the evidence is masked partially by physical uncertainties. It is, therefore, plausible that reduction in uncertainties and their incorporation in the estimation of dose actually delivered may isolate and reveal the variability of RBE in clinical practice. Nevertheless, clinical evidence of RBE variability is slowly emerging as more patients are treated with protons and their response data are analyzed. Modelling and Incorporation of RBE in the Optimization of Proton Therapy: The improvement in the knowledge of RBE could lead to better understanding of outcomes of proton therapy and in the improvement of models to predict RBE. Prospectively, the incorporation of such models in the optimization of intensity-modulated proton therapy could lead to improvements in the therapeutic ratio of proton therapy.

A phenomenological biological dose model for proton therapy based on linear energy transfer spectra

PURPOSE

The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET_d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model.

METHOD

The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET_d based models for a simulated spread out Bragg peak (SOBP) scenario.

RESULTS

The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22).

CONCLUSION

The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were observed for the SOBP scenario, both non-linear LET spectrum- and linear LET_d based models should be further evaluated in clinically realistic scenarios.