The FLUKA Monte Carlo code is used extensively at CERN for all beam-machine interactions, radioprotection calculations and facility design of forthcoming projects. Such needs require the code to be ...consistently reliable over the entire energy range (from MeV to TeV) for all projectiles (full suite of elementary particles and heavy ions). Outside CERN, among various applications worldwide, FLUKA serves as a core tool for the HIT and CNAO hadron-therapy facilities in Europe. Therefore, medical applications further impose stringent requirements in terms of reliability and predictive power, which demands constant refinement of sophisticated nuclear models and continuous code improvement. Some of the latest developments implemented in FLUKA are presented in this paper, with particular emphasis on issues and concerns pertaining to CERN and medical applications.
While Monte Carlo (MC) codes are considered as the gold standard for dosimetric calculations, the availability of user friendly MC codes suited for particle therapy is limited. Based on the FLUKA MC ...code and its graphical user interface (GUI) Flair, we developed an easy-to-use tool which enables simple and reliable simulations for particle therapy. In this paper we provide an overview of functionalities of the tool and with the presented clinical, proton and carbon ion therapy examples we demonstrate its reliability and the usability in the clinical environment and show its flexibility for research purposes. The first, easy-to-use FLUKA MC platform for particle therapy with GUI functionalities allows a user with a minimal effort and reduced knowledge about MC details to apply MC at their facility and is expected to enhance the popularity of the MC for both research and clinical quality assurance and commissioning purposes.
The introduction of 'new' ion species in particle therapy needs to be supported by a thorough assessment of their dosimetric properties and by treatment planning comparisons with clinically used ...proton and carbon ion beams. In addition to the latter two ions, helium and oxygen ion beams are foreseen at the Heidelberg Ion Beam Therapy Center (HIT) as potential assets for improving clinical outcomes in the near future. We present in this study a dosimetric validation of a FLUKA-based Monte Carlo treatment planning tool (MCTP) for protons, helium, carbon and oxygen ions for spread-out Bragg peaks in water. The comparisons between the ions show the dosimetric advantages of helium and heavier ion beams in terms of their distal and lateral fall-offs with respect to protons, reducing the lateral size of the region receiving 50% of the planned dose up to 12 mm. However, carbon and oxygen ions showed significant doses beyond the target due to the higher fragmentation tail compared to lighter ions (p and He), up to 25%. The Monte Carlo predictions were found to be in excellent geometrical agreement with the measurements, with deviations below 1 mm for all parameters investigated such as target and lateral size as well as distal fall-offs. Measured and simulated absolute dose values agreed within about 2.5% on the overall dose distributions. The MCTP tool, which supports the usage of multiple state-of-the-art relative biological effectiveness models, will provide a solid engine for treatment planning comparisons at HIT.
In the field of radiotherapy, Monte Carlo (MC) particle transport calculations are recognized for their superior accuracy in predicting dose and fluence distributions in patient geometries compared ...to analytical algorithms which are generally used for treatment planning due to their shorter execution times. In this work, a newly developed MC-based treatment planning (MCTP) tool for proton therapy is proposed to support treatment planning studies and research applications. It allows for single-field and simultaneous multiple-field optimization in realistic treatment scenarios and is based on the MC code FLUKA. Relative biological effectiveness (RBE)-weighted dose is optimized either with the common approach using a constant RBE of 1.1 or using a variable RBE according to radiobiological input tables. A validated reimplementation of the local effect model was used in this work to generate radiobiological input tables. Examples of treatment plans in water phantoms and in patient-CT geometries together with an experimental dosimetric validation of the plans are presented for clinical treatment parameters as used at the Italian National Center for Oncological Hadron Therapy. To conclude, a versatile MCTP tool for proton therapy was developed and validated for realistic patient treatment scenarios against dosimetric measurements and commercial analytical TP calculations. It is aimed to be used in future for research and to support treatment planning at state-of-the-art ion beam therapy facilities.
As carbon ions, at therapeutic energies, penetrate tissue, they undergo inelastic nuclear reactions and give rise to significant yields of secondary fragment fluences. Therefore, an accurate ...prediction of these fluences resulting from the primary carbon interactions is necessary in the patient's body in order to precisely simulate the spatial dose distribution and the resulting biological effect. In this paper, the performance of nuclear fragmentation models of the Monte Carlo transport codes, FLUKA and GEANT4, in tissue-like media and for an energy regime relevant for therapeutic carbon ions is investigated. The ability of these Monte Carlo codes to reproduce experimental data of charge-changing cross sections and integral and differential yields of secondary charged fragments is evaluated. For the fragment yields, the main focus is on the consideration of experimental approximations and uncertainties such as the energy measurement by time-of-flight. For GEANT4, the hadronic models G4BinaryLightIonReaction and G4QMD are benchmarked together with some recently enhanced de-excitation models. For non-differential quantities, discrepancies of some tens of percent are found for both codes. For differential quantities, even larger deviations are found. Implications of these findings for the therapeutic use of carbon ions are discussed.
Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence ...computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), the MCTP tool is able to perform TP studies using ions with atomic numbers Z ≤ 8. Example treatment plans created with the MCTP tool are presented for carbon ions in comparison with a certified analytical treatment-planning system. Furthermore, the usage of the tool to compute and optimize mixed-ion treatment plans, i.e. plans including pencil beams of ions with different atomic numbers, is demonstrated. The tool is aimed for future use in research applications and to support treatment planning at ion beam facilities.
Uncertainties in determining clinically used relative biological effectiveness (RBE) values for ion beam therapy carry the risk of absolute and relative misestimations of RBE-weighted doses for ...clinical scenarios. This study assesses the consequences of hypothetical misestimations of input parameters to the RBE modelling for carbon ion treatment plans by a variational approach. The impact of the variations on resulting cell survival and RBE values is evaluated as a function of the remaining ion range. In addition, the sensitivity to misestimations in RBE modelling is compared for single fields and two opposed fields using differing optimization criteria. It is demonstrated for single treatment fields that moderate variations (up to ±50%) of representative nominal input parameters for four tumours result mainly in a misestimation of the RBE-weighted dose in the planning target volume (PTV) by a constant factor and only smaller RBE-weighted dose gradients. Ensuring a more uniform radiation quality in the PTV eases the clinical importance of uncertainties in the radiobiological treatment parameters, as for such a condition uncertainties tend to result only in a systematic misestimation of RBE-weighted dose in the PTV by a constant factor. Two opposed carbon ion fields with a constant RBE in the PTV are found to result in rather robust conditions. Treatments using two ion species may be used to achieve a constant RBE in the PTV irrespective of the size and depth of the spread-out Bragg peak.
Proton therapy treatment planning systems (TPSs) are based on the assumption of a constant relative biological effectiveness (RBE) of 1.1 without taking into account the found in vitro experimental ...variations of the RBE as a function of tissue type, linear energy transfer (LET) and dose. The phenomenological RBE models available in literature are based on the dose-averaged LET (LET
) as an indicator of the physical properties of the proton radiation field. The LET
values are typically calculated taking into account primary and secondary protons, neglecting the biological effect of heavier secondaries. In this work, we have introduced a phenomenological RBE approach which considers the biological effect of primary protons, and of secondary protons, deuterons, tritons (Z = 1) and He fragments (
He and
He, Z = 2). The calculation framework, coupled with a Monte Carlo (MC) code, has been successfully benchmarked against clonogenic in vitro data measured in this work for two cell lines and then applied to determine biological quantities for spread-out Bragg peaks and a prostate and a head case. The introduced RBE formalism, which depends on the mixed radiation field, the dose and the ratio of the linear-quadratic model parameters for the reference radiation Formula: see text, predicts, when integrated in an MC code, higher RBE values in comparison to LET
-based parameterizations. This effect is particular enhanced in the entrance channel of the proton field and for low Formula: see text tissues. For the prostate and the head case, we found higher RBE-weighted dose values up to about 5% in the entrance channel when including or neglecting the Z = 2 secondaries in the RBE calculation. TPSs able to proper account for the mixed radiation field in proton therapy are thus recommended for an accurate determination of the RBE in the whole treatment field.
•Optimal RT outcomes requires accurate robust predictive radiation oncology models.•Present challenges in model and data quality must be addressed to improve RO models.•Mechanistic understanding of ...radiobiological concepts can inform RO models.•Integrating novel computational and modeling methods will advance model development.•Interdisciplinary RO model development leverages the expertise of all stakeholders.
Radiotherapy developed empirically through experience balancing tumour control and normal tissue toxicities. Early simple mathematical models formalized this practical knowledge and enabled effective cancer treatment to date. Remarkable advances in technology, computing, and experimental biology now create opportunities to incorporate this knowledge into enhanced computational models.
The ESTRO DREAM (Dose Response, Experiment, Analysis, Modelling) workshop brought together experts across disciplines to pursue the vision of personalized radiotherapy for optimal outcomes through advanced modelling. The ultimate vision is leveraging quantitative models dynamically during therapy to ultimately achieve truly adaptive and biologically guided radiotherapy at the population as well as individual patient-based levels. This requires the generation of models that inform response-based adaptations, individually optimized delivery and enable biological monitoring to provide decision support to clinicians. The goal is expanding to models that can drive the realization of personalized therapy for optimal outcomes.
This position paper provides their propositions that describe how innovations in biology, physics, mathematics, and data science including AI could inform models and improve predictions. It consolidates the DREAM team’s consensus on scientific priorities and organizational requirements. Scientifically, it stresses the need for rigorous, multifaceted model development, comprehensive validation and clinical applicability and significance. Organizationally, it reinforces the prerequisites of interdisciplinary research and collaboration between physicians, medical physicists, radiobiologists, and computational scientists throughout model development. Solely by a shared understanding of clinical needs, biological mechanisms, and computational methods, more informed models can be created. Future research environment and support must facilitate this integrative method of operation across multiple disciplines.
The FLASH effect is characterized by normal tissue sparing without compromising tumor control. Although demonstrated in various preclinical models, safe translation of FLASH-radiotherapy stands to ...benefit from larger vertebrate animal models. Based on prior results, we designed a randomized phase III trial to investigate the FLASH effect in cat patients with spontaneous tumors. In parallel, the sparing capacity of FLASH-radiotherapy was studied on mini pigs by using large field irradiation.
Cats with T1-T2, N0 carcinomas of the nasal planum were randomly assigned to two arms of electron irradiation: arm 1 was the standard of care (SoC) and used 10 × 4.8 Gy (90% isodose); arm 2 used 1 × 30 Gy (90% isodose) FLASH. Mini pigs were irradiated using applicators of increasing size and a single surface dose of 31 Gy FLASH.
In cats, acute side effects were mild and similar in both arms. The trial was prematurely interrupted due to maxillary bone necrosis, which occurred 9 to 15 months after radiotherapy in 3 of 7 cats treated with FLASH-radiotherapy (43%), as compared with 0 of 9 cats treated with SoC. All cats were tumor-free at 1 year in both arms, with one cat progressing later in each arm. In pigs, no acute toxicity was recorded, but severe late skin necrosis occurred in a volume-dependent manner (7-9 months), which later resolved.
The reported outcomes point to the caveats of translating single-high-dose FLASH-radiotherapy and emphasizes the need for caution and further investigations. See related commentary by Maity and Koumenis, p. 3636.
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