Modelling the HPRT-gene mutation induction of particle beams: systematicin vitrodata collection, analysis and microdosimetric kinetic model implementation.

Objective. Since the early years, particle therapy treatments have been associated with concerns for late toxicities, especially secondary cancer risk (SCR). Nowadays, this concern is related to patients for whom long-term survival is expected (e.g. breast cancer, lymphoma, paediatrics). In the aim to contribute to this research, we present a dedicated statistical and modelling analysis aiming at improving our understanding of the RBE for mutation induction (RBEM˜) for different particle species.Approach. We built a new database based on a systematic collection of RBE data for mutation assays of the gene encoding for the purine salvage enzyme hypoxanthine-guanine phosphoribosyltransferase from literature (105 entries, distributed among 3 cell lines and 16 particle species). The data were employed to perform statistical and modelling analysis. For the latter, we adapted the microdosimetric kinetic model (MKM) to describe the mutagenesis in analogy to lethal lesion induction.Main results. Correlation analysis between RBE for survival (RBES) andRBEM˜reveals significant correlation between these two quantities (ρ= 0.86,p< 0.05). The correlation gets stronger when looking at subsets of data based on cell line and particle species. We also show that the MKM can be successfully employed to describeRBEM˜,obtaining comparably good agreement with the experimental data. Remarkably, to improve the agreement with experimental data the MKM requires, consistently in all the analysed cases, a reduced domain size for the description of mutation induction compared to that adopted for survival.Significance. We were able to show that RBESandRBEM˜are strongly related quantities. We also showed for the first time that the MKM could be successfully applied to the description of mutation induction, representing an endpoint different from the more traditional cell killing. In analogy to the RBES,RBEM˜can be implemented into treatment planning system evaluations.

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

Clinical routine in proton therapy currently neglects the radiobiological impact of nuclear target fragments generated by proton beams. This is partially due to the difficult characterization of the irradiation field. The detection of low energetic fragments, secondary protons and fragments, is in fact challenging due to their very short range. However, considering their low residual energy and therefore high LET, the possible contribution of such heavy particles to the overall biological effect could be not negligible. In this context, we performed a systematic analysis aimed at an explicit assessment of the RBE (relative biological effectiveness, i.e., the ratio of photon to proton physical dose needed to achieve the same biological effect) contribution of target fragments in the biological dose calculations of proton fields. The TOPAS Monte Carlo code has been used to characterize the radiation field, i.e., for the scoring of primary protons and fragments in an exemplary water target. TRiP98, in combination with LEM IV RBE tables, was then employed to evaluate the RBE with a mixed field approach accounting for fragments' contributions. The results were compared with that obtained by considering only primary protons for the pristine beam and spread out Bragg peak (SOBP) irradiations, in order to estimate the relative weight of target fragments to the overall RBE. A sensitivity analysis of the secondary particles production cross-sections to the biological dose has been also carried out in this study. Finally, our modeling approach was applied to the analysis of a selection of cell survival and RBE data extracted from published in vitro studies. Our results indicate that, for high energy proton beams, the main contribution to the biological effect due to the secondary particles can be attributed to secondary protons, while the contribution of heavier fragments is mainly due to helium. The impact of target fragments on the biological dose is maximized in the entrance channels and for small α/ß values. When applied to the description of survival data, model predictions including all fragments allowed better agreement to experimental data at high energies, while a minor effect was observed in the peak region. An improved description was also obtained when including the fragments' contribution to describe RBE data. Overall, this analysis indicates that a minor contribution can be expected to the overall RBE resulting from target fragments. However, considering the fragmentation effects can improve the agreement with experimental data for high energy proton beams.

Accuracy assessment of the CNAO dose delivery system in the initial period of clinical activity and impact of later improvements on delivered dose distributions.

PURPOSE: A retrospective analysis of the dose delivery system (DDS) performances of the initial clinical operation at CNAO (Centro Nazionale di Adroterapia Oncologica) is reported, and compared with the dose delivery accuracy following the implementation of a position feedback control. METHODS: Log files and raw data of the DDS were analyzed for every field of patients treated with protons and carbon ions between January 2012 and April 2013 (~3800 fields). To investigate the DDS accuracy, the spot positions and the number of particles per spot measured by the DDS and prescribed by the treatment planning system were compared for each field. The impact of deviations on dose distributions was studied by comparing, through the gamma-index method, 2 three-dimensional (3D) physical dose maps (one for prescribed, one for measured data), generated by a validated dose computation software. The maximum gamma and the percentage of points with gamma ≤ 1 (passing volume) were studied as a function of the treatment day, and correlated with the deviations from the prescription in the measured number of particles and spot positions. Finally, delivered dose distributions of same treatment plans were compared before and after the implementation of a feedback algorithm for the correction of small position deviations, to study the effect on the delivery quality. A double comparison of prescribed and measured 3D maps, before and after feedback implementation, is reported and studied for a representative treatment delivered in 2012, redelivered on a polymethyl methacrylate (PMMA) block in 2018. RESULTS: Systematic deviations of spot positions, mainly due to beam lateral offsets, were always found within 1.5 mm, with the exception of the initial clinical period. The number of particles was very stable, as possible deviations are exclusively related to the quantization error in the conversion from monitor counts to particles. For the chosen representative patient treatment, the gamma-index evaluation of prescribed and measured dose maps, before and after feedback implementation, showed a higher variability of maximum gamma for the 2012 irradiation, with respect to the reirradiation of 2018. However, the 2012 passing volume is >99.8% for the sum of all fields, which is comparable to the value of 2018, with the exception of one day with 98.2% passing volume, probably related to an instability of the accelerating system. CONCLUSIONS: A detailed retrospective analysis of the DDS performances in the initial period of CNAO clinical activity is reported. The spot position deviations are referable to beam lateral offset fluctuations, while almost no deviation was found in the number of particles. The impact of deviations on dose distributions showed that the position feedback implementation and the increased beam control capability acquired after the first years of clinical experience led to an evident improvement in the DDS stability, evaluated in terms of gamma-index as a measure of the impact on dose distributions. However, the clinical effect of the maximum gamma variability found in the 2012 representative irradiation is mitigated by averaging along the number of fractions, and the high percentage of passing volumes confirmed the accuracy of the delivery even before the feedback implementation.

Targeted dose enhancement in radiotherapy for breast cancer using gold nanoparticles, part 1: A radiobiological model study.

PURPOSE: Gold nanoparticles (GNPs) are being proposed in combination with radiotherapy to improve tumor control. However, the exact mechanisms underlying GNP radiosensitization are yet to be understood, thus, we present a new approach to estimate the nanoparticle-driven increase in radiosensitivity. METHODS: A stochastic radiobiological model, derived from the Local Effect Model (LEM), was coupled with Monte Carlo simulations to estimate the increase in radiosensitivity produced by the interactions between photons and GNPs at nanometric scale. The model was validated using in vitro survival data of MDA-MB-231 breast cancer cells containing different concentrations of 2 nm diameter GNPs receiving different doses using 160 kVp, 6 MV, and 15 MV photons. A closed analytical formulation of the model was also derived and a study of RBE and TCP behavior was conducted. RESULTS: Results support the increased radiosensitivity due to GNP-driven dose inhomogeneities on a nanometric scale. The model is in good agreement with experimental clonogenic survival assays for 160 kVp, 6 MV, and 15 MV photons. The model suggests a RBE and TCP enhancement when lower energies and lower doses per fraction are used in the presence of GNPs. CONCLUSIONS: The evolution of the local effect model was implemented to assess cellular radiosensitization in the presence of GNPs and then validated with in vitro data. The model provides a useful framework to estimate the nanoparticle-driven radiosensitivity in treatment irradiations and could be applied to real clinical treatment predictions (described in a second part of this paper).

Targeted dose enhancement in radiotherapy for breast cancer using gold nanoparticles, part 2: A treatment planning study.

PURPOSE: In recent years, there has been growing interest in the use of gold nanoparticles (GNPs) combined with radiotherapy to improve tumor control. However, the complex interplay between GNP uptake and dose distribution in realistic clinical treatment are still somewhat unknown. METHODS: The effects of different concentrations of 2 nm diameter GNP, ranging from 0 to 5×105 nanoparticles per tumoral cell, were theoretically investigated. A parametrization of the GNP distribution outside the target was carried out using a Gaussian standard deviation σ, from a zero value, relative to a selective concentration of GNPs inside the tumor volume alone, to 50mm, when GNPs are spatially distributed also in the healthy tissues surrounding the tumor. Treatment simulations of five patients with breast cancer were performed with 6 and 15 MV photons assuming a partial breast irradiation. A closed analytical reformulation of the Local Effect Model coupled with the estimation of local dose deposited around a GNP was validated using an in vitro study for MDA-MB-231 tumoral cells. The expected treatment outcome was quantified in terms of tumor control probability (TCP) and normal tissue complication probability (NTCP) as a function of the spatially varying gold uptake. RESULTS: Breast cancer treatment planning simulations show improved treatment outcomes when GNPs are selectively concentrated in the tumor volume (i.e., σ = 0 mm). In particular, the TCP increases up to 18% for 5×105 nanoparticles per cell in the tumor region depending on the treatment schedules, whereas an improvement of the therapeutic index is observed only for concentrations of about 105 GNPs per tumoral cell and limited spatial distribution in the normal tissue. CONCLUSIONS: The model provides a useful framework to estimate the nanoparticle-driven radiosensitivity in breast cancer treatment irradiation, accounting for the complex interplay between dose and GNP uptake distributions.

A Monte Carlo approach to the microdosimetric kinetic model to account for dose rate time structure effects in ion beam therapy with application in treatment planning simulations.

PURPOSE: Advanced ion beam therapeutic techniques, such as hypofractionation, respiratory gating, or laser-based pulsed beams, have dose rate time structures which are substantially different from those found in conventional approaches. The biological impact of the time structure is mediated through the ß parameter in the linear quadratic (LQ) model. The aim of this study was to assess the impact of changes in the value of the ß parameter on the treatment outcomes, also accounting for noninstantaneous intrafraction dose delivery or fractionation and comparing the effects of using different primary ions. METHODS: An original formulation of the microdosimetric kinetic model (MKM) is used (named MCt-MKM), in which a Monte Carlo (MC) approach was introduced to account for the stochastic spatio-temporal correlations characteristic of the irradiations and the cellular repair kinetics. A modified version of the kinetic equations, validated on experimental cell survival in vitro data, was also introduced. The model, trained on the HSG cells, was used to evaluate the relative biological effectiveness (RBE) for treatments with acute and protracted fractions. Exemplary cases of prostate cancer irradiated with different ion beams were evaluated to assess the impact of the temporal effects. RESULTS: The LQ parameters for a range of cell lines (V79, HSG, and T1) and ion species (H, He, C, and Ne) were evaluated and compared with the experimental data available in the literature, with good results. Notably, in contrast to the original MKM formulation, the MCt-MKM explicitly predicts an ion and LET-dependent ß compatible with observations. The data from a split-dose experiment were used to experimentally determine the value of the parameter related to the cellular repair kinetics. Concerning the clinical case considered, an RBE decrease was observed, depending on the dose, ion, and LET, exceeding up to 3% of the acute value in the case of a protraction in the delivery of 10 min. The intercomparison between different ions shows that the clinical optimality is strongly dependent on a complex interplay between the different physical and biological quantities considered. CONCLUSIONS: The present study provides a framework for exploiting the temporal effects of dose delivery. The results show the possibility of optimizing the treatment outcomes accounting for the correlation between the specific dose rate time structure and the spatial characteristic of the LET distribution, depending on the ion type used.

INSIDE in-beam positron emission tomography system for particle range monitoring in hadrontherapy.

The quality assurance of particle therapy treatment is a fundamental issue that can be addressed by developing reliable monitoring techniques and indicators of the treatment plan correctness. Among the available imaging techniques, positron emission tomography (PET) has long been investigated and then clinically applied to proton and carbon beams. In 2013, the Innovative Solutions for Dosimetry in Hadrontherapy (INSIDE) collaboration proposed an innovative bimodal imaging concept that combines an in-beam PET scanner with a tracking system for charged particle imaging. This paper presents the general architecture of the INSIDE project but focuses on the in-beam PET scanner that has been designed to reconstruct the particles range with millimetric resolution within a fraction of the dose delivered in a treatment of head and neck tumors. The in-beam PET scanner has been recently installed at the Italian National Center of Oncologic Hadrontherapy (CNAO) in Pavia, Italy, and the commissioning phase has just started. The results of the first beam test with clinical proton beams on phantoms clearly show the capability of the in-beam PET to operate during the irradiation delivery and to reconstruct on-line the beam-induced activity map. The accuracy in the activity distal fall-off determination is millimetric for therapeutic doses.

Quantitative analysis of basal and interim PET/CT images for predicting tumor recurrence in patients with Hodgkin's lymphoma.

OBJECTIVES: The qualitative analysis of interim PET has been reported to be useful for predicting the outcome of Hodgkin's lymphoma (HL) after chemotherapy. As the next step, our study aims to present a quantitative analysis on the basis of both a basal (PET/CT0) and an interim (PET/CT2) scan to improve the prognostic value of imaging in HL patients. PATIENTS AND METHODS: A cohort of 68 patients undergoing a basal and an interim scan with F-fluorodeoxyglucose after two cycles of chemotherapy consisting of adriamycin, bleomycin, vinblastine, and dacarbazine were examined. Two subsets of patients with a positive and a negative interim scan were selected. RESULTS: In patients with a negative scan, a total of 108 lymph node lesions showing a good response to chemotherapy were contoured, whereas in the remaining patients with positive scans, six responder and 12 relapsing lymph node lesions were contoured. Standardized uptake value (SUV) and Hounsfield unit (HU) values were included in the volumes contoured on coregistered basal and interim scans and included in a database. A linear regression model was used to identify the predictor of relapse at the lesion level. The support vector machine analysis and bootstrap approach were used to determine the model capability. The predictive models were presented as nomograms on the basis of basal or both basal and interim studies. SUV at the basal/interim study and basal HU values were predictors of a poor prognosis. In particular, the higher points were associated with lower values of SUV and HU at baseline and the higher values of SUV at the interim study. Using the bootstrap and support vector machine approach, the cut-off of the model increased up to 89%. CONCLUSION: The novel tool enables estimation of the risk of tumor relapse after chemotherapy in HL patients on the basis of basal and interim PET/CT scans including SUV and densitometric information.

Extension of TOPAS for the simulation of proton radiation effects considering molecular and cellular endpoints.

The aim of this work is to extend a widely used proton Monte Carlo tool, TOPAS, towards the modeling of relative biological effect (RBE) distributions in experimental arrangements as well as patients. TOPAS provides a software core which users configure by writing parameter files to, for instance, define application specific geometries and scoring conditions. Expert users may further extend TOPAS scoring capabilities by plugging in their own additional C++ code. This structure was utilized for the implementation of eight biophysical models suited to calculate proton RBE. As far as physics parameters are concerned, four of these models are based on the proton linear energy transfer, while the others are based on DNA double strand break induction and the frequency-mean specific energy, lineal energy, or delta electron generated track structure. The biological input parameters for all models are typically inferred from fits of the models to radiobiological experiments. The model structures have been implemented in a coherent way within the TOPAS architecture. Their performance was validated against measured experimental data on proton RBE in a spread-out Bragg peak using V79 Chinese Hamster cells. This work is an important step in bringing biologically optimized treatment planning for proton therapy closer to the clinical practice as it will allow researchers to refine and compare pre-defined as well as user-defined models.

A novel chimera: the "truncated hemoglobin-antibiotic monooxygenase" from Streptomyces avermitilis.

Novel chimeric proteins made of a globin domain fused with a "cofactor free" monooxygenase domain have been identified within the Streptomyces avermitilis and Frankia sp. genomes by means of bioinformatics methods. Structure based sequence alignments show that the globin domains of both proteins can be unambiguously assigned to the truncated hemoglobin family, in view of the striking similarity to the truncated hemoglobins from Mycobacterium tuberculosis, Thermobifida fusca and Bacillus subtilis. In turn, the non-heme domains belong to a family of small (about 100 aminoacids) homodimeric proteins annotated as antibiotic biosynthesis monooxygenases, despite the lack of a cofactor (e.g., a metal, a flavin or a heme) necessary for oxygen activation. The chimeric protein from S. avermitilis has been cloned, expressed and characterized. The protein is a stable dimer in solution based on analytical ultracentrifugation experiments. The heme ligand binding properties with oxygen and carbonmonoxide resemble those of other Group II truncated hemoglobins. In addition, an oxygen dependent redox activity has been demonstrated towards easily oxidizable substrates such as menadiol and p-aminophenol. These findings suggest novel functional roles of truncated hemoglobins, which might represent a vast class of multipurpose oxygen activating/scavenging proteins whose catalytic action is mediated by the interaction with cofactor free monooxygenases.