Marco Pinto

Objective. Prompt gamma (PG) detection enables beam range verification and margin reduction in proton therapy, but its effectiveness is limited by counting statistics. Spot boosting has been proposed to enhance the signal-to-noise ratio by increasing the number of protons in selected spots of a pencil beam scanning treatment plan. This work integrates PG monitoring into an multi-criteria optimization (MCO) framework to investigate trade-offs between proton counts in boosted spots and dosimetric metrics. Approach. Intensity modulated proton therapy plans for a prostate-tumor and a brain-tumor patient were optimized in OpenTPS. Dose, LET weighted dose (LETxdose) and PG distributions were simulated for each pencil beam using the fast Monte Carlo (MC) engine MCSquare. For each field, ten candidate spots were selected based on three metrics quantifying the quality of PG monitoring and an even spatial distribution across the clinical target volume. Initial pencil beam weights and corresponding dose and LETxdose distributions were imported into an MCO framework for re-optimization, simultaneously considering both dosimetric goals and boosting objectives. Main results. Boosting up to 5 ⋅ 10 8 protons/spot maintained the plan quality without violating constraints in the prostate case. In the brain case, spot boosting required moderate deviations from the initial target dose constraints. For both cases, only minor boosting gains were obtained by relaxing dose metrics for organs at risk. Significance. This study is the first to visualize spot boosting trade-offs via Pareto fronts to support an informed decision, integrating verification quality aspects into the treatment planning stage. The approach enables selection of plans that preserve dose and LETxdose objectives while enhancing PG signal in targeted spots for reliable in-vivo range verification. The framework is broadly applicable and can provide a strategy for embedding verification-driven objectives into treatment optimization beyond PG monitoring.

Objective. As carbon ion therapy is highly sensitive to range uncertainties, it can benefit greatly from range verification. Positron emission tomography (PET) provides a valuable approach, in which predicted positron emitter distributions (PED) can be used to calculate the expected activity distribution, which is then compared with the irradiation-induced PET signal. In a previous work, we developed an analytical approach to predict 3D positron emitter distributions from dose distributions, providing a faster alternative to Monte Carlo (MC) simulations at a comparable accuracy, and with potential for integration into analytical treatment planning systems (TPS). The purpose of this work is to validate this analytical approach using real clinical cases where offline PET/Computed tomography (CT) monitoring was employed. Approach. Four carbon ion therapy patients treated at the Heidelberg Ion Beam Therapy Center (HIT) were selected, and their treatment plans and CT images were used for MC simulations and analytical prediction of β +activity distributions. The analytically predicted activity distributions, derived from the simulated dose with our analytical approach, were then compared with both simulated results and measured offline PET data. M ain results. The analytical and MC activity distributions demonstrated a good match in range with mean deviations less than 0.5 mm, and in amplitude with mean normalized rootmean-square error (NRMSE) less than 2%. Range shifts between the measured PET signals and the analytical activity patterns were evaluated and found to be consistent with published results. Signif icance. The obtained results demonstrate the capability of our analytical approach to predict PET images for range verification in carbon ion therapy under real clinical scenarios, offering faster predictions than MC simulations while maintaining comparable accuracy. The solution proposed also offers the possibility of a straightforward integration into TPS by leveraging the commonly used pencil beam algorithms (PBAs) present in analytical carbon ion dose engines.

Modélisation et simulation des processus physiques pour l’imagerie en ligne de l’hadronthérapie: L'hadronthérapie joue un rôle de plus en plus important au sein des techniques de radiothérapie grâce aux propriétés balistiques des ions et, dans le cas de ceux plus lourds que les protons, à une augmentation de l'efficacité biologique dans la région tumorale. Ces caractéristiques permettent une meilleure conformation de la dose délivrée au volume tumoral et elles permettent en particulier de traiter des tumeurs radio-résistantes. Elles conduisent cependant à une grande sensibilité du parcours des ions aux incertitudes du traitement. C'est dans ce contexte qu'a été proposée la détection de radiations secondaires émises lors des interactions nucléaires induites par les ions incidents dans le patient. La tomographie par émission de positons et la détection des rayons gamma prompts ont notamment fait l'objet d'une recherche intense ces dernières années. Le réseau de formation européen ENTERVISION, soutenu par la communauté ENLIGHT, a été crée fin 2009 pour développer ce type d'imagerie et, plus généralement, traiter les incertitudes de traitement en hadronthérapie. Le travail présenté dans ce manuscrit et intitulé ≪ Modélisation et simulation des processus physiques pour l'imagerie en ligne de l'hadronthérapie ≫ est l'un des nombreux travaux issus de ce projet. Bien que le sujet soit particulièrement large, le fil conducteur de ce travail a été une étude systématique visant in fine une implémentation d'un dispositif d'imagerie ≪ gamma prompts ≫ utilisable à la fois en faisceau de protons et d'ions carbone

Objective. Range and dose monitoring with secondary radiation can help minimizing the issues of range uncertainties in proton cancer therapy. Prompt gammas (PGs) have been widely investigated as a promising secondary radiation for in vivo verification. Since it can be argued that for a proper delivery of the intended treatment the most desirable quantity to assess is the dose distribution in vivo , this work aims at the reconstruction of the delivered proton dose from distributions of PG radiation. Approach. Some techniques have already been proposed in the literature to reconstruct the dose from a distribution of detected secondary radiation, mostly positron emitters. Among them, very promising methods are the analytical deconvolution approach, the evolutionary algorithm and the maximum-likelihood expectation-maximization (MLEM) algorithm. Herein, the feasibility of the application of these approaches to PG distributions at emission stage is assessed with simulated mono- and polyenergetic proton beams, irradiating homogeneous and inhomogeneous phantoms, and a realistic case of a head and neck (H&N) tumor patient. Main results. The accuracy of the reconstructed dose is evaluated via comparison with the corresponding simulated ground truth dose distributions using different metrics. For the case of 1D reconstruction on phantoms, the Δ R 80 , Δ R 50 and Δ R 10 , with Δ R % being the difference of the positions at the % of the dose maximum in the distal fall-off region between the simulated and reconstructed curves, are always less or of the order of 1 mm in absolute value. For 3D reconstruction on phantoms and on the H&N case, the γ (1%/1 mm) passing rate is always above or equal to 97%. Significance. This study demonstrates the applicability of the analytical deconvolution, the evolutionary and the MLEM algorithms to dose reconstruction from PG emissions, providing a step forward toward the final goal of real-time verification of the dose delivery for real-time adaptive particle therapy.

Background and purpose: Successful clinical integration of pMBRT requires comprehensive investigations of the relationship between various pMBRT parameters and their associated biological effects. Such investigations are critically dependent on small animal models. Therefore, a state-of-the-art small animal irradiation platform like SIRMIO (Small Animal Proton Irradiator for Research in Molecular Image-guided Radiation-Oncology), capable of delivering precisely controlled spatially fractionated doses, is highly desirable for advancing preclinical pMBRT research. Material and methods: This in silico study evaluates the SIRMIO beamline’s capability to deliver beams essential for pMBRT experiments. We used Geant4-based Monte Carlo simulations to investigate two configurations: one without a collimator, and one using a 30 mm thick brass multislit collimator (MSC). For both configurations, we examined center-to-center (CTC) of 3, 4, and 5 mm, with a constant 1 mm slit width when MSC is used. Results: The SIRMIO beamline can effectively generate spatially fractionated dose profiles with varying CTC. Without a collimator, sufficient dose contrast for pMBRT can be achieved with CTC of 4 mm and above, as evidenced by peak-to-valley dose ratios (PVDR) of 3.44 and 6.57 for 4 and 5 mm CTC, respectively. MSC further enhances dose contrast, achieving PVDR of 11.3, 20.7, and 28.7 for 3, 4, and 5 mm CTC, respectively. Furthermore, we explored interlacing beams as a means of achieving a uniform target dose while preserving dose contrast in normal tissue, demonstrating the potential of this approach using the SIRMIO beamline. Interpretation: The SIRMIO platform can be a viable option for pMBRT experiments.

Objective. This work aims to evaluate the ability of novel detector components to measure with submillimeter resolution in beam positron emission tomography (PET) signals produced by ¹⁰C and ¹¹C radioactive ion beams stopped in PMMA targets and to validate a simulation toolkit for reproducing beam physics and PET detector responses within the framework of the biomedical applications of radioactive ion beam (BARB) project. Approach. The PET system response was assessed by visualizing the radioactive distributions of the beams stopped in tissue surrogate phantoms, and the capacity of the simulation toolkit was evaluated by comparing the experimental results with simulations, both for the depth-dose distribution and PET imaging. Main results. The detector assembly accurately visualized the PET signal with submillimeter resolution, achieving the objective of measuring the difference in the positron range between ¹⁰C and ¹¹C. The simulation toolkit effectively reproduced the beam characteristics and detector responses, showing a high degree of agreement between the simulated and experimental PET profiles under different beam delivery conditions. Significance. These findings demonstrate the precision and reliability of the novel in-beam PET detector technology and simulation toolkit for small animals, establishing a solid foundation for the second phase of the BARB project, which involves preclinical irradiation of living mice.

Objective. Carbon ion therapy could benefit from range verification due to its sensitivity to range uncertainties. Positron emission tomography (PET) aids in this and comparing PET signals to a predicted positron emitter distribution (PED) is one viable approach. Monte Carlo (MC) simulations are one way to predict PED but are computationally intensive and time-consuming. To address this, an analytical approach was previously suggested to predict 1D PED from depth dose profiles. Here we aim to develop a computational framework for 3D PED prediction in carbon ion therapy, building on the 1D approach to provide a faster method than MC simulations, with potential for integration into treatment planning systems (TPS). Approach. The 1D approach was revised by considering more PEs channels and introducing new modeling functions. A mapping process for handling longitudinal heterogeneity effects in projectile PED was developed. Then, a dedicated framework for 3D PED generation based on a pencil beam algorithm (PBA) and the updated 1D method was proposed. Validation was performed through in-silico studies against MC calculations for several phantoms as well as realistic computed tomography scans from patient data. Main results. For range assessment, the differences between distal fall-off positions of predicted and simulated 1D PED profiles were calculated to be below 0.8 mm for all validation cases. The comparison of predicted 3D PED with simulated results was performed by global gamma index analysis using the 2%/2 mm and 1%/1 mm criteria. For patient cases, the passing rates for 1%/1 mm criteria were above 95%. Significance. These results demonstrated the capability of our approach to predict 3D PED with good accuracy in terms of range and magnitude, paving the way to future implementation in a TPS, which commonly relies on PBA for ¹²C ions. Moreover, a significant speed-up compared to MC simulations was achieved, with future speed-optimized implementations.

Objectives. Preclinical small animal proton beam irradiation systems are increasingly in demand. However, the absence of dedicated systems comparable in precision to those in clinical settings presents a considerable hurdle to investigations in this field. To address this need, the SIRMIO project has developed a novel compact beam transport system configured to degrade and focus clinical proton beams. The beamline, about 1 m long, housed in an environment to minimize scatter, includes degraders, collimators, and a permanent magnet quadrupole triplet to focus protons degraded from clinical energies. It is tailored to transport focused proton beams within the energy range of 20 to 50 MeV, ideal for small animal preclinical studies. The flexibility of this beamline design allows achieving beam-spot sizes of 1 mm sigma at the isocenter for all focused energies, with the particle fluence and spot sizes being variable through dynamic adjustment of the collimator and magnetic lattice. 3D scanning of the target volume is possible due to lateral beam scanning integrated into this design, without the use of additional scanning dipole magnets. Approach. The beamline was optimized using an accelerator beam optics code, followed by a Monte Carlo (MC) model to account for beam-matter interactions. Using an experimentally validated clinical proton beam phase space as input, degraded beams are transported through the MC model. Outcomes are assessed for beam characteristics and dosimetric properties. Main results. Beams transported by our proposed beamline design are shown to result in dosimetric properties suitable for preclinical studies, while also emulating realistic clinically relevant beam delivery scenarios like pencil beam scanning. Compared to a similar-sized collimator-only beamline, this design enhances transmission and reduces secondary dose at the target due to absence of scattering elements nearby. Significance. The portable SIRMIO beamline offers a flexible, precise alternative to passive methods for adapting clinical proton beams for small animal irradiation, enhancing preclinical research with clinically relevant beam delivery and enabling experiments in conditions more closely matching clinical practice.

Objective. Secondary electron bremsstrahlung (SEB) imaging, along with prompt gamma (PG) and positron emission tomography (PET) imaging, has been proposed as an in vivo range verification tool for proton therapy. This study presents the first simulation based on patient computed tomography (CT) data to investigate the feasibility of SEB imaging for range verification in proton therapy, while comparing the characteristics of SEB imaging with those of PG and PET imaging. Approach. A Monte Carlo simulation was performed using patient CT data for the irradiation of monoenergetic pencil beams and spread-out Bragg peak proton beams. The physical characteristics of SEB imaging were analyzed at three different anatomical sites and compared with those of PG and PET imaging. Main results. In all the treatment cases, SEB imaging exhibited higher production rates than PG and PET imaging, particularly in the regions with high CT values along the beam path. Although the SEB signal was more affected by scattering and absorption than the PET or PG signals, sufficient statistical counts for range verification (∼3 × 10^–3 SEBs/proton) could potentially be detected outside the patient geometry. For pencil beam cases, the SEB and PET fall-offs were located 4–5 mm proximal to the dose fall-off, while the PG fall-off was located 0–1 mm distal to it. Significance. Results suggest that SEB imaging has the potential to offer a real-time range verification tool (by comparing measured and expected images), particularly for treating shallow-seated tumors using proton pencil-beam scanning delivery. Thus, this study represents a significant step towards the clinical application of range verification based on SEB imaging and promotes future efforts in this direction.