In photon external beam radiotherapy, out-of-field doses resulting from photon scattering and leakage are unavoidable and may contribute to radiation-induced side effects. However, modern treatment planning systems are not commissioned to accurately estimate doses outside the treatment field. This underscores the need for dedicated experimental protocols for accurate measurements. Radiophotoluminescent glass dosimeters (RPLGDs) are well suited for this task due to their low detection threshold. Yet, because they are energy-dependent, beam quality calibration is required. The purpose was to experimentally measure effective energies of photons outside the treatment field and to define beam quality correction factors for the GD-302M and GD-352M RPLGDs to be used in out-of-field dosimetry. A solid phantom was assembled using water-equivalent plates. GD-302M and GD-352M RPLGDs were positioned at various distances from the beam central axis (0, 10, 20, 30, and 40 cm), at different depths (1, 10, and 15 cm), and measurements were performed for multiple field sizes (5, 10, and 15 cm). The experiment was repeated using a PTW30010 ionization chamber. Different beam qualities were tested, including 6 and 18 MV photon beams from an Elekta VERSA HD and 6 and 20 MV photon beams from a Varian Clinac 2300 CD. The low-energy filter in the RPL GD-352M modifies the signal relative to the unfiltered GD-302M. We exploit this differential to estimate out-of-field effective energy, using a calibration curve derived from literature data based on the GD-302M/GD-352M signal ratio. Across all beam qualities and configurations tested, effective energies ranged from 180 keV (±15 keV) to 1302 keV (±106 keV). Effective energy decreased as the distance from the axis increased, with an upward trend beyond 30 cm from the beam axis. Beam quality correction factors for GD-302M RPLGDs varied between 0.745 (±0.002) and 1.284 (±0.027), while for GD-352M they ranged from 0.568 (±0.004) to 1.649 (±0.123). Feature analysis showed that, for the beam quality correction factors, off-axis distance and depth were the most important variables, with importance values of 39.3% (±2.7) and 35.0% (±1.8) for the GD-302M, and 29.0% (±0.8) and 47.5% (±1.8) for the GD-352M, respectively. For the effective energies, the importance of off-axis distance and depth variables was 28.1% (±0.6) and 22.6% (±1.3), respectively. In this work, we determined experimentally effective photon energies outside the treatment field. We developed a methodology to establish out-of-field distance-dependent beam quality correction factors for RPLGDs. The results demonstrate the need to take into account those correction factors to ensure accurate out-of-field dose measurements.

PURPOSE:This study evaluates EBT3, EBT-XD (Ashland) and OC-1 (OrthoChrome) films for reference dosimetry in electron beams, focusing on their use in ultra-high dose rate (UHDR) conditions. METHODS:Responses of the three film types were compared and the influence of calibration methodology and background correction method on accuracy were evaluated by irradiating the films at doses between 2.5-30 Gy in a 12 MeV electron beam with a conventional linac (CONV, 600 monitor units/mins). Measured doses were compared to a calibrated Advanced Markus ionization chamber (IC). Finally, films were irradiated alongside a flashDiamond (fD) at UHDR (mean dose rate 150 Gy/s) under various beam parameters (Pulse Width (PW): 0.5-4 µs, Pulse Repetition Frequency (PRF): 10-250 Hz) using the FLASHKNiFE system (THERYQ, Peynier, France). Films measurements were compared to those obtained with the fD. RESULTS:EBT3 films showed the least influence from their intrinsic properties and the scanning process. The background correction method did not improve measurement accuracy. A calibration curve generated on a different day from the irradiations provided accuracy comparable to simultaneous calibration and irradiation. Relative deviation with IC below 2.5 % at CONV dose rate was observed for the 3 film types. On average, doses measured with the 3 types of films and fD at UHDR were consistent within 5%, and showed independent responses to PW, PRF, and dose per pulse. CONCLUSION:EBT3, EBT-XD and OC-1 films have demonstrated suitability for absolute dosimetry of electron beams in UHDR conditions, with EBT3 and EBT-XD films emerging as the optimal choice.

Treatment protocols of cancer combining radiotherapy and nanoparticles are rapidly evolving. To evaluate their efficacy, spheroids provide a 3D in vitro model that better reflects tumor architecture than traditional 2D cell cultures. This article presents a workflow to prepare and characterize spheroids, optimize the protocols for irradiation with medical photon and ion beams and for exposure to nanoparticles, and, finally, to evaluate the effects of radiation, nanoparticles, and their combination on spheroids. Illustrations with HeLa, U-87 MG, and BxPC-3 tumor cell lines and HDFn are reported. Using this workflow, we observed that spheroids exhibit variable cell organization and interstitial spaces, which affect nutrient and oxygen diffusion and, consequently, cell proliferation. These structural differences also affect enzyme diffusion, limiting the applicability of the clonogenic assay in densely packed spheroids, as the assay requires enzymatic disaggregation of the spheroids. The clonogenic assay remains essential for quantitatively comparing spheroid irradiation results with 2D cell culture experiments. It has long been used as the reference method in radiobiology because it assesses mitotic death and long-term proliferative capacity. Protocols were adapted to ensure the feasibility of the clonogenic assay when possible, depending on cell line characteristics. Interstitial spaces also influenced nanoparticle internalization, which was more efficient in spheroids with larger interstitial spaces. This workflow and associated techniques verified the characteristic effect of carbon ion irradiation with a relative biological effectiveness of 3 and demonstrated a 30

OBJECTIVE:This study aimed to evaluate and validate the new FLASHKNiFE ultra-high dose rate (UHDR) radiotherapy system by commissioning and assessing the dosimetric performance of its electron UHDR beams to ensure accuracy and stability. MATERIAL AND METHODS:The FLASHKNiFE system is a mobile linear accelerator delivering UHDR electron beams (>40 Gy/s, 6 and 10 MeV) at various pulse repetition frequencies (10-250 Hz) and pulse widths (0.5-4 μs). Its dose monitoring system includes two independent current transformers for precise dose measurements. Performance tests were adapted from AAPM reports, IEC standards, and recent recommendations, focusing on repeatability, output stability, PDD curves, cross profiles, dose linearity, and the influence of UHDR parameters on dose distribution. Dose-independent detectors, such as radiochromic films and the FlashDiamond, ensured measurement accuracy. RESULTS:Long-term output reproducibility was better than 5 %, and energy stability was within 2.5 %. PDD curves remained consistent within 1 mm. Delivered dose was proportional to pulse number and PW within 2 %, except for the lowest settings. Cross profiles met IEC standards for flatness and symmetry. Maximum axis doses for a 10-cm applicator were 1.3 Gy/pulse (10 MeV) and 1.1 Gy/pulse (6 MeV) at PW = 2 μs, achieving dose rates over 275 Gy/s. Dosimeter results were consistent within uncertainties. CONCLUSION:The FLASHKNiFE system has been validated for preclinical studies, demonstrating robust, reproducible performance and providing a solid foundation for ongoing QA processes.

Purpose The OMET GORTEC 2014-04 trial showed prolonged survival with multisite Stereotactic Ablative Body Radiation therapy (SABR) in patients with oligometastatic head and neck cancer. However, deviations from radiation therapy protocol can be a confounding factor in clinical trials. The impact of SABR quality assurance by individual case review (ICR) of protocol deviations and quality metrics on survival and local control at SABR-treated oligometastases was assessed. Methods and Materials The SABR planning and delivery protocol was standardized based on the oligometastasis number/size/nearby critical structures (organs at risk [OARs]) across SABR techniques. ICR assessed oligometastatic topological complexity, indication, delineation (targets, OARs), image guidance, prescription, target coverage, and OAR doses. An exploratory analysis of quantitative dosimetric indices was also performed. Results Among 69 patients (98 metastases, unique 58.0%, lung-only 82.6%), there was no imbalance of deviations between the trial arms. Median follow-up was 55.3 months. Median overall survival was 61.7 months (IQR, 41.1-Not reached) in patients (N = 19) without deviation, 50.9 months (IQR, 32.1-Not reached) in patients (N = 36) with at least a minor deviation, and 20.9 months (IQR, 12.1-81.7) in those (N = 12) with at least a major deviation. Among patients with a major deviation, the conformity number (P < .001) and modified gradient index (P = .01) deviated more from their optimal values. Conclusions Deviations from protocol by ICR were evenly distributed between arms. Major deviations were mostly related to the cumulative size of the oligometastases and OAR proximity and were associated with poorer survival in this SABR trial.

PURPOSE:The dose deposited outside of the treatment field during external photon beam radiation therapy treatment, also known as out-of-field dose, is the subject of extensive study as it may be associated with a higher risk of developing a second cancer and could have deleterious effects on the immune system that compromise the efficiency of combined radio-immunotherapy treatments. Out-of-field dose estimation tools developed today in research, including Monte Carlo simulations and analytical methods, are not suited to the requirements of clinical implementation because of their lack of versatility and their cumbersome application. We propose a proof of concept based on deep learning for out-of-field dose map estimation that addresses these limitations. METHODS AND MATERIALS:For this purpose, a 3D U-Net, considering as inputs the in-field dose, as computed by the treatment planning system, and the patient's anatomy, was trained to predict out-of-field dose maps. The cohort used for learning and performance evaluation included 3151 pediatric patients from the FCCSS database, treated in 5 clinical centers, whose whole-body dose maps were previously estimated with an empirical analytical method. The test set, composed of 433 patients, was split into 5 subdata sets, each containing patients treated with devices unseen during the training phase. Root mean square deviation evaluated only on nonzero voxels located in the out-of-field areas was computed as performance metric. RESULTS:Root mean square deviations of 0.28 and 0.41 cGy/Gy were obtained for the training and validation data sets, respectively. Values of 0.27, 0.26, 0.28, 0.30, and 0.45 cGy/Gy were achieved for the 6 MV linear accelerator, 16 MV linear accelerator, Alcyon cobalt irradiator, Mobiletron cobalt irradiator, and betatron device test sets, respectively. CONCLUSIONS:This proof-of-concept approach using a convolutional neural network has demonstrated unprecedented generalizability for this task, although it remains limited, and brings us closer to an implementation compatible with clinical routine.

We introduce a novel unsupervised approach to recovering and registering a 3D volume from only two planar projections that exploits a previously-captured 3D volume of the patient. Such pre-capturing volume is readily available in many important medical procedures and previous methods already used such a volume. Earlier methods that work by deforming this volume to match the projections can fail when the number of projections is very low as the alignment becomes underconstrained. We show how to use a generative model of the volume structures to constrain the deformation and obtain a correct estimate. Moreover, our method is independant of the number, calibration and geometry of projections and could be adapted to new configurations without retraining. We evaluate our approach on a challenging dataset and show it outperforms state-of-the-art methods. As a result, our method could be used in treatment scenarios such as surgery and radiotherapy while drastically reducing patient radiation exposure.

Objective. Severe radiation-induced lymphopenia occurs in 40% of patients treated for primary brain tumors and is an independent risk factor of poor survival outcomes. We developed anin-silicoframework that estimates the radiation doses received by lymphocytes during volumetric modulated arc therapy brain irradiation.Approach. We implemented a simulation consisting of two interconnected compartmental models describing the slow recirculation of lymphocytes between lymphoid organs (M1) and the bloodstream (M2). We used dosimetry data from 33 patients treated with chemo-radiation for glioblastoma to compare three cases of the model, corresponding to different physical and biological scenarios: (H1) lymphocytes circulation only in the bloodstream i.e. circulation inM2only; (H2) lymphocytes recirculation between lymphoid organs i.e. circulation inM1andM2interconnected; (H3) lymphocytes recirculation between lymphoid organs and deep-learning computed out-of-field (OOF) dose to head and neck (H&N) lymphoid structures. A sensitivity analysis of the model's parameters was also performed.Main results. For H1, H2 and H3 cases respectively, the irradiated fraction of lymphocytes was 99.8 ± 0.7%, 40.4 ± 10.2% et 97.6 ± 2.5%, and the average dose to irradiated pool was 309.9 ± 74.7 mGy, 52.6 ± 21.1 mGy and 265.6 ± 48.5 mGy. The recirculation process considered in the H2 case implied that irradiated lymphocytes were irradiated in the field only 1.58 ± 0.91 times on average after treatment. The OOF irradiation of H&N lymphoid structures considered in H3 was an important contribution to lymphocytes dose. In all cases, the estimated doses are low compared with lymphocytes radiosensitivity, and other mechanisms could explain high prevalence of RIL in patients with brain tumors.Significance. Our framework is the first to take into account OOF doses and recirculation in lymphocyte dose assessment during brain irradiation. Our results demonstrate the need to clarify the indirect effects of irradiation on lymphopenia, in order to potentiate the combination of radio-immunotherapy or the abscopal effect.

Combination of nanoagents with radiations has opened up new perspectives in cancer treatment, improving both tumor diagnosis and therapeutic index. This work presents the first investigation of an innovative strategy that combines porous metal-organic frameworks (nanoMOFs) loaded with the anti-cancer drug Gemcitabine monophosphate (GemMP) and particle therapy-a globally emerging technique that offers more precise radiation targeting and enhanced biological efficacy compared to conventional radiotherapy. This radiochemotherapy has been confronted with two major obstacles limiting the efficacy of therapeutics when tested in vivo: (i) the presence of hypoxia, one of the most important causes for radiotherapy failure and (ii) the presence of a microenvironment, main biological barrier to the direct penetration of nanoparticles into cancer cells. On the one hand, this study explore the effects of hypoxia on drug delivery systems in combination with radiation, demonstrating that GemMP-loaded nanoMOFs significantly enhance the anticancer efficacy of particle therapy under both normoxic (pO2 = 20 %) and hypoxic (pO2 = 0.5 %) conditions. Notably, the presence of GemMP-loaded nanoMOFs allows the irradiation dose to be reduced by 1.4-fold in normoxia and at least 1.6-fold in hypoxia, achieving the same cytotoxic effect (SF=10 %) as carbon or helium ions alone. Synergistic effects between GemMP-loaded nanoMOFs and radiations have been observed and quantified. On the other hand, we also highlighted the ability of the nanoMOFs to diffuse through an extracellular matrix and accumulate in cells. An higher effect of the encapsulated GemMP than the free drug was observed, confirming the key role of the nanoMOFs in transporting the active substance to the cancer cells as a Trojan horse. This paves the way to the design of "all-in-one" nanodrugs where each component plays a role in the optimization of cancer therapy to maximize cytotoxic effects on hypoxic tumor cells while minimizing toxicity on healthy tissue.

We introduce a novel unsupervised approach to reconstructing a 3D volume from only two planar projections that exploits a previous­ly-captured 3D volume of the patient. Such volume is readily available in many important medical procedures and previous methods already used such a volume. Earlier methods that work by deforming this volume to match the projections typically fail when the number of projections is very low as the alignment becomes underconstrained. We show how to use a generative model of the volume structures to constrain the deformation and obtain a correct estimate. Moreover, our method is not bounded to a specific sensor calibration and can be applied to new calibrations without retraining. We evaluate our approach on a challenging dataset and show it outperforms state-of-the-art methods. As a result, our method could be used in treatment scenarios such as surgery and radiotherapy while drastically reducing patient radiation exposure.