PURPOSE:To evaluate the impact of tuning the beam configurations parameters on the Analytical Anisotropic Algorithm (AAA) and the Acuros XB (AXB) algorithm for small fields using Monte Carlo simulations and measurements. METHODS:The TrueBeam STx with the high-definition 120 multi-leaf collimator (HD120-MLC) was modeled with Geant4 application for emission tomography (GATE) Monte Carlo platform and validated against measurements. The impact of varying the effective spot size (ESS) and dosimetric leaf gap (DLG) on AAA and AXB calculations was carried out for small MLC-fields ranging from 0.5×0.5 cm2 to 3 × 3 cm2. Beam penumbras, field sizes and output factors calculated by AAA and AXB were compared to GATE calculations and measurements. RESULTS:The beam penumbra comparisons showed that the best ESS value for AXB was about 1.0 mm in the crossplane direction and 0.5 mm in the inplane direction. By optimizing the ESS values, AXB could provide output factor results almost within 2% of GATE calculations and measurements for fields down to 0.5×0.5 cm2. For AAA, significant output factor differences were observed for all ESS values and tuning the DLG in addition to the ESS optimization resulted in an absorbed dose difference of less than 2.5% for MLC-fields down to 1 × 1 cm2. CONCLUSION:By optimizing the ESS values, AXB can achieve accurate output factors in the case of small MLC-fields without the need of DLG tuning. Nevertheless, compromises between the output factor, DLG and ESS values were found necessary for AAA calculations. A MLC model improvement would allow to avoid the complexity related to tuning the configuration parameters.

In radiotherapy, patient positioning has long been ensured by ionizing imaging (kV or MV). Over the past ten years, surface-guided radiotherapy has appeared in radiotherapy departments. It is a continuous three-dimensional acquisition of the surface of the patient, based on the use of several optical cameras. The acquired surface is compared to an expected surface (usually taken from the planning scanner). Operators can constantly appreciate poor position, anatomical deformity or patient shift. Thus, the system allows an aid to the positioning of the patient, possibly without tattooing, but also a follow-up of the patient during the duration of the session. The most obvious contribution of the system concerns the treatment of the breast. In fact, for this location, the bone registration is not ideal and the target is visible in surface-guided radiotherapy. These systems also make it possible to treat in deep inspiration breath hold. But several other locations can benefit from it (pelvis, thorax, etc.). & COPY; 2023 Soci ete franc, aise de radiotherapie oncologique (SFRO). Published by Elsevier Masson SAS. All rights reserved.

In radiotherapy, patient positioning has long been ensured by ionizing imaging (kV or MV). Over the past ten years, surface-guided radiotherapy has appeared in radiotherapy departments. It is a continuous three-dimensional acquisition of the surface of the patient, based on the use of several optical cameras. The acquired surface is compared to an expected surface (usually taken from the planning scanner). Operators can constantly appreciate poor position, anatomical deformity or patient shift. Thus, the system allows an aid to the positioning of the patient, possibly without tattooing, but also a follow-up of the patient during the duration of the session. The most obvious contribution of the system concerns the treatment of the breast. In fact, for this location, the bone registration is not ideal and the target is visible in surface-guided radiotherapy. These systems also make it possible to treat in deep inspiration breath hold. But several other locations can benefit from it (pelvis, thorax, etc.).

Radiotherapy for Hodgkin lymphomas has evolved a lot over time, but still plays an important role, almost always in addition to chemotherapy, for the management of the early stages. The major objective is to preserve the quality of life of patients who will be cured from this disease in the vast majority of cases. Also, the personalization of the indications for the purpose of de-escalating toxicity is very refined and is essentially based on the pre- and pertherapeutic assessment by FDG-PET. The indications for radiotherapy are more limited for non-Hodgkin lymphomas, but the same principles are found, regardless of the histological type. We present the update of the recommendations of the French society of oncological radiotherapy for radiotherapy of lymphomas, which remains a very evolving field in terms of therapeutic strategy and evaluation.

We present the update of the recommendations of the French society of oncological radiotherapy on respiratory motion management for external radiotherapy treatment. Since twenty years and the report 62 of ICRU, motion management during the course of radiotherapy treatment has become an increasingly significant concern, particularly with the development of hypofractionated treatments under stereotactic conditions, using reduced safety margins. This article related orders of motion amplitudes for different organs as well as the definition of the margins in radiotherapy. An updated review of the various movement management strategies is presented as well as main technological solutions enabling them to be implemented: when acquiring anatomical data, during planning and when carrying out treatment. Finally, the management of these moving targets, such as it can be carried out in radiotherapy departments, will be detailed for a few concrete examples of localizations (abdominal, thoracic and hepatic).

Introduction:We report on our experience of using Helical Tomotherapy (HT) in the context of post-mastectomy radiation therapy (PMRT) with or without immediate implant-based breast Reconstruction (IBR). Material and methods:The study included a total of 173 patients who underwent PMRT with HT between 2013 and 2015 in our institution (87 immediate breast reconstructions with retropectoral implants (IBR + ), 86 without reconstructions (IBR-)). The chest wall target volume included subcutaneous tissue and pectoralis muscle and excluded the posterior region of the implant as well as the ribs. Results:Median time to initiation of the first adjuvant treatment from mastectomy was similar between the two groups (p = 0.134). Dose coverage to the chest wall was significantly improved for the IBR + group (V95% = 95.1 % versus 92.0 %; p < 0.0001). The irradiated volume of the ipsilateral lung was significantly decreased in the IBR + group with a median V20Gy of 11.6 %, compared to 15.2 % for the control group (p < 0.0001). The median heart V15Gy was also significantly lower in the IBR + group than in the control group (1.7 vs 2.5 %; p = 0.0280). The reconstruction failure rate was 14.9% (n = 13). After a median follow-up of 65 months, loco regional recurrence rate was low in both groups: 3 patients (3.4%) in the IBR + group and 5 patients (5.8%) in the control group, without any local recurrence in the posterior part of the implant. Conclusions:The presence of a breast implant reduces cardiac and pulmonary doses during Tomotherapy irradiation, without compromising oncological outcomes.

Topographical cues in the micron and nanoscale regime represent a powerful and effective method for controlling neuron and glial cell behavior. Previous studies have shown that contact guidance can facilitate axon pathfinding, accelerate neurite growth and induce glial cell alignment. In this paper, we exploit the concept of haptotaxis via implementation into three-dimensional neural based scaffolds. Polymeric poly-l-lactic acid (PLLA) conduits possessing multiple intralumenal walls and precise topography along the longitudinal axis were fabricated using solvent casting, physical imprinting and a rolling-fusing method. Measurements made on scanning electron micrographs show the conduits demonstrate a transparency factor (void to polymer ratio) of up to 87.9% and an increase in surface area of four to eight times over comparably sized hollow conduits. Intralumenal wall thickness was approximately 20μm and physical parameters such as the number of lumens, conduit length and diameter were controllable. These results imply that the structures are conducive for cellular infiltration and proliferation. Although PLLA was used, the manufacturing techniques are highly flexible and are compatible with multiple polymer–solvent systems. Thus, the proposed conduits can be custom tailored to resorb in parallel with the healing process. Applications for these scaffolds include autograft substitutes for peripheral nerve transection or potential use in spinal cord related injuries.

Deep-learning (DL)-based auto-contouring solutions have recently been proposed as a convincing alternative to decrease workload of target volumes and organs-at-risk (OAR) delineation in radiotherapy planning and improve inter-observer consistency. However, there is minimal literature of clinical implementations of such algorithms in a clinical routine. In this paper we first present an update of the state-of-the-art of DL-based solutions. We then summarize recent recommendations proposed by the European society for radiotherapy and oncology (ESTRO) to be followed before any clinical implementation of artificial intelligence-based solutions in clinic. The last section describes the methodology carried out by three French radiation oncology departments to deploy CE-marked commercial solutions. Based on the information collected, a majority of OAR are retained by the centers among those proposed by the manufacturers, validating the usefulness of DL-based models to decrease clinicians’ workload. Target volumes, with the exception of lymph node areas in breast, head and neck and pelvic regions, whole breast, breast wall, prostate and seminal vesicles, are not available in the three commercial solutions at this time. No implemented workflows are currently available to continuously improve the models, but these can be adapted/retrained in some solutions during the commissioning phase to best fit local practices. In reported experiences, automatic workflows were implemented to limit human interactions and make the workflow more fluid. Recommendations published by the ESTRO group will be of importance for guiding physicists in the clinical implementation of patient specific and regular quality assurances.

PURPOSE:Monte Carlo (MC) is the reference computation method for medical physics. In radiotherapy, MC computations are necessary for some issues (such as assessing figures of merit, double checks, and dose conversions). A tool based on GATE is proposed to easily create full MC simulations of the Varian TrueBeam STx.METHODS:GAMMORA is a package that contains photon phase spaces as a pre-trained generative adversarial network (GAN) and the TrueBeam's full geometry. It allows users to easily create MC simulations for simple or complex radiotherapy plans such as VMAT. To validate the model, the characteristics of generated photons are first compared to those provided by Varian (IAEA format). Simulated data are also compared to measurements in water and heterogeneous media. Simulations of 8 SBRT plans are compared to measurements (in a phantom). Two examples of applications (a second check and interplay effect assessment) are presented.RESULTS:The simulated photons generated by the GAN have the same characteristics (energy, position, and direction) as the IAEA data. Computed dose distributions of simple cases (in water) and complex plans delivered in a phantom are compared to measurements, and the Gamma index (3%/3mm) was always superior to 98%. The feasibility of both clinical applications is shown.CONCLUSIONS:This model is now shared as a free and open-source tool that generates radiotherapy MC simulations. It has been validated and used for five years. Several applications can be envisaged for research and clinical purposes.

Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topic in radiotherapy. Today, the first commercial automated treatment planning solutions are available and implemented in a growing number of clinical radiotherapy departments. It should be noted that these various commercial solutions are based on very different methods, implying a daily practice that varies from one center to another. It is likely that this change in planning practices is still in its infancy. Indeed, the rise of artificial intelligence methods, based in particular on deep learning, has recently revived research interest in this subject. The numerous articles currently being published announce a lasting and profound transformation of radiotherapy planning practices in the years to come. From this perspective, an evolution of initial training for clinical teams and the drafting of new quality assurance recommendations is desirable.

The benefits of using an algorithm that reports absorbed dose-to-medium have been jeopardized by the clinical experience and the experimental protocols that have mainly relied on absorbed dose-to-water. The aim of the present work was to investigate the physical aspects that govern the dosimetry in heterogeneous media using Monte Carlo method and to introduce a formalism for the experimental validation of absorbed dose-to-medium reporting algorithms. Particle fluence spectra computed within the sensitive volume of two simulated detectors (T31016 Pinpoint 3D ionization chamber and EBT3 radiochromic film) placed in different media (water, RW3, lung and bone) were compared to those in the undisturbed media for 6 MV photon beams. A heterogeneity correction factor that takes into account the difference between the detector perturbation in medium and under reference conditions as well as the stopping-power ratios was then derived for all media using cema calculations. Furthermore, the different conversion approaches and Eclipse treatment planning system algorithms were compared against the Monte Carlo absorbed dose reports. The detectors electron fluence perturbation in RW3 and lung media were close to that in water (≤1.5%). However, the perturbation was greater in bone (∼4%) and impacted the spectral shape. It was emphasized that detectors readings should be corrected by the heterogeneity correction factor that ranged from 0.932 in bone to 0.985 in lung. Significant discrepancies were observed between all the absorbed dose reports and conversions, especially in bone (exceeding 10%) and to a lesser extent in RW3. Given the ongoing advances in dose calculation algorithms, it is essential to standardize the absorbed dose report mode with absorbed dose-to-medium as a favoured choice. It was concluded that a retrospective conversion should be avoided and switching from absorbed dose-to-water to absorbed dose-to-medium reporting algorithm should be carried out by a direct comparison of both algorithms.

PURPOSE:In modulated radiotherapy, breathing motion can lead to Interplay (IE) and Blurring (BE) effects that can modify the delivered dose. The aim of this work is to present the implementation, the validation and the use of an open-source Monte-Carlo (MC) model that computes the delivered dose including these motion effects.METHODS:The MC model of the Varian TrueBeam was implemented using GATE. The dose delivered by different modulated plans is computed for several breathing patterns. A validation of these MC predictions is achieved by a comparison with measurements performed using a dedicated programmable motion platform, carrying a quality assurance phantom. A specific methodology was used to separate the IE and the BE. The influence of different motion parameters (period, amplitude, shape) and plan parameters (volume margin, dose per fraction) was also analyzed.RESULTS:The MC model was validated against measurement performed with motion with a mean 3D global gamma index pass rate of 97.5% (3%/3 mm). A significant correlation is found between the IE and the period and the antero-posterior amplitude of the motion but not between the IE and the CTV margin or the shape of motion. The results showed that the IE increases D2% and decreases the D98% of CTV with mean values of +6.9% and -3.3% respectively.CONCLUSIONS:We validated the feasibility to assess the IE using a MC model. We found that the most important parameter is the number of breathing cycles that must be greater than 20 for one arc to limit the IE.

In radiotherapy, patient-specific quality assurance is very time-consuming and causes machine downtime. It consists of testing (using measurement with a phantom and detector) if a modulated plan is correctly delivered by a treatment unit. Artificial intelligence and in particular machine learning algorithms were mentioned in recent reports as promising solutions to reduce or eliminate the patient-specific quality assurance workload. Several teams successfully experienced a virtual patient-specific quality assurance by training a machine learning tool to predict the results. Training data are generally composed of previous treatment plans and associated patient-specific quality assurance results. However, other training data types were recently introduced such as actual positions and velocities of multileaf collimators, metrics of the plan's complexity, and gravity vectors. Different types of machine learning algorithms were investigated (Poisson regression algorithms, convolutional neural networks, support vector classifiers) with sometimes promising results. These tools are being used for treatment units' quality assurance as well, in particular to analyse the results of imaging devices. Most of these reports were feasibility studies. Using machine learning in clinical routines as a tool that could fully replace quality assurance tests conducted by physics teams has yet to be implemented.

PURPOSE:To assess the accuracy of volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) when treating moving targets (such as lung or liver lesions), focusing on the impact of the interplay effect in the event of complex breathing motion and when a gating window is used.METHODS:A dedicated programmable motion platform was implemented. This platform can carry large quality assurance (QA) phantoms and achieve complex three-dimensional (3D) motion. Volumetric modulated arc therapy SBRT plans were delivered with TrueBeam linac to this moving setup and the measured dose was compared to the computed one. Several parameters were assessed such as breathing period, dose rate, dose prescription, shape of the breathing pattern, the use of a planning target volume (PTV) margin, and the use of a gating window.RESULTS:Loss of dose coverage (D95%) was acceptable in most situations. The doses received by 95% of the CTV, D95% ( C T V m ) ranged from 94 to 101% (mean 98%) and the doses received by 2% of the CTV D2% ( C T V m ) ranged from 94% to 110% of the prescribed dose. A visible interplay effect was observed when no margin was used or when the number of breathing cycles during the treatment delivery was lower than 20.CONCLUSIONS:In our clinical context, treating lung and liver lesions using VMAT SBRT is reasonable. The interplay effect was moderated and acceptable in all simulated situations.

Introduction. Radiation Therapy of the thoracic region is confronted to the respiratory movement. When fluency is modulated (VMAT) and high doses (SBRT) are used, an Interplay Effect (IE) can appear. This is an unfortunate combination of the respiratory and leaf movements of the Multi-leafs Collimator that could lead to under-dosing of the target or over-dosing of risk organs. In the literature, the IE has been studied and depends on a large number of parameters: dose rate, dose per fraction, number of fractions, period and amplitude of breathing, beam energy, complexity of modulation, etc. A motion platform was developed to carry phantoms and to perform programmed 3D movements. This work aims to evaluate the IE for stereotactic lung and liver treatments and study the possibility of treating our patients using VMAT SBRT.

The aim of this work was to use the Artificial Neural Network (ANN) in External Beam Radiation Therapy (EBRT), especially for pre-treatment patient-specific quality assurance of Conformational Radiation Therapy (CRT) and Intensity-Modulated Radiation Therapy (IMRT) using Electronic Portal Imaging Device (EPID). The EPIDs need frequent calibration and complex setting in order to be used with dedicated dosimetry software. The idea was to create a model with ANN algorithms allowing the reconstruction of the 2D dose distribution comparable with a corresponding Treatment Planning System (TPS) solution. The supervised ANN algorithms work with two phases—learning and recognition. Learning was performed using data sets regarding CRT and IMRT composed of 8 and 11 input/output respectively. To compare ANN predicted and planned results the global gamma index was used, obtaining a \( \gamma_{{(2\% ,2\,\text{mm})}} = 99.78\% \) and \( \gamma_{{(2\% ,2\,\text{mm})}} = 99.7\% \), respectively. This first work showed the capability of ANN to reconstruct the absorbed dose distribution based on EPID signals.

PurposeHolmium 166 (166Ho) is a potential candidate for internal radiotherapy due to high-energy beta radiation (1.77 and 1.85 MeV) and gamma ray (80.6 keV) adapted to SPECT imaging albeit with poor spatial resolution (cm). The spatial resolution at which activity distribution is determined impacts the absorbed dose calculation algorithm that needs to be implemented: For example, SPECT spatial resolution will often lead to the Local Energy Deposition (LED) approximation. In this study, we investigated the potential of CT for holmium quantification, and compared various absorbed dose calculation algorithms in a context of micro-brachytherapy.MethodsFor CT calibration, acquisitions were performed on a General Electric BrightSpeed 16 using a CIRS 62 phantom with known holmium concentration in order to get a calibration curve. We then assessed holmium concentration in brain tumours implanted in Yucatan minipigs treated by 166Ho microbrachytherapy. Acquisition parameters were as follows: voltage = 140 kV; reconstruction filter B31s, matrix size: 512 × 512; pixel size: 0.488 × 0.488 mm2; slice thickness = 0.625 mm. Holmium segmentation was based-on pre and post injection CT image subtraction. From the CT calibration curve, and with a prior knowledge of 166Ho specific activity, it was possible to get a 3D activity distribution. Different absorbed dose computation approaches were implemented: Local Energy Deposition (LED), superposition/convolution of dose-point kernels assuming homogenous or heterogeneous media, and Monte Carlo modelling (GATE) taken as the reference. Gamma-index criteria (0.1%, 0.5 mm) were used to compare approaches.ResultsThe LED approach was clearly not appropriated due to 166Ho range vs. CT resolution (0.15% passing rate according to the gamma-index criteria). Homogenous and heterogeneous convolution/superposition approaches provided 78% passing rate in a situation of homogenous soft tissues, compared to GATE. Discrepancies were mainly visible in a situation of heterogeneous densities.ConclusionsCT-based holmium quantification can provide relevant density information with good spatial resolution (as compared to SPECT imaging), broadening the possibilities for absorbed dose calculation algorithms. This work was partially sponsored by BPI-France under the scope of the Industrial Strategic Innovation project (projet d’Innovation Stratégique Industrielle) “TheraneaM.

Introduction The size of Radiotherapy (RT) departments makes difficult to organize a complete in-house training for the therapists. In a French center there are often 40 to 50 therapists and treatment time slots are large so it is difficult to achieve a classic training. Moreover the training is mainly achieved by people who are poorly available (physicists, physicians, therapists …). Nevertheless the needs of training are very important. Indeed, RT therapists have a central role in the patient security chain and technologies evolve very quickly. New skills and knowledge are continuously asked (new devices, new treatment techniques or a simple software or hardware update). We present in this work the MYRE (MY Recordable E-Learning) database developed in our cancer center that is a full solution of e-learning of RT therapists. Methods A Microsoft ACCESS database (BDD) was implemented. It contains all the information concerning the therapists and a link to approximately 200 micro-modules. It allows recording and requesting every training act (request can be done for a given therapist, a given module, a year…). These 200 micro-modules are separated in three types: 1. Simple written procedures from the institutional document database that the user must read. 2. Some particular techniques that the user must see. 3. SPOC (Small Private Online Classes): these videos that we made last generally 10 min and are associated to an online multiple-choice test (MCT). This MCT are auto-corrected: the user obtains a score and explanations are given to understand the correct answers. The therapists can access to MYRE in complete autonomy (training, evaluation, and recording of the acquired micro-modules). Results Between January and March 2018, approximately 600 training acts were recorded in MYRE. Special requests were implemented to allow the manager to edit some specific lists like “list of therapists with all the mandatory skills for a given medical device”. Some therapists are involved in the database maintenance and the making of videos and MCT. Conclusion A database with a link to 200 documents (videos or written procedures) was developed and deployed in the department. It allows the therapists to train in full autonomy. In this study we made a lot of videos and observed that they are an effective tool to introduce technical concepts while written procedures are better for the description of tasks. MYRE is well accepted by therapists (results of an internal audit).