We investigated the relationship between RBE-weighted dose (DRBE) calculated with constant (cRBE) and variable RBE (vRBE), dose-averaged linear energy transfer (LETd) and the risk of radiographic changes in skull base patients treated with protons. Clinical treatment plans of 45 patients were recalculated with Monte Carlo tool FRED. Radiographic changes (i.e. edema and/or necrosis) were identified by MRI. Dosimetric parameters for cRBE and vRBE were computed. Biological margin extension and voxel-based analysis were employed looking for association of DRBE(vRBE) and LETd with brain edema and/or necrosis. When using vRBE, Dmax in the brain was above the highest dose limits for 38% of patients, while such limit was never exceeded assuming cRBE. Similar values of Dmax were observed in necrotic regions, brain and temporal lobes. Most of the brain necrosis was in proximity to the PTV. The voxel-based analysis did not show evidence of an association with high LETd values. When looking at standard dosimetric parameters, the higher dose associated with vRBE seems to be responsible for an enhanced risk of radiographic changes. However, as revealed by a voxel-based analysis, the large inter-patient variability hinders the identification of a clear effect for high LETd.

Objective. This paper reports on the implementation and shows examples of the use of the ProTheRaMon framework for simulating the delivery of proton therapy treatment plans and range monitoring using positron emission tomography (PET). ProTheRaMon offers complete processing of proton therapy treatment plans, patient CT geometries, and intra-treatment PET imaging, taking into account therapy and imaging coordinate systems and activity decay during the PET imaging protocol specific to a given proton therapy facility. We present the ProTheRaMon framework and illustrate its potential use case and data processing steps for a patient treated at the Cyclotron Centre Bronowice (CCB) proton therapy center in Krakow, Poland. Approach. The ProTheRaMon framework is based on GATE Monte Carlo software, the CASToR reconstruction package and in-house developed Python and bash scripts. The framework consists of five separated simulation and data processing steps, that can be further optimized according to the user’s needs and specific settings of a given proton therapy facility and PET scanner design. Main results. ProTheRaMon is presented using example data from a patient treated at CCB and the J-PET scanner to demonstrate the application of the framework for proton therapy range monitoring. The output of each simulation and data processing stage is described and visualized. Significance. We demonstrate that the ProTheRaMon simulation platform is a high-performance tool, capable of running on a computational cluster and suitable for multi-parameter studies, with databases consisting of large number of patients, as well as different PET scanner geometries and settings for range monitoring in a clinical environment. Due to its modular structure, the ProTheRaMon framework can be adjusted for different proton therapy centers and/or different PET detector geometries. It is available to the community via github (Borys et al 2022).

Objective. The Jagiellonian positron emission tomography (J-PET) technology, based on plastic scintillators, has been proposed as a cost effective tool for detecting range deviations during proton therapy. This study investigates the feasibility of using J-PET for range monitoring by means of a detailed Monte Carlo simulation study of 95 patients who underwent proton therapy at the Cyclotron Centre Bronowice (CCB) in Krakow, Poland. Approach. Discrepancies between prescribed and delivered treatments were artificially introduced in the simulations by means of shifts in patient positioning and in the Hounsfield unit to the relative proton stopping power calibration curve. A dual-layer, cylindrical J-PET geometry was simulated in an in-room monitoring scenario and a triple-layer, dual-head geometry in an in-beam protocol. The distribution of range shifts in reconstructed PET activity was visualized in the beam’s eye view. Linear prediction models were constructed from all patients in the cohort, using the mean shift in reconstructed PET activity as a predictor of the mean proton range deviation. Main results. Maps of deviations in the range of reconstructed PET distributions showed agreement with those of deviations in dose range in most patients. The linear prediction model showed a good fit, with coefficient of determination r ² = 0.84 (in-room) and 0.75 (in-beam). Residual standard error was below 1 mm: 0.33 mm (in-room) and 0.23 mm (in-beam). Significance. The precision of the proposed prediction models shows the sensitivity of the proposed J-PET scanners to shifts in proton range for a wide range of clinical treatment plans. Furthermore, it motivates the use of such models as a tool for predicting proton range deviations and opens up new prospects for investigations into the use of intra-treatment PET images for predicting clinical metrics that aid in the assessment of the quality of delivered treatment.

Objective. Verification of delivered proton therapy treatments is essential for reaping the many benefits of the modality, with the most widely proposed in vivo verification technique being the imaging of positron emitting isotopes generated in the patient during treatment using positron emission tomography (PET). The purpose of this work is to reduce the computational resources and time required for simulation of patient activation during proton therapy using the GPU accelerated Monte Carlo code FRED, and to validate the predicted activity against the widely used Monte Carlo code GATE. Approach. We implement a continuous scoring approach for the production of positron emitting isotopes within FRED version 5.59.9. We simulate treatment plans delivered to 95 head and neck patients at Centrum Cyklotronowe Bronowice using this GPU implementation, and verify the accuracy using the Monte Carlo toolkit GATE version 9.0. Main results. We report an average reduction in computational time by a factor of 50 when using a local system with 2 GPUs as opposed to a large compute cluster utilising between 200 to 700 CPU threads, enabling simulation of patient activity within an average of 2.9 min as opposed to 146 min. All simulated plans are in good agreement across the two Monte Carlo codes. The two codes agree within a maximum of 0.95 σ on a voxel-by-voxel basis for the prediction of 7 different isotopes across 472 simulated fields delivered to 95 patients, with the average deviation over all fields being 6.4 × 10 ⁻³ σ . Significance. The implementation of activation calculations in the GPU accelerated Monte Carlo code FRED provides fast and reliable simulation of patient activation following proton therapy, allowing for research and development of clinical applications of range verification for this treatment modality using PET to proceed at a rapid pace.

Background: Due to the rarity of osteosarcoma and limited indications for radiotherapy (RT), data on RT for this tumor are scarce. This study aimed to investigate the utilization of RT for osteosarcomas in the recent 20 years and to identify factors related to patients’ response to radiation. Methods: We performed a retrospective analysis of patients irradiated for osteosarcoma treatment. We planned to assess differences in the utilization of RT between the periods of 2000–2010 and 2011–2020, identify the risk factors associated with local progression (LP), determine whether RT-related parameters are associated with LP, and calculate patients’ survival. Results: A total of 126 patients with osteosarcoma who received 181 RT treatments were identified. We found a difference in RT techniques between RT performed in the years 2000–2010 and that performed in the years 2011–2020. LP was observed after 37 (20.4%) RT treatments. Intent of RT, distant metastases, and concomitant systemic treatment affected the risk of LP. Five-year overall survival was 33% (95% confidence interval (26%–43%)). Conclusions: RT for osteosarcoma treatment has evolved from simple two-dimensional palliative irradiation into more conformal RT applied for new indications including oligometastatic and oligoprogressive disease. RT may be a valuable treatment modality for selected patients with osteosarcoma.

Approximately 60 % of patients with locally advanced laryngeal cancer (LALC) treated primarily with surgery require adjuvant radiotherapy. In the available literature predominate series of patients were with pathologically confirmed node-positive status. Subgroups of pN0 patients with LALC are scarce. The aim of the study is to evaluate the efficacy of postoperative radiotherapy in patients with pathological stage T3-4N0M0 and identification of prognostic factors in this group. Between 1975 and 2005, 138 patients with squamous pT3-4N0 laryngeal cancer were irradiated postoperatively. Primary surgical treatment consisted of total laryngectomy and cervical lymphadenectomy. The median time between surgery and the implementation of radiotherapy was 56 days. The median total dose was 60 Gy (range 40–70 Gy). Five-year disease-free survival (DFS5) was achieved in 76 % of patients. Cancer recurrence was observed in 34 patients. In 28 (82 %) cases it was locoregional failure. DFS5 rates for pT3 and pT4 were 92 and 69 %, for margin status R0, R1 and R2 were 82, 72 and 67 %, respectively. The pharyngeal invasion was related to a decrease in DFS5 from 80 to 59 %. Postoperative irradiation in patients with pT3-4N0 LALC is an effective treatment method. The main reason of the failure is local recurrence. The following independent prognostic factors were identified in this group of patients: pT stage, surgical margin status and pharyngeal invasion.