In multicentric studies, data sharing between institutions might negatively impact patient privacy or data security. An alternative is federated analysis by secure multiparty computation. This pilot study demonstrates an architecture and implementation addressing both technical challenges and legal difficulties in the particularly demanding setting of clinical research on cancer patients within the strict European regulation on patient privacy and data protection: 24 patients from LMU University Hospital in Munich, Germany, and 24 patients from Policlinico Universitario Fondazione Agostino Gemelli, Rome, Italy, were treated for adrenal gland metastasis with typically 40 Gy in 3 or 5 fractions of online-adaptive radiotherapy guided by real-time MR. High local control (21% complete remission, 27% partial remission, 40% stable disease) and low toxicity (73% reporting no toxicity) were observed. Median overall survival was 19 months. Federated analysis was found to improve clinical science through privacy-friendly evaluation of patient data in the European health data space.

Background: We describe and evaluate a deep network algorithm which automatically contours organs at risk in the thorax and pelvis on computed tomography (CT) images for radiation treatment planning. Methods: The algorithm identifies the region of interest (ROI) automatically by detecting anatomical landmarks around the specific organs using a deep reinforcement learning technique. The segmentation is restricted to this ROI and performed by a deep image-to-image network (DI2IN) based on a convolutional encoder-decoder architecture combined with multi-level feature concatenation. The algorithm is commercially available in the medical products “syngo.via RT Image Suite VB50” and “AI-Rad Companion Organs RT VA20” (Siemens Healthineers). For evaluation, thoracic CT images of 237 patients and pelvic CT images of 102 patients were manually contoured following the Radiation Therapy Oncology Group (RTOG) guidelines and compared to the DI2IN results using metrics for volume, overlap and distance, e.g., Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD₉₅). The contours were also compared visually slice by slice. Results: We observed high correlations between automatic and manual contours. The best results were obtained for the lungs (DSC 0.97, HD₉₅ 2.7 mm/2.9 mm for left/right lung), followed by heart (DSC 0.92, HD₉₅ 4.4 mm), bladder (DSC 0.88, HD₉₅ 6.7 mm) and rectum (DSC 0.79, HD₉₅ 10.8 mm). Visual inspection showed excellent agreements with some exceptions for heart and rectum. Conclusions: The DI2IN algorithm automatically generated contours for organs at risk close to those by a human expert, making the contouring step in radiation treatment planning simpler and faster. Few cases still required manual corrections, mainly for heart and rectum.

Background and purpose: To report on our clinical experience with a newly implemented workflow for radiotherapy (RT) emergency treatments, which allows for a fast treatment application outside the regular working-hours, and its clinical applicability. Methods: Treatment planning of 18 emergency RT patients was carried out using diagnostic computed tomography (CT) without a dedicated RT simulation CT. The cone-beam CT (CBCT) deviations of the first RT treatment were analyzed regarding setup accuracy. Furthermore, feasibility of the “fast-track” workflow was evaluated with respect to dose deviations caused by different Hounsfield unit (HU) to relative electron density (rED) calibrations and RT treatment couch surface shapes via 3D gamma index analysis of exemplary treatment plans. The dosimetric uncertainty introduced by different CT calibrations was quantified. Results: Mean patient setup vs. CBCT isocenter deviations were (0.49 ± 0.44) cm (x), (2.68 ± 1.63) cm (y) and (1.80 ± 1.06) cm (z) for lateral, longitudinal and vertical directions, respectively. Three out of four dose comparisons between the emergency RT plan calculated on the diagnostic CT and the same plan calculated on the treatment planning CT showed clinically acceptable gamma passing rates, when correcting for surface artifacts. The maximum difference of rED was 0.054, while most parts of the CT calibration curves coincided well. Conclusion: In an emergency RT setting, the use of diagnostic CT data for treatment planning might be time-saving and was shown to be suitable for many cases, considering reproducibility of patient setup, accuracy of initial patient setup and accuracy of dose-calculation.

Background and purpose: Radiation-induced pneumonitis (RP), diagnosed 6-12 weeks after treatment, is a complication of lung tumor radiotherapy. So far, clinical and dosimetric parameters have not been reliable in predicting RP. We propose using non-contrast enhanced magnetic resonance imaging (MRI) based functional parameters acquired over the treatment course for patient stratification for improved follow-up. Materials and methods: 23 lung tumor patients received MR-guided hypofractionated stereotactic body radiation therapy at a 0.35 T MR-Linac. Ventilation- and perfusion-maps were generated from 2D-cine MRIscans acquired after the first and last treatment fraction (Fx) using non-uniform Fourier decomposition. The relative differences in ventilation and perfusion between last and first Fx in three regions (planning target volume (PTV), lung volume receiving more than 20 Gy (V20) excluding PTV, whole tumor-bearing lung excluding PTV) and three dosimetric parameters (mean lung dose, V20, mean dose to the gross tumor volume) were investigated. Univariate receiver operating characteristic curve- area under the curve (ROC- AUC) analysis was performed (endpoint RP grade >= 1) using 5000 bootstrapping samples. Differences between RP and non-RP patients were tested for statistical significance with the non-parametric Mann-Whitney U test (alpha = 0.05). Results: 14/23 patients developed RP of grade >= 1 within 3 months. The dosimetric parameters showed no significant differences between RP and non-RP patients. In contrast, the functional parameters, especially the relative ventilation difference in the PTV, achieved a p-value <0.05 and an AUC value of 0.84. Conclusion: MRI-based functional parameters extracted from 2D-cine MRI-scans were found to be predictive of RP development in lung tumor patients.

Background: Starting in December 2019, the current pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) confronts the world with an unprecedented challenge. With no vaccine or drug being currently available to control the pandemic spread, prevention and PCR (Polymerase chain reaction) testing becomes a crucial pillar of medical systems. Aim of the present study was to report on the first results of the measures taken in a large German Department of Radiation Oncology, including PCR testing of asymptomatic cancer patients. Methods: Pandemic-adapted hygiene regulations and prevention measures for patients and staff were implemented. A visiting ban on both wards was implemented from the beginning and medical staff and patients were required to wear face masks at all times. The waiting rooms were rearranged to ensure distance between patients of at least 1.5 m. Clinical follow up was mainly done by telephone and all patients had to complete a questionnaire regarding symptoms and contacts with COVID-19 patients before entering our department. Educational documents were created for patients to raise awareness of symptoms and avoidance strategies for interactions with other people. Indications for therapy and fractionation schemes were adapted when possible. In a subsequent step, all new asymptomatic patients were tested via nasopharyngeal swab at our screening station shortly before their simulation CT. Results: All these measures and implementations have been well accepted semiquantitatively measured by the consent received from patients and staff. Regarding the PCR testing, only 1 out of 139 asymptomatic patients of our cohort so far tested positive for SARS-CoV-2, reflecting a prevalence of 0.72% in this cancer patient population. Up to this point no staff members was tested positive. The start of the treatment for the PCR-positive patient was deferred for 2 weeks. Conclusion: Due to the pandemic-adapted implementations, our department seems well prepared during this crisis. The initial screening helps to identify asymptomatic COVID-19 patients in order to protect other patients and our staff from infection and the observed PCR prevalence is in line with comparable studies. A regular PCR testing (e.g. twice a week) of all patients and staff would in principle be desirable but is limited due to testing capacities at present.