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Background Linac-based stereotactic radiosurgery or fractionated stereotactic radiotherapy (SRS/FSRT) of multiple brain lesions using volumetric modulated arc therapy (VMAT) is typically performed by a multiple-isocenter approach, i.e. one isocenter per lesion, which is time-demanding for the need of independent setup verifications of each isocenter. Here, we present our initial experience with a new dedicated mono-isocenter technique with multiple non-coplanar arcs (HyperArc™, Varian Inc.) in terms of a plan comparison with a multiple-isocenter VMAT approach. Methods From August 2017 to October 2017, 20 patients with multiple brain metastases (mean 5, range 2–10) have been treated by HyperArc in 1–3 fractions. The prescribed doses (Dp) were 18–25 Gy in single-fraction, and 21–27 Gy in three-fractions. Planning Target Volume (PTV), defined by a 2 mm isotropic margin from each lesion, had mean dimension of 9.6 cm 3 (range 0.5–27.9 cm 3 ). Mono-isocenter HyperArc VMAT plans (HA) with 5 non-coplanar 180°-arcs (couch at 0°, ±45°, ±90°) were generated and compared to multiple-isocenter VMAT plans (RA) with 2 coplanar 360°-arcs per isocenter. A dose normalization of 100%Dp at 98%PTV was adopted, while D 2% (PTV) < 150%D p was accepted. All plans had to respect the constraints on maximum dose to the brainstem (D 0.5cm3  < 18 Gy) as well as to the optical nerves/chiasm, eyes and lenses (D 0.5cm3  < 15 Gy). HA and RA plans were compared in terms of dose-volume metrics, by Paddick conformity (CI) and gradient (GI) index and by V 12 and mean dose to the brain-minus-PTV, and in terms of MU and overall treatment time (OTT) per fraction. OTT was measured for HA treatments, whereas for RA plans OTT was estimated by assuming 3 min. For initial patient setup plus 5 min. For each CBCT-guided setup correction per isocenter. Results Significant variations in favour of HA plans were computed for both target dose indexes, CI ( p  < .01) and GI ( p  < .01). The lower GI in HA plans was the likely cause of the significant reduction in V 12 to the brain-minus-PTV ( p  = .023). Although at low doses, below 2–5 Gy, the sparing of the brain-minus-PTV was in favour of RA plans, no significant difference in terms of mean doses to the brain-minus-PTV was observed between the two groups ( p  = .31). Finally, both MU ( p  < .01) and OTT ( p  < .01) were significantly reduced by HyperArc plans. Conclusions For linac-based SRS/FSRT of multiple brain lesions, HyperArc plans assured a higher CI and a lower GI than standard multiple-isocenter VMAT plans. This is consistent with the computed reduction in V 12 to the brain-minus-PTV. Finally, HyperArc treatments were completed within a typical 20 min. time slot, with a significant time reduction with respect to the expected duration of multiple-isocenters VMAT.

Radiation therapy is an integral part of the multidisciplinary management of breast cancer. Regional lymph node irradiation in younger trials seems to provide superior target coverage as well as a reduction in long-term toxicity resulting in a small benefit in the overall survival rate. For partial breast irradiation there are now two large trials available which support the role of partial breast irradiation in low risk breast cancer patients. Multiple randomized trials have established that a sequentially applied dose to the tumor bed improves local control with the cost of worse cosmetic results.

Background Hybrid magnetic resonance (MR)-Linac systems have recently been introduced into clinical practice. The systems allow online adaption of the treatment plan with the aim of compensating for interfractional anatomical changes. The aim of this study was to evaluate the dose volume histogram (DVH)-based dosimetric benefits of online adaptive MR-guided radiotherapy (oMRgRT) across different tumor entities and to investigate which subgroup of plans improved the most from adaption. Methods Fifty patients treated with oMRgRT for five different tumor entities (liver, lung, multiple abdominal lymph nodes, pancreas, and prostate) were included in this retrospective analysis. Various target volume (gross tumor volume GTV, clinical target volume CTV, and planning target volume PTV) and organs at risk (OAR) related DVH parameters were compared between the dose distributions before and after plan adaption. Results All subgroups clearly benefited from online plan adaption in terms of improved PTV coverage. For the liver, lung and abdominal lymph nodes cases, a consistent improvement in GTV coverage was found, while many fractions of the prostate subgroup showed acceptable CTV coverage even before plan adaption. The largest median improvements in GTV near-minimum dose (D 98% ) were found for the liver (6.3%, p  < 0.001), lung (3.9%, p  < 0.001), and abdominal lymph nodes (6.8%, p  < 0.001) subgroups. Regarding OAR sparing, the largest median OAR dose reduction during plan adaption was found for the pancreas subgroup (-87.0%). However, in the pancreas subgroup an optimal GTV coverage was not always achieved because sparing of OARs was prioritized. Conclusion With online plan adaptation, it was possible to achieve significant improvements in target volume coverage and OAR sparing for various tumor entities and account for interfractional anatomical changes.

IntroductionRadiosurgery (SRS) or stereotactic fractionated radiotherapy (SFRT) is increasing in the treatment of brain metastases (BMs). Aim of the present study was to evaluate the safety and effectiveness of SRS/SFRT for BMs, using a new mono-isocenter non-coplanar solution (HyperArc™ Varian Medical System).MethodsBMs patients with a diameter inferior to 3 cm, a life expectancy of more than 3 months and a good performance status, were eligible for Linac-based volumetric modulated arc therapy (VMAT) SFRT/SRS with HyperArc™. A retrospective analysis of patients and BMs was performed.ResultsFrom August 2017 to May 2018, 381 BMs in 64 patients were treated and 246 BMs (43 patients, median number of BMs: 5) of them were suitable for analysis. With a median FU time of 6 months, 244 out 246 (99%) BMs were controlled (18% complete response; 41% partial response, 40% stable disease), 2 BMs showed a progression, at the first control. No acute or late toxicities were reported. Median overall survival (OS) has not yet been achieved, while median time to progression was 5 months. In univariate analysis, statistically negative prognostic factors for OS were histology of primary tumor (p = 0.009): lung/breast cancer had better survival rates as compared to others. Cumulative intracranial volume disease ≥ 15 cc and systemic progression disease were independent prognostic factors for OS at univariate (p = 0.04; p = 0.005) and multivariate (p = 0.04; p = 0.009) analysis, respectively.ConclusionThe present first clinical data show that SFRT/SRS with HyperArc™ is safe and effective for BMs patients. The utilization of SFRT/SRS for BMs is promising and should be further explored in randomized trials.

Background and purpose Magnetic resonance imaging guided radiotherapy (MRgRT) offers treatment plan adaptation to the anatomy of the day. In the current MRgRT workflow, this requires the time consuming and repetitive task of manual delineation of organs-at-risk (OARs), which is also prone to inter- and intra-observer variability. Therefore, deep learning autosegmentation (DLAS) is becoming increasingly attractive. No investigation of its application to OARs in thoracic magnetic resonance images (MRIs) from MRgRT has been done so far. This study aimed to fill this gap. Materials and methods 122 planning MRIs from patients treated at a 0.35 T MR-Linac were retrospectively collected. Using an 80/19/23 (training/validation/test) split, individual 3D U-Nets for segmentation of the left lung, right lung, heart, aorta, spinal canal and esophagus were trained. These were compared to the clinically used contours based on Dice similarity coefficient (DSC) and Hausdorff distance (HD). They were also graded on their clinical usability by a radiation oncologist. Results Median DSC was 0.96, 0.96, 0.94, 0.90, 0.88 and 0.78 for left lung, right lung, heart, aorta, spinal canal and esophagus, respectively. Median 95th percentile values of the HD were 3.9, 5.3, 5.8, 3.0, 2.6 and 3.5 mm, respectively. The physician preferred the network generated contours over the clinical contours, deeming 85 out of 129 to not require any correction, 25 immediately usable for treatment planning, 15 requiring minor and 4 requiring major corrections. Conclusions We trained 3D U-Nets on clinical MRI planning data which produced accurate delineations in the thoracic region. DLAS contours were preferred over the clinical contours.

In the human population, social contacts are a key for transmission of bacteria and viruses. The use of face masks seems to be critical to prevent the transmission of SARS-CoV-2 for the period, in which therapeutic interventions are lacking. In this review, we describe the history of masks from the middle age to modern times.

Purpose In 2016, the University of Munich Molecular Tumor Board (MTB) was implemented to initiate a precision oncology program. This review of cases was conducted to assess clinical implications and functionality of the program, to identify current limitations and to inform future directions of these efforts. Methods Charts, molecular profiles, and tumor board decisions of the first 1000 consecutive cases (01/2016–03/2020) were reviewed. Descriptive statistics were applied to describe relevant findings. Results Of the first 1000 patients presented to the MTB; 914 patients received comprehensive genomic profiling. Median age of patients was 56 years and 58% were female. The most prevalent diagnoses were breast (16%) and colorectal cancer (10%). Different types of targeted or genome-wide sequencing assays were used; most of them offered by the local department of pathology. Testing was technically successful in 88%. In 41% of cases, a genomic alteration triggered a therapeutic recommendation. The fraction of patients receiving a tumor board recommendation differed significantly between malignancies ranging from over 50% in breast or biliary tract to less than 30% in pancreatic cancers. Based on a retrospective chart review, 17% of patients with an MTB recommendation received appropriate treatment. Conclusion Based on these retrospective analyses, patients with certain malignancies (breast and biliary tract cancer) tend to be more likely to have actionable variants. The low rate of therapeutic implementation (17% of patients receiving a tumor board recommendation) underscores the importance of meticulous follow-up for these patients and ensuring broad access to innovative therapies for patients receiving molecular tumor profiling.

The COVID-19 pandemic is challenging modern radiation oncology. At University Hospitals, we have a mandate to offer high-end treatments to all cancer patients. However, in times of crisis we must learn to prioritize resources, especially personnel. Compromising oncological outcome will blur all statistics, therefore all measures must be taken with great caution. Communication with our neighboring countries, within societies and between departments can help meet the challenge. Here, we report on our learning system and preparation measures to effectively tackle the COVID-19 challenge in University-Based Radiation Oncology Departments.

Deep learning models based on medical images play an increasingly important role for cancer outcome prediction. The standard approach involves usage of convolutional neural networks (CNNs) to automatically extract relevant features from the patient’s image and perform a binary classification of the occurrence of a given clinical endpoint. In this work, a 2D-CNN and a 3D-CNN for the binary classification of distant metastasis (DM) occurrence in head and neck cancer patients were extended to perform time-to-event analysis. The newly built CNNs incorporate censoring information and output DM-free probability curves as a function of time for every patient. In total, 1037 patients were used to build and assess the performance of the time-to-event model. Training and validation was based on 294 patients also used in a previous benchmark classification study while for testing 743 patients from three independent cohorts were used. The best network could reproduce the good results from 3-fold cross validation [Harrell’s concordance indices (HCIs) of 0.78, 0.74 and 0.80] in two out of three testing cohorts (HCIs of 0.88, 0.67 and 0.77). Additionally, the capability of the models for patient stratification into high and low-risk groups was investigated, the CNNs being able to significantly stratify all three testing cohorts. Results suggest that image-based deep learning models show good reliability for DM time-to-event analysis and could be used for treatment personalisation.

PurposeModern breast cancer radiotherapy techniques, such as respiratory-gated radiotherapy in deep-inspiration breath-hold (DIBH) or volumetric-modulated arc radiotherapy (VMAT) have been shown to reduce the high dose exposure of the heart in left-sided breast cancer. The aim of the present study was to comparatively estimate the excess relative and absolute risks of radiation-induced secondary lung cancer and ischemic heart disease for different modern radiotherapy techniques.MethodsFour different treatment plans were generated for ten computed tomography data sets of patients with left-sided breast cancer, using either three-dimensional conformal radiotherapy (3D-CRT) or VMAT, in free-breathing (FB) or DIBH. Dose–volume histograms were used for organ equivalent dose (OED) calculations using linear, linear–exponential, and plateau models for the lung. A linear model was applied to estimate the long-term risk of ischemic heart disease as motivated by epidemiologic data. Excess relative risk (ERR) and 10-year excess absolute risk (EAR) for radiation-induced secondary lung cancer and ischemic heart disease were estimated for different representative baseline risks.ResultsThe DIBH maneuver resulted in a significant reduction of the ERR and estimated 10-year excess absolute risk for major coronary events compared to FB in 3D-CRT plans (p = 0.04). In VMAT plans, the mean predicted risk reduction through DIBH was less pronounced and not statistically significant (p = 0.44). The risk of radiation-induced secondary lung cancer was mainly influenced by the radiotherapy technique, with no beneficial effect through DIBH. VMAT plans correlated with an increase in 10-year EAR for radiation-induced lung cancer as compared to 3D-CRT plans (DIBH p = 0.007; FB p = 0.005, respectively). However, the EARs were affected more strongly by nonradiation-associated risk factors, such as smoking, as compared to the choice of treatment technique.ConclusionThe results indicate that 3D-CRT plans in DIBH pose the lowest risk for both major coronary events and secondary lung cancer.