Процес «Спілки Визволення України» та зростання селянського опору в умовах суцільної колективізації

Мета даної роботи полягає у з’ясуванні механізму використання матеріалів процесу «СВУ» на території сучасної Чернігівщини, пропагандистських цілях та реакції на нього з боку як населення, лояльного до влади, так і селян, які вперто чинили опір політиці колективізації

Intra-fractional per-beam adaptive workflow to mitigate the need for a rotating gantry during MRI-guided proton therapy

The integration of real-time magnetic resonance imaging (MRI) guidance and proton therapy would potentially improve the proton dose steering capability by reducing daily uncertainties due to anatomical variations. The use of a fixed beamline coupled with an axial patient couch rotation would greatly simplify the proton delivery with MRI guidance. Nonetheless, it is mandatory to assure that the plan quality is not deteriorated by the anatomical deformations due to patient rotation. In this work, an in-house tool allowing for intra-fractional per-beam adaptation of intensity-modulated proton plans (BeamAdapt) was implemented through features available in RayStation. A set of three MRIs was acquired for two healthy volunteers (V1, V2): (1) no rotation/static, (2) rotation to the right and (3) left. V1 was rotated by 15°, to simulate a clinical pediatric abdominal case and V2 by 45°, to simulate an extreme patient rotation case. For each volunteer, a total of four intensity-modulated pencil beam scanning plans were optimized on the static MRI using virtual abdominal targets and two-three posterior-oblique beams. Beam angles were defined according to the angulations on the rotated MRIs. With BeamAdapt, each original plan was initially converted into separate plans with one beam per plan. In an iterative order, individual beam doses were non-rigidly deformed to the rotated anatomies and re-optimized accounting for the consequent deformations and the beam doses delivered so far. For evaluation, the final accumulated dose distribution was propagated back to the static MRI. Planned and adapted dose distributions were compared by computing relative differences between dose-volume histogram metrics. Absolute target dose differences were on average below 1% and organs-at-risk mean dose differences were below 3%. With BeamAdapt, not only intra-fractional per-beam proton plan adaptation coupled with axial patient rotation is possible but also the need for a rotating gantry during MRI guidance might be mitigated

Technical Note: Intensity-based quality assurance criteria for deformable image registration in image-guided radiotherapy

BACKGROUND: Deformable image registration is increasingly used in radiotherapy to adapt the treatment plan and accumulate the delivered dose. Consequently, clinical workflows using deformable image registration require quick and reliable quality assurance to accept registrations. Additionally, for online adaptive radiotherapy, quality assurance without the need for an operator to delineate contours while the patient is on the treatment table is needed. Established quality assurance criteria such as the Dice similarity coefficient or Hausdorff distance lack these qualities and also display a limited sensitivity to registration errors beyond soft tissue boundaries. PURPOSE: The purpose of this study is to investigate the existing intensity-based quality assurance criteria structural similarity and normalized mutual information for their ability to quickly and reliably identify registration errors for (online) adaptive radiotherapy and compare them to contour-based quality assurance criteria. METHODS: All criteria were tested using synthetic and simulated biomechanical deformations of 3D MR images as well as manually annotated 4D CT data. The quality assurance criteria were scored for classification performance, for their ability to predict the registration error, and for their spatial information. RESULTS: We found that besides being fast and operator-independent, the intensity-based criteria have the highest area under the receiver operating characteristic curve and provide the best input for models to predict the registration error on all data sets. Structural similarity furthermore provides spatial information with a higher gamma pass rate of the predicted registration error than commonly used spatial quality assurance criteria. CONCLUSIONS: Intensity-based quality assurance criteria can provide the required confidence in decisions about using mono-modal registrations in clinical workflows. They thereby enable automated quality assurance for deformable image registration in adaptive radiotherapy treatments

Deep learning prediction of proton and photon dose distributions for paediatric abdominal tumours

OBJECTIVE: Dose prediction using deep-learning networks prior to radiotherapy might lead to more efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess their clinical usage for paediatric abdominal tumours. MATERIAL &METHODS: Data from 80 patients with neuroblastoma or Wilms' tumour was included. Pencil beam scanning (PBS) (5mm/3%) and volumetric-modulated arc therapy (VMAT) plans (5mm) were robustly optimized on the internal target volume (ITV). Separate 3-dimensional patch-based U-net networks were trained to predict PBS and VMAT dose distributions. Doses, planning-computed tomography images and relevant optimization masks (ITV, vertebra and organs-at-risk) of 60 patients were used for training with a 5-fold cross validation. The networks' performance was evaluated by computing the relative error between planned and predicted dose-volume histogram (DVH) parameters for 20 inference patients. In addition, the organs-at-risk mean dose difference between modalities was calculated using planned and predicted dose distributions (ΔDmean= DVMAT-DPBS). Two radiation oncologists performed a blind PBS/VMAT modality selection based on either planned or predicted ΔDmean. RESULTS: Average DVH differences between planned and predicted dose distributions were ≤|6%|for both modalities. The networks classified the organs-at-risk difference as a gain (ΔDmean>0) with 98% precision. An identical modality selection based on planned compared to predicted ΔDmean was made for 18/20 patients. CONCLUSION: Deep-learning networks for accurate prediction of proton and photon dose distributions for abdominal paediatric tumours were established. These networks allowing fast dose visualization might aid in identifying the optimal radiotherapy technique when experience and/or resources are unavailable

Dosimetric evaluation of off-axis fields and angular transmission for the 1.5 T MR-linac

Objective. GPU-oriented Monte Carlo dose (GPUMCD) is a fast dose calculation algorithm used for treatment planning on the Unity MR-linac. Treatments for the MR-linac must be calculated quickly and accurately, and must account for two important MR-linac aspects: off-axis positions and angular transmission through the cryostat, couch and MR-coils. Therefore, the aim of this research is to quantify the system-related errors for GPUMCD calculations over the range of clinically-relevant field configurations and gantry angles. Approach. Dose profiles (crossline, inline and PDD) were measured and calculated for varying field sizes, off-axis positions and depths. Eleven different (off-axis) positions were included. The angular transmission was investigated by measuring and calculating the transmission for multiple angles, taking the cryostat, couch and coils into account. Main results. Differences between absolute point doses were found to be within 1.7% for field sizes 2 × 2 cm2 and larger. The relative dose profiles in the crossline, inline and PDD direction illustrated maximum mean dose differences of 0.9pp, 0.8pp and 0.7pp of D max in the central region for field sizes 2 × 2 cm2 and larger. The 1 × 1 cm2 field size showed larger dosimetric errors for absolute point doses and relative dose profiles. The maximum mean DTA in the penumbra was 0.7 mm. The mean difference in angular transmission ranged from −0.33% ± 0.60% to 0.27% ± 0.91% using three treatment machines. Additionally, 77.1%-93.7% of the datapoints remained within 1% transmission difference. The largest transmission differences were present at the edges of the table. Significance. This research showed that the GPUMCD algorithm provides reliable dose calculations with a low uncertainty for field sizes 2 × 2 cm2 and larger, focusing on off-axis fields and angular transmission

Seminal vesicle intrafraction motion during the delivery of radiotherapy sessions on a 1.5 T MR-Linac

Purpose To evaluate seminal vesicle (SV) intrafraction motion using cinematic magnetic resonance imaging (cine-MR) during the delivery of online adaptive MR-Linac radiotherapy fractions, in preparation of MR-guided extremely hypofractionated radiotherapy for intermediate to high-risk prostate cancer patients. Material and Methods Fifty prostate cancer patients were treated with 5 × 7.25 Gy on a 1.5 Tesla MR-Linac. 3D Cine-MR imaging was started simultaneously and acquired over the full beam-on period. Intrafraction motion in this cine-MR was determined for each SV separately with a previously validated soft-tissue contrast-based tracking algorithm. Motion statistics and coverage probability for the SVs and prostate were determined based on the obtained results. Results SV motion was automatically determined during the beam-on period (approx. 10 min) for 247 fractions. SV intrafraction motion shows larger spread than prostate intrafraction motion and increases over time. This difference is especially evident in the anterior and cranial translation directions. Significant difference in rotation about the left–right axis was found, with larger rotation for the SVs than the prostate. Intra-fraction coverage probability of 99% can be achieved when using 5 mm isometric expansion for the left and right SV and 3 mm for the prostate. Conclusion This is the first study to investigate SV intrafraction motion during MR-guided RT sessions on an MR-Linac. We have shown that high quality 3D cine-MR imaging and SV tracking during RT is feasible with beam-on. The tracking method as described may be used as input for a fast replanning algorithm, which allows for intrafraction plan adaptation

Dosimetric feasibility of hypofractionation for SBRT treatment of lymph node oligometastases on the 1.5T MR-linac

PURPOSE: At our department, MR-guided stereotactic body radiation therapy (SBRT) using the 1.5T MR-linac system (Unity, Elekta AB, Stockholm, Sweden) has been initiated for patients with lymph node oligometastases. Superior soft tissue contrast and the possibility for online plan adaptation on the Unity may allow for hypofractionated treatment. The purpose of this study was to investigate the dosimetric feasibility and compare the plan quality of different hypofractionated schemes. METHODS AND MATERIALS: Data was used from 12 patients with single lymph node oligometastases (10 pelvic, 2para-aortic), which were all treated on the Unity with a prescribed dose of 5x7 Gy to 95% of the PTV. Hypofractionation was investigated for 3x10 Gy and 1x20 Gy schemes (all 60 Gy BED α/ β=10). The pre-treatment plans were evaluated based on dose criteria and plan quality. If all criteria were met, the number of online adapted plans which also met all dose criteria was investigated. For pre-treatment plans meeting the criteria for all three fractionation schemes, the plan quality after online adaptation was compared using the four parameters described in the NRG-BR001 phase 1 trial. RESULTS: Pre-treatment plans met all clinical criteria for the three different fractionation schemes in 10, 9 and 6 cases. 50/50, 45/45 17/30 of the corresponding online adapted plans met all criteria, respectively. Violations were primarily caused by surrounding organs at risk overlapping or adjacent to the PTV. The 1x20 Gy treatment plans were, in general, of lesser quality than the 5x7 Gy and 3x10 Gy plans. CONCLUSION: Hypofractionated radiotherapy for lymph node oligometastases on the 1.5T MR-linac is feasible based on dose criteria and plan quality metrics. The location of the target relative to critical structures should be considered in choosing the most suitable fractionation scheme. Especially for single fraction treatment, meeting all dose criteria in the pre-treatment situation does not guarantee that this also applies during online treatment

Prostate intrafraction motion during the preparation and delivery of MR-guided radiotherapy sessions on a 1.5T MR-Linac

Purpose: To evaluate prostate intrafraction motion using MRI during the full course of online adaptive MR-Linac radiotherapy (RT) fractions, in preparation of MR-guided extremely hypofractionated RT. Material and methods: Five low and intermediate risk prostate cancer patients were treated with 20 × 3.1 Gy fractions on a 1.5T MR-Linac. Each fraction, initial MRI (Pre) scans were obtained at the start of every treatment session. Pre-treatment planning MRI contours were propagated and adapted to this Pre scan after which plan re-optimization was started in the treatment planning system followed by dose delivery. 3D Cine-MR imaging was started simultaneously with beam-on and acquired over the full beam-on period. Prostate intrafraction motion in this cine-MR was determined with a previously validated soft-tissue contrast based tracking algorithm. In addition, absolute accuracy of the method was determined using a 4D phantom. Results: Prostate motion was completely automatically determined over the full on-couch period (approx. 45 min) with no identified mis-registrations. The translation 95% confidence intervals are within clinically applied margins of 5 mm, and plan adaption for intrafraction motion was required in only 4 out of 100 fractions. Conclusion: This is the first study to investigate prostate intrafraction motions during entire MR-guided RT sessions on an MR-Linac. We have shown that high quality 3D cine-MR imaging and prostate tracking during RT is feasible with beam-on. The clinically applied margins of 5 mm have proven to be sufficient for these treatments and may potentially be further reduced using intrafraction plan adaptation guided by cine-MR imaging

ReconSocket : A low-latency raw data streaming interface for real-time MRI-guided radiotherapy

With the recent advent of hybrid MRI-guided radiotherapy systems, continuous intra-fraction MR imaging for motion monitoring has become feasible. The ability to perform real-time custom image reconstructions is however often lacking. In this work we present a low-latency streaming solution, ReconSocket, which provides a real-time stream of k-space data from the magnetic resonance imaging (MRI) to custom reconstruction servers. We determined the performance of the data streaming by measuring the streaming latency (i.e. non-zero time delay due to data transfer and processing) and jitter (i.e. deviations from periodicity) using an ultra-fast 1D MRI acquisition of a moving phantom. Simultaneously, its position was recorded with near-zero time delay. The feasibility of low-latency custom reconstructions was tested by measuring the imaging latency (i.e. time delay between physical change and appearance of that change on the image) for several non-Cartesian 2D and 3D acquisitions using an in-house implemented reconstruction server. The measured streaming latency of the ReconSocket interface was ms. 98% of the incoming data packets arrived within a jitter range of 367 s. This shows that the ReconSocket interface can provide reliable real-time access to MRI data, acquired during the course of a MRI-guided radiotherapy fraction. The total imaging latency was measured to be 221 ms (2D) and 3889 ms (3D) for exemplary acquisitions, using the custom image reconstruction server. These imaging latencies are approximately equal to half of the temporal footprint (T acq/2) of the respective 2D and 3D golden-angle radial sequences. For radial sequences, it was previously showed that T acq/2 is the expected contribution of only the data acquisition to the total imaging latency. Indeed, the contribution of the non-Cartesian reconstruction to the total imaging latency was minor (<10%): 21 ms for 2D, 300 ms for 3D, indicating that the acquisition, i.e. the physical encoding of the image itself is the major contributor to the total imaging latency