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To date, no universally accepted technique for the evaluation of the overall dosimetric performance of hybrid integrated magnetic resonance imaging (MR) – linear accelerators (linacs) is available. We report on the suitability and reliability of a novel phantom with modular inserts for combined polymer gel (PG) and ionisation chamber (IC) measurements at a 0.35 T MR-linac. Three 3D-printed, modular head phantoms, based on real patient anatomy, were used for repeated (2 times) PG irradiations of cranial treatment plans on a 0.35 T MR-linac. The PG readout was performed on two 1.5 T diagnostic MR-scanners to reduce scanning time. The PG dose volumes were normalised to the IC dose (normalised dose N1) and to the median planning target volume dose (normalised dose N2). Linearity of the PG dose response was validated and dose profiles, centres of mass (COM) of the 95% isodoses and dose volume histograms (DVH) were compared between planned and measured dose distributions and a 3D gamma analysis was performed. Dose linearity of the PG was good (R 2 > 0.99 for all linear fit functions). High agreement was found between planned and measured dose volumes in the dose profiles and DVHs. The largest dose deviation was found in the intermediate dose region (mean dose deviation 0.2 Gy; 5.6%). A mean COM offset of 1.2 mm indicated high spatial accuracy. Mean 3D gamma passing rates (2%, 2 mm) of 83.3% for N1 and 91.6% for N2 dose distributions were determined. When comparing repeated PG measurements to each other, a mean gamma passing rate of 95.7% was found. The new modular phantom was found practical for use at a 0.35 T MR-linac. In contrast to the high dose region, larger mean deviations were found in the mid dose range. The PG measurements showed high reproducibility. The MR-linac performed well in a non-adaptive setting in terms of spatial and dosimetric accuracy. [ABSTRACT FROM AUTHOR]

• GANs segment organs-at-risk in pelvic 0.35T MRIs with high accuracy. • Segmented organs: rectum, bladder and femoral heads (left and right) • Our networks generalised well on an external independent dataset. • 3D GAN outperforms its 2D equivalent in both accuracy and generation time. • This is the first attempt of organ auto-segmentation in 0.35T MRI with GANs. Manual recontouring of targets and Organs At Risk (OARs) is a time-consuming and operator-dependent task. We explored the potential of Generative Adversarial Networks (GAN) to auto-segment the rectum, bladder and femoral heads on 0.35T MRIs to accelerate the online MRI-guided-Radiotherapy (MRIgRT) workflow. 3D planning MRIs from 60 prostate cancer patients treated with 0.35T MR-Linac were collected. A 3D GAN architecture and its equivalent 2D version were trained, validated and tested on 40, 10 and 10 patients respectively. The volumetric Dice Similarity Coefficient (DSC) and 95th percentile Hausdorff Distance (HD95th) were computed against expert drawn ground-truth delineations. The networks were also validated on an independent external dataset of 16 patients. In the internal test set, the 3D and 2D GANs showed DSC/HD95th of 0.83/9.72 mm and 0.81/10.65 mm for the rectum, 0.92/5.91 mm and 0.85/15.72 mm for the bladder, and 0.94/3.62 mm and 0.90/9.49 mm for the femoral heads. In the external test set, the performance was 0.74/31.13 mm and 0.72/25.07 mm for the rectum, 0.92/9.46 mm and 0.88/11.28 mm for the bladder, and 0.89/7.00 mm and 0.88/10.06 mm for the femoral heads. The 3D and 2D GANs required on average 1.44 s and 6.59 s respectively to generate the OARs' volumetric segmentation for a single patient. The proposed 3D GAN auto-segments pelvic OARs with high accuracy on 0.35T, in both the internal and the external test sets, outperforming its 2D equivalent in both segmentation robustness and volume generation time. [ABSTRACT FROM AUTHOR]

In a radiation therapy workflow based on Magnetic Resonance Imaging (MRI), dosimetric errors may arise due to geometric distortions introduced by MRI. The aim of this study was to quantify the dosimetric effect of system-dependent geometric distortions in an MRI-only workflow for proton therapy applied at extra-cranial sites. An approach was developed, in which computed tomography (CT) images were distorted using an MRI displacement map, which represented the MR distortions in a spoiled gradient-echo sequence due to gradient nonlinearities and static magnetic field inhomogeneities. A retrospective study was conducted on 4DCT/MRI digital phantoms and 18 4DCT clinical datasets of the thoraco-abdominal site. The treatment plans were designed and separately optimized for each beam in a beam specific Planning Target Volume on the distorted CT, and the final dose distribution was obtained as the average. The dose was then recalculated in undistorted CT using the same beam geometry and beam weights. The analysis was performed in terms of Dose Volume Histogram (DVH) parameters. No clinically relevant dosimetric impact was observed on organs at risk, whereas in the target structure, geometric distortions caused statistically significant variations in the planned dose DVH parameters and dose homogeneity index (DHI). The dosimetric variations in the target structure were smaller in abdominal cases (Δ D 2% , Δ D 98% , and Δ D mean all below 0.1% and Δ DHI below 0.003) compared to the lung cases. Indeed, lung patients with tumors isolated inside lung parenchyma exhibited higher dosimetric variations (Δ D 2% ≥ 0.3%, Δ D 98% ≥ 15.9%, Δ D mean ≥ 3.3% and Δ DHI ≥ 0.102) than lung patients with tumor close to soft tissue (Δ D 2% ≤ 0.4%, Δ D 98% ≤ 5.6%, Δ D mean ≤ 0.9% and Δ DHI ≤ 0.027) potentially due to higher density variations along the beam path. Results suggest the potential applicability of MRI-only proton therapy, provided that specific analysis is applied for isolated lung tumors. [ABSTRACT FROM AUTHOR]

Ventilation-induced tumour motion remains a challenge for the accuracy of proton therapy treatments in lung patients. We investigated the feasibility of using a 4D virtual CT (4D-vCT) approach based on deformable image registration (DIR) and motion-aware 4D CBCT reconstruction (MA-ROOSTER) to enable accurate daily proton dose calculation using a gantry-mounted CBCT scanner tailored to proton therapy. Ventilation correlated data of 10 breathing phases were acquired from a porcine ex-vivo functional lung phantom using CT and CBCT. 4D-vCTs were generated by (1) DIR of the mid-position 4D-CT to the mid-position 4D-CBCT (reconstructed with the MA-ROOSTER) using a diffeomorphic Morphons algorithm and (2) subsequent propagation of the obtained mid-position vCT to the individual 4D-CBCT phases. Proton therapy treatment planning was performed to evaluate dose calculation accuracy of the 4D-vCTs. A robust treatment plan delivering a nominal dose of 60 Gy was generated on the average intensity image of the 4D-CT for an approximated internal target volume (ITV). Dose distributions were then recalculated on individual phases of the 4D-CT and the 4D-vCT based on the optimized plan. Dose accumulation was performed for 4D-vCT and 4D-CT using DIR of each phase to the mid position, which was chosen as reference. Dose based on the 4D-vCT was then evaluated against the dose calculated on 4D-CT both, phase-by-phase as well as accumulated, by comparing dose volume histogram (DVH) values (D mean , D 2% , D 98% , D 95%) for the ITV, and by a 3D-gamma index analysis (global, 3%/3 mm, 5 Gy, 20 Gy and 30 Gy dose thresholds). Good agreement was found between the 4D-CT and 4D-vCT-based ITV-DVH curves. The relative differences ((CT-vCT)/CT) between accumulated values of ITV D mean , D 2% , D 95% and D 98% for the 4D-CT and 4D-vCT-based dose distributions were −0.2%, 0.0%, −0.1% and −0.1%, respectively. Phase specific values varied between −0.5% and 0.2%, −0.2% and 0.5%, −3.5% and 1.5%, and −5.7% and 2.3%. The relative difference of accumulated D mean over the lungs was 2.3% and D mean for the phases varied between −5.4% and 5.8%. The gamma pass-rates with 5 Gy, 20 Gy and 30 Gy thresholds for the accumulated doses were 96.7%, 99.6% and 99.9%, respectively. Phase-by-phase comparison yielded pass-rates between 86% and 97%, 88% and 98%, and 94% and 100%. Feasibility of the suggested 4D-vCT workflow using proton therapy specific imaging equipment was shown. Results indicate the potential of the method to be applied for daily 4D proton dose estimation. [ABSTRACT FROM AUTHOR]

Inter-fractional variations of breathing pattern and patient anatomy introduce dose uncertainties in proton therapy. One approach to monitor these variations is to utilize the cone-beam computed tomography (CT, CBCT) scans routinely taken for patient positioning, reconstruct them as 4DCBCTs, and generate 'virtual CTs' (vCTs), combining the accurate CT numbers of the diagnostic 4DCT and the geometry of the daily 4DCBCT by using deformable image registration (DIR). In this study different algorithms for 4DCBCT reconstruction and DIR were evaluated. For this purpose, CBCT scans of a moving ex vivo porcine lung phantom with 663 and 2350 projections respectively were acquired, accompanied by an additional 4DCT as reference. The CBCT projections were sorted in 10 phase bins with the Amsterdam-shroud method and reconstructed phase-by-phase using first a FDK reconstruction from the Reconstruction Toolkit (RTK) and again an iterative reconstruction algorithm implemented in the Gadgetron Toolkit. The resulting 4DCBCTs were corrected by DIR of the corresponding 4DCT phases, using both a morphons algorithm from REGGUI and a b-spline deformation from Plastimatch. The resulting 4DvCTs were compared to the 4DCT by visual inspection and by calculating water equivalent thickness (WET) maps from the phantom's surface to the distal edge of a target from various angles. The optimized procedure was successfully repeated with mismatched input phases and on a clinical patient dataset. Proton treatment plans were simulated on the 4DvCTs and the dose distributions compared to the reference based on the 4DCT via gamma pass rate analysis. A combination of iterative reconstruction and morphons DIR yielded the most accurate 4DvCTs, with median WET differences under 2 mm and 3%/3 mm gamma pass rates per phase between 89% and 99%. These results suggest that image correction of iteratively reconstructed 4DCBCTs with a morphons DIR of the planning CT may yield sufficiently accurate 4DvCTs for daily time resolved proton dose calculations. [ABSTRACT FROM AUTHOR]

Proton radiotherapy (PT) requires accurate target alignment before each treatment fraction, ideally utilizing 3D in-room X-ray computed tomography (CT) imaging. Typically, the optimal patient position is determined based on anatomical landmarks or implanted markers. In the presence of non-rigid anatomical changes, however, the planning scenario cannot be exactly reproduced and positioning should rather aim at finding the optimal position in terms of the actually applied dose. In this work, dose-guided patient alignment, implemented as multicriterial optimization (MCO) problem, was investigated in the scope of intensity-modulated and double-scattered PT (IMPT and DSPT) for the first time. A method for automatically determining the optimal patient position with respect to pre-defined clinical goals was implemented. Linear dose interpolation was used to access a continuous space of potential patient shifts. Fourteen head and neck (H&N) and eight prostate cancer patients with up to five repeated CTs were included. Dose interpolation accuracy was evaluated and the potential dosimetric advantages of dose-guided over bony-anatomy-based patient alignment investigated by comparison of clinically relevant target and organ-at-risk (OAR) dose-volume histogram (DVH) parameters. Dose interpolation was found sufficiently accurate with average pass-rates of 90% and 99% for an exemplary H&N and prostate patient, respectively, using a 2% dose-difference criterion. Compared to bony-anatomy-based alignment, the main impact of automated MCO-based dose-guided positioning was a reduced dose to the serial OARs (spinal cord and brain stem) for the H&N cohort. For the prostate cohort, under-dosage of the target structures could be efficiently diminished. Limitations of dose-guided positioning were mainly found in reducing target over-dosage due to weight loss for H&N patients, which might require adaptation of the treatment plan. Since labor-intense online quality-assurance is not required for dose-guided patient positioning, it might, nevertheless, be considered an interesting alternative to full online re-planning for initially mitigating the effects of anatomical changes. [ABSTRACT FROM AUTHOR]

Proton beams used for radiotherapy have potential for superior sparing of normal tissue, although range uncertainties are among the main limiting factors in the accuracy of dose delivery. The aim of this study was to benchmark an N-vinylpyrrolidone based polymer gel to perform three-dimensional measurement of geometric proton beam characteristics and especially to test its suitability as a range probe in combination with an anthropomorphic phantom. For single proton pencil beams as well as for 3 × 3 cm2 mono-energy layers depth dose profiles, lateral dose distribution at different depths and proton range were evaluated in simple cubic gel phantoms at different energies from 75 to 115 MeV and different dose levels. In addition, a 90 MeV mono-energetic beam was delivered to an anthropomorphic 3D printed head phantom, which was filled with gel. Subsequently, all phantoms underwent magnetic resonance imaging using an axial pixel size of 0.68–0.98 mm and with slice thicknesses of 2 or 3 mm to derive a 3-dimensional distribution of the T 2 relaxation time, which correlates with radiation dose. Indices describing lateral dose distribution and proton range were compared against predictions from a treatment planning system (TPS, for cubic and head phantoms) and Monte Carlo simulations (MC, for the head phantom) after manual rigid co-registration with the T 2 relaxation time datasets. For all pencil beams, the FWHM agreement with TPS was better than 1 mm or 7%. For the mono-energetic layer, the agreement with TPS in this respect was even better than 0.3 mm in each case. With respect to range, results from gel measurements differed no more than 0.9 mm (1.6%) from values predicted by TPS. In case of the anthropomorphic phantom, deviations with respect to a nominal range of about 61 mm as well as in FWHM were slightly higher, namely within 1.0 mm and 1.1 mm respectively. Average deviations between gel and TPS/MC were similar (−0.3 mm ± 0.4 mm/−0.2 ± 0.5 mm). In conclusion, polymer gel dosimetry was found to be a valuable tool to determine geometric proton beam properties three-dimensionally and with high spatial resolution in simple cubic as well as in a more complex anthropomorphic phantom. Post registration range errors of the order of 1 mm could be achieved. The additional registration uncertainty (95%) was 1 mm. [ABSTRACT FROM AUTHOR]

This report, compiled by experts on the treatment of mobile targets with advanced radiotherapy, summarizes the main conclusions and innovations achieved during the 4D treatment planning workshop 2013. This annual workshop focuses on research aiming to advance 4D radiotherapy treatments, including all critical aspects of time resolved delivery, such as in-room imaging, motion detection, motion managing, beam application, and quality assurance techniques. The report aims to revise achievements in the field and to discuss remaining challenges and potential solutions. As main achievements advances in the development of a standardized 4D phantom and in the area of 4D-treatment plan optimization were identified. Furthermore, it was noticed that MR imaging gains importance and high interest for sequential 4DCT/MR data sets was expressed, which represents a general trend of the field towards data covering a longer time period of motion. A new point of attention was work related to dose reconstructions, which may play a major role in verification of 4D treatment deliveries. The experimental validation of results achieved by 4D treatment planning and the systematic evaluation of different deformable image registration methods especially for inter-modality fusions were identified as major remaining challenges. A challenge that was also suggested as focus for future 4D workshops was the adaptation of image guidance approaches from conventional radiotherapy into particle therapy. Besides summarizing the last workshop, the authors also want to point out new evolving demands and give an outlook on the focus of the next workshop. [ABSTRACT FROM AUTHOR]

Purpose The clinical introduction of an MR-guided radiotherapy unit offers great potential to improve future patient treatment but is at the same time associated with several challenges from the perspective of medical physics. Before the final implementation of an MR-Linac in our clinical environment several preliminary studies are performed to prepare the introduction of the new system into the routine patient care as well as covering medical physics related research aspects. Methods One focus of the projects is a comparison of the adaptive workflow based on daily MR and daily cone beam CT imaging. In order to mimic the MR-guided radiotherapy workflow an MR-compatible flat table top is equipped with immobilization devices for offline MR imaging in treatment position. A flexible, modular phantom is developed based on lego bricks, enabling fast distortion phantom prototyping and consequently distortion measurements. The effect of magnetic fields on dose measurements with thermoluminescent dosimeters is evaluated. Image registration methods are applied to time-resolved 4D MR and 4D CT images of patients as well as to breathing phantoms evaluating how to include 4D data into the online adaptive treatment workflow. Results The preliminary results of the projects mentioned above will be presented and discussed. This includes a comparison of CT- and MR-based internal target volume concepts as a surrogate for reproducibility of breathing motion of the patient, the first results of the 4D phantom studies and the TLD measurements in a magnetic field. Conclusions Several studies are performed at the university hospital of the LMU in Munich to pave the way for a smooth introduction of the MR-Linac into clinical routine and into research in MR-guided radiotherapy. [ABSTRACT FROM AUTHOR]

The adoption of cone beam computed tomography (CBCT) image guidance in proton therapy has spurred research on CBCT image correction for dose calculation. Initially, methods based on deformable image registration gained attention [1] , however projection correction approaches based on prior CT information [2] have been shown to perform well for several body sites [3] . The shading correction algorithm used in [2,3] relies on image processing of the subtraction of digitally reconstructed radiographs (DRR) of a DIR-registered prior CT, and CBCT projections. In this study we have performed Monte Carlo (MC) simulation of CBCT imaging to disentangle the different sources of projection degradation, and to evaluate the physicality of the shading correction. The GATE MC toolkit’s fixed-forced-detection actor was employed, along with source and detector models optimized for an Elekta XVI CBCT system, to simulate CBCT imaging of an electron density phantom. The shading correction algorithm was applied to the measured projections and the so-called scatter component (SCA) was compared to the MC simulated scatter. Measured and simulated CBCT projections (scatter + primary) agreed well, with the largest discrepancy found for a bone insert (3% of log transformed projections). Important disagreement was observed with the MC scatter signal when the contribution from beam hardening was kept in the SCA. Undoing the beam hardening correction from the SCA using functions derived from MC primary projections and DRRs greatly improved agreement of scatter signals from MC and SCA (3% on average), with the largest discrepancy found for the bone insert (12%). Residual discrepancies were shown to stem from the intrinsic limitations of the SCA. Proton therapy dose calculations on corrected CBCT will be presented in addition to the results above. [ABSTRACT FROM AUTHOR]

Purpose This study investigates for the first time the feasibility of using deep learning for cone-beam CT (CBCT) intensity correction to enable accurate daily dose calculation and treatment adaptation in volumetric-modulated arc therapy (VMAT) and intensity-modulated proton therapy (IMPT). Current CBCT intensity correction approaches often show a lack of either speed or accuracy, which might be overcome by deep learning approaches. Methods Pre-treatment CBCTs and corresponding projections of 30 prostate cancer patients were considered. A previously validated technique for CBCT intensity correction, based on deformable image registration (DIR) of the planning CT to the daily CBCT and scatter estimation in projection space, served as reference (CBCT cor ) [1] . Two alternative methods were investigated: A U-shaped deep convolutional neural network (U-Net) was trained to perform scatter correction in projection space, i.e., going from measured to corrected projections before reconstruction (CBCT ScatterNet ). Moreover, a generative adversarial network (GAN) was trained to perform a translation from the original CBCT (CBCT org ) to CBCT cor in image space, generating a so-called CBCT corGAN . CBCT ScatterNet and CBCT corGAN were compared to CBCT cor in terms of mean absolute error (MAE) and mean error (ME). For eight exemplary patients, dose calculation accuracy in VMAT and IMPT was evaluated with respect to CBCT org . Results Both, CBCT ScatterNet and CBCT corGAN , showed a substantially improved agreement to CBCT cor compared to CBCT org . Mean MAE and ME decreased from 158HU and 152HU for CBCT org to 39HU and 4HU for CBCT ScatterNet and 57HU and −2HU for CBCT corGAN , respectively. In a 2% dose-difference test, considering only voxels above 50% of the prescribed dose, mean pass-rates were 53% and 64% for CBCT ScatterNet and CBCT corGAN in IMPT. In VMAT, pass-rates of 90% and 97% were obtained for CBCT ScatterNet and CBCT corGAN using a 1% dose-difference criterion. Conclusions CBCT intensity correction using two different implementations of deep learning was found feasible. For VMAT, dose calculation accuracy was high, while for IMPT further improvements may be required. Compared to the reference correction method, deep learning techniques were less affected by DIR inaccuracies and allowed considerably faster CBCT correction within few seconds instead of minutes. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this paper is to describe the experiments and methods that led to the geometrical interpretation of new-generation commercial PET-CT scanners, finalized to off-line PET-based treatment verification in ion beam therapy. Typically, the geometrical correspondence between the image domain (i.e., the dicom PET) and the sinogram domain (i.e., the PET raw data) is not explicitly described by scanner vendors. Hence, the proposed characterization can be applied to commercial PET-CT scanners used in biomedical research, for the development of technologies and methods requiring the use of PET raw data, without having access to confidential information from the vendors. [Copyright &y& Elsevier]

Abstract: Background and purpose: We report on the implementation of offline PET/CT-based treatment verification at the Heidelberg Ion Beam Therapy Centre (HIT) and present first clinical cases for post-activation measurements after scanned carbon ion irradiation. Key ingredient of this in-vivo treatment verification is the comparison of irradiation-induced patient activation measured by a PET scanner with a prediction simulated by means of Monte Carlo techniques. Material and methods: At HIT, a commercial full-ring PET/CT scanner has been installed in close vicinity to the treatment rooms. After selected irradiation fractions, the patient either walks to the scanner for acquisition of the activation data or is transported using a shuttle system. The expected activity distribution is obtained from the production of β+-active isotopes simulated by the FLUKA code on the basis of the patient-specific treatment plan, post-processed considering the time course of the respective treatment fraction, the estimated biological washout of the induced activity and a simplified model of the imaging process. Results: We present four patients with different indications of head, head/neck, liver and pelvic tumours. A clear correlation between the measured PET signal and the simulated activity pattern is observed for all patients, thus supporting a proper treatment delivery. In the case of a pelvic tumour patient it was possible to detect minor treatment delivery inaccuracies. Conclusions: The initial clinical experience proves the feasibility of the implemented strategy for offline confirmation of scanned carbon ion irradiation and therefore constitutes a first step towards a comprehensive PET/CT-based treatment verification in the clinical routine at HIT. [Copyright &y& Elsevier]