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Aims With interest in normal tissue sparing and dose-escalated radiotherapy in the treatment of inoperable locally advanced non-small cell lung cancer, this study investigated the impact of motion-managed moderate deep inspiration breath hold (mDIBH) on normal tissue sparing and dose-escalation potential and compared this to planning with a four-dimensional motion-encompassing internal target volume or motion-compensating mid-ventilation approach. Materials and methods Twenty-one patients underwent four-dimensional and mDIBH planning computed tomography scans. Internal and mid-ventilation target volumes were generated on the four-dimensional scan, with mDIBH target volumes generated on the mDIBH scan. Isotoxic target dose-escalation guidelines were used to generate six plans per patient: three with a target dose cap and three without. Target dose-escalation potential, normal tissue complication probability and differences in pre-specified dose-volume metrics were evaluated for the three motion-management techniques. Results The mean total lung volume was significantly greater with mDIBH compared with four-dimensional scans. Lung dose (mean and V21 Gy) and mean heart dose were significantly reduced with mDIBH in comparison with four-dimensional-based approaches, and this translated to a significant reduction in heart and lung normal tissue complication probability with mDIBH. In 20/21 patients, the trial target prescription dose cap of 79.2 Gy was achievable with all motion-management techniques. Conclusion mDIBH aids lung and heart dose sparing in isotoxic dose-escalated radiotherapy compared with four-dimensional planning techniques. Given concerns about lung and cardiac toxicity, particularly in an era of consolidation immunotherapy, reduced normal tissue doses may be advantageous for treatment tolerance and outcome.

Highlights • The MR-Linac provides the tools to deliver online MR-guided Adaptive Radiotherapy • Adapt-to-Shape-Lite is a novel radiotherapy planning workflow on the Elekta Unity MR-Linac • Adapt-to-Shape-Lite generated plans that fulfilled 99.9% of mandatory dose constraints • Adapt-to-Shape-Lite workflow can generate plans in relatively short durations • Therefore, we prefer Adapt-To-Shape-Lite as the primary workflow to treat Head-and-Neck cancers, Introduction The Elekta Unity MR-Linac (MRL) has enabled adaptive radiotherapy (ART) for patients with head and neck cancers (HNC). Adapt-To-Shape-Lite (ATS-Lite) is a novel Adapt-to-Shape strategy that provides ART without requiring daily clinician presence to perform online target and organ at risk (OAR) delineation. In this study we compared the performance of our clinically-delivered ATS-Lite strategy against three Adapt-To-Position (ATP) variants: Adapt Segments (ATP-AS), Optimise Weights (ATP-OW), and Optimise Shapes (ATP-OS). Methods Two patients with HNC received radical-dose radiotherapy on the MRL. For each fraction, an ATS-Lite plan was generated online and delivered and additional plans were generated offline for each ATP variant. To assess the clinical acceptability of a plan for every fraction, twenty clinical goals for targets and OARs were assessed for all four plans. Results 53 fractions were analysed. ATS-Lite passed 99.9% of mandatory dose constraints. ATP-AS and ATP-OW each failed 7.6% of mandatory dose constraints. The Planning Target Volumes for 54 Gy (D95% and D98%) were the most frequently failing dose constraint targets for ATP. ATS-Lite median fraction times for Patient 1 and 2 were 40 mins 9 s (range 28 mins 16 s – 47 mins 20 s) and 32 mins 14 s (range 25 mins 33 s – 44 mins 27 s), respectively. Conclusions Our early data show that the novel ATS-Lite strategy produced plans that fulfilled 99.9% of clinical dose constraints in a time frame that is tolerable for patients and comparable to ATP workflows. Therefore, ATS-Lite, which bridges the gap between ATP and full ATS, will be further utilised and developed within our institute and it is a workflow that should be considered for treating patients with HNC on the MRL.

Purpose: High-field magnetic resonance-linear accelerators (MR-Linacs), linear accelerators combined with a diagnostic magnetic resonance imaging (MRI) scanner and online adaptive workflow, potentially give rise to novel online anatomic and response adaptive radiation therapy paradigms. The first high-field (1.5T) MR-Linac received regulatory approval in late 2018, and little is known about clinical use, patient tolerability of daily high-field MRI, and toxicity of treatments. Herein we report the initial experience within the MOMENTUM Study (NCT04075305), a prospective international registry of the MRLinac Consortium. Methods and Materials: Patients were included between February 2019 and October 2020 at 7 institutions in 4 countries. We used descriptive statistics to describe the patterns of care, tolerability (the percentage of patients discontinuing their course early), and safety (grade 3-5 Common Terminology Criteria for Adverse Events v.5 acute toxicity within 3 months after the end of treatment). Results: A total 943 patients participated in the MOMENTUM Study, 702 of whom had complete baseline data at the time of this analysis. Patients were primarily male (79%) with a median age of 68 years (range, 22-93) and were treated for 39 different indications. The most frequent indications were prostate (40%), oligometastatic lymph node (17%), brain (12%), and rectal (10%) cancers. The median number of fractions was 5 (range, 1-35). Six patients discontinued MR-Linac treatments, but none due to an inability to tolerate repeated high-field MRI. Of the 415 patients with complete data on acute toxicity at 3 month follow-up, 18 (4%) patients experienced grade 3 acute toxicity related to radiation. No grade 4 or 5 acute toxicity related to radiation was observed. Conclusions: In the first 21 months of our study, patterns of care were diverse with respect to clinical utilization, body sites, and radiation prescriptions. No patient discontinued treatment due to inability to tolerate daily high-field MRI scans, and the acute radiation toxicity experience was encouraging. (c) 2021 Published by Elsevier Inc.

Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.

Highlights • Deep learning accelerates 4D-MRI recon for online adaptive MR-guided radiotherapy. • First reconstruction of high resolution whole thorax 4D-MRI for 16 phases in 28 s. • First use of dCNNs for midposition reconstruction from undersampled 4D-MRI in 28 s. • Excellent agreement between deep learning-based tumour midposition and reference., Background and Purpose 4D and midposition MRI could inform plan adaptation in lung and abdominal MR-guided radiotherapy. We present deep learning-based solutions to overcome long 4D-MRI reconstruction times while maintaining high image quality and short scan times. Methods Two 3D U-net deep convolutional neural networks were trained to accelerate the 4D joint MoCo-HDTV reconstruction. For the first network, gridded and joint MoCo-HDTV-reconstructed 4D-MRI were used as input and target data, respectively, whereas the second network was trained to directly calculate the midposition image. For both networks, input and target data had dimensions of 256 × 256 voxels (2D) and 16 respiratory phases. Deep learning-based MRI were verified against joint MoCo-HDTV-reconstructed MRI using the structural similarity index (SSIM) and the naturalness image quality evaluator (NIQE). Moreover, two experienced observers contoured the gross tumour volume and scored the images in a blinded study. Results For 12 subjects, previously unseen by the networks, high-quality 4D and midposition MRI (1.25 × 1.25 × 3.3 mm3) were each reconstructed from gridded images in only 28 seconds per subject. Excellent agreement was found between deep-learning-based and joint MoCo-HDTV-reconstructed MRI (average SSIM ≥ 0.96, NIQE scores 7.94 and 5.66). Deep-learning-based 4D-MRI were clinically acceptable for target and organ-at-risk delineation. Tumour positions agreed within 0.7 mm on midposition images. Conclusion Our results suggest that the joint MoCo-HDTV and midposition algorithms can each be approximated by a deep convolutional neural network. This rapid reconstruction of 4D and midposition MRI facilitates online treatment adaptation in thoracic or abdominal MR-guided radiotherapy.

Aims Target delineation uncertainty is arguably the largest source of geometric uncertainty in radiotherapy. Several factors can affect it, including the imaging modality used for delineation. It is accounted for by applying safety margins to the target to produce a planning target volume (PTV), to which treatments are designed. To determine the margin, the delineation uncertainty is measured as the delineation error, and then a margin recipe used. However, there is no published evidence of such analysis for recurrent gynaecological cancers (RGC). The aims of this study were first to quantify the delineation uncertainty for RGC gross tumour volumes (GTVs) and to calculate the associated PTV margins and then to quantify the difference in GTV, delineation uncertainty and PTV margin, between a computed tomography-magnetic resonance imaging (CT-MRI) and MRI workflow. Materials and methods Seven clinicians delineated the GTV for 20 RGC tumours on co-registered CT and MRI datasets (CT-MRI) and on MRI alone. The delineation error, the standard deviation of distances from each clinician's outline to a reference, was measured and the required PTV margin determined. Differences between using CT-MRI and MRI alone were assessed. Results The overall delineation error and the resulting margin were 3.1 mm and 8.5 mm, respectively, for CT-MRI, reducing to 2.5 mm and 7.1 mm, respectively, for MRI alone. Delineation errors and therefore the theoretical margins, varied widely between patients. MRI tumour volumes were on average 15% smaller than CT-MRI tumour volumes. Discussion This study is the first to quantify delineation error for RGC tumours and to calculate the corresponding PTV margin. The determined margins were larger than those reported in the literature for similar patients, bringing into question both current margins and margin calculation methods. The wide variation in delineation error between these patients suggests that applying a single population-based margin may result in PTVs that are suboptimal for many. Finally, the reduced tumour volumes and safety margins suggest that patients with RGC may benefit from an MRI-only treatment workflow., Highlights • The first paper to focus on recurrent gynaecological tumour radiotherapy targets • Presents values for delineation error and the corresponding safety margins • Standard methods produce margins larger than those reportedly used elsewhere • Using MRI alone results in smaller target volumes than using CT and MRI together

Highlights • Deliverable plans for 1 and 2 fraction SBRT can be created for the Unity MR-Linac. • Dose constraints and objectives from HDR and SBRT clinical studies were applied. • In 40% of 1 and 2 fraction plans target doses were compromised to meet OAR goals., The drive towards hypofractionated prostate radiotherapy is motivated by a low alpha/beta ratio for prostate cancer (1 to 3 Gy) compared to surrounding organs at risk, implying an improved therapeutic ratio with increasing dose per fraction. Early evidence from studies of ultrahypofractionated (UHF) prostate HDR brachytherapy has shown good tolerability in terms of normal tissue toxicities and clinical outcomes similar to conventional fractionation schedules. MR-guided stereotactic body radiotherapy (SBRT) with online plan adaptation and real-time tumour imaging may enable UHF doses to be delivered to the prostate safely, without the invasiveness of brachytherapy. The feasibility of UHF prostate treatment planning for the Unity MR-Linac (MRL, Elekta AB, Stockholm) was investigated for target prescriptions and planning constraints derived from the HDR brachytherapy and SBRT literature. Monaco 5.40 (Elekta) was used to generate MRL step-and-shoot IMRT plans for three dose fractionation protocols (5, 2 and 1 fractions), for ten randomly selected previously treated prostate cancer patients. Of the ten plans per UHF scheme, all clinical goals were met in all cases for 5 fractions, and in six cases for both 2 and 1 fraction schemes. PTV D95% was compromised by up to 6.4% and 3.9% of the associated target dose for 2 and 1 fraction plans respectively. There were two cases of PTV D95% compromise greater than a 5% dose decrease for the 2 fraction plans. The study suggests feasibility of the UHF treatment planning approaches if combined with real-time motion mitigation strategies.

Purpose Online adaptive radiotherapy would greatly benefit from the development of reliable auto-segmentation algorithms for organs-at-risk and radiation targets. Current practice of manual segmentation is subjective and time-consuming. While deep learning-based algorithms offer ample opportunities to solve this problem, they typically require large datasets. However, medical imaging data is generally sparse, in particular annotated MR images for radiotherapy. In this study, we developed a method to exploit the wealth of publicly available, annotated CT images to generate synthetic MR images, which could then be used to train a convolutional neural network (CNN) to segment the parotid glands on MR images of head and neck cancer patients. Methods Imaging data comprised 202 annotated CT and 27 annotated MR images. The unpaired CT and MR images were fed into a 2D CycleGAN network to generate synthetic MR images from the CT images. Annotations of axial slices of the synthetic images were generated by propagating the CT contours. These were then used to train a 2D CNN. We assessed the segmentation accuracy using the real MR images as test dataset. The accuracy was quantified with the 3D Dice similarity coefficient (DSC), Hausdorff distance (HD) and mean surface distance (MSD) between manual and auto-generated contours. We benchmarked the approach by a comparison to the inter-observer variation determined for the real MR images, as well as to the accuracy when training the 2D CNN to segment the CT images. Results The determined accuracy (DSC: 0.77±0.07, HD: 18.04±12.59 mm, MSD: 2.51 ± 1.47mm) was close to the inter-observer variation (DSC: 0.84±0.06, HD: 10.85±5.74 mm, MSD: 1.50±0.77 mm), as well as to the accuracy when training the 2D CNN to segment the CT images (DSC: 0.81±0.07, HD: 13.00±7.61 mm, MSD: 1.87±0.84 mm). Conclusion The introduced cross-modality learning technique can be of great value for segmentation problems with sparse training data. We anticipate using this method with any non-annotated MRI dataset to generate annotated synthetic MR images of the same type via image style transfer from annotated CT images. Furthermore, as this technique allows for fast adaptation of annotated datasets from one imaging modality to another, it could prove useful for translating between large varieties of MRI contrasts due to differences in imaging protocols within and between institutions.

This study aims to develop and validate a simple geometric model of the accelerator head, from which a particle phase space can be calculated for application to fast Monte Carlo dose calculation in real-time adaptive photon radiotherapy. With this objective in view, the study investigates whether the phase space model can facilitate dose calculations which are compatible with those of a commercial treatment planning system, for convenient interoperability.A dual-source model of the head of a Versa HD accelerator (Elekta AB, Stockholm, Sweden) was created. The model used parameters chosen to be compatible with those of 6-MV flattened and 6-MV flattening filter-free photon beams in the RayStation treatment planning system (RaySearch Laboratories, Stockholm, Sweden). The phase space model was used to calculate a photon phase space for several treatment plans, and the resulting phase space was applied to the Dose Planning Method (DPM) Monte Carlo dose calculation algorithm. Simple fields and intensity-modulated radiation therapy (IMRT) treatment plans for prostate and lung were calculated for benchmarking purposes and compared with the convolution-superposition dose calculation within RayStation.For simple square fields in a water phantom, the calculated dose distribution agrees to within ±2% with that from the commercial treatment planning system, except in the buildup region, where the DPM code does not model the electron contamination. For IMRT plans of prostate and lung, agreements of ±2% and ±6%, respectively, are found, with slightly larger differences in the high dose gradients.The phase space model presented allows convenient calculation of a phase space for application to Monte Carlo dose calculation, with straightforward translation of beam parameters from the RayStation beam model. This provides a basis on which to develop dose calculation in a real-time adaptive setting.

Microbeam radiotherapy (MRT) is a preclinical method of delivering spatially-fractionated radiotherapy aiming to improve the therapeutic window between normal tissue complication and tumour control. Previously, MRT was limited to ultra-high dose rate synchrotron facilities. The aim of this study was to investigate in vitro effects of MRT on tumour and normal cells at conventional dose rates produced by a bench-top X-ray source. Two normal and two tumour cell lines were exposed to homogeneous broad beam (BB) radiation, MRT, or were separately irradiated with peak or valley doses before being mixed. Clonogenic survival was assessed and compared to BB-estimated surviving fractions calculated by the linear-quadratic (LQ)-model. All cell lines showed similar BB sensitivity. BB LQ-model predictions exceeded the survival of cell lines following MRT or mixed beam irradiation. This effect was stronger in tumour compared to normal cell lines. Dose mixing experiments could reproduce MRT survival. We observed a differential response of tumour and normal cells to spatially fractionated irradiations in vitro, indicating increased tumour cell sensitivity. Importantly, this was observed at dose rates precluding the presence of FLASH effects. The LQ-model did not predict cell survival when the cell population received split irradiation doses, indicating that factors other than local dose influenced survival after irradiation., Cancers, 13 (13), ISSN:2072-6694

Geometric uncertainties in radiotherapy are conventionally addressed by defining a safety margin around the radiotherapy target. Misappropriation of such margins could result in disease recurrence from geometric miss or unnecessary irradiation of normal tissue. Numerous quantitative organ motion studies in adults have been published, but the first paediatric-specific studies were only published in recent years. In the very near future, intensity-modulated proton beam therapy and magnetic resonance-guided radiotherapy will be clinically implemented in the UK. Such techniques offer the ability to deliver radiotherapy to the pinnacle of precision and accuracy, if geometric uncertainty relating to internal organ motion and deformation can be optimally managed. The optimal margin to account for internal organ motion in children remains largely undefined. Continuing efforts to characterise motion in children and young people is necessary to optimally define safety margins and to realise the full potential of intensity-modulated radiotherapy, magnetic resonance-guided radiotherapy and intensity-modulated proton beam therapy. This overview offers a timely review of published reports on paediatric organ motion, in anticipation of the increasing application of advanced radiotherapy techniques in paediatric radiotherapy.

Highlights • A fast optimisation framework is used to create IMRT SABR plans for Cyberknife. • The value of the Cyberknife multileaf collimator is investigated. • A beam selection algorithm is used to determine a subset of beam orientations. • Fifteen selected beams are sufficient to create high-quality treatment plans. • Treatment time is minimised using this approach., The Cyberknife system (Accuray Inc., Sunnyvale, CA) enables radiotherapy using stereotactic ablative body radiotherapy (SABR) with a large number of non-coplanar beam orientations. Recently, a multileaf collimator has also been available to allow flexibility in field shaping. This work aims to evaluate the quality of treatment plans obtainable with the multileaf collimator. Specifically, the aim is to find a subset of beam orientations from a predetermined set of candidate directions, such that the treatment quality is maintained but the treatment time is reduced. An evolutionary algorithm is used to successively refine a randomly selected starting set of beam orientations. By using an efficient computational framework, clinically useful solutions can be found in several hours. It is found that 15 beam orientations are able to provide treatment quality which approaches that of the candidate beam set of 110 beam orientations, but with approximately half of the estimated treatment time. Choice of an efficient subset of beam orientations offers the possibility to improve the patient experience and maximise the number of patients treated.

Highlights • Treatment de-escalation in HPV+ oropharynx cancer is an active area of research. • A Bayesian phase II trial of MR-guided radiotherapy dose adaptation is proposed. • High dose volume will be adapted on weekly MRI based on tumor response. • The non-inferiority of dose adaptation compared to standard IMRT will be assessed., Background Current standard radiotherapy for oropharynx cancer (OPC) is associated with high rates of severe toxicities, shown to adversely impact patients’ quality of life. Given excellent outcomes of human papilloma virus (HPV)-associated OPC and long-term survival of these typically young patients, treatment de-intensification aimed at improving survivorship while maintaining excellent disease control is now a central concern. The recent implementation of magnetic resonance image – guided radiotherapy (MRgRT) systems allows for individual tumor response assessment during treatment and offers possibility of personalized dose-reduction. In this 2-stage Bayesian phase II study, we propose to examine weekly radiotherapy dose-adaptation based on magnetic resonance imaging (MRI) evaluated tumor response. Individual patient’s plan will be designed to optimize dose reduction to organs at risk and minimize locoregional failure probability based on serial MRI during RT. Our primary aim is to assess the non-inferiority of MRgRT dose adaptation for patients with low risk HPV-associated OPC compared to historical control, as measured by Bayesian posterior probability of locoregional control (LRC). Methods Patients with T1-2 N0-2b (as per AJCC 7th Edition) HPV-positive OPC, with lymph node

Adaptive online MRI-guided radiotherapy of head and neck cancer requires the reliable segmentation of the parotid glands as important organs at risk in clinically acceptable time frames. This can hardly be achieved by manual contouring. We therefore designed deep learning-based algorithms which automatically perform this task.Imaging data comprised two datasets: 27 patient MR images (T1-weighted and T2-weighted) and eight healthy volunteer MR images (T2-weighted), together with manually drawn contours by an expert. We used four different convolutional neural network (CNN) designs that each processed the data differently, varying the dimensionality of the input. We assessed the segmentation accuracy calculating the Dice similarity coefficient (DSC), Hausdorff distance (HD) and mean surface distance (MSD) between manual and auto-generated contours. We benchmarked the developed methods by comparing to the inter-observer variability and to atlas-based segmentation. Additionally, we assessed the generalisability, strengths and limitations of deep learning-based compared to atlas-based methods in the independent volunteer test dataset.With a mean DSC of 0.85± 0.11 and mean MSD of 1.82 ±1.94 mm, a 2D CNN could achieve an accuracy comparable to that of an atlas-based method (DSC: 0.85 ±0.05, MSD: 1.67 ±1.21 mm) and the inter-observer variability (DSC: 0.84 ±0.06, MSD: 1.50 ±0.77 mm) but considerably faster (±0.10, MSD: 1.72 ±0.96 mm)We demonstrated the enormous potential for the application of CNNs to segment the parotid glands for online MRI-guided radiotherapy. The short computation times render deep learning-based methods suitable for online treatment planning workflows.

Magnetic resonance imaging (MRI)-guided radiotherapy (RT) (MRIgRT) falls outside the scope of existing high energy photon therapy dosimetry protocols, because those protocols do not consider the effects of the magnetic field on detector response and on absorbed dose to water. The aim of this study is to evaluate and demonstrate the traceable measurement of absorbed dose in MRIgRT systems using alanine, made possible by the characterisation of alanine sensitivity to magnetic fields reported previously by Billas et al (2020 Phys. Med. Biol. 65 115001), in a way which is compatible with existing standards and calibrations available for conventional RT. In this study, alanine is used to transfer absorbed dose to water to MRIgRT systems from a conventional linac. This offers an alternative route for the traceable measurement of absorbed dose to water, one which is independent of the transfer using ionisation chambers. The alanine dosimetry is analysed in combination with measurements with several Farmer-type chambers, PTW 30013 and IBA FC65-G, at six different centres and two different MRIgRT systems (Elekta Unity™ and ViewRay MRIdian™). The results are analysed in terms of the magnetic field correction factors, and in terms of the absorbed dose calibration coefficients for the chambers, determined at each centre. This approach to reference dosimetry in MRIgRT produces good consistency in the results, across the centres visited, at the level of 0.4% (standard deviation). Farmer-type ionisation chamber magnetic field correction factors were determined directly, by comparing calibrations in some MRIgRT systems with and without the magnetic field ramped up, and indirectly, by comparing calibrations in all the MRIgRT systems with calibrations in a conventional linac. Calibration coefficients in the MRIgRT systems were obtained with a standard uncertainty of 1.1% (Elekta Unity™) and 0.9% (ViewRay MRIdian™), for three different chamber orientations with respect to the magnetic field. The values obtained for the magnetic field correction factor in this investigation are consistent with those presented in the summary by de Pooter et al (2021 Phys. Med. Biol. 66 05TR02), and would tend to support the adoption of a magnetic field correction factor which depends on the chamber type, PTW 30013 or IBA FC65-G.

Purpose: MR-guided Radiation Therapy (MRgRT) allows for high-precision radiotherapy under real-time MR visualization. This enables margin reduction and subsequent dose escalation which may lead to higher tumor control and less toxicity. The Unity MR-linac (Elekta AB, Stockholm, Sweden) integrates a linear accelerator with a 1.5T diagnostic quality MRI and an online adaptive workflow. A prospective international registry was established to facilitate the evidence-based implementation of the Unity MR-linac into clinical practice, to systemically evaluate long-term outcomes, and to aid further technical development of MR-linac-based MRgRT. Methods and Results: In February 2019, the Multi-OutcoMe EvaluatioN of radiation Therapy Using the MR-linac study (MOMENTUM) started within the MR-linac Consortium. The MOMENTUM study is an international academic-industrial partnership between several hospitals and industry partner Elekta. All patients treated on the MR-linac are eligible for inclusion in MOMENTUM. For participants, we collect clinical patient data (e.g., patient, tumor, and treatment characteristics) and technical patient data which is defined as information generated on the MR-linac during treatment. The data are captured, pseudonymized, and stored in an international registry at set time intervals up to two years after treatment. Patients can choose to provide patient-reported outcomes and consent to additional MRI scans acquired on the MR-linac. This registry will serve as a data platform that supports multicenter research investigating the MR-linac. Rules and regulations on data sharing, data access, and intellectual property rights are summarized in an academic-industrial collaboration agreement. Data access rules ensure secure data handling and research integrity for investigators and institutions. Separate data access rules exist for academic and industry partners. This study is registered at ClinicalTrials.gov with ID: NCT04075305 (https://clinicaltrials.gov/ct2/show/NCT04075305). Conclusion: The multi-institutional MOMENTUM study has been set up to collect clinical and technical patient data to advance technical development, and facilitate evidenced-based implementation of MR-linac technology with the ultimate purpose to improve tumor control, survival, and quality of life of patients with cancer.

Reference dosimetry in the presence of a strong magnetic field is challenging. Ionisation chambers have shown to be strongly affected by magnetic fields. There is a need for robust and stable detectors in MRI-guided radiotherapy (MRIgRT). This study investigates the behaviour of the alanine dosimeter in magnetic fields and assesses its suitability to act as a reference detector in MRIgRT. Alanine pellets were loaded in a waterproof holder, placed in an electromagnet and irradiated by 60Co and 6 MV and 8 MV linac beams over a range of magnetic flux densities. Monte Carlo simulations were performed to calculate the absorbed dose, to water and to alanine, with and without magnetic fields. Combining measurements with simulations, the effect of magnetic fields on alanine response was quantified and a correction factor for the presence of magnetic fields on alanine was determined. This study finds that the response of alanine to ionising radiation is modified when the irradiation is in the presence of a magnetic field. The effect is energy independent and may increase the alanine/electron paramagnetic resonance (EPR) signal by 0.2% at 0.35 T and 0.7% at 1.5 T. In alanine dosimetry for MRIgRT, this effect, if left uncorrected, would lead to an overestimate of dose. Accordingly, a correction factor, k Q B , Q , is defined. Values are obtained for this correction as a function of magnetic flux density, with a standard uncertainty which depends on the magnetic field and is 0.6% or less. The strong magnetic field has a measurable effect on alanine dosimetry. For alanine which is used to measure absorbed dose to water in a strong magnetic field, but which has been calibrated in the absence of a magnetic field, a small correction to the reported dose is required. With the inclusion of this correction, alanine/EPR is a suitable reference dosimeter for measurements in MRIgRT.

Previous work has shown that PRESAGE® can be used successfully to perform 3D dosimetric measurements of complex radiotherapy treatments. However, measurements near the sample edges are known to be difficult to achieve. This is an issue when the doses at air-material interfaces are of interest, for example when investigating the electron return effect (ERE) present in treatments delivered by magnetic resonance (MR)-linac systems. To study this effect, a set of 3.5 cm-diameter cylindrical PRESAGE® samples was uniformly irradiated with multiple dose fractions, using either a conventional linac or an MR-linac. The samples were imaged between fractions using an optical-CT, to read out the corresponding accumulated doses. A calibration between TPS-predicted dose and optical-CT pixel value was determined for individual dosimeters as a function of radial distance from the axis of rotation. This data was used to develop a correction that was applied to four additional samples of PRESAGE® of the same formulation, irradiated with 3D-CRT and IMRT treatment plans, to recover significantly improved 3D measurements of dose. An alternative strategy was also tested, in which the outer surface of the sample was physically removed prior to irradiation. Results show that for the formulation studied here, PRESAGE® samples have a central region that responds uniformly and an edge region of 6-7 mm where there is gradual increase in dosimeter response, rising to an over-response of 24%-36% at the outer boundary. This non-uniform dose response increases in both extent and magnitude over time. Both mitigation strategies investigated were successful. In our four exemplar studies, we show how discrepancies at edges are reduced from 13%-37% of the maximum dose to between 2 and 8%. Quantitative analysis shows that the 3D gamma passing rates rise from 90.4, 69.3, 63.7 and 43.6% to 97.3, 99.9, 96.7 and 98.9% respectively.

For multimodality therapies such as the combination of hyperthermia and radiation, quantification of biological effects is key for dose prescription and response prediction. Tumour spheroids have a microenvironment that more closely resembles that of tumours in vivo and may thus be a superior in vitro cancer model than monolayer cultures. Here, the response of tumour spheroids formed from two established human cancer cell lines (HCT116 and CAL27) to single and combination treatments of radiation (0–20 Gy), and hyperthermia at 47 °C (0–780 CEM43) has been evaluated. Response was analysed in terms of spheroid growth, cell viability and the distribution of live/dead cells. Time-lapse imaging was used to evaluate mechanisms of cell death and cell detachment. It was found that sensitivity to heat in spheroids was significantly less than that seen in monolayer cultures. Spheroids showed different patterns of shrinkage and regrowth when exposed to heat or radiation: heated spheroids shed dead cells within four days of heating and displayed faster growth post-exposure than samples that received radiation or no treatment. Irradiated spheroids maintained a dense structure and exhibited a longer growth delay than spheroids receiving hyperthermia or combination treatment at (thermal) doses that yielded equivalent levels of clonogenic cell survival. We suggest that, unlike radiation, which kills dividing cells, hyperthermia-induced cell death affects cells independent of their proliferation status. This induces microenvironmental changes that promote spheroid growth. In conclusion, 3D tumour spheroid growth studies reveal differences in response to heat and/or radiation that were not apparent in 2D clonogenic assays but that may significantly influence treatment efficacy.

An MR-Linac can provide motion information of tumour and organs-at-risk before, during, and after beam delivery. However, MR imaging cannot provide real-time high-quality volumetric images which capture breath-to-breath variability of respiratory motion. Surrogate-driven motion models relate the motion of the internal anatomy to surrogate signals, thus can estimate the 3D internal motion from these signals. Internal surrogate signals based on patient anatomy can be extracted from 2D cine-MR images, which can be acquired on an MR-Linac during treatment, to build and drive motion models. In this paper we investigate different MRI-derived surrogate signals, including signals generated by applying principal component analysis to the image intensities, or control point displacements derived from deformable registration of the 2D cine-MR images. We assessed the suitability of the signals to build models that can estimate the motion of the internal anatomy, including sliding motion and breath-to-breath variability. We quantitatively evaluated the models by estimating the 2D motion in sagittal and coronal slices of 8 lung cancer patients, and comparing them to motion measurements obtained from image registration. For sagittal slices, using the first and second principal components on the control point displacements as surrogate signals resulted in the highest model accuracy, with a mean error over patients around 0.80 mm which was lower than the in-plane resolution. For coronal slices, all investigated signals except the skin signal produced mean errors over patients around 1 mm. These results demonstrate that surrogate signals derived from 2D cine-MR images, including those generated by applying principal component analysis to the image intensities or control point displacements, can accurately model the motion of the internal anatomy within a single sagittal or coronal slice. This implies the signals should also be suitable for modelling the 3D respiratory motion of the internal anatomy.

Highlights • Real-time respiratory motion management (RRMM) practice, evaluated for 200 centres. • Sixty-eight percent of respondents used RRMM for at least one tumour site. • Across all tumour sites, external marker was the main RRMM signal used. • Overall 71% of respondents wished to implement RRMM for a new treatment site. • The main barriers were human/financial resources and capacity on the machine., Purpose The POP-ART RT study aims to determine to what extent and how intra-fractional real-time respiratory motion management (RRMM) and plan adaptation for inter-fractional anatomical changes (ART), are used in clinical practice and to understand barriers to implementation. Here we report on part I: RRMM. Material and methods A questionnaire was distributed worldwide to assess current clinical practice, wishes for expansion or new implementation and barriers to implementation. RRMM was defined as inspiration/expiration gating in free-breathing or breath-hold, or tracking where the target and the beam are continuously realigned. Results The questionnaire was completed by 200 centres from 41 countries. RRMM was used by 68% of respondents (‘users’) for a median (range) of 2 (1–6) tumour sites. Eighty-one percent of users applied inspiration breath-hold in at least one tumour site (breast: 96%). External marker was used to guide RRMM by 61% of users. KV/MV imaging was frequently used for liver and pancreas (with fiducials) and for lung (with or without fiducials). Tracking was mainly performed on robotic linacs with hybrid internal-external monitoring. For breast and lung, approximately 75% of respondents used or wished to implement RRMM, which was lower for liver (44%) and pancreas (27%). Seventy-one percent of respondents wished to implement RRMM for a new tumour site. Main barriers were human/financial resources and capacity on the machine. Conclusion Sixty-eight percent of respondents used RRMM and 71% wished to implement RRMM for a new tumour site. The main barriers to implementation were human/financial resources and capacity on treatment machines.

Highlights • The patterns of practice for adaptive radiotherapy were evaluated for 177 centres. • Over half performed ad-hoc adaption but less than a third used specific protocols. • CBCT was the main imaging modality in general but MR was used for daily replanning. • 2/3 centres wished to implement ART; 40% of them had plans to do it within 2 years. • The main barriers were human/material resources and technical limitations., Purpose The POP-ART RT study aims to determine to what extent and how intrafractional real-time respiratory motion management (RRMM), and plan adaptation for interfractional anatomical changes (ART) are used in clinical practice and to understand barriers to implementation. Here we report on part II: ART using more than one plan per target per treatment course. Materials and methods A questionnaire on the current practice of ART, wishes for expansion or implementation, and barriers to implementation was distributed worldwide. Four types of ART were discriminated: daily online replanning, online plan library, protocolled offline replanning (all three based on a protocol), and ad-hoc offline replanning. Results The questionnaire was completed by 177 centres from 40 countries. ART was used by 61% of respondents (31% with protocol) for a median (range) of 3 (1–8) tumour sites. CBCT/MVCT was the main imaging modality except for online daily replanning (11 users) where 10 users used MR. Two thirds of respondents wished to implement ART for a new tumour site; 40% of these had plans to do it in the next 2 years. Human/material resources and technical limitations were the main barriers to further use and implementation. Conclusions ART was used for a broad range of tumour sites, mainly with ad-hoc offline replanning and for a median of 3 tumour sites. There was a large interest in implementing ART for more tumour sites, mainly limited by human/material resources and technical limitations. Daily online replanning was primarily performed on MR-linacs.

Thermo-radiosensitisation is a promising approach for treatment of radio-resistant tumours such as those containing hypoxic subregions. Response prediction and treatment planning should account for tumour response heterogeneity, e.g. due to microenvironmental factors, and quantification of the biological effects induced. 3D tumour spheroids provide a physiological in vitro model of tumour response and a systems oncology framework for simulating spheroid response to radiation and hyperthermia is presented. Using a cellular automaton model, 3D oxygen diffusion, delivery of radiation and/or hyperthermia were simulated for many ($${\bf{1}}{{\bf{0}}}^{{\bf{4}}}{\boldsymbol{-}}{\bf{1}}{{\bf{0}}}^{{\bf{7}}}$$ 1 0 4 − 1 0 7 ) individual cells forming a spheroid. The iterative oxygen diffusion model was compared to an analytical oxygenation model and simulations were calibrated and validated against experimental data for irradiated (0–10 Gy) and/or heated (0–240 CEM43) HCT116 spheroids. Despite comparable clonogenic survival, spheroid growth differed significantly following radiation or hyperthermia. This dynamic response was described well by the simulation ($${{\bf{R}}}^{{\bf{2}}}$$ R 2 > 0.85). Heat-induced cell death was implemented as a fast, proliferation-independent process, allowing reoxygenation and repopulation, whereas radiation was modelled as proliferation-dependent mitotic catastrophe. This framework stands out both through its experimental validation and its novel ability to predict spheroid response to multimodality treatment. It provides a good description of response where biological dose-weighting based on clonogenic survival alone was insufficient.