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Purpose: In modern conformal radiation therapy of distal esophageal cancer, target coverage can be affected by variations in the diaphragm position. We investigated if daily position verification (PV) extended by a diaphragm position correction would optimize target dose coverage for esophageal cancer treatment.Methods and Materials: For 15 esophageal cancer patients, intensity modulated proton therapy (IMPT) and volumetric modulated arc therapy (VMAT) plans were computed. Displacements of the target volume were correlated with diaphragm displacements using repeated 4-dimensional computed tomography images to determine the correction needed to account for diaphragm variations. Afterwards, target coverage was evaluated for 3 PV approaches based on: (1) bony anatomy (PV_B), (2) bony anatomy corrected for the diaphragm position (PV_BD) and (3) target volume (PV_T).Results: The cranial-caudal mean target displacement was congruent with almost half of the diaphragm displacement (y = 0.459x), which was used for the diaphragm correction in PV_BD. Target dose coverage using PV_B was adequate for most patients with diaphragm displacements up till 10 mm (>= 94% of the dose in 98% of the volume [D-98%]). For larger displacements, the target coverage was better maintained by PV_T and PV_BD. Overall, PV_BD accounted best for target displacements, especially in combination with tissue density variations (D-98%: IMPT 94% +/- 5%, VMAT 96% +/- 5%). Diaphragm displacements of more than 10 mm were observed in 22% of the cases.Conclusions: PV_B was sufficient to achieve adequate target dose coverage in case of small deviations in diaphragm position. However, large deviations of the diaphragm were best mitigated by PV_BD. To detect the cases where target dose coverage could be compromised due to diaphragm position variations, we recommend monitoring of the diaphragm position before treatment through online imaging. (C) 2021 Elsevier Inc. All rights reserved.

PURPOSE: To ensure target coverage in the treatment of esophageal cancer, a density override to the region of diaphragm motion can be applied in the optimization process. Here, we evaluate the benefit of this approach during robust optimization for intensity modulated proton therapy (IMPT) planning.MATERIALS AND METHODS: For ten esophageal cancer patients, two robustly optimized IMPT plans were created either using (WDO) or not using (NDO) a diaphragm density override of 1.05 g/cm3 during plan optimization. The override was applied to the excursion of the diaphragm between exhale and inhale. Initial robustness evaluation was performed for plan acceptance (setup errors of 8 mm, range errors of ±3%), and subsequently, on all weekly repeated 4DCTs (setup errors of 2 mm, range errors of ±3%). Target coverage and hotspots were analyzed on the resulting voxel-wise minimum (Vwmin ) and voxel-wise maximum (Vwmax ) dose distributions.RESULTS: The nominal dose distributions were similar for both WDO and NDO plans. However, visual inspection of the Vwmax of the WDO plans showed hotspots behind the right diaphragm override region. For one patient, target coverage and hotspots improved by applying the diaphragm override. We found no differences in target coverage in the weekly evaluations between the two approaches.CONCLUSION: The diaphragm override approach did not result in a clinical benefit in terms of planning and interfractional robustness. Therefore, we don't see added value in employing this approach as a default option during robust optimization for IMPT planning in esophageal cancer.

PURPOSE: The capability of proton therapy to provide highly conformal dose distributions is impaired by range uncertainties. The aim of this work is to apply range probing (RP), a form of a proton radiography-based quality control (QC) procedure for range accuracy assessment in head and neck cancer (HNC) patients in a clinical setting.METHODS AND MATERIALS: This study included seven HNC patients. RP acquisition was performed using a multi-layer ionization chamber (MLIC). Per patient, two RP frames were acquired within the first two weeks of treatment, on days when a repeated CT scan was obtained. Per RP frame, integral depth dose (IDD) curves of 81 spots around the treatment isocentre were acquired. Range errors are determined as a discrepancy between calculated IDDs in the treatment planning system and measured residual ranges by the MLIC. Range errors are presented relative to the water equivalent path length of individual proton spots. In addition to reporting results for complete measurement frames, an analysis, excluding range error contributions due to anatomical changes, is presented.RESULTS: Discrepancies between measured and calculated ranges are smaller when performing RP calculations on the day-specific patient anatomy rather than the planning CT. The patient-specific range evaluation shows an agreement between calculated and measured ranges for spots in anatomically consistent areas within 3% (1.5 standard deviation).CONCLUSIONS: The results of a RP-based QC procedure implemented in the clinical practice for HNC patients have been demonstrated. The agreement of measured and simulated proton ranges confirms the 3% uncertainty margin for robust optimization. Anatomical variations show a predominant effect on range accuracy, motivating efforts towards the implementation of adaptive radiotherapy.

The 4D Treatment Planning Workshop for Particle Therapy, a workshop dedicated to the treatment of moving targets with scanned particle beams, started in 2009 and since then has been organized annually. The mission of the workshop is to create an informal ground for clinical medical physicists, medical physics researchers and medical doctors interested in the development of the 4D technology, protocols and their translation into clinical practice. The 10th and 11th editions of the workshop took place in Sapporo, Japan in 2018 and Krakow, Poland in 2019, respectively. This review report from the Sapporo and Krakow workshops is structured in two parts, according to the workshop programs. The first part comprises clinicians and physicists review of the status of 4D clinical implementations. Corresponding talks were given by speakers from five centers around the world: Maastro Clinic (The Netherlands), University Medical Center Groningen (The Netherlands), MD Anderson Cancer Center (United States), University of Pennsylvania (United States) and The Proton Beam Therapy Center of Hokkaido University Hospital (Japan). The second part is dedicated to novelties in 4D research, i.e. motion modelling, artificial intelligence and new technologies which are currently being investigated in the radiotherapy field.

OBJECTIVE: To establish optimal robust optimization uncertainty settings for clinical head and neck cancer (HNC) patients undergoing 3D image-guided pencil beam scanning (PBS) proton therapy.METHODS: We analyzed ten consecutive HNC patients treated with 70 and 54.25 GyRBE to the primary and prophylactic clinical target volumes (CTV) respectively using intensity-modulated proton therapy (IMPT). Clinical plans were generated using robust optimization with 5 mm/3% setup/range uncertainties (RayStation v6.1). Additional plans were created for 4, 3, 2 and 1 mm setup and 3% range uncertainty and for 3 mm setup and 3%, 2% and 1% range uncertainty. Systematic and random error distributions were determined for setup and range uncertainties based on our quality assurance program. From these, 25 treatment scenarios were sampled for each plan, each consisting of a systematic setup and range error and daily random setup errors. Fraction doses were calculated on the weekly verification CT closest to the date of treatment as this was considered representative of the daily patient anatomy.RESULTS: Plans with a 2 mm/3% setup/range uncertainty setting adequately covered the primary and prophylactic CTV (V95≥ 99% in 98.8% and 90.8% of the treatment scenarios respectively). The average organ-at-risk dose decreased with 1.1 GyRBE/mm setup uncertainty reduction and 0.5 GyRBE/1% range uncertainty reduction. Normal tissue complication probabilities decreased by 2.0%/mm setup uncertainty reduction and by 0.9%/1% range uncertainty reduction.CONCLUSION: The results of this study indicate that margin reduction below 3 mm/3% is possible but requires a larger cohort to substantiate clinical introduction.

BACKGROUND AND PURPOSE: Intensity-modulated proton therapy (IMPT) is expected to result in clinical benefits by lowering radiation dose to organs-at-risk (OARs). However, there are concerns about plan robustness due to motion. To address this uncertainty we evaluated the robustness of IMPT compared to the widely clinically used volumetric modulated arc therapy (VMAT) on weekly repeated computed tomographies (CT).MATERIALS AND METHODS: 19 patients with oesophageal cancer were evaluated. IMPT and VMAT plans were created on a planning 4-Dimensional CT (p4DCT) and evaluated on weekly repeated 4DCTs (r4DCT). In case of inadequate target coverage or unacceptable high dose to normal tissue, re-planning was performed. Dose distributions of the r4DCTs were warped to p4DCT, resulting in an estimated actual given dose (EAGD).RESULTS: Compared to VMAT, IMPT resulted in significantly lowered dose to heart, lungs, spleen, liver and kidneys. For IMPT, target coverage was adequate (after max 1 replanning) in 17/19 cases. In two cases target coverage remained insufficient. However, in one of these patients the summed dose was insufficient (due to tumor shrinkage) while weekly coverage was adequate. For the other patient the target coverage was also insufficient by VMAT, due to large anatomical changes during treatment. For VMAT, adequate target coverage was achieved in 18/19 cases without re-planning. However, for reasons of high OAR dose re-planning was required in two cases.CONCLUSION: IMPT reduces the dose to OARs significantly, while achieving adequate target coverage in the majority of patients. Re-planning was necessary for both IMPT and VMAT due to anatomical changes.

Background and purpose Non-small cell lung cancer (NSCLC) patients show typically large anatomical changes during treatment, making recalculation or adaption necessary. For report and review, the applied treatment dose can be accumulated on the reference planning CT using deformable image registration (DIR). We investigated the dosimetric impact of using six different clinically available DIR algorithms for dose accumulation in presence of inter-fractional anatomy variations. Materials and methods For seven NSCLC patients, proton treatment plans with 66 Gy-RBE to the planning target volume (PTV) were optimised. Nine repeated CTs were registered to the planning CT using six DIR algorithms each. All CTs were acquired in visually guided deep-inspiration breath-hold. The plans were recalculated on the repeated CTs and warped back to the planning CT using the corresponding DIRs. Fraction doses warped with the same DIR were summed up to six different accumulated dose distributions per patient, and compared to the initial dose. Results The PTV-V95 of accumulated doses decreased by 16% on average over all patients, with variations due to DIR selection of 8.7%. A separation of the dose effects caused by anatomical changes and DIR uncertainty showed a good agreement between the dose degradation caused by anatomical changes and the dose predicted from the average of all DIRs (differences of only 1.6%). Conclusion The dose degradation caused by anatomical changes was more pronounced than the uncertainty of employing different DIRs for dose accumulation, with averaged results from several DIRs providing a good representation of dose degradation caused by anatomy. However, accumulated dose variations between DIRs can be substantial, leading to an additional dose uncertainty., Radiotherapy & Oncology, 147, ISSN:0167-8140, ISSN:1879-0887

Objective: Proton range uncertainties can compromise the effectiveness of proton therapy treatments. Water equivalent path length (WEPL) assessment by flat panel detector proton radiography (FP-PR) can provide means of range uncertainty detection. Since WEPL accuracy intrinsically relies on the FP-PR calibration parameters, the purpose of this study is to establish an optimal calibration procedure that ensures high accuracy of WEPL measurements. To that end, several calibration settings were investigated. Approach: FP-PR calibration datasets were obtained simulating PR fields with different proton energies, directed towards water-equivalent material slabs of increasing thickness. The parameters investigated were the spacing between energy layers (ΔE) and the increment in thickness of the water-equivalent material slabs (ΔX) used for calibration. 30 calibrations were simulated, as a result of combining ΔE = 9, 7, 5, 3, 1 MeV and ΔX = 10, 8, 5, 3, 2, 1 mm. FP-PRs through a CIRS electron density phantom were simulated, and WEPL images corresponding to each calibration were obtained. Ground truth WEPL values were provided by range probing multi-layer ionization chamber simulations on each insert of the phantom. Relative WEPL errors between FP-PR simulations and ground truth were calculated for each insert. Mean relative WEPL errors and standard deviations across all inserts were computed for WEPL images obtained with each calibration. Main results: Large mean and standard deviations were found in WEPL images obtained with large ΔE values (ΔE = 9 or 7 MeV), for any ΔX. WEPL images obtained with ΔE ≤ 5 MeV and ΔX ≤ 5 mm resulted in a WEPL accuracy with mean values within ±0.5% and standard deviations around 1%. Significance: An optimal FP calibration in the framework of this study was established, characterized by 3 MeV ≤ ΔE ≤ 5 MeV and 2 mm ≤ ΔX ≤ 5 mm. Within these boundaries, highly accurate WEPL acquisitions using FP-PR are feasible and practical, holding the potential to assist future online range verification quality control procedures.

PURPOSE: Cone beam CT (CBCT) based synthetic CTs (sCT) produced with a deep convolutional neural network (DCNN) show high image quality, suggesting their potential usability in adaptive proton therapy workflows. However, the nature of such workflows involving DCNNs prevents the user from having direct control over their output. Therefore, quality control (QC) tools that monitor the sCTs and detect failures or outliers in the generated images are needed. This work evaluates the potential of using a range probing (RP) based QC tool to verify sCTs generated by a DCNN. Such a RP QC tool experimentally assesses the CT number accuracy in sCTs.METHODS: A RP QC dataset consisting of repeat CTs (rCT), CBCTs and RP acquisitions of 7 head and neck cancer patients was retrospectively assessed. CBCT based sCTs were generated using a DCNN. The CT number accuracy in the sCTs was evaluated by computing relative range errors between measured RP fields and RP field simulations based on rCT and sCT images.RESULTS: Mean relative range errors showed agreement between measured and simulated RP fields, ranging from -1.2% to 1.5% in rCTs, and from -0.7% to 2.7% in sCTs.CONCLUSIONS: The agreement between measured and simulated RP fields suggests the suitability of sCTs for proton dose calculations. This outcome brings sCTs generated by DCNNs closer towards clinical implementation within adaptive proton therapy treatment workflows. The proposed RP QC tool allows for CT number accuracy assessment in sCTs and can provide means of in vivo range verification.

Radiation therapy (RT) is an integral component of potentially curative management of esophageal cancer (EC). However, RT can cause significant acute and late morbidity due to excess radiation exposure to nearby critical organs, especially the heart and lungs. Sparing these organs from both low and high radiation dose has been demonstrated to achieve clinically meaningful reductions in toxicity and may improve long-term survival. Accruing dosimetry and clinical evidence support the consideration of proton beam therapy (PBT) for the management of EC. There are critical treatment planning and delivery uncertainties that should be considered when treating EC with PBT, especially as there may be substantial motion-related interplay effects. The Particle Therapy Co-operative Group Thoracic and Gastrointestinal Subcommittees jointly developed guidelines regarding patient selection, treatment planning, clinical trials, and future directions of PBT for EC.

To optimize beam delivery and conformality of proton therapy, MRI integration has been proposed. Therefore, we investigated if proton irradiation in a magnetic field would change biological responses. Our data in cancer cell lines and stem cell-derived organoid models suggest that a magnetic field does not modify the biological response. (C) 2019 Elsevier B.V. All rights reserved.

The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated with proton beams worldwide and the number of operating proton therapy (PT) facilities will soon reach one hundred. PT has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy. While PT has become mainstream and has established itself as a treatment option for many cancers, it is still an area of active research for various reasons: the advanced dose shaping capabilities of PT cause susceptibility to uncertainties, the high degrees of freedom in dose delivery offer room for further improvements, the limited experience and understanding of optimizing pencil beam scanning, and the biological effect difference compared to photon radiation. In addition to these challenges and opportunities currently being investigated, there is an economic aspect because PT treatments are, on average, still more expensive compared to conventional photon based treatment options. This roadmap highlights the current state and future direction in PT categorized into four different themes, ‘improving efficiency’, ‘improving planning and delivery’, ‘improving imaging’, and ‘improving patient selection’.

This study evaluates the suitability of convolutional neural networks (CNNs) to automatically process proton radiography (PR)-based images. CNNs are used to classify PR images impaired by several sources of error affecting the proton range, more precisely setup and calibration curve errors. PR simulations were performed in 40 head and neck cancer patients, at three different anatomical locations (fields A, B and C, centered for head and neck, neck and base of skull coverage). Field sizes were 26 × 26cm2 for field A and 4.5 × 4.5cm2 for fields B and C. Range shift maps were obtained by comparing an unperturbed reference PR against a PR where one or more sources of error affected the proton range. CT calibration curve errors in soft, bone and fat tissues and setup errors in the anterior–posterior and inferior–superior directions were simulated individually and in combination. A CNN was trained for each type of PR field, leading to three CNNs trained with a mixture of range shift maps arising from one or more sources of range error. To test the full/partial/wrong agreement between predicted and actual sources of range error in the range shift maps, exact, partial and wrong match percentages were computed for an independent test dataset containing range shift maps arising from isolated or combined errors, retrospectively. The CNN corresponding to field A showed superior capability to detect isolated and combined errors, with exact matches of 92% and 71% respectively. Field B showed exact matches of 80% and 54%, and field C resulted in exact matches of 77% and 41%. The suitability of CNNs to classify PR-based images containing different sources of error affecting the proton range was demonstrated. This procedure enables the detection of setup and calibration curve errors when they appear individually or in combination, providing valuable information for the interpretation of PR images.

Purpose 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. Methods 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 (Dmean, D2%, D98%, D95%) for the ITV, and by a 3D-gamma index analysis (global, 3%/3 mm, 5 Gy, 20 Gy and 30 Gy dose thresholds). Results 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 Dmean, D2%, D95% and D98% 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 Dmean over the lungs was 2.3% and Dmean 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%. Conclusions 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.

Objective Dose prediction using deep learning networks prior to radiotherapy might lead tomore 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 and methods Data from 80 patients with neuroblastoma or Wilms’ tumour was included. Pencil beam scanning (PBS) (5 mm/ 3%) and volumetric-modulated arc therapy (VMAT) plans (5 mm) 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 Dmean 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 visualisation might aid in identifying the optimal radiotherapy technique when experience and/or resources are unavailable.

Purpose: To assess the feasibility of magnetic resonance imaging (MRI)-only treatment planning for photon and proton radiotherapy in children with abdominal tumours.Materials and methods: The study was conducted on 66 paediatric patients with Wilms' tumour or neuroblastoma (age 4 +/- 2 years) who underwent MR and computed tomography (CT) acquisition on the same day as part of the clinical protocol. MRI intensities were converted to CT Hounsfield units (HU) by means of a UNet-like neural network trained to generate synthetic CT (sCT) from T1- and T2-weighted MR images. The CT-to-sCT image similarity was evaluated by computing the mean error (ME), mean absolute error (MAE), peak signal-to-noise ratio (PSNR) and Dice similarity coefficient (DSC). Synthetic CT dosimetric accuracy was verified against CT-based dose distributions for volumetric-modulated arc therapy (VMAT) and intensity-modulated pencil-beam scanning (PBS). Relative dose differences (D-diff) in the internal target volume and organs-at-risk were computed and a three-dimensional gamma analysis (2 mm, 2%) was performed.Results: The average +/- standard deviation ME was -5 +/- 12 HU, MAE was 57 +/- 12 HU, PSNR was 30.3 +/- 1. 6 dB and DSC was 76 +/- 8% for bones and 92 +/- 9% for lungs. Average D-diff were 99% (range [85; 100]%) for VMAT and >96% (range [87; 100]%) for PBS.Conclusion: The deep learning-based model generated accurate sCT from planning T1w- and T2w-MR images. Most dosimetric differences were within clinically acceptable criteria for photon and proton radiotherapy, demonstrating the feasibility of an MRI-only workflow for paediatric patients with abdominal tumours. (C) 2020 The Authors. Published by Elsevier B.V.

PURPOSE: Patient specific quality assurance (PSQA) is required to verify the treatment delivery and the dose calculation by the treatment planning system (TPS). The objective of this work is to demonstrate the feasibility to substitute resource consuming measurement based PSQA (PSQAM) by independent dose recalculations (PSQAIDC), and that PSQAIDC results may be interpreted in a clinically relevant manner using normal tissue complication probability (NTCP) and tumor control probability (TCP) models.METHODS AND MATERIALS: A platform for the automatic execution of the two following PSQAIDC workflows was implemented: (i) using the TPS generated plan and (ii) using treatment delivery log files (log-plan). 30 head and neck cancer (HNC) patients were retrospectively investigated. PSQAM results were compared with those from the two PSQAIDC workflows. TCP / NTCP variations between PSQAIDC and the initial TPS dose distributions were investigated. Additionally, for two example patients that showed low passing PSQAM results, eight error scenarios were simulated and verified via measurements and log-plan based calculations. For all error scenarios ΔTCP / NTCP values between the nominal and the log-plan dose were assessed.RESULTS: Results of PSQAM and PSQAIDC from both implemented workflows agree within 2.7% in terms of gamma pass ratios. The verification of simulated error scenarios shows comparable trends between PSQAM and PSQAIDC. Based on the 30 investigated HNC patients, PSQAIDC observed dose deviations translate into a minor variation in NTCP values. As expected, TCP is critically related to observed dose deviations.CONCLUSIONS: We demonstrated a feasibility to substitute PSQAM with PSQAIDC. In addition, we showed that PSQAIDC results can be interpreted in clinically more relevant manner, for instance using TCP / NTCP.

Purpose Radiation therapy for mesothelioma remains challenging, as normal tissue toxicity limits the amount of radiation that can be safely delivered to the pleural surfaces, especially radiation dose to the contralateral lung. The physical properties of proton therapy result in better sparing of normal tissues when treating the pleura, both in the postpneumonectomy setting and the lung-intact setting. Compared with photon radiation, there are dramatic reductions in dose to the contralateral lung, heart, liver, kidneys, and stomach. However, the tissue heterogeneity in the thorax, organ motion, and potential for changing anatomy during the treatment course all present challenges to optimal irradiation with protons. Methods The clinical data underlying proton therapy in mesothelioma are reviewed here, including indications, advantages, and limitations. Results The Particle Therapy Cooperative Group Thoracic Subcommittee task group provides specific guidelines for the use of proton therapy for mesothelioma. Conclusions This consensus report can be used to guide clinical practice, insurance approval, and future research.

Purpose Compared to volumetric modulated arc therapy (VMAT), clinical benefits are anticipated when treating thoracic tumours with intensity-modulated proton therapy (IMPT). However, the current concern of plan robustness as a result of motion hampers its wide clinical implementation. To define an optimal protocol to treat lung and oesophageal cancers, we present a comprehensive evaluation of IMPT planning strategies, based on patient 4DCTs and machine log files. Materials and methods For ten lung and ten oesophageal cancer patients, a planning 4DCT and weekly repeated 4DCTs were collected. For these twenty patients, the CTV volume and motion were assessed based on the 4DCTs. In addition to clinical VMAT plans, layered rescanned 3D and 4D robust optimised IMPT plans (IMPT_3D and IMPT_4D respectively) were generated, and approved clinically, for all patients. The IMPT plans were then delivered in dry runs at our proton facility to obtain log files, and subsequently evaluated through our 4D robustness evaluation method (4DREM). With this method, for each evaluated plan, fourteen 4D accumulated scenario doses were obtained, representing 14 possible fractionated treatment courses. Results From VMAT to IMPT_3D, nominal Dmean(lungs-GTV) decreased 2.75 ± 0.56 GyRBE and 3.76 ± 0.92 GyRBE over all lung and oesophageal cancer patients, respectively. A more pronounced reduction was verified for Dmean(heart): 5.38 ± 7.36 GyRBE (lung cases) and 9.51 ± 2.25 GyRBE (oesophagus cases). Target coverage robustness of IMPT_3D was sufficient for 18/20 patients. Averaged dose in critical structures over all 4DREM scenarios changed only slightly for both IMPT_3D and IMPT_4D. Relative to IMPT_3D, no gain in IMPT_4D was observed. Conclusion The dosimetric superiority of IMPT over VMAT has been established. For most thoracic tumours, our IMPT_3D planning protocol showed to be robust and clinically suitable. Nevertheless, accurate patient positioning and adapting to anatomical variations over the course of treatment remain compulsory.

Background The targeting accuracy of proton therapy (PT) for moving soft-tissue tumours is expected to greatly improve by real-time magnetic resonance imaging (MRI) guidance. The integration of MRI and PT at the treatment isocenter would offer the opportunity of combining the unparalleled soft-tissue contrast and real-time imaging capabilities of MRI with the most conformal dose distribution and best dose steering capability provided by modern PT. However, hybrid systems for MR-integrated PT (MRiPT) have not been realized so far due to a number of hitherto open technological challenges. In recent years, various research groups have started addressing these challenges and exploring the technical feasibility and clinical potential of MRiPT. The aim of this contribution is to review the different aspects of MRiPT, to report on the status quo and to identify important future research topics. Methods Four aspects currently under study and their future directions are discussed: modelling and experimental investigations of electromagnetic interactions between the MRI and PT systems, integration of MRiPT workflows in clinical facilities, proton dose calculation algorithms in magnetic fields, and MRI-only based proton treatment planning approaches. Conclusions Although MRiPT is still in its infancy, significant progress on all four aspects has been made, showing promising results that justify further efforts for research and development to be undertaken. First non-clinical research solutions have recently been realized and are being thoroughly characterized. The prospect that first prototype MRiPT systems for clinical use will likely exist within the next 5 to 10 years seems realistic, but requires significant work to be performed by collaborative efforts of research groups and industrial partners.

In this review article, we introduced the importance of “motion management” in advanced particle therapy. Several publications have reported that organ motion causes dose distribution disturbances due to interplay and blurring effects. Furthermore, motion can result in target dose miss and unwanted dose to healthy structures around the target. To avoid these problems, motion should be assessed and monitored prior and during treatment. In this review article, we give an overview about clinically available motion monitoring systems. Based on the acquired motion information an adequate motion mitigation technique should be chosen. This article reviews the clinical status of motion mitigation techniques like rescanning, gating and tracking. A limited number of centers have now started the treatment of targets in the thorax and abdomen using scanned particle beams. Therefore, the establishment of guidelines for motion monitoring and motion mitigation will be essential in the coming years.

In 2016 and 2017, the 8th and 9th 4D treatment planning workshop took place in Groningen (the Netherlands) and Vienna (Austria), respectively. This annual workshop brings together international experts to discuss research, advances in clinical implementation as well as problems and challenges in 4D treatment planning, mainly in spot scanned proton therapy. In the last two years several aspects like treatment planning, beam delivery, Monte Carlo simulations, motion modeling and monitoring, QA phantoms as well as 4D imaging were thoroughly discussed.This report provides an overview of discussed topics, recent findings and literature review from the last two years. Its main focus is to highlight translation of 4D research into clinical practice and to discuss remaining challenges and pitfalls that still need to be addressed and to be overcome.

In 2016 and 2017, the 8th and 9th 4D treatment planning workshop took place in Groningen (the Netherlands) and Vienna (Austria), respectively. This annual workshop brings together international experts to discuss re- search, advances in clinical implementation as well as problems and challenges in 4D treatment planning, mainly in spot scanned proton therapy. In the last two years several aspects like treatment planning, beam delivery, Monte Carlo simulations, motion modeling and monitoring, QA phantoms as well as 4D imaging were thor- oughly discussed. This report provides an overview of discussed topics, recent findings and literature review from the last two years. Its main focus is to highlight translation of 4D research into clinical practice and to discuss remaining challenges and pitfalls that still need to be addressed and to be overcome.

BACKGROUND: The interplay effect might degrade the dose of pencil beam scanning proton therapy to a degree that free-breathing treatment might be impossible without further motion mitigation techniques, which complicate and prolong the treatment. We assessed whether treatment of free-breathing patients without motion mitigation is feasible.MATERIAL AND METHODS: For 40 lung cancer patients, 4DCT datasets and individual breathing patterns were used to simulate 4D dynamic dose distributions of 3D treatment plans over 33 fractions delivered with an IBA universal nozzle. Evaluation was done by assessing under- and overdosage in the target structure using the parameters V90, V95, V98, D98, D2, V107 and V110. The impact of using beam-specific target volumes and the impact of changes in motion and patient anatomy in control 4DCTs were assessed.RESULTS: Almost half of the patients had tumour motion amplitudes of less than 5 mm. Under- and overdosage was significantly smaller for patients with tumour motion below 5 mm compared to patients with larger motion (2% vs. 13% average absolute reduction of V95, 2% vs. 8% average increase in V107, p CONCLUSION: Tumour motion amplitude is an indicator of dose degradation caused by the interplay effect. Fractionation reduces the dose degradation allowing the unmitigated treatment of patients with small tumour motions of less than 5 mm. The beam-specific target approach improves the dose coverage. The tumour motion and position needs to be assessed during treatment for all patients, to quickly react to possible changes, which might require treatment adaptation.

Pencil-beam scanning (PBS) proton therapy (PT), particularly intensity modulated PT, represents the latest advanced PT technology for treating cancers, including thoracic malignancies. On the basis of virtual clinical studies, PBS-PT appears to have great potential in its ability to tightly tailor the dose to the target while sparing critical structures, thereby reducing treatment-related toxicities, particularly for tumors in areas with complicated anatomy. However, implementing PBS-PT for moving targets has several additional technical challenges compared with intensity modulated photon radiation therapy or passive scattering PT. Four-dimensional computed tomographye based motion management and robust optimization and evaluation are crucial for minimizing uncertainties associated with beam range and organ motion. Rigorous quality assurance is required to validate dose delivery both before and during the course of treatment. Active motion management (eg, breath hold), beam gating, rescanning, tracking, or adaptive planning may be needed for cases involving significant motion or changes in motion or anatomy over the course of treatment. (C) 2017 The Authors. Published by Elsevier Inc.

Background: The aim of this study was to compare adaptive intensity modulated proton therapy (IMPT) robustness and organ sparing capabilities with that of adaptive volumetric arc photon therapy (VMAT). Material and methods: Eighteen lung cancer patients underwent a planning 4DCT (p4DCT) and 5 weekly repeated 4DCT (r4DCT) scans. Target volumes and organs at risk were manually delineated on the three-dimensional (3D) average scans of the p4DCT (av_p4DCT) and of the r4DCT scans (av_r4DCT). Planning target volume (PTV)-based VMAT plans and internal clinical target volume (ICTV)-based robust IMPT plans were optimized in 3D on the av_p4DCT and re-calculated on the av_r4DCTs. Re-planning on av_r4DCTs was performed when indicated and accumulated doses were evaluated on the av_p4DCT. Results: Adaptive VMAT and IMPT resulted in adequate ICTV coverage on av_r4DCT in all patients and adequate accumulated-dose ICTV coverage on av_p4DCT in 17/18 patients (due to a shrinking target in one patient). More frequent re-planning was needed for IMPT than for VMAT. The average mean heart dose reduction with IMPT compared with VMAT was 4.6 Gy (p = .001) and it was >5 Gy for five patients (6, 7, 8, 15, and 22 Gy). The average mean lung dose reduction was 3.2 Gy (p

Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to ‘see what we treat, as we treat’ and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

Due to anticipated clinical benefits, moving targets are potential future indications for pencil beam scanned proton therapy (PBS-PT). However, currently they are not widely treated at PBS-PT facilities due to dosimetric uncertainties caused by motion. We developed a method, the 4D robustness evaluation method (4DREM), to realistically and efficiently assess all possible events impacting PBS-PT treatments in the thorax. Using the 4DREM in large cohorts of lung and oesophageal cancer patients, it will become possible to illustrate, in clinical practice, how to trigger robustness settings for plan optimisation and to select and apply motion mitigation techniques. (C) 2019 Elsevier B.V. All rights reserved. Radiotherapy and Oncology

Background and purpose Motion-induced uncertainties hamper the clinical implementation of pencil beam scanning proton therapy (PBS-PT). Prospective pretreatment evaluations only provide multiscenario predictions without giving a clear conclusion for the actual treatment. Therefore, in this proof-of-concept study we present a methodology for a fraction-wise retrospective four-dimensional (4D) dose reconstruction and accumulation aiming at the evaluation of treatment quality during and after treatment. Material and methods We implemented an easy-to-use, script-based 4D dose assessment of PBS-PT for patients with moving tumors in a commercially available treatment planning system. This 4D dose accumulation uses treatment delivery log files and breathing pattern records of each fraction as well as weekly repeated 4D-CT scans acquired during the treatment course. The approach was validated experimentally and was executed for an exemplary dataset of a lung cancer patient. Results The script-based 4D dose reconstruction and accumulation was implemented successfully, requiring minimal user input and a reasonable processing time (around 10 min for a fraction dose assessment). An experimental validation using a dynamic CIRS thorax phantom confirmed the precision of the 4D dose reconstruction methodology. In a proof-of-concept study, the accumulation of 33 reconstructed fraction doses showed a linear increase of D98 values. Projected treatment course D98 values revealed a CTV underdosage after fraction 25. This loss of target coverage was confirmed in a dose volume histogram comparison of the nominal, the projected (after 16 fractions) and the accumulated (after 33 fractions) dose distribution. Conclusions The presented method allows for the assessment of the conformity between planned and delivered dose as the treatment course progresses. The implemented approach considers the influence of changing patient anatomy and variations in the breathing pattern. This facilitates treatment quality evaluation and supports decisions regarding plan adaptation. In a next step, this approach will be applied to a larger patient cohort to investigate its capability as 4D quality control and decision support tool for treatment adaptation. (c) 2019 American Association of Physicists in Medicine

Purpose Respiratory impacts in pencil beam scanned proton therapy (PBS-PT) are accounted by extensive 4D dose calculations, where deformable image registration (DIR) is necessary for estimating deformation vector fields (DVFs). We aim here to evaluate the dosimetric errors induced by different DIR algorithms in their resulting 4D dose calculations by using ground truth(GT)-DVFs from 4DMRI. Materials and methods Six DIR methods: ANACONDA, Morfeus, B-splines, Demons, CT Deformable, and Total Variation, were respectively applied to nine 4DCT-MRI liver data sets. The derived DVFs were then used as input for 4D dose calculation. The DIR induced dosimetric error was assessed by individually comparing the resultant 4D dose distributions to those obtained with GT-DVFs. Both single-/three-field plans and single/rescanned strategies were investigated. Results Differences in 4D dose distributions among different DIR algorithms, and compared to the results using GT-DVFs, were pronounced. Up to 40 % of clinically relevant dose calculation points showed dose differences of 10 % or more between the GT. Differences in V95(CTV) reached up to 11.34 ± 12.57 %. The dosimetric errors became in general less substantial when applying multiple-field plans or using rescanning. Conclusion Intrinsic geometric errors by DIR can influence the clinical evaluation of liver 4D PBS-PT plans. We recommend the use of an error bar for correctly interpreting individual 4D dose distributions., Radiotherapy & Oncology, 128 (1), ISSN:0167-8140, ISSN:1879-0887

Background and purpose: The treatment of moving targets with scanned proton beams is challenging. For motion mitigation, an Active Breathing Coordinator (ABC) can be used to assist with breath-holding. We evaluated the robustness of scanned proton therapy against anatomical uncertainties when treating lung patients during ABC controlled breath-hold. Materials and methods: Four subsequent MRIs of five healthy volunteers were acquired under ABC controlled breath-hold during two simulated treatment fractions. Deformation vector fields between these MRIs were used to deform CTs of three non-small-cell lung cancer patients. Per patient eight cases with different tumour sizes and locations were modeled. Intensity-modulated proton plans were created and split into sub-plans of 20 seconds duration (assumed breath-hold duration), and recalculated on the deformed CTs. Results: Dosimetric evaluation showed

Purpose: Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CT can significantly reduce lung imaging artifacts. Methods: Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) “conventional” 4D CT that uses a constant imaging and couch-shift frequency, (ii) “beam paused” 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) “respiratory-gated” 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a setmore » of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm{sup 3} spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Results: Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10{sup −19}). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%–1.4%), false positives (4.0%–2.6%), and false negatives (2.7%–1.3%). These percentage reductions correspond to gating reducing image artifacts by 24–90 cm{sup 3} of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. Conclusions: For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm{sup 3} of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.« less