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Background: The accuracy of intensity-modulated proton therapy (IMPT) is greatly affected by anatomy variations that might occur during the treatment course. Online plan adaptations have been proposed as a solution to intervene promptly during a treatment session once the anatomy changes are detected. The implementation of online-adaptive proton therapy (OAPT) is still hindered by time-consuming tasks in the workflow. Purpose: The study introduces the novel concept of partial adaptation and aims at investigating its feasibility as a potential solution to parallelize tasks during an OAPT workflow for saving valuable in-room time. Methods: The proof-of-principle simulation study includes datasets from six head-and-neck cancer (HNC) patients each consisting of one planning CT (pCT) and three contoured control CTs (cCTs). Robust 3-field normo-fractionated initial IMPT plans were generated on the pCTs with a standardized field configuration, delivering 66 Gy and 54 Gy to the high-risk and low-risk clinical target volume (CTVHigh and CTVLow), respectively. For each cCT, a dose mimicking-based partial adaptation was applied: two fields were adapted on the current anatomy taking into account the background dose of the first non-adapted field supposedly delivered in the meantime. Fraction doses on the cCTs resulting from partially adapted plans with different first (non-adapted) field assignments were compared against those from non-adapted and fully adapted plans regarding target coverage and organs at risk (OARs) sparing. The robustness of partially adapted plans was also evaluated. Results: Partially adapted plans showed comparable results to fully adapted plans and were superior to non-adapted plans for both target coverage and OAR sparing. Target coverage degradation in the non-adapted plans (median D98%: 95.9% and 97.5 for CTVLow and CTVHigh, respectively) was recovered by both partial (98.0% and 98.5%) and full adaptation (98.2% and 98.7%) in comparison to the initial

Purpose/Objective Cone-beam CT (CBCT) is a promising solution for 3D in situ imaging in an online-adaptive proton therapy workflow. However, CBCT scans have an increased uncertainty in determined CT numbers, making online treatment verification essential. Our aim is to verify adapted treatment plans based on CBCTs with prompt-gamma imaging (PGI) to detect unexpected treatment deviations as well as to offer independent quality assurance of adaptation and treatment. A reliable reference simulation is a prerequisite for PGI-based online treatment verification where measured PGI data are compared with reference simulations based on the CBCT (Figure 1a). In this study, we investigated whether CBCTs are suitable for PGI reference simulations. Material/Methods For a homogeneous PMMA cylinder (∅: 18 cm) and an anthropomorphic head phantom (CIRS 731 HN), two CT scans were acquired – a conventional fan-beam CT for reference and a CBCT. For each phantom, a corrected CBCT (cCBCT) and a virtual CT (vCT) were generated using RayStation (v13.0, RaySearch Laboratories AB), yielding 3 CBCT datasets and one fan-beam CT dataset. For both phantoms, a treatment plan with one field on a cuboid target structure (30.6 cm3) was generated (Figure 1b). PGI simulations were performed on all 3 CBCT datasets as well as on the fan-beam CT, serving as reference. Spot-wise range shifts between PGI simulations on the fan-beam CT and each CBCT dataset were extracted to examine the change in reference range due to the CT number differences. According to [1], the potential deviation in CT number (CBCT vs fan-beam CT) influences both, the depth dose distribution depending on the SPR value and the material assignment as well as the spectral prompt gamma (PG) emission depending on the material assignment. Both quantities (depth dose distribution and spectral PG emission) impact the simulated PGI profile. To distinguish both effects, we additionally calculated the depth dose distribution independently by d

X-ray computed tomography (CT) is the clinical standard for treatment planning in particle therapy. In this chapter, the basic principles of this state-of-the-art image modality will be described, as well as strategies to account for uncertainties of the conversion from CT number to ion stopping power.

Overview of needs and status of near real-time adaptive particle therapy In this overview talk the following questions will be addressed: -What is the status concerning fast adaptions in particle therapy also in relation to photon therapy? -Why we need online-adaptive particle therapy (OAPT)? -What are different approaches also in relation to different adaption speed? -What are the different imaging approaches for OAPT? -How can we verify the treatment delivery when no pre-treatment phantom QA is performed? -What is the role of I-based decision support? -What initiatives exist on national and international level? Where do we stand?

Dual energy/spectral CT

CT for RTP*: technical requirements and QA guidlines

Purpose/Objective Within a dedicated consortium, two clinical proton therapy (PT) centers collaborate with two industrial partners (PT system and treatment planning provider, respectively) to jointly develop, implement and evaluate an industrial solution for online-adaptive proton therapy (OAPT). This also requires a dedicated approach for patient-specific QA (pre- and post-treatment PSQA). As first step, we conducted a comprehensive assessment of the current clinical pre-treatment PSQA protocols in the two clinical PT facilities. Furthermore, so-called “sanity checks” have been defined, which play a crucial role in the OAPT QA concept: First, they speed up and automate checks that are currently performed manually and second, in combination with secondary dose calculation, they provide additional trust/evidence that the treatment is safe and as expected, before the delivery is started. Materials/Methods The current PSQA workflows (from plan approval until delivery of first fraction, Fig. 1A) were systematically analyzed for both PT facilities. Center 1 employs the MOSAIQ (Elekta AB, SE) oncology information system (OIS) in combination with RayStation (RaySearch Laboratories, Stockholm, SE) as treatment planning system (TPS). Center 2 utilizes the RayCare OIS (RaySearch Laboratories, SE) in combination with RayStation. The two workflows are hereinafter referred to as “Separate-OIS” and “Integrated-OIS”, respectively. Time required for all human operations in these systems, including data preparation for phantom measurements and double checks was assessed via the number of required mouse clicks and manual entries. Sanity checks (SCs) are automated QA routines, aiming to replace manual checks carried out by the medical physics expert (MPE). They serve as an additional safety mechanism, which guarantees the plausibility of plan parameter adjustments induced by the adaptation process and verifies the integrity of transferred DICOM data. To achieve an OAPT-ready PSQA work

Cone-beam CTs are a promising solution for fast imaging required by Online Adaptive Proton Therapy. Verifying adapted treatment plans with prompt-gamma-imaging (PGI) requires a reference simulation on the respective planning image. Cone-beam CTs and conventional fan-beam CTs were acquired for a homogeneous PMMA cylinder and an antropomorphic head phantom. Two RayStation algorithms were used to create a corrected cone-beam CT and a virtual CT for each phantom. PGI simulations were performed on all datasets and compared to a corresponding dose evaluation. CBCT data was shown to be suitable for PGI reference simulations if range prediction is correct, which is a requirement for plan adaptation. Uncertainty in material assignment due to noise in CBCT does not worsen PGI emission signal.

Motivation Large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres were observed in recent studies. To standardise CT-based SPR prediction using a Hounsfield look-up table (HLUT), a step-by-step consensus guide, created within the ESTRO Physics Workshop 2021 in a joint effort with EPTN-WP5, is presented. Methods The HLUT specification process includes six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate phantom inserts are tissue-equivalent for both X-ray and proton interactions and are scanned in head- and body-sized phantoms to mimic different beam hardening conditions. Soft tissue inserts can be scanned together, while scanning bone inserts individually reduces imaging artefacts. For optimal HLUT specification, the SPR of phantom inserts is measured and the SPR of tabulated human tissues is computed stoichiometrically. The HLUT stability is increased by including both phantom inserts and tabulated human tissues. Piecewise linear regressions of CT numbers and SPRs are performed for four tissue groups (lung, adipose, soft tissue, and bone) and then connected. Finally, a thorough validation is performed. Results The best practices and individual challenges are explained comprehensively for each step. A well-defined strategy for specifying the connection points between the individual line segments of the HLUT is presented. The guide was tested exemplarily on three CT scanners from different vendors, proving its feasibility on both single-energy CT and virtual monoenergetic images from dual-energy CT. Conclusion The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can increase the clinical range prediction accuracy and reduce its inter-centre variation.

Cone-beam CTs are a promising solution for fast imaging required by Online Adaptive Proton Therapy. Verifying adapted treatment plans with prompt-gamma-imaging (PGI) requires a reference simulation on the respective planning image. Cone-beam CTs and conventional fan-beam CTs were acquired for a homogeneous PMMA cylinder and an antropomorphic head phantom. Two RayStation algorithms were used to create a corrected cone-beam CT and a virtual CT for each phantom. PGI simulations were performed on all datasets and compared to a corresponding dose evaluation. CBCT data was shown to be suitable for PGI reference simulations if range prediction is correct, which is a requirement for plan adaptation. Uncertainty in material assignment due to noise in CBCT does not worsen PGI emission signal.

Real-time and online adaptive particle therapy in 10 years: a Delphi consensus analysis P. Trnkova1, Y. Zhang2, T. Toshito3, B. Heijmen4, C. Richter5, M. Aznar6, F. Albertini2, A. Bolsi2, J. Daartz7, A. Knopf2,8, J. Bertholet9 1Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria 2Center for Proton Therapy, Paul Scherrer Institute; Villigen, Switzerland 3Nagoya Proton Therapy Center, Nagoya City University West Medical Center, Nagoya, Japan 4Department of Radiotherapy, Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands 5 OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Dresden, Germany 6 Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom 7Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston MA 02114, United States of America 8 Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University for Applied Sciences and Arts Northwestern Switzerland. 9 Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, Bern, Switzerland Purpose/objectives: To collect experts’ opinion on the future of Online Adaptive Particle Therapy (OAPT) and Real Time Motion Management (RRMM) for a vision with a ten-year horizon. Material/Methods: Following the POP-ART PT survey on current status [1], the present 3-round Delphi consensus study addresses the future of OAPT and RRMM with a panel of 11 experts using questionnaires. Second and third rounds were adapted based on the answers from the previous round to generate controlled opinion feedback (Figure 1). Full consensus (FC) or partial consensus (PC) were reached when all experts agreed or only one expert had a different opinion, respectively. R

Purpose/Objective The preparation for an online-adaptive replanning in proton therapy (OAPT), including e.g. daily anatomy assessment and contouring of relevant structures, can considerably prolong the treatment session. We therefore propose for the first time a concept of partial adaptation as a step towards near real-time OAPT: the first non-adapted field is delivered during the replanning process while the remaining adapted fields shall also compensate for the suboptimal dose from the first field. The dosimetric consequences are demonstrated for head and neck cancer (HNC) patients. Materials/Methods A partial adaptation workflow was implemented in RayStation (v.11.0.100) via the dose tracking module and the consideration of field-wise background dose. For six HNC patients, simultaneous integrated boost plans with three fields delivering 54Gy/66Gy to the low-risk/high-risk clinical target volume (CTVLow/CTVHigh) in 33 fractions were robustly optimized. Partially adapted fraction doses considering a non-adapted posterior field were generated on 3 control CTs (cCT) per patient, acquired in the first week, at mid of treatment and in the last week. Results were compared with doses from the non-adapted plan and from fully adapted plans on the cCT anatomy by analysing CTV coverage (D98%>95%), overdose (D1%) and organ at risk (OAR) sparing. Paired t-tests were used to indicate significant differences (p<0.05). Results In general, dose distributions from the partial and full adaptations/partial and full adaptation strategy were quite similar, while non-adapted plans resulted in different individual deficits (Fig.1). In all 18 fractions (Fig.2), partial as well as full adaptation led to sufficient coverage of both CTVs without significant differences (median D98% for both strategies: 97.2%/98.5% for CTVLow/CTVHigh), while the D98% of non-adapted plans was significantly lower, even below 95% in 6 and 3 cases and had median values of 95.3% and 97.5% for CTVLow and CTVHigh, r

Background and purpose: Studies have shown large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres. To standardise this process, a step-by-step guide on specifying a Hounsfield look-up table (HLUT) is presented here. Materials and methods: The HLUT specification process is divided into six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate CT phantoms have a head- and body-sized part, with tissue-equivalent inserts in regard to X-ray and proton interactions. CT numbers are extracted from a region-of-interest covering the inner 70% of each insert in-plane and several axial CT slices in scan direction. For optimal HLUT specification, the SPR of phantom inserts is measured in a proton beam and the SPR of tabulated human tissues is computed stoichiometrically at 100 MeV. Including both phantom inserts and tabulated human tissues increases HLUT stability. Piecewise linear regressions are performed between CT numbers and SPRs for four tissue groups (lung, adipose, soft tissue, and bone) and then connected with straight lines. Finally, a thorough but simple validation is performed. Results: The best practices and individual challenges are explained comprehensively for each step. A well-defined strategy for specifying the connection points between the individual line segments of the HLUT is presented. The guide was tested exemplarily on three CT scanners from different vendors, proving its feasibility. Conclusion: The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can contribute to reduce inter-centre variations in SPR prediction.

Background and purpose: Organ motion compromises accurate particle therapy delivery. This study reports on the practice patterns for real-time intrafractional motion-management in particle therapy to evaluate current clinical practice and wishes and barriers to implementation. Materials and methods: An institutional questionnaire was distributed to particle therapy centres worldwide (7/ 2020–6/2021) asking which type(s) of real-time respiratory motion management (RRMM) methods were used, for which treatment sites, and what were the wishes and barriers to implementation. This was followed by a three-round DELPHI consensus analysis (10/2022) to define recommendations on required actions and future vision. With 70 responses from 17 countries, response rate was 100% for Europe (23/23 centres), 96% for Japan (22/23) and 53% for USA (20/38). Results: Of the 68 clinically operational centres, 85% used RRMM, with 41% using both rescanning and active methods. Sixty-four percent used active-RRMM for at least one treatment site, mostly with gating guided by an external marker. Forty-eight percent of active-RRMM users wished to expand or change their RRMM technique. The main barriers were technical limitations and limited resources. From the DELPHI analysis, optimisation of rescanning parameters, improvement of motion models, and pre-treatment 4D evaluation were unanimously considered clinically important future focus. 4D dose calculation was identified as the top requirement for future commercial treatment planning software. Conclusion: A majority of particle therapy centres have implemented RRMM. Still, further development and clinical integration were desired by most centres. Joint industry, clinical and research efforts are needed to translate innovation into efficient workflows for broad-scale implementation.

Background and purpose: Anatomical changes may compromise the planned target coverage and organs-at-risk dose in particle therapy. This study reports on the practice patterns for adaptive particle therapy (APT) to evaluate current clinical practice and wishes and barriers to further implementation. Materials and methods: An institutional questionnaire was distributed to PT centres worldwide (7/2020–6/2021) asking which type of APT was used, details of the workflow, and what the wishes and barriers to implementation were. Seventy centres from 17 countries participated. A three-round Delphi consensus analysis (10/2022) among the authors followed to define recommendations on required actions and future vision. Results: Out of the 68 clinically operational centres, 84% were users of APT for at least one treatment site with head and neck being most common. APT was mostly performed offline with only two online APT users (plan-library). No centre used online daily re-planning. Daily 3D imaging was used for APT by 19% of users. Sixty-eight percent of users had plans to increase their use or change their technique for APT. The main barrier was “lack of integrated and efficient workflows”. Automation and speed, reliable dose deformation for dose accumulation and higher quality of in-room volumetric imaging were identified as the most urgent task for clinical implementation of online daily APT. Conclusion: Offline APT was implemented by the majority of PT centres. Joint efforts between industry research and clinics are needed to translate innovations into efficient and clinically feasible workflows for broad-scale implementation of online APT.

The recently observed FLASH effect provides normal tissue protection at a similar tumor treatment efficacy via ultra-high dose rate (UHDR) irradiation and promises great benefits for radiotherapy patients. Dedicated studies are now necessary to define a robust set of dose application parameters for FLASH radiotherapy and to identify underlying mechanisms. These studies require particle accelerators with variable temporal dose application characteristics for numerous radiation qualities, equipped for preclinical radiobiological research. Here we present the DRESDEN PLATFORM, a research hub for ultra-high dose rate radiobiology. By uniting clinical and research accelerators with radiobiology infrastructure and know-how, the DRESDEN PLATFORM offers a unique environment for studying the FLASH effect. We introduce its experimental capabilities and qualify the platform for systematic investigation of FLASH by presenting results from a concerted in vivo radiobiology study with zebrafish embryos. The comparative pre-clinical study was conducted across three accelerator facilities, including an advanced laser-driven proton source applied for FLASH-relevant in vivo irradiations for the first time. The data show a protective effect of UHDR irradiation up to 10^5 Gy/s and suggests consistency of the protective effect even at escalated dose rates of 10^9 Gy/s. With the first clinical FLASH studies underway, research facilities like the DRESDEN PLATFORM, addressing the open questions surrounding FLASH, are essential to accelerate FLASH’s translation into clinical practice.

Background and purpose: There is no consensus about an ideal robust optimization (RO) strategy for proton therapy of targets with large intra-fractional motion. We investigated the plan robustness of different RO strategies regarding setup/range errors, interplay effects and interfractional anatomical changes. Materials and methods: For eight non-small cell lung cancer patients with primary and/or nodal clinical target volume (CTVp/CTVn) with motion >5mm, different RO approaches were investigated: 3DRO considering the average CT (AvgCT) with a target density override, 4DRO considering three/all 4DCT phases, and 4DRO considering the AvgCT and three/all 4DCT phases. Realistic interplay scenarios were reconstructed based on patient breathing and machine logfile data for deliveries with/without layered rescanning. Robustness against setup/range errors, interplay effects and interfractional anatomical changes were analyzed for target coverage and OAR sparing. Results: All nominal plans fulfilled the clinical requirements, while 4DRO without AvgCT generated the most conformal dose distributions. Robustness against setup/range errors was best for 4DRO with AvgCT. No RO strategy was sufficient in countervailing fraction-wise dose distortions caused by interplay effects. Irrespective of rescanning, target coverage was restored in all cases when accumulating four interplay scenarios. 4DRO with AvgCT showed higher CTVp robustness against interfractional changes, but plan adaptations are necessary for all RO strategies in case of relevant anatomical changes. Conclusion: All RO strategies are clinically acceptable but exhibit equally low robustness against interplay effects. To ensure fraction-wise target coverage, additional motion mitigation is required for CTVs with large motion amplitudes and interfractional changes need to be monitored.

Neural-network-based outcome predictions may enable further treatment personalization of patients with head and neck cancer. The development of neural networks can prove challenging when a limited number of cases is available. Therefore, we investigated whether multitask learning strategies, implemented through the simultaneous optimization of two distinct outcome objectives (multi-outcome) and combined with a tumor segmentation task, can lead to improved performance of convolutional neural networks (CNN) and vision transformers (ViT). Model training was conducted on two distinct multicenter datasets for the endpoints loco-regional control (LRC) and progression-free survival (PFS), respectively. The first dataset consisted of pre-treatment computed tomography (CT) imaging for 290 patients and the second dataset contained combined positron emission tomography (PET)/CT for 224 patients. Discriminative performance was assessed by the concordance index (C-index). Risk stratification was evaluated using log-rank tests. Across both datasets, CNN and ViT model ensembles achieved similar results. Multitask approaches showed favorable performance in most investigations. Multi-outcome CNN models trained with segmentation loss were identified as the optimal strategy across cohorts. On the PET/CT dataset, an ensemble of multi-outcome CNNs trained with segmentation loss achieved the best discrimination (C-index: 0.29, 95% confidence interval (CI): 0.22-0.36) and successfully stratified patients into groups with low and high risk of disease progression (p=0.003). On the CT dataset, ensembles of multi-outcome CNNs and of single-outcome ViTs trained with segmentation loss performed best (C-index: 0.26 and 0.26, CI: 0.18-0.34 and 0.18-0.35, respectively), both with significant risk stratification for LRC in independent validation (p=0.002 and p=0.011). Further validation of the developed multitask-learning models is planned based on a prospective validation study, which is currently

An estimation for the potential reduction of clinical margins when using prompt gamma imaging for online treatment verification in proton therapy of prostate cancer is provided. For two adaptive scenarios a potential reduction relative to the clinical practice was evaluated. Using the current trolley-mounted PGI system for online treatment verification to trigger an adaptation, the current range uncertainty margins used at our institute could be reduced by 57%. Additional volumetric imaging at isocenter before irradiation could also reduce the setup uncertainty margins by 66%. A case example illustrates the corresponding dose sparing.

In this overview talk the following questions will be addressed: - What is the status concerning fast adaptations in particle therapy also in relation to photon therapy? - Why we need online-adaptive particle therapy (OAPT)? - What are different approaches also in relation to different adaption speed? - What are the different imaging approaches for OAPT? - How can we verify the treatment delivery when no pre-treatment phantom QA is performed? - What is the role of AI-based decision support? - What initiatives exist on national and international level? Where do we stand?

Motivation Large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres were observed in recent studies. To standardise CT-based SPR prediction using a Hounsfield look-up table (HLUT), a step-by-step consensus guide, created within the ESTRO Physics Workshop 2021 in a joint effort with EPTN-WP5, is presented. Methods The HLUT specification process includes six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate phantom inserts are tissue-equivalent for both X-ray and proton interactions and are scanned in head- and body-sized phantoms to mimic different beam hardening conditions. Soft tissue inserts can be scanned together, while scanning bone inserts individually reduces imaging artefacts. For optimal HLUT specification, the SPR of phantom inserts is measured and the SPR of tabulated human tissues is computed stoichiometrically. The HLUT stability is increased by including both phantom inserts and tabulated human tissues. Piecewise linear regressions of CT numbers and SPRs are performed for four tissue groups (lung, adipose, soft tissue, and bone) and then connected. Finally, a thorough validation is performed. Results The best practices and individual challenges are explained comprehensively for each step. A well-defined strategy for specifying the connection points between the individual line segments of the HLUT is presented. The guide was tested exemplarily on three CT scanners from different vendors, proving its feasibility on both single-energy CT and virtual monoenergetic images from dual-energy CT. Conclusion The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can increase the clinical range prediction accuracy and reduce its inter-centre variation.

Purpose/Objective Studies within the European Particle Therapy Network (EPTN) have shown a large variation in the estimation of proton stopping-power ratio (SPR) from computed tomography (CT) scans across European proton centres. To standardise the SPR prediction process, we present a step-by-step guide on the Hounsfield look-up table (HLUT) specification process. This consensus guide was created within the ESTRO Physics Workshop 2021 on CT in radiotherapy in a joint effort with the EPTN Work Package 5 (WP5). Material/Methods The HLUT specification procedure is divided into six steps (Figure 1): 1) phantom setup, 2) CT scanning, 3) CT number extraction, 4) SPR determination, 5) HLUT specification, 6) HLUT evaluation. For each step, considerations and recommendations are given based on literature and additional experimental evaluations. Appropriate phantom inserts are tissue-equivalent for both X-ray and proton interactions and are scanned in head- and body-sized phantoms to mimic different beam hardening conditions. Soft tissue inserts can be scanned together, while bone inserts are scanned individually to avoid imaging artefacts. CT numbers are extracted in material-specific regions-of-interest covering the inner 70% of each phantom insert in-plane and several axial CT slices in scan direction. For an appropriate HLUT specification, the SPR of phantom inserts is experimentally determined in proton range measurements at an energy >200 MeV, and the SPR of tabulated human tissues is computed stoichiometrically at 100 MeV. By including both phantom inserts and tabulated human tissues in the HLUT specification, the influence of the respective dataset-specific uncertainties are mitigated and thus the HLUT accuracy is increased. Piecewise linear regressions are performed between CT numbers and SPRs for four individual tissue segments (lung, adipose, soft tissue and bone) and then connected with straight lines. A thorough but simple validation is finally performed. Results

Real-time and online adaptive particle therapy in 10 years: a Delphi consensus analysis P. Trnkova1, Y. Zhang2, T. Toshito3, B. Heijmen4, C. Richter5, M. Aznar6, F. Albertini2, A. Bolsi2, J. Daartz7, A. Knopf2,8, J. Bertholet9 1Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria 2Center for Proton Therapy, Paul Scherrer Institute; Villigen, Switzerland 3Nagoya Proton Therapy Center, Nagoya City University West Medical Center, Nagoya, Japan 4Department of Radiotherapy, Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands 5 OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Dresden, Germany 6 Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom 7Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston MA 02114, United States of America 8 Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University for Applied Sciences and Arts Northwestern Switzerland. 9 Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, Bern, Switzerland Purpose/objectives: To collect experts’ opinion on the future of Online Adaptive Particle Therapy (OAPT) and Real Time Motion Management (RRMM) for a vision with a ten-year horizon. Material/Methods: Following the POP-ART PT survey on current status [1], the present 3-round Delphi consensus study addresses the future of OAPT and RRMM with a panel of 11 experts using questionnaires. Second and third rounds were adapted based on the answers from the previous round to generate controlled opinion feedback (Figure 1). Full consensus (FC) or partial consensus (PC) were reached when all experts agreed or only one expert had a different opinion, respectively. R

Source data, scripts and parts of figures to generate the figures in publication

Real-time and online adaptive particle therapy in 10 years: a Delphi consensus analysis P. Trnkova1, Y. Zhang2, T. Toshito3, B. Heijmen4, C. Richter5, M. Aznar6, F. Albertini2, A. Bolsi2, J. Daartz7, A. Knopf2,8, J. Bertholet9 1Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria 2Center for Proton Therapy, Paul Scherrer Institute; Villigen, Switzerland 3Nagoya Proton Therapy Center, Nagoya City University West Medical Center, Nagoya, Japan 4Department of Radiotherapy, Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands 5 OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Dresden, Germany 6 Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom 7Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston MA 02114, United States of America 8 Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University for Applied Sciences and Arts Northwestern Switzerland. 9 Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, Bern, Switzerland Purpose/objectives: To collect experts’ opinion on the future of Online Adaptive Particle Therapy (OAPT) and Real Time Motion Management (RRMM) for a vision with a ten-year horizon. Material/Methods: Following the POP-ART PT survey on current status [1], the present 3-round Delphi consensus study addresses the future of OAPT and RRMM with a panel of 11 experts using questionnaires. Second and third rounds were adapted based on the answers from the previous round to generate controlled opinion feedback (Figure 1). Full consensus (FC) or partial consensus (PC) were reached when all experts agreed or only one expert had a different opinion, respectively. R

This dataset contains the model checkpoints, predictions and performance metrics for the multitask neural networks presented in the corresponding manuscript.

Online-adaptive particle therapy: Current status and vision for the future Richter, Christian

Recent oncological studies identified beneficial properties of radiation applied at ultra-high dose rates several orders of magnitude higher than the clinical standard of the order of Gy/min. Sources capable of providing these ultra-high dose rates are under investigation. Here, we show that a stable, compact laser-driven proton source with energies greater than 60 MeV enables radiobiological in vivo studies. We performed a pilot irradiation study on human tumors in a mouse model, showing the concerted preparation of mice and laser accelerator, the dose-controlled, tumor-conform irradiation using a laser-driven as well as a clinical reference proton source, and the radiobiological evaluation of irradiated and unirradiated mice for radiation-induced tumor growth delay. The prescribed homogeneous dose of 4 Gy was precisely delivered at the laser-driven source. The results demonstrate a complete laser-driven proton research platform for diverse user-specific small animal models, able to deliver tunable single-shot doses up to around 20 Gy to millimeter-scale volumes on nanosecond time scales, equivalent to around 1E9 Gy/s, spatially homogenized and tailored to the sample. The platform provides a unique infrastructure for translational research with protons at ultra-high dose rate.

Highlights in der Medizinphysik

Laser-plasma based proton accelerators as a novel accelerator technology have matured to a level at which laboratory-scale setups for the emerging topic of image-guided precision small animal irradiation studies come into reach [Bra2019]. Providing a high proton energy bandwidth [Sch2016] which is filtered in a tunable pulsed magnet beam transport, these accelerators enable flexibility in terms of scattering-free irradiation field formation [Mas2014, Mas2015]. Regarding temporal dose delivery, with single pulse doses reaching the Gy level at unprecedented peak dose rates of up to 1012 Gy/s [Sch2016], laser-plasma based proton accelerator setups can give access to the dose rate regime of FLASH [Fav2014, Voz2019]. The realization of a full-scale setup for image-guided precision radiobiological studies for small animals focusing on dose rate dependent effects is currently prepared at the PENELOPE laser-plasma based proton accelerator at HZDR and will be presented with a focus on the technological requirements and solutions for dose delivery at laser-plasma based sources. This development relies on our experience in performing dose-controlled radiobiological in vitro studies [Kra2010, Zei2013] and first in vivo irradiation experiments at the DRACO laser-plasma based proton accelerator at HZDR, where we have established a pulsed solenoid beamline for 3D irradiation field formation, yielding a (5 mm)³ homogeneous volumetric dose distribution at a Gy single pulse dose level [8]. [Bra2019] F.-E. Brack, F. Kroll, L. Gaus, C. Bernert, E. Beyreuther, T. E. Cowan, L. Karsch, S. D. Kraft, L. A. Kunz-Schughart, E. Lessmann, J. Metzkes-Ng, L. Obst-Hübl, J. Pawelke, M. Rehwald, H.-P. Schlenvoigt, U. Schramm, M. Sobiella, E. R. Szabó, T. Ziegler, K. Zeil, Spectral and spatial shaping of laser-driven proton beams using a pulsed high-field magnet beamline. arXiv:1910.08430 (2019) [Sch2016] J. Schreiber, P. Bolton, K. Parodi, “Hands-on” laser-driven ion acceleration: A primer for laser

Purpose/Objective In this systematic study, we investigate the sensitivity of prompt-gamma imaging (PGI) towards the field-wise detection of inter-fractional anatomical changes in proton therapy (PT) of head and neck cancer (HNC) patients. Materials/Methods Spot-wise range shifts ∆RPGI were monitored with a PGI-slit-camera during 22 field deliveries of HNC pencil beam scanning (PBS) treatments of 4 patients (field-wise dose per fraction: 0.7-1.0GyE). In-room CTs were acquired for all monitored fractions and range shifts ∆RIDD at the 80% falloff of spot-wise integrated depth-dose (IDD) profiles served as input for an automatic field-wise ground truth classification (Fig.1). To receive results consistent with an additional manual dose-based classification per field, a PBS spot with relative weight to the field >0.1% was rated as relevant if |∆RIDD| was ≥5mm for that and at least 1 neighboring spot. Subsequently, a field was classified as relevantly changed if at least 1.5% of all spots were rated relevant. For the independent PGI evaluation, spots were clustered based on Bragg-peak position and proton number to mitigate statistical measurement uncertainty. Clusters with |∆RPGI|≥5mm were classified as relevant. For training of the field-wise PGI classification model, the number of relevant clusters, that is necessary to classify the whole field as relevantly changed, was optimized with respect to the IDD ground truth classification using a training set of 11 fields. Finally, the classification model was validated on an independent test set (11 fields). Results On the level of PGI spot clusters, there is a significant correlation (rPearson=0.3, p<0.01) between IDD and PGI range shifts over all 22 monitored fields (Fig.2B). The only moderate correlation is mainly due to statistical uncertainty of the clusters, represented by the mean absolute error between IDD and PGI range shifts of 3.4mm. The correlation might also be affected by difficult range shift determination due

First studies on range verification in proton therapy using prompt gamma-ray spectroscopy (PGS) or imaging (PGI) have been recently conducted with patients. To benchmark the performance of each method, we designed a multi-center experiment between Massachusetts General Hospital and OncoRay with a shared anthropomorphic head phantom irradiated under equalized conditions. The treatment plan was delivered at clinical beam currents and doses in the respective proton therapy hospitals. Two gantry beam angles were used: horizontal and oblique (270° and 350°). Each field contained the same spot positions and energies as well as target volume in both institutions. The experimentally measured range was compared against the ground truth based on the reference stopping-power map of the phantom. The absolute range error of PGS or PGI was 2.4 mm or -0.5 mm for the horizontal field and 1.3 mm or 2.4 mm for the oblique one, respectively. The ability to detect relative range deviations was assessed by introducing 2 mm and 5 mm plastic slabs on the ventral half of the horizontal field. The measured range shifts were 1.8 mm or 4.8 mm for PGS, and 2.0 mm or 4.2 mm for PGI, respectively. The designed set of experiments represents the first systematic comparison of prompt gamma-ray systems for proton range verification across different institutions using a ground-truth head phantom as reference, and effectively proposes a standard testing platform for benchmarking future proton range verification prototypes in reproducible conditions.

Next-generation radiation therapy: Towards near-realtime adaptive proton therapy

Real-time respiratory motion management (RRMM, intra-fraction geometrical intervention) and Adaptive Particle Therapy (APT, inter-fraction adaptation of treatment plans) enable to account for anatomical variations and changes to optimize target coverage and organs-at-risk sparing. However, their current clinical implementation is unclear and expected to be highly heterogeneous. An institutional questionnaire, Patterns Of Practice for Adaptive and Real-Time Particle Therapy (POP-ART-PT), was distributed between 2021/01-06 to evaluate current clinical practice and wishes and barriers of the implementation. Here, we summarise the international survey results on APT for mitigation of interfractional anatomical changes from 70 particle therapy centers in 17 countries. The response rate was 100% for Europe, 96% for Japan and 53% for USA. Of the 68 centers in operation, 84% (Figure1a) were APT users for at least one treatment site, with head and neck being the most common. APT was mostly performed offline (ad-hoc or per protocol) with only two users of online APT (plan library) and none using online daily replanning. Plan adaptation was in all cases motivated by both, target and OAR dose considerations (Figure1b). The most common imaging modality guiding APT was X-ray computed tomography. Sixty-eight percent of users plan to increase or change their APT technique. The greatest barriers to implementation were lack of integrated and efficient workflows and human resources (Figure2) Offline APT has been widely implemented internationally, but online APT is still very rarely used. More research and development for integrated and efficient workflow is needed to facilitate the use of offline APT and enable online APT.

Real-time respiratory motion management (RRMM, intra-fraction geometrical intervention) and Adaptive Particle Therapy (APT, inter-fraction adaptation of treatment plans) enable to account for anatomical variations and changes to optimize target coverage and organs-at-risk sparing. However, their current clinical implementation is unclear and expected to be highly heterogeneous. An institutional questionnaire, Patterns Of Practice for Adaptive and Real-Time Particle Therapy (POP-ART-PT), was distributed between 2021/01-06 to evaluate current clinical practice and wishes and barriers of the implementation. Here, we summarise the international survey results on APT for mitigation of interfractional anatomical changes from 70 particle therapy centers in 17 countries. The response rate was 100% for Europe, 96% for Japan and 53% for USA. Of the 68 centers in operation, 84% (Figure1a) were APT users for at least one treatment site, with head and neck being the most common. APT was mostly performed offline (ad-hoc or per protocol) with only two users of online APT (plan library) and none using online daily replanning. Plan adaptation was in all cases motivated by both, target and OAR dose considerations (Figure1b). The most common imaging modality guiding APT was X-ray computed tomography. Sixty-eight percent of users plan to increase or change their APT technique. The greatest barriers to implementation were lack of integrated and efficient workflows and human resources (Figure2) Offline APT has been widely implemented internationally, but online APT is still very rarely used. More research and development for integrated and efficient workflow is needed to facilitate the use of offline APT and enable online APT.

Recent oncological studies identified beneficial properties of radiation applied at ultra-high dose rates several orders of magnitude higher than the clinical standard of the order of Gy/min. Sources capable of providing these ultra-high dose rates are under investigation. Here, we show that a stable, compact laser-driven proton source with energies greater than 60 MeV enables radiobiological in vivo studies. We performed a pilot irradiation study on human tumors in a mouse model, showing the concerted preparation of mice and laser accelerator, the dose-controlled, tumor-conform irradiation using a laser-driven as well as a clinical reference proton source, and the radiobiological evaluation of irradiated and unirradiated mice for radiation-induced tumor growth delay. The prescribed homogeneous dose of 4 Gy was precisely delivered at the laser-driven source. The results demonstrate a complete laser-driven proton research platform for diverse user-specific small animal models, able to deliver tunable single-shot doses up to around 20 Gy to millimeter-scale volumes on nanosecond time scales, equivalent to around 1E9 Gy/s, spatially homogenized and tailored to the sample. The platform provides a unique infrastructure for translational research with protons at ultra-high dose rate.

Purpose/objective: Experimental in vivo determination of radiological tissue parameters of organs in the head and pelvis within a large patient cohort, expanding on the current standard human tissue database summarized in ICRU46. Material/methods: Relative electron density (RED), effective atomic number (EAN) and stopping-power ratio (SPR) were obtained from clinical dual-energy CT scans using a clinically validated DirectSPR imple- mentation and organ segmentations of 107 brain-tumor (brain, brainstem, spinal cord, chiasm, optical nerve, lens) and 120 pelvic cancer patients (prostate, kidney, liver, bladder). The impact of contamination by surrounding tissues on the tissue parameters was reduced with a dedicated contour adaption routine. Tissue parameters were characterized regarding the cohort mean value as well as the variation within each patient (2rintra) and between patients (2rinter ). For the brain, age-dependent differences were deter- mined. Results: For 10 organs, including 4 structures not listed in ICRU46, the mean RED, EAN and SPR as well as their respective intra- and inter-patient variation were determined. SPR intra-patient variation was higher than 1.3% (1.3–4.6%) in all organs and always exceeded the inter-patient variation of the organ mean SPR (0.6–2.1%). For the brain, a significant SPR variation between pediatric and non-pediatric patients was determined. Conclusion: Radiological tissue parameters in the head and pelvis were characterized in vivo for a large patient cohort using dual-energy CT. This reassesses parts of the current standard database defined in ICRU46, furthermore complementing the data described in literature by smaller substructures in the brain as well as by the quantification of organ-specific inter- and intra-patient variation.

Bronchialkarzinome sind in Deutschland die dritthäufigste Tumorerkrankung. Trotz erheblicher therapeutischer Fortschritte ist die Prognose der Lungentumoren nach wie vor ungünstig, die relative 5-Jahres- Überlebensrate nach Diagnose eines Bron- chialkarzinoms beträgt lediglich 16 % [3]. Hinsichtlich der Tumorart werden nicht- kleinzellige (NSCLC) und kleinzellige Bron- chialkarzinome unterschieden. Bei fortgeschrittenen NSCLC besteht die Standardtherapie aus einer gleichzei- tig durchgeführten Radiochemotherapie, gefolgt von einer Immuntherapie. In Metaanalysen konnte die Überlegenheit der simultanen Radiochemotherapie ge- genüber einem sequenziellen Vorgehen gezeigt werden.

In radiation oncology, CT imaging is of crucial importance for consistent and accurate delineation of target and organ-at-risk structures as well as for highly precise treatment planning and prediction of the deposited dose. Even though the potential benefit of dual-energy CT for those purposes was identified early, its implementation in clinical practice is still in an early stage. Here, we want to give an overview of current and potential future applications of dual-energy CT in the field of radiation oncology. Since the next generation of X-ray computed tomography with a photon-counting detector technology is rising at the horizon, we also want to give an outlook on radiotherapeutic applications that will benefit or even become possible for the first time with this technological evolution.

consensus and controversial aspects of CT innovation in RT

Laser-plasma based proton accelerators as a novel accelerator technology have matured to a level at which laboratory-scale setups for the emerging topic of image-guided precision small animal irradiation studies come into reach [Bra2019]. Providing a high proton energy bandwidth [Sch2016] which is filtered in a tunable pulsed magnet beam transport, these accelerators enable flexibility in terms of scattering-free irradiation field formation [Mas2014, Mas2015]. Regarding temporal dose delivery, with single pulse doses reaching the Gy level at unprecedented peak dose rates of up to 1012 Gy/s [Sch2016], laser-plasma based proton accelerator setups can give access to the dose rate regime of FLASH [Fav2014, Voz2019]. The realization of a full-scale setup for image-guided precision radiobiological studies for small animals focusing on dose rate dependent effects is currently prepared at the PENELOPE laser-plasma based proton accelerator at HZDR and will be presented with a focus on the technological requirements and solutions for dose delivery at laser-plasma based sources. This development relies on our experience in performing dose-controlled radiobiological in vitro studies [Kra2010, Zei2013] and first in vivo irradiation experiments at the DRACO laser-plasma based proton accelerator at HZDR, where we have established a pulsed solenoid beamline for 3D irradiation field formation, yielding a (5 mm)³ homogeneous volumetric dose distribution at a Gy single pulse dose level [8]. [Bra2019] F.-E. Brack, F. Kroll, L. Gaus, C. Bernert, E. Beyreuther, T. E. Cowan, L. Karsch, S. D. Kraft, L. A. Kunz-Schughart, E. Lessmann, J. Metzkes-Ng, L. Obst-Hübl, J. Pawelke, M. Rehwald, H.-P. Schlenvoigt, U. Schramm, M. Sobiella, E. R. Szabó, T. Ziegler, K. Zeil, Spectral and spatial shaping of laser-driven proton beams using a pulsed high-field magnet beamline. arXiv:1910.08430 (2019) [Sch2016] J. Schreiber, P. Bolton, K. Parodi, “Hands-on” laser-driven ion acceleration: A primer for laser

Next-generation radiation therapy: Towards near-realtime adaptive proton therapy

Highlights in der Medizinphysik

Purpose & Objective A clinical study (PRIMA) regarding the potential of range verification in proton therapy by prompt-gamma imaging (PGI) is carried out at our institution. As a step towards the automatic evaluation of the measured PGI data, we present an approach to detect anatomical changes in prostate cancer patients from realistically simulated PGI data using convolutional neural networks (CNNs). Materials & Methods In-room control CTs (cCTs) were acquired in treatment position before monitoring 146 field deliveries of 10 hypo-fractioned (3Gy/fraction) prostate cancer patients with a PGI slit camera (range: 8-18 fields/patient). After manual CT registration and dose recalculation, spot-wise shifts of integrated depth-dose (IDD) profiles between cCTs and planning CTs were extracted at the 80% distal falloff position and used for ground-truth classification. Treatment fields were considered to be affected by relevant anatomical changes of the patient if >0.1% of all spots (with at least 0.1% of the total monitor units per field) had absolute IDD shifts above 5 mm. These parameters lead to a field-wise IDD ground-truth classification in optimal agreement with a prior manual field-wise classification based on dose difference maps. Based on the cCTs, we simulated realistic PGI profiles, including Poisson noise and a positioning uncertainty of the PGI slit camera, and extracted spot-wise range shifts by comparison with the expected reference profiles for the planning CT. Spots with reliable PGI information (inside field-of-view and >5E7 protons), were considered with their Bragg peak position for generating two independent 3D spatial maps of 161616 voxels (0.740.740.66 cm3): (1) The PGI-determined range shift in each voxel is the weighted average taking the spot-wise proton number into account. (2) The proton number in each voxel is summed over all respective spots and normalized per field (Fig. 1). With these maps and the IDD classification, 3D-CNNs (6 convoluti

The lecture will give an overview of the utilization of prompt-gamma (PG) radiation, emitted from the patient’s body during fractionated particle therapy treatment, for range and treatment verification. After the nuclear physics basics of the emission of prompt gamma rays have been refreshed, the three fundamental approaches for PG-based particle range determination will be discussed, which use either spatial, temporal or spectroscopic information of PG - namely prompt gamma imaging (PGI), prompt gamma timing (PGT) and prompt gamma spectroscopy (PGS), respectively. Special emphasis will be on the interpretation of the complex PG data for the distinction of clinically relevant from irrelevant treatment deviations, necessary for the clinical application of PG for treatment intervention in an online-adaptive PT realization. Results from the evaluation of clinically acquired PGI data will be presented

Online-adaptive particle therapy: Current status and vision for the future Richter, Christian

Recent oncological studies identified beneficial properties of radiation applied at ultra-high dose rates several orders of magnitude higher than the clinical standard of the order of Gy/min. Sources capable of providing these ultra-high dose rates are under investigation. Here, we show that a stable, compact laser-driven proton source with energies greater than 60 MeV enables radiobiological in vivo studies. We performed a pilot irradiation study on human tumors in a mouse model, showing the concerted preparation of mice and laser accelerator, the dose-controlled, tumor-conform irradiation using a laser-driven as well as a clinical reference proton source, and the radiobiological evaluation of irradiated and unirradiated mice for radiation-induced tumor growth delay. The prescribed homogeneous dose of 4 Gy was precisely delivered at the laser-driven source. The results demonstrate a complete laser-driven proton research platform for diverse user-specific small animal models, able to deliver tunable single-shot doses up to around 20 Gy to millimeter-scale volumes on nanosecond time scales, equivalent to around 1E9 Gy/s, spatially homogenized and tailored to the sample. The platform provides a unique infrastructure for translational research with protons at ultra-high dose rate.

Purpose/Objective In this systematic study, we investigate the sensitivity of prompt-gamma imaging (PGI) towards the field-wise detection of inter-fractional anatomical changes in proton therapy (PT) of head and neck cancer (HNC) patients. Materials/Methods Spot-wise range shifts ∆RPGI were monitored with a PGI-slit-camera during 22 field deliveries of HNC pencil beam scanning (PBS) treatments of 4 patients (field-wise dose per fraction: 0.7-1.0GyE). In-room CTs were acquired for all monitored fractions and range shifts ∆RIDD at the 80% falloff of spot-wise integrated depth-dose (IDD) profiles served as input for an automatic field-wise ground truth classification (Fig.1). To receive results consistent with an additional manual dose-based classification per field, a PBS spot with relative weight to the field >0.1% was rated as relevant if |∆RIDD| was ≥5mm for that and at least 1 neighboring spot. Subsequently, a field was classified as relevantly changed if at least 1.5% of all spots were rated relevant. For the independent PGI evaluation, spots were clustered based on Bragg-peak position and proton number to mitigate statistical measurement uncertainty. Clusters with |∆RPGI|≥5mm were classified as relevant. For training of the field-wise PGI classification model, the number of relevant clusters, that is necessary to classify the whole field as relevantly changed, was optimized with respect to the IDD ground truth classification using a training set of 11 fields. Finally, the classification model was validated on an independent test set (11 fields). Results On the level of PGI spot clusters, there is a significant correlation (rPearson=0.3, p<0.01) between IDD and PGI range shifts over all 22 monitored fields (Fig.2B). The only moderate correlation is mainly due to statistical uncertainty of the clusters, represented by the mean absolute error between IDD and PGI range shifts of 3.4mm. The correlation might also be affected by difficult range shift determination due

First studies on range verification in proton therapy using prompt gamma-ray spectroscopy (PGS) or imaging (PGI) have been recently conducted with patients. To benchmark the performance of each method, we designed a multi-center experiment between Massachusetts General Hospital and OncoRay with a shared anthropomorphic head phantom irradiated under equalized conditions. The treatment plan was delivered at clinical beam currents and doses in the respective proton therapy hospitals. Two gantry beam angles were used: horizontal and oblique (270° and 350°). Each field contained the same spot positions and energies as well as target volume in both institutions. The experimentally measured range was compared against the ground truth based on the reference stopping-power map of the phantom. The absolute range error of PGS or PGI was 2.4 mm or -0.5 mm for the horizontal field and 1.3 mm or 2.4 mm for the oblique one, respectively. The ability to detect relative range deviations was assessed by introducing 2 mm and 5 mm plastic slabs on the ventral half of the horizontal field. The measured range shifts were 1.8 mm or 4.8 mm for PGS, and 2.0 mm or 4.2 mm for PGI, respectively. The designed set of experiments represents the first systematic comparison of prompt gamma-ray systems for proton range verification across different institutions using a ground-truth head phantom as reference, and effectively proposes a standard testing platform for benchmarking future proton range verification prototypes in reproducible conditions.

Introduction We present results of the worldwide first systematic study on the sensitivity of prompt-gamma-imaging (PGI) to detect anatomical changes in proton therapy for the ongoing evaluation in prostate-cancer treatments. Materials&Methods Spot-wise range shifts were monitored with a PGI-slit-camera during 40 fractions of hypo-fractionated prostate-cancer treatments (5 patients, 2 fields, each 1.5GyE). In-room CTs were acquired for these fractions and range shifts of spot-wise integrated depth-dose (IDD) profiles serve as ground-truth. For both PGI and IDD data, spots were clustered based on Bragg-peak position and proton number to mitigate statistical uncertainty in the PGI measurement using a low-dose spot cut-off at 5e7 protons, a minimum number of 3e9 protons per cluster, and a minimum/maximum cluster volume of 1cm3/8cm3. Clusters with absolute range shift ≥5mm were classified as relevant anatomical changes. Results A strong correlation (rPearson=0.72) was found between ground-truth IDD and PGI range shifts per cluster with an average absolute deviation of 1.3mm over all fractions. In total, 245/7143 (3.4%) clusters (found within 24/72 fields) contained relevant IDD-based range shifts. PGI detected these changes with a sensitivity of 68%, specificity of 96%, and accuracy of 95%. The results might be affected by potential intra-fractional changes between in-room CT acquisition and treatment delivery. A higher sensitivity is also expected for a gantry-mounted camera system with decreased positioning uncertainty. Conclusion Our systematic investigation on the sensitivity of a PGI-slit-camera with a first quantitative comparison of range shifts from PGI and IDD profiles demonstrates the capability to locally detect relevant anatomical changes in patients.