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There is a rising interest in developing and utilizing arc delivery techniques with charged particle beams, e.g., proton, carbon or other ions, for clinical implementation. In this work, perspectives from the European Society for Radiotherapy and Oncology (ESTRO) 2022 physics workshop on particle arc therapy are reported. This outlook provides an outline and prospective vision for the path forward to clinically deliverable proton, carbon, and other ion arc treatments. Through the collaboration among industry, academic, and clinical research and development, the scientific landscape and outlook for particle arc therapy are presented here to help our community understand the physics, radiobiology, and clinical principles. The work is presented in three main sections: (i) treatment planning, (ii) treatment delivery, and (iii) clinical outlook., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Sophie Wuyckens is funded by the Walloon Region as part of the Arc Proton Therapy convention (Pôles Mecatech et Biowin). Liu Hong and Guillaume Jansens are employed by ION BEAM APPLICATIONS SA (IBA Ltd). Research by Bas De Jong and Stefan Both is partly funded byION BEAM APPLICATIONS SA (IBA Ltd). Thomas Mackie is on the Board and has a financialinterest(stocks) and salary from Leo Cancer Care.Erik Engwall is employed by RaySearch. Martin Soukup is employed by Elekta. Xuanfeng Ding and Xiaoqiang Li have patents related to the particle arc therapy and it has been licensed to IBA. Xuanfeng Ding received honorium from IBA and Elekta’s speaker Bureau and the research project on proton arc therapy is in part supported by IBA and Elekta., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background and Purpose: Compared to intensity modulated proton therapy (IMPT), proton arc therapy (PAT) is expected to improve dose conformality, delivery efficiency, and provide a more favorable LET distribution. Alternatively, the low-dose bath is potentially spread over larger volumes, which could impact the likelihood of developing a radiation-induced, secondary cancer (SC). The goal of this study was to evaluate this risk in several anatomical sites using newly developed commercial tools., Materials and Methods: Treatment plans encompassing six anatomical sites, five patients per site, and three techniques per patient were created using RayStation. Techniques included PAT and IMPT for protons, and either volumetrically modulated radiotherapy (VMAT) or intensity modulated radiotherapy (IMRT) for photons. Risk estimates were based on the organ-equivalent dose (OED) concept using both Schneider's mechanistic dose-response model for carcinoma induction and a linear dose-response model., Results: With few exceptions, mean and integral dose were lowest with PAT. For protons, the factor OED IMPT /OED PAT ranged from 0.7 to 1.8 with both the mechanistic and linear model, while for photons OED photon /OED PAT ranged from 1.5 to 10 using the mechanistic model and 1.3 to using the linear model. A strong correlation was found between mean dose and OED for organs with significant repopulation/repair (high R value) and less cell death from single hit interactions (low α value)., Conclusion: Based on results from both mechanistic and linear risk models, the transition from IMPT to PAT should not substantially affect SC risk in patients treated with proton therapy. Additionally, when using Schneider's model, the shapes of the dose-response curves can be used as a good predictor of how SC risk will respond to shifts from intermediate dose to low dose as anticipated when moving from IMPT to PAT., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: This work was funded by Ion Beam Applications (IBA – Louvain-la-Neuve)., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Microvascular obstruction (MVO) measured by cardiac magnetic resonance (CMR) after ST-segment elevation myocardial infarction (STEMI) has important prognostic implications. While invasive index of microvascular resistance (IMR) have been shown to predict the occurrence and extent of MVO, the role of the angiography-based microvascular resistance (Angio-IMR) for this purpose remains unknown. The present study aims to perform a head-to-head comparison of wire-based and angiography-derived microcirculatory resistance (IMR and Angio-IMR, respectively) for the detection of MVO., Methods: Patients with a first STEMI and multivessel disease underwent CMR for detection of MVO, and angio-IMR and IMR measurements during PPCI and at 30 day follow up, both in STEMI culprit and non-culprit vessels., Results: 58 patients were included (mean age 60.7 ± 9.9 years, 82% male). At the time of PPCI, angio-IMR and IMR exhibited significant correlation (r = 0.70, P < 0.001), and agreement (coefficient of agreement 0.58). Both indices showed good predictive value of MVO [Angio IMR: AUC 0.79 (95% CI: 0.667-0.928); IMR: AUC 0.70 (95% CI: 0.539-0.853); p = 0.15]. Angio-IMR 40 U and IMR 34 U were identified as best cut-offs for prediction of MVO. In non-culprit vessels, angio-IMR and IMR also correlated well (rho = 0.59, p < 0.001), with overall lower mean values compared to culprit vessels (Angio-IMR: 36 vs. 23; IMR: 39 vs. 22, p < 0.001 for both comparisons)., Conclusion: Angio-IMR constitutes a valid alternative to wire-based IMR in predicting MVO in STEMI. Angio-IMR and IMR show a good correlation in the acute and subacute STEMI phases, both in culprit and non-culprit vessels., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective. Prompt gamma (PG) radiation generated from nuclear reactions between protons and tissue nuclei can be employed for range verification in proton therapy. A typical clinical workflow for PG range verification compares the detected PG profile with a predicted one. Recently, a novel analytical PG prediction algorithm based on the so-called filtering formalism has been proposed and implemented in a research version of RayStation (RaySearch Laboratories AB), which is a widely adopted treatment planning system. This work validates the performance of the filtering PG prediction approach. Approach. The said algorithm is validated against experimental data and benchmarked with another well-established PG prediction algorithm implemented in a MATLAB-based software REGGUI. Furthermore, a new workflow based on several PG profile quality criteria and analytical methods is proposed for data selection. The workflow also calculates sensitivity and specificity information, which can help practitioners to decide on irradiation course interruption during treatment and monitor spot selection at the treatment planning stage. With the proposed workflow, the comparison can be performed on a limited number of selected high-quality irradiation spots without neighbouring-spot aggregation. Main results. The mean shifts between the experimental data and the predicted PG detection (PGD) profiles (ΔPGD) by the two algorithms are estimated to be1.5±2.1mm and-0.6±2.2mm for the filtering and REGGUI prediction methods, respectively. The ΔPGD difference between two algorithms is observed to be consistent with the beam model difference within uncertainty. However, the filtering approach requires a much shorter computation time compared to the REGGUI approach. Significance. The novel filtering approach is successfully validated against experimental data and another widely used PG prediction algorithm. The workflow designed in this work selects spots with high-quality PGD shift calculation results, and performs sensitivity and specificity analyses to assist clinical decisions., (Creative Commons Attribution license.)

Background: Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional proton treatments. However, the delivery speed achievable in proton arc relies on dedicated algorithms, which currently do not generate plans with a clear speed-up and sometimes even result in increased delivery time., Purpose: This study aims to address the challenge of minimizing delivery time through a hybrid method combining a fast geometry-based energy layer (EL) pre-selection with a dose-based EL filtering, and comparing its performance to a baseline approach without filtering., Methods: Three methods of EL filtering were developed: unrestricted, switch-up (SU), and switch-up gap (SU gap) filtering. The unrestricted method filters the lowest weighted EL while the SU gap filtering removes the EL around a new SU to minimize the gantry rotation braking. The SU filtering removes the lowest weighted group of EL that includes a SU. These filters were combined with the RayStation dynamic proton arc optimization framework energy layer selection and spot assignment (ELSA). Four bilateral oropharyngeal and four lung cancer patients' data were used for evaluation. Objective function values, target coverage robustness, organ-at-risk doses and normal tissue complication probability evaluations, as well as comparisons to intensity-modulated proton therapy (IMPT) plans, were used to assess plan quality., Results: The SU gap filtering algorithm performed best in five out of the eight cases, maintaining plan quality within tolerance while reducing beam delivery time, in particular for the oropharyngeal cohort. It achieved up to approximately 22% and 15% reduction in delivery time for oropharyngeal and lung treatment sites, respectively. The unrestricted filtering algorithm followed closely. In contrast, the SU filtering showed limited improvement, suppressing one or two SU without substantial delivery time shortening. Robust target coverage was kept within 1% of variation compared to the PAT baseline plan while organs-at-risk doses slightly decreased or kept about the same for all patients., Conclusions: This study provides insights to accelerate PAT delivery without compromising plan quality. These advancements could enhance treatment efficiency and patient throughput., (© 2024 American Association of Physicists in Medicine.)

Natural mineral water (termed hora in Afan Oromo) and surrounding soils are the most important source of mineral supplement traditionally used for livestock in many parts of Ethiopia. However, limited information exists on feeding practices and the impact of hora on animal performance. Thus, the present study aimed to assess farmers' feeding practices and perceptions about the role of hora and surrounding soils on animal performance. Data were collected from 385 households in four districts (Bedele, Dabo, Gechi and Boracha) through face-to-face interviews using a semi-structured questionnaire with the help of the KoboCollect application. Data were analyzed using SPSS version 26. The majority (72.3 %) of respondents reported hora as an important source of mineral supplement for livestock. About 78.1 % of respondents in Boracha routinely supplement their animals compared with farmers from other districts. Large ruminants were given first priority in supplementation with hora compared to other livestock. Interviewed farmers trekked their animals a distance of 6.5 ± 0.2 km to access hora twice a year during the dry season. The majority of the farmers (68.1 %) believed that hora supplementation improved animal performance, while 35.1 % noted negative impacts such as abortions, birth defects, delayed puberty, decreased conception rates and paralysis due to excessive consumption. This study underscores the perceived importance of hora as a natural source of mineral supplementation for livestock health and productivity. It emphasizes the need for improved management and conservation practices to ensure sustainable utilisation and mitigate negative impacts associated with excessive consumption. Moreover, to validate local farmers' perceptions regarding the importance of hora mineral water in animal nutrition and health, further research is needed to determine mineral composition of hora and livestock responses under controlled feeding trials., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 Published by Elsevier Ltd.)