Report of a National Cancer Institute special panel: Characterization of the physical parameters of particle beams for biological research

Durante, Marco; Paganetti, Harald; Pompoš, A.; Kry, Stephen F; Wu, Xiaodong; Grosshans, David R.

doi:10.1002/mp.13324

Cited by 24 publications

(22 citation statements)

References 99 publications

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“…Machine learning techniques could also be applied to find dependencies in the database. If full LET spectrum data extracted from the experiments will be reported in the future, as discussed in recent reviews (Durante et al 2019, Paganetti et al 2019b, spectral unfolding techniques could alternatively be used to find the best fitting model functions (Reginatto 2010). As our investigations in Paper I shows, most models can be described by simple functions with one to four coefficients.…”

Section: Regression Techniquesmentioning

confidence: 99%

“…The publications may include and report different errors or correct the experiments for different effects (Paganetti 2014). Recently, two guides on reporting of experimental data have been published, which could contribute to more coherent methods in future experiments (Paganetti et al 2019b, Durante et al 2019.…”

Section: Experimental Databasesmentioning

confidence: 99%

“…As recently suggested by the work groups on RBE experiments (Durante et al 2019, Paganetti et al 2019b, the full LET spectrum from experiments could be reported.…”

Section: Suggestions To Experimental Reportingmentioning

confidence: 99%

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Exploration and application of phenomenological RBE models for proton therapy

et al. 2018

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The relative biological effectiveness (RBE) of protons varies with multiple physical and biological factors. Phenomenological RBE models have been developed to include such factors in the estimation of a variable RBE, in contrast to the clinically applied constant RBE of 1.1. In this study, eleven published phenomenological RBE models and two plan-based models were explored and applied to simulated patient cases. All models were analysed with respect to the distribution and range of linear energy transfer (LET) and reference radiation fractionation sensitivity ((α/β) ) of their respective experimental databases. Proton therapy plans for a spread-out Bragg peak in water and three patient cases (prostate adenocarcinoma, pituitary adenoma and thoracic sarcoma) were optimised using an RBE of 1.1 in the Eclipse treatment planning system prior to recalculation and modelling in the FLUKA Monte Carlo code. Model estimated dose-volume parameters for the planning target volumes (PTVs) and organs at risk (OAR) were compared. The experimental in vitro databases for the various models differed greatly in the range of (α/β) values and dose-averaged LET (LET). There were significant variations between the model estimations, which arose from fundamental differences in the database definitions and model assumptions. The greatest variations appeared in organs with low (α/β) and high LET, e.g. biological doses given to late responding OARs located distal to the target in the treatment field. In general, the variation in maximum dose (D) was larger than the variation in mean dose and other dose metrics, with D of the left optic nerve ((α/β) = 2.1 Gy) in the pituitary adenoma case showing the greatest discrepancies between models: 28-52 Gy(RBE), while D for RBE was 30 Gy(RBE). For all patient cases, the estimated mean RBE to the PTV was in the range 1.09-1.29 ((α/β) = 1.5/3.1/10.6 Gy). There were considerable variations between the estimations of RBE and RBE-weighted doses from the different models. These variations were a consequence of fundamental differences in experimental databases, model assumptions and regression techniques. The results from the implementation of RBE models in dose planning studies should be evaluated in light of these deviations.

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Section: Regression Techniquesmentioning

confidence: 99%

Section: Experimental Databasesmentioning

confidence: 99%

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Exploration and application of phenomenological RBE models for proton therapy

et al. 2018

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“…Most published in vitro RBE experiments do not provide the LET d at the measurement points, and when it has been reported it is often roughly estimated from stopping power tables, based on the beam energy (Paganetti 2014). To ensure accurate LET estimations of the beam, it is therefore important with proper implementation of the experimental setup in Monte Carlo codes (Durante et al 2019). This was also emphasized in an editorial following the publication of Paper I (Grassberger and Paganetti 2017), which highlighted how Paper I and similar studies are necessary in paving the way for clinically biological treatment modelling, by decreasing experimental error by characterizing the incoming beam…”

Section: Improving Rbe Measurement Datamentioning

confidence: 99%

Sensitivity study of the microdosimetric kinetic model parameters for carbon ion radiotherapy

Magro¹,

Ytre-Hauge²,

Stokkevåg³

et al. 2018

Phys. Med. Biol.

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Acknowledgements This thesis could not have been written without help and support from the people I have worked with the last four years. I am very grateful and privileged for the opportunity this thesis has given me to work with all of you. The thesis would neither have been possible without funding. I am grateful for the financial support from the University of Bergen and the Trond Mohn Foundation. However, I would first and foremost like to thank my main supervisor, Kristian Smeland Ytre-Hauge, for all the help and encouragement throughout these years. Thank you for giving me this opportunity and for guiding me through these four years. Your support in all parts of this PhD project has been invaluable. I really appreciate all the time you spend on making your group in medical physics into such a good place to be. I want to give warm thanks to my co-supervisors Andrea Mairani and Camilla Stokkevåg. Thank you, Andrea, for inviting me to spend five weeks at CNAO in Pavia. Our discussions and your help with FLUKA have been very valuable. I really appreciate that you always have been available, also after my stay in Pavia. To Camilla: Thank you for your guidance during these years. I really appreciate your clinical insight and all the work you have put into helping me, especially by giving positive and constructive feedback on my work. My stay at CNAO gave me a more practical insight to the field of particle therapy, and I got to know many people who helped me with my work. Thanks to Giuseppe Magro, for welcoming me to CNAO and making sure that I had a good time both at and after work. Your help, both at CNAO and later, has really been appreciated. I would also like to thank Kyungdon Choi for help with programming during and after my stay at CNAO. I would like to acknowledge all my collaborators in Oslo. I am especially grateful to Eirik Malinen, who has been my main contact there and who has been involved in all my work with the Oslo group. I would also like to thank Nina Edin and Anne Marit Rykkelid for giving me insight into cell irradiation experiments and for help on the Oslo Cyclotron Laboratory beamline, and Espen Rusten for help with the hypoxia project, especially with analyzing PET images. Through the people in Oslo, I was also introduced to several PET experts in Turku, Finland, and I would like to thank you all for sharing your knowledge.

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“…This systematic and coordinated approach will highlight factors leading to variation and propose mitigation strategies for future studies. These mitigation strategies will help to develop best practices for proton radiobiology research and build upon previous work on the topic [36]. Alongside coordinated research INSPIRE also seeks to improve the infrastructure available to European researchers through its TNA.…”

Section: Introductionmentioning

confidence: 99%

Mapping the Future of Particle Radiobiology in Europe: The INSPIRE Project

et al. 2020

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Particle therapy is a growing cancer treatment modality worldwide. However, there still remains a number of unanswered questions considering differences in the biological response between particles and photons. These questions, and probing of biological mechanisms in general, necessitate experimental investigation. The "Infrastructure in Proton International Research" (INSPIRE) project was created to provide an infrastructure for European research, unify research efforts on the topic of proton and ion therapy across Europe, and to facilitate the sharing of information and resources. This work highlights the radiobiological capabilities of the INSPIRE partners, providing details of physics (available particle types and energies), biology (sample preparation and post-irradiation analysis), and researcher access (the process of applying for beam time). The collection of information reported here is designed to provide researchers both in Europe and worldwide with the tools required to select the optimal center for their research needs. We also highlight areas of redundancy in capabilities and suggest areas for future investment.

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Report of a National Cancer Institute special panel: Characterization of the physical parameters of particle beams for biological research

Cited by 24 publications

References 99 publications

Exploration and application of phenomenological RBE models for proton therapy

Exploration and application of phenomenological RBE models for proton therapy

Sensitivity study of the microdosimetric kinetic model parameters for carbon ion radiotherapy

Mapping the Future of Particle Radiobiology in Europe: The INSPIRE Project

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