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- Aad, G, et al.
(författare)
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- 2015
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swepub:Mat__t
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- Schael, S, et al.
(författare)
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Precision electroweak measurements on the Z resonance
- 2006
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Ingår i: Physics Reports. - : Elsevier BV. - 0370-1573 .- 1873-6270. ; 427:5-6, s. 257-454
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Forskningsöversikt (refereegranskat)abstract
- We report on the final electroweak measurements performed with data taken at the Z resonance by the experiments operating at the electron-positron colliders SLC and LEP. The data consist of 17 million Z decays accumulated by the ALEPH, DELPHI, L3 and OPAL experiments at LEP, and 600 thousand Z decays by the SLID experiment using a polarised beam at SLC. The measurements include cross-sections, forward-backward asymmetries and polarised asymmetries. The mass and width of the Z boson, m(Z) and Gamma(Z), and its couplings to fermions, for example the p parameter and the effective electroweak mixing angle for leptons, are precisely measured: m(Z) = 91.1875 +/- 0.0021 GeV, Gamma(Z) = 2.4952 +/- 0.0023 GeV, rho(l) = 1.0050 +/- 0.0010, sin(2)theta(eff)(lept) = 0.23153 +/- 0.00016. The number of light neutrino species is determined to be 2.9840 +/- 0.0082, in agreement with the three observed generations of fundamental fermions. The results are compared to the predictions of the Standard Model (SM). At the Z-pole, electroweak radiative corrections beyond the running of the QED and QCD coupling constants are observed with a significance of five standard deviations, and in agreement with the Standard Model. Of the many Z-pole measurements, the forward-backward asymmetry in b-quark production shows the largest difference with respect to its SM expectation, at the level of 2.8 standard deviations. Through radiative corrections evaluated in the framework of the Standard Model, the Z-pole data are also used to predict the mass of the top quark, m(t) = 173(+10)(+13) GeV, and the mass of the W boson, m(W) = 80.363 +/- 0.032 GeV. These indirect constraints are compared to the direct measurements, providing a stringent test of the SM. Using in addition the direct measurements of m(t) and m(W), the mass of the as yet unobserved SM Higgs boson is predicted with a relative uncertainty of about 50% and found to be less than 285 GeV at 95% confidence level. (c) 2006 Elsevier B.V. All rights reserved.
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- Fager, Marcus, et al.
(författare)
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Linear energy transfer painting with proton therapy : a means of reducing radiation doses with equivalent clinical effectiveness
- 2015
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Ingår i: International Journal of Radiation Oncology, Biology, Physics. - : Elsevier BV. - 0360-3016 .- 1879-355X. ; 91:5, s. 1057-1064
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The purpose of this study was to propose a proton treatment planning method that trades physical dose (D) for dose-averaged linear energy transfer (LETd) while keeping the radiobiologically weighted dose (DRBE) to the target the same.Methods and Materials: The target is painted with LETd by using 2, 4, and 7 fields aimed at the proximal segment of the target (split target planning [STP]). As the LETd within the target increases with increasing number of fields, D decreases to maintain the DRBE the same as the conventional treatment planning method by using beams treating the full target (full target planning [FTP]).Results: The LETd increased 61% for 2-field STP (2STP) compared to FTP, 72% for 4STP, and 82% for 7STP inside the target. This increase in LETd led to a decrease of D with 5.3 ± 0.6 Gy for 2STP, 4.4 ± 0.7 Gy for 4STP, and 5.3 ± 1.1 Gy for 7STP, keeping the DRBE at 90% of the volume (DRBE, 90) constant to FTP.Conclusions: LETd painting offers a method to reduce prescribed dose at no cost to the biological effectiveness of the treatment.
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- Henthorn, Nicholas T., et al.
(författare)
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Mapping the Future of Particle Radiobiology in Europe : The INSPIRE Project
- 2020
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Ingår i: Frontiers in Physics. - : Frontiers Media SA. - 2296-424X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- 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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- Sørensen, Brita S., et al.
(författare)
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Does uncertainty in variability in relative biological effectiveness affect patient treatment in proton therapy?
- 2021
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Ingår i: Radiotherapy and Oncology. - : Elsevier. - 0167-8140 .- 1879-0887. ; 163, s. 177-184
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Forskningsöversikt (refereegranskat)abstract
- Clinical treatment with protons uses the concept of relative biological effectiveness (RBE) to convert the absorbed dose into an RBE-weighted dose that equals the dose for radiotherapy with photons causing the same biological effect. Currently, in proton therapy a constant RBE of 1.1 is generically used. However, empirical data indicate that the RBE is not constant, but increases at the distal edge of the proton beam. This increase in RBE is of concern, as the clinical impact is still unresolved, and clinical studies demonstrating a clinical effect of an increased RBE are emerging. Within the European Particle Therapy Network (EPTN) work package 6 on radiobiology and RBE, a workshop was held in February 2020 in Manchester with one day of discussion dedicated to the impact of proton RBE in a clinical context. Current data on RBE effects, patient outcome and modelling from experimental as well as clinical studies were presented and discussed. Furthermore, representatives from European clinical proton therapy centres, who were involved in patient treatment, laid out their current clinical practice on how to consider the risk of a variable RBE in their centres. In line with the workshop, this work considers the actual impact of RBE issues on patient care in proton therapy by reviewing pre clinical data on the relation between linear energy transfer (LET) and RBE, current clinical data sets on RBE effects in patients, and applied clinical strategies to manage RBE uncertainties. A better understanding of the variability in RBE would allow development of proton treatments which are safer and more effective.
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- Unkelbach, Jan, et al.
(författare)
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The role of computational methods for automating and improving clinical target volume definition
- 2020
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Ingår i: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140 .- 1879-0887. ; 153, s. 15-25
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Tidskriftsartikel (refereegranskat)abstract
- Treatment planning in radiotherapy distinguishes three target volume concepts: the gross tumor volume(GTV), the clinical target volume (CTV), and the planning target volume (PTV). Over time, GTV definitionand PTV margins have improved through the development of novel imaging techniques and better imageguidance, respectively. CTV definition is sometimes considered the weakest element in the planning pro-cess. CTV definition is particularly complex since the extension of microscopic disease cannot be seenusing currently available in-vivo imaging techniques. Instead, CTV definition has to incorporate knowl-edge of the patterns of tumor progression. While CTV delineation has largely been considered the domainof radiation oncologists, this paper, arising from a 2019 ESTRO Physics research workshop, discusses thecontributions that medical physics and computer science can make by developing computational meth-ods to support CTV definition. First, we overview the role of image segmentation algorithms, which mayin part automate CTV delineation through segmentation of lymph node stations or normal tissues repre-senting anatomical boundaries of microscopic tumor progression. The recent success of deep convolu-tional neural networks has also enabled learning entire CTV delineations from examples. Second, wediscuss the use of mathematical models of tumor progression for CTV definition, using as example theapplication of glioma growth models to facilitate GTV-to-CTV expansion for glioblastoma that is consis-tent with neuroanatomy. We further consider statistical machine learning models to quantify lymphaticmetastatic progression of tumors, which may eventually improve elective CTV definition. Lastly, we dis-cuss approaches to incorporate uncertainty in CTV definition into treatment plan optimization as well asgeneral limitations of the CTV concept in the case of infiltrating tumors without natural boundaries.
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