ENLIGHT and LEIR biomedical facility.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) 30:5 (2014) 544-550
Abstract:
Particle therapy (including protons and carbon ions) allows a highly conformal treatment of deep-seated tumours with good accuracy and minimal dose to surrounding tissues, compared to conventional radiotherapy using X-rays. Following impressive results from early phase trials, over the last decades particle therapy in Europe has made considerable progress in terms of new institutes dedicated to charged particle therapy in several countries. Particle therapy is a multidisciplinary subject that involves physicists, biologists, radio-oncologists, engineers and computer scientists. The European Network for Light Ion Hadron Therapy (ENLIGHT) was created in response to the growing needs of the European community to coordinate such efforts. A number of treatment centres are already operational and treating patients across Europe, including two dual ion (protons and carbon ions) centres in Heidelberg (the pioneer in Europe) and Pavia. However, much more research needs to be carried out and beamtime is limited. Hence there is a strong interest from the biomedical research community to have a facility with greater access to relevant beamtime. Such a facility would facilitate research in radiobiology and the development of more accurate techniques of dosimetry and imaging. The Low Energy Ion Ring (LEIR) accelerator at CERN presents such an opportunity, and relies partly on CERN's existing infrastructure. The ENLIGHT network, European Commission projects under the ENLIGHT umbrella and the future biomedical facility are discussed.Education and training in medical imaging for conventional and particle radiation therapy through the EC funded envision and ENTERVISION
Romanian Reports in Physics 66:1 (2014) 22-29
Abstract:
A key challenge in particle therapy today is quality assurance during treatment, which needs advanced medical imaging techniques. This issue is tackled by the EC funded project ENVISION, an R&D consortium of sixteen leading European research centres and one industrial partner, co-ordinated by CERN. ENVISION covers developments in Time Of Flight in-beam PET, in-beam single particle tomography, organ motion monitoring techniques, simulation, and treatment planning. Additionally, ENVISION serves as a training platform for the ENTERVISION project, a Marie-Curie Initial Training Network aimed at educating young researchers in online 3D digital imaging for hadron therapy. ENTERVISION brings together ten academic institutes and research centres of excellence and a leading European company in particle therapy, and is coordinated by CERN. Its multi-disciplinary training programme of ENTERVISION includes a diversified portfolio of scientific courses, complemented by specific courses aimed at developing soft skills. The ENTERVISION researchers will also benefit from the involvement in the research activity of ENVISION, and in the European Network for Light Ion Hadron Therapy (ENLIGHT). The trainees are encouraged to build a multidisciplinary network which will not only help them with their future careers but ultimately improve the transfer of knowledge and collaboration between the various disciplines of cancer treatment.A Monte Carlo-based treatment-planning tool for ion beam therapy.
Journal of radiation research 54 Suppl 1 (2013) i77-i81
Abstract:
Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), the MCTP tool is able to perform TP studies using ions with atomic numbers Z ≤ 8. Example treatment plans created with the MCTP tool are presented for carbon ions in comparison with a certified analytical treatment-planning system. Furthermore, the usage of the tool to compute and optimize mixed-ion treatment plans, i.e. plans including pencil beams of ions with different atomic numbers, is demonstrated. The tool is aimed for future use in research applications and to support treatment planning at ion beam facilities.Data-driven Markov models and their application in the evaluation of adverse events in radiotherapy.
Journal of radiation research 54 Suppl 1 (2013) i49-i55
Abstract:
Decision-making processes in medicine rely increasingly on modelling and simulation techniques; they are especially useful when combining evidence from multiple sources. Markov models are frequently used to synthesize the available evidence for such simulation studies, by describing disease and treatment progress, as well as associated factors such as the treatment's effects on a patient's life and the costs to society. When the same decision problem is investigated by multiple stakeholders, differing modelling assumptions are often applied, making synthesis and interpretation of the results difficult. This paper proposes a standardized approach towards the creation of Markov models. It introduces the notion of 'general Markov models', providing a common definition of the Markov models that underlie many similar decision problems, and develops a language for their specification. We demonstrate the application of this language by developing a general Markov model for adverse event analysis in radiotherapy and argue that the proposed method can automate the creation of Markov models from existing data. The approach has the potential to support the radiotherapy community in conducting systematic analyses involving predictive modelling of existing and upcoming radiotherapy data. We expect it to facilitate the application of modelling techniques in medical decision problems beyond the field of radiotherapy, and to improve the comparability of their results.Feasibility study for a biomedical experimental facility based on LEIR at CERN.
Journal of radiation research 54 Suppl 1 (2013) i162-i167