Gabriele Parisi, Lucrezia Bianchi, Pierre Couture, Vladimir Palitsin, Andrea Fabbri, Giuseppe Schettino, Francesco Romano, Claudio Verona
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引用次数: 0
Abstract
Objective.The increasing interest in hadron therapy has heightened the need for accurate and reliable methods to assess radiation quality and the biological effectiveness of particles used in treatment. Microdosimetry has emerged as a key tool for this, demonstrating its potential, reliability, and suitability. In this context, solid-state microdosimeters offer technological advantages over traditional tissue-equivalent proportional counters, and recent advancements have further improved their performance and reliability. However, one critical challenge in solid-state microdosimetry is the so-called 'border effect', which can impact measurement accuracy.Approach.In this study, the border effect in diamond microdosimeters was thoroughly studied using ion beam induced charge analysis. The research, relying on experiments conducted at the Surrey Ion Beam Centre, developed an effective method to characterise and quantify the border effect. Geant4 Monte Carlo simulations were also employed to assess the impact of the border effect under typical proton therapy conditions.Main results. The border effect in diamond microdosimeter was characterised and studied as a function of detector thickness, particle atomic number and particle range. A border effect model was developed and validated to reproduce the border effect in Monte Carlo simulations. The results of its application to the microdosimetry of a proton beam at different depths in water showed potential significant variations of up to 40% iny¯Fand 20% iny¯Dvalues.Significance.The results of this work highlight the importance of accurately characterising the border effect and encouraging further research to mitigate its influence on microdosimetry measurements.
期刊介绍:
The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry