Hadrontherapy uses charged particles to destroy tumors. For improving the quality assurance tools, specially range verification, the European Commission funded the project ENVISION. This paper summarizes the activities carried out within the work package two devoted to improve the visualization of the spatial distribution of positron emitters that are produced during patient irradiation. Allowing the beam passage implies a reduction in the angular coverage which degrades the range assessment. The aim of the work package two was to investigate the potential use of time-of-flight information for compensating this degradation. The studies can be classified into hardware and software developments. For the former, several ASICs and DAQs have been investigated. Also, the potential application of resistive plate chambers has been assessed. Four dual-head demonstrators have been produced by the end of the project. The software developments are divided into simulations and image reconstruction. Several algorithms able to include the time-of-flight information have been developed. Direct reconstruction has been implemented and compared with conventional maximum-likelihood methods. The results show that direct time-of-flight for on-line reconstruction is possible although iterative algorithms can achieve further improvements. However, time-of-flight alone might not be sufficient due to the low emission rates.
Accidental coincidences are one of the main sources of image degradation in positron emission tomography. It is possible to compensate for their degradation effects, but an accurate method to estimate the randoms rate is required. Two conventional methods are used for random rate estimation: the "singles rate" method and the "delayed window" method. In this work we propose a mathematical model that describes the process of accidental coincidence formation. By using it, we are able to predict the correct number of randoms as well as the estimations provided the singles rate and delayed window methods. The model is used to propose a novel estimation method: the "singles-prompt". The aim of this work is to assess the performance of the singles-prompt method and, specially, the model capabilities at several levels. The results agree with all the predictions of the model. In particular, the singles rate and delayed window estimations behave as described by the model and the singles-prompt method estimates the correct number of randoms regardless of the source distribution and total activities.
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