Influence of sub-nanosecond time of flight resolution for online range verification in proton therapy using the line-cone reconstruction in Compton imaging

Near-field coded-mask technique and its potential for proton therapy monitoring

Objective.Prompt-gamma imaging encompasses several approaches to the online monitoring of the beam range or deposited dose distribution in proton therapy. We test one of the imaging techniques - a coded mask approach - both experimentally and via simulations.Approach.Two imaging setups have been investigated experimentally. Each of them comprised a structured tungsten collimator in the form of a modified uniformly redundant array mask and a LYSO:Ce scintillation detector of fine granularity. The setups differed in detector dimensions and operation mode (1D or 2D imaging). A series of measurements with radioactive sources have been conducted, testing the performance of the setups for near-field gamma imaging. Additionally, Monte Carlo simulations of a larger setup of the same type were conducted, investigating its performance with a realistic gamma source distribution occurring during proton therapy.Main results.The images of point-like sources reconstructed from two small-scale prototypes' data using the maximum-likelihood expectation maximisation algorithm constitute the experimental proof of principle for the near-field coded-mask imaging modality, both in the 1D and the 2D mode. Their precision allowed us to calibrate out certain systematic offsets appearing due to the limited alignment accuracy of setup elements. The simulation of the full-scale setup yielded a mean distal falloff retrieval precision of 0.72 mm in the studies for beam energy range 89.5-107.9 MeV and with 1 × 108protons (a typical number for distal spots). The implemented algorithm of image reconstruction is relatively fast-a typical procedure needs several seconds.Significance.Coded-mask imaging appears a valid option for proton therapy monitoring. The results of simulations let us conclude that the proposed full-scale setup is competitive with the knife-edge-shaped and the multi-parallel slit cameras investigated by other groups.

The OpenGATE ecosystem for Monte Carlo simulation in medical physics

This paper reviews the ecosystem of GATE, an open-source Monte Carlo toolkit for medical physics. Based on the shoulders of Geant4, the principal modules (geometry, physics, scorers) are described with brief descriptions of some key concepts (Volume, Actors, Digitizer). The main source code repositories are detailed together with the automated compilation and tests processes (Continuous Integration). We then described how the OpenGATE collaboration managed the collaborative development of about one hundred developers during almost 20 years. The impact of GATE on medical physics and cancer research is then summarized, and examples of a few key applications are given. Finally, future development perspectives are indicated.

Proton range monitoring based on picosecond detection using a Cherenkov radiation detector: A Monte Carlo study

In this study, we analyzed the performance of a PbF₂ crystal-based detector at proton range monitoring with Monte Carlo simulations. The correlations between the depth-dose and Cherenkov profiles showed that the changes in the peak position in the Cherenkov profiles corresponded to the changes in the corresponding depth-dose profiles. Moreover, the deviations between the changes in the peak positions in the two curves were generally less than 2 mm. The results also showed that the actual proton range could be obtained using flight time information. When the proton energy was 160 MeV, the peak position detected in the Cherenkov profile detected was 14.83 cm with a flight time of 5.3-5.4 ns (starting from the time when protons were emitted), and the actual proton range in polymethyl-methacrylate was 15 cm. Therefore, the accuracy of the proton range measurements could be improved and the absolute range obtained by using the fast and time-sensitive characteristics of the proposed Cherenkov radiator.