Proton range verification with MACACO II Compton camera enhanced by a neural network for event selection.

The applicability extent of hadron therapy for tumor treatment is currently limited by the lack of reliable online monitoring techniques. An active topic of investigation is the research of monitoring systems based on the detection of secondary radiation produced during treatment. MACACO, a multi-layer Compton camera based on LaBr3 scintillator crystals and SiPMs, is being developed at IFIC-Valencia for this purpose. This work reports the results obtained from measurements of a 150 MeV proton beam impinging on a PMMA target. A neural network trained on Monte Carlo simulations is used for event selection, increasing the signal to background ratio before image reconstruction. Images of the measured prompt gamma distributions are reconstructed by means of a spectral reconstruction code, through which the 4.439 MeV spectral line is resolved. Images of the emission distribution at this energy are reconstructed, allowing calculation of the distal fall-off and identification of target displacements of 3 mm.

A spectral reconstruction algorithm for two-plane Compton cameras.

One factor limiting the current applicability extent of hadron therapy is the lack of a reliable method for real time treatment monitoring. The use of Compton imaging systems as monitors requires the correct reconstruction of the distribution of prompt gamma productions during patient irradiation. In order to extract the maximum information from all the measurable events, we implemented a spectral reconstruction method that assigns to all events a probability of being either partial or total energy depositions. The method, implemented in a list-mode maximum likelihood expectation maximization algorithm, generates a four dimensional image in the joint spatial-spectral domain, in which the voxels containing the emission positions and energies are obtained. The analytical model used for the system response function is also employed to derive an analytical expression for the sensitivity, which is calculated via Monte Carlo integration. The performance of the method is evaluated through reconstruction of various experimental and simulated sources with different spatial and energy distributions. The results show that the proposed method can recover the spectral and spatial information simultaneously, but only under the assumption of ideal measurements. The analysis of the Monte Carlo simulations has led to the identification of two important degradation sources: the mispositioning of the gamma interaction point and the missing energy recorded in the interaction. Both factors are related to the high energy transferred to the recoil electrons, which can travel far from the interaction point and even escape the detector. These effects prevent the direct application of the current method in more realistic scenarios. Nevertheless, experimental point-like sources have been accurately reconstructed and the spatial distributions and spectral emission of complex simulated phantoms can be identified.

Study and comparison of different sensitivity models for a two-plane Compton camera.

Given the strong variations in the sensitivity of Compton cameras for the detection of events originating from different points in the field of view (FoV), sensitivity correction is often necessary in Compton image reconstruction. Several approaches for the calculation of the sensitivity matrix have been proposed in the literature. While most of these models are easily implemented and can be useful in many cases, they usually assume high angular coverage over the scattered photon, which is not the case for our prototype. In this work, we have derived an analytical model that allows us to calculate a detailed sensitivity matrix, which has been compared to other sensitivity models in the literature. Specifically, the proposed model describes the probability of measuring a useful event in a two-plane Compton camera, including the most relevant physical processes involved. The model has been used to obtain an expression for the system and sensitivity matrices for iterative image reconstruction. These matrices have been validated taking Monte Carlo simulations as a reference. In order to study the impact of the sensitivity, images reconstructed with our sensitivity model and with other models have been compared. Images have been reconstructed from several simulated sources, including point-like sources and extended distributions of activity, and also from experimental data measured with 22Na sources. Results show that our sensitivity model is the best suited for our prototype. Although other models in the literature perform successfully in many scenarios, they are not applicable in all the geometrical configurations of interest for our system. In general, our model allows to effectively recover the intensity of point-like sources at different positions in the FoV and to reconstruct regions of homogeneous activity with minimal variance. Moreover, it can be employed for all Compton camera configurations, including those with low angular coverage over the scatterer.