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Etxebeste, A., Barrio, J., Muñoz, E., Oliver, J. F., Solaz, C., & Llosa, G. (2016). 3D position determination in monolithic crystals coupled to SiPMs for PET. Phys. Med. Biol., 61(10), 3914–3934.
Abstract: The interest in using continuous monolithic crystals in positron emission tomography (PET) has grown in the last years. Coupled to silicon photomultipliers (SiPMs), the detector can combine high sensitivity and high resolution, the two main factors to be maximized in a positron emission tomograph. In this work, the position determination capability of a detector comprised of a 12 x 12 x 10 mm(3) LYSO crystal coupled to an 8 x 8-pixel array of SiPMs is evaluated. The 3D interaction position of.-rays is estimated using an analytical model of the light distribution including reflections on the facets of the crystal. Monte Carlo simulations have been performed to evaluate different crystal reflectors and geometries. The method has been characterized and applied to different cases. Intrinsic resolution obtained with the position estimation method used in this work, applied to experimental data, achieves sub-millimetre resolution values. Average resolution over the detector surface for 5 mm thick crystal is similar to 0.9 mm FWHM and similar to 1.2 mm FWHM for 10 mm thick crystal. Depth of interaction resolution is close to 2 mm FWHM in both cases, while the FWTM is similar to 5.3 mm for 5 mm thick crystal and similar to 9.6 mm for 10 mm thick crystal.
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Solevi, P. et al, Oliver, J. F., Gillam, J. E., & Rafecas, M. (2013). A Monte-Carlo based model of the AX-PET demonstrator and its experimental validation. Phys. Med. Biol., 58(16), 5495–5510.
Abstract: AX-PET is a novel PET detector based on axially oriented crystals and orthogonal wavelength shifter (WLS) strips, both individually read out by silicon photo-multipliers. Its design decouples sensitivity and spatial resolution, by reducing the parallax error due to the layered arrangement of the crystals. Additionally the granularity of AX-PET enhances the capability to track photons within the detector yielding a large fraction of inter-crystal scatter events. These events, if properly processed, can be included in the reconstruction stage further increasing the sensitivity. Its unique features require dedicated Monte-Carlo simulations, enabling the development of the device, interpreting data and allowing the development of reconstruction codes. At the same time the non-conventional design of AX-PET poses several challenges to the simulation and modeling tasks, mostly related to the light transport and distribution within the crystals and WLS strips, as well as the electronics readout. In this work we present a hybrid simulation tool based on an analytical model and a Monte-Carlo based description of the AX-PET demonstrator. It was extensively validated against experimental data, providing excellent agreement.
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Muñoz, E., Barrientos, L., Bernabeu, J., Borja-Lloret, M., Llosa, G., Ros, A., et al. (2020). A spectral reconstruction algorithm for two-plane Compton cameras. Phys. Med. Biol., 65(2), 025011–17pp.
Abstract: 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.
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Oliver, J. F., Fuster-Garcia, E., Cabello, J., Tortajada, S., & Rafecas, M. (2013). Application of Artificial Neural Network for Reducing Random Coincidences in PET. IEEE Trans. Nucl. Sci., 60(5), 3399–3409.
Abstract: Positron Emission Tomography (PET) is based on the detection in coincidence of the two photons created in a positron annihilation. In conventional PET, this coincidence identification is usually carried out through a coincidence electronic unit. An accidental coincidence occurs when two photons arising from different annihilations are classified as a coincidence. Accidental coincidences are one of the main sources of image degradation in PET. Some novel systems allow coincidences to be selected post-acquisition in software, or in real time through a digital coincidence engine in an FPGA. These approaches provide the user with extra flexibility in the sorting process and allow the application of alternative coincidence sorting procedures. In this work a novel sorting procedure based on Artificial Neural Network (ANN) techniques has been developed. It has been compared to a conventional coincidence sorting algorithm based on a time coincidence window. The data have been obtained from Monte-Carlo simulations. A small animal PET scanner has been implemented to this end. The efficiency (the ratio of correct identifications) can be selected for both methods. In one case by changing the actual value of the coincidence window used, and in the other by changing a threshold at the output of the neural network. At matched efficiencies, the ANN-based method always produces a sorted output with a smaller random fraction. In addition, two differential trends are found: the conventional method presents a maximum achievable efficiency, while the ANN-based method is able to increase the efficiency up to unity, the ideal value, at the cost of increasing the random fraction. Images reconstructed using ANN sorted data (no compensation for randoms) present better contrast, and those image features which are more affected by randoms are enhanced. For the image quality phantom used in the paper, the ANN method decreases the spill-over ratio by a factor of 18%.
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Bolle, E., Casella, C., Chesi, E., De Leo, R., Dissertori, G., Fanti, V., et al. (2012). AX-PET: A novel PET concept with G-APD readout. Nucl. Instrum. Methods Phys. Res. A, 695, 129–134.
Abstract: The AX-PET collaboration has developed a novel concept for high resolution PET imaging to overcome some of the performance limitations of classical PET cameras, in particular the compromise between spatial resolution and sensitivity introduced by the parallax error. The detector consists of an arrangement of long LYSO scintillating crystals axially oriented around the field of view together with arrays of wave length shifter strips orthogonal to the crystals. This matrix allows a precise 3D measurement of the photon interaction point. This is valid both for photoelectric absorption at 511 key and for Compton scattering down to deposited energies of about 100 keV. Crystals and WLS strips are individually read out using Geiger-mode Avalanche Photo Diodes (G-APDs). The sensitivity of such a detector can be adjusted by changing the number of layers and the resolution is defined by the crystal and strip dimensions. Two AX-PET modules were built and fully characterized in dedicated test set-ups at CERN, with point-like Na-22 sources. Their performance in terms of energy (Renew approximate to 11.8% (FWMH) at 511 key) and spatial resolution was assessed (sigma(axial) approximate to 0.65 mm), both individually and for the two modules in coincidence. Test campaigns at ETH Zurich and at the company AAA allowed the tomographic reconstructions of more complex phantoms validating the 3D reconstruction algorithms. The concept of the AX-PET modules will be presented together with some characterization results. We describe a count rate model which allows to optimize the planing of the tomographic scans.
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