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Roser, J., Muñoz, E., Barrientos, L., Barrio, J., Bernabeu, J., Borja-Lloret, M., et al. (2020). Image reconstruction for a multi-layer Compton telescope: an analytical model for three interaction events. Phys. Med. Biol., 65(14), 145005–17pp.
Abstract: Compton Cameras are electronically collimated photon imagers suitable for sub-MeV to few MeV gamma-ray detection. Such features are desirable to enablein vivorange verification in hadron therapy, through the detection of secondary Prompt Gammas. A major concern with this technique is the poor image quality obtained when the incoming gamma-ray energy is unknown. Compton Cameras with more than two detector planes (multi-layer Compton Cameras) have been proposed as a solution, given that these devices incorporate more signal sequences of interactions to the conventional two interaction events. In particular, three interaction events convey more spectral information as they allow inferring directly the incident gamma-ray energy. A three-layer Compton Telescope based on continuous Lanthanum (III) Bromide crystals coupled to Silicon Photomultipliers is being developed at the IRIS group of IFIC-Valencia. In a previous work we proposed a spectral reconstruction algorithm for two interaction events based on an analytical model for the formation of the signal. To fully exploit the capabilities of our prototype, we present here an extension of the model for three interaction events. Analytical expressions of the sensitivity and the System Matrix are derived and validated against Monte Carlo simulations. Implemented in a List Mode Maximum Likelihood Expectation Maximization algorithm, the proposed model allows us to obtain four-dimensional (energy and position) images by using exclusively three interaction events. We are able to recover the correct spectrum and spatial distribution of gamma-ray sources when ideal data are employed. However, the uncertainties associated to experimental measurements result in a degradation when real data from complex structures are employed. Incorrect estimation of the incident gamma-ray interaction positions, and missing deposited energy associated with escaping secondaries, have been identified as the causes of such degradation by means of a detailed Monte Carlo study. As expected, our current experimental resolution and efficiency to three interaction events prevents us from correctly recovering complex structures of radioactive sources. However, given the better spectral information conveyed by three interaction events, we expect an improvement of the image quality of conventional Compton imaging when including such events. In this regard, future development includes the incorporation of the model assessed in this work to the two interaction events model in order to allow using simultaneously two and three interaction events in the image reconstruction.
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Etxebeste, A., Dauvergne, D., Fontana, M., Letang, J. M., Llosa, G., Muñoz, E., et al. (2020). CCMod: a GATE module for Compton camera imaging simulation. Phys. Med. Biol., 65(5), 055004–17pp.
Abstract: Compton cameras are gamma-ray imaging systems which have been proposed for a wide variety of applications such as medical imaging, nuclear decommissioning or homeland security. In the design and optimization of such a system Monte Carlo simulations play an essential role. In this work, we propose a generic module to perform Monte Carlo simulations and analyses of Compton Camera imaging which is included in the open-source GATE/Geant4 platform. Several digitization stages have been implemented within the module to mimic the performance of the most commonly employed detectors (e.g. monolithic blocks, pixelated scintillator crystals, strip detectors...). Time coincidence sorter and sequence coincidence reconstruction are also available in order to aim at providing modules to facilitate the comparison and reproduction of the data taken with different prototypes. All processing steps may be performed during the simulation (on-the-fly mode) or as a post-process of the output files (offline mode). The predictions of the module have been compared with experimental data in terms of energy spectra, angular resolution, efficiency and back-projection image reconstruction. Consistent results within a 3-sigma interval were obtained for the energy spectra except for low energies where small differences arise. The angular resolution measure for incident photons of 1275 keV was also in good agreement between both data sets with a value close to 13 degrees. Moreover, with the aim of demonstrating the versatility of such a tool the performance of two different Compton camera designs was evaluated and compared.
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Llosa, G., & Rafecas, M. (2023). Hybrid PET/Compton-camera imaging: an imager for the next generation. Eur. Phys. J. Plus, 138(3), 214–19pp.
Abstract: Compton cameras can offer advantages over gamma cameras for some applications, since they are well suited for multitracer imaging and for imaging high-energy radiotracers, such as those employed in radionuclide therapy. While in conventional clinical settings state-of-the-art Compton cameras cannot compete with well-established methods such as PET and SPECT, there are specific scenarios in which they can constitute an advantageous alternative. The combination of PET and Compton imaging can benefit from the improved resolution and sensitivity of current PET technology and, at the same time, overcome PET limitations in the use of multiple radiotracers. Such a system can provide simultaneous assessment of different radiotracers under identical conditions and reduce errors associated with physical factors that can change between acquisitions. Advances are being made both in instrumentation developments combining PET and Compton cameras for multimodal or three-gamma imaging systems, and in image reconstruction, addressing the challenges imposed by the combination of the two modalities or the new techniques. This review article summarizes the advances made in Compton cameras for medical imaging and their combination with PET.
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Llosa, G. (2019). SiPM-based Compton cameras. Nucl. Instrum. Methods Phys. Res. A, 926, 148–152.
Abstract: Compton cameras have been developed for almost fifty years in various fields (astronomy, medical imaging, safety and industrial inspections, etc.), employing different types of detectors. Their potential use has gained renewed interest with the emergence of high light yield scintillator crystals and silicon photomultipliers (SiPMs). This combination provides good performance and operation simplicity at an affordable cost, raising again the interest in this type of systems. SiPM-based Compton cameras are being assessed for diverse applications with promising results.
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Lerendegui-Marco, J., Balibrea-Correa, J., Babiano-Suarez, V., Ladarescu, I., & Domingo-Pardo, C. (2022). Towards machine learning aided real-time range imaging in proton therapy. Sci Rep, 12(1), 2735–17pp.
Abstract: Compton imaging represents a promising technique for range verification in proton therapy treatments. In this work, we report on the advantageous aspects of the i-TED detector for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that have been specifically designed for neutron-capture nuclear physics experiments, which are characterized by gamma-ray energies spanning up to 5-6 MeV, rather low gamma-ray emission yields and very intense neutron induced gamma-ray backgrounds. Our developments to cope with these three aspects are concomitant with those required in the field of hadron therapy, especially in terms of high efficiency for real-time monitoring, low sensitivity to neutron backgrounds and reliable performance at the high gamma-ray energies. We find that signal-to-background ratios can be appreciably improved with i-TED thanks to its light-weight design and the low neutron-capture cross sections of its LaCl3 crystals, when compared to other similar systems based on LYSO, CdZnTe or LaBr3. Its high time-resolution (CRT similar to 500 ps) represents an additional advantage for background suppression when operated in pulsed HT mode. Each i-TED Compton module features two detection planes of very large LaCl3 monolithic crystals, thereby achieving a high efficiency in coincidence of 0.2% for a point-like 1 MeV gamma-ray source at 5 cm distance. This leads to sufficient statistics for reliable image reconstruction with an array of four i-TED detectors assuming clinical intensities of 10(8) protons per treatment point. The use of a two-plane design instead of three-planes has been preferred owing to the higher attainable efficiency for double time-coincidences than for threefold events. The loss of full-energy events for high energy gamma-rays is compensated by means of machine-learning based algorithms, which allow one to enhance the signal-to-total ratio up to a factor of 2.
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NEXT Collaboration(Monrabal, F. et al), Laing, A., Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., et al. (2018). The NEXT White (NEW) detector. J. Instrum., 13, P12010–38pp.
Abstract: Conceived to host 5 kg of xenon at a pressure of 15 bar in the fiducial volume, the NEXT-White apparatus is currently the largest high pressure xenon gas TPC using electroluminescent amplification in the world. It is also a 1:2 scale model of the NEXT-100 detector for Xe-136 beta beta 0 nu decay searches, scheduled to start operations in 2019. Both detectors measure the energy of the event using a plane of photomultipliers located behind a transparent cathode. They can also reconstruct the trajectories of charged tracks in the dense gas of the TPC with the help of a plane of silicon photomultipliers located behind the anode. A sophisticated gas system, common to both detectors, allows the high gas purity needed to guarantee a long electron lifetime. NEXT-White has been operating since October 2016 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. This paper describes the detector and associated infrastructures, as well as the main aspects of its initial operation.
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Barenboim, G., Denton, P. B., & Oldengott, I. M. (2019). Constraints on inflation with an extended neutrino sector. Phys. Rev. D, 99(8), 083515–9pp.
Abstract: Constraints on inflationary models typically assume only the standard models of cosmology and particle physics. By extending the neutrino sector to include a new interaction with a light scalar mediator (m(phi) similar to MeV), it is possible to relax these constraints, in particular via opening up regions of the parameter space of the spectral index n(s). These new interactions can be probed at IceCube via interactions of astrophysical neutrinos with the cosmic neutrino background for nearly all of the relevant parameter space.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Barranco Navarro, L., Cabrera Urban, S., et al. (2019). Constraints on mediator-based dark matter and scalar dark energy models using root s= 13 TeV pp collision data collected by the ATLAS detector. J. High Energy Phys., 05(5), 142–87pp.
Abstract: Constraints on selected mediator-based dark matter models and a scalar dark energy model using up to 37 fb(-1) = 13 TeV pp collision data collected by the ATLAS detector at the LHC during 2015-2016 are summarised in this paper. The results of experimental searches in a variety of final states are interpreted in terms of a set of spin-1 and spin-0 single-mediator dark matter simplified models and a second set of models involving an extended Higgs sector plus an additional vector or pseudo-scalar mediator. The searches considered in this paper constrain spin-1 leptophobic and leptophilic mediators, spin-0 colour-neutral and colour-charged mediators and vector or pseudo-scalar mediators embedded in extended Higgs sector models. In this case, also = 8 TeV pp collision data are used for the interpretation of the results. The results are also interpreted for the first time in terms of light scalar particles that could contribute to the accelerating expansion of the universe (dark energy).
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cantero, J., et al. (2023). Constraints on the Higgs boson self-coupling from single- and double-Higgs production with the ATLAS detector using pp collisions at & RADIC;s=13 TeV. Phys. Lett. B, 843, 137745–20pp.
Abstract: Constraints on the Higgs boson self-coupling are set by combining double-Higgs boson analyses in the bb over bar bb over bar , bb over bar & tau;+& tau;- and bb over bar & gamma; & gamma; decay channels with single-Higgs boson analyses targeting the & gamma;& gamma;, Z Z*, W W *, & tau;+& tau;- and bb over bar decay channels. The data used in these analyses were recorded by the ATLAS detector at the LHC in proton-proton collisions at & RADIC;s = 13 TeV and correspond to an integrated luminosity of 126-139 fb-1. The combination of the double-Higgs analyses sets an upper limit of & mu;HH < 2.4 at 95% confidence level on the double-Higgs production cross-section normalised to its Standard Model prediction. Combining the single-Higgs and double-Higgs analyses, with the assumption that new physics affects only the Higgs boson self-coupling (& lambda;HHH), values outside the interval -0.4 < & kappa;& lambda; = (& lambda;HHH/& lambda;SM H H H ) < 6.3 are excluded at 95% confidence level. The combined single-Higgs and double-Higgs analyses provide results with fewer assumptions, by adding in the fit more coupling modifiers introduced to account for the Higgs boson interactions with the other Standard Model particles. In this relaxed scenario, the constraint becomes -1.4 < & kappa;& lambda; < 6.1 at 95% CL.
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Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
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