Borja-Lloret, M., Barrientos, L., Bernabeu, J., Lacasta, C., Muñoz, E., Ros, A., et al. (2023). Influence of the background in Compton camera images for proton therapy treatment monitoring. Phys. Med. Biol., 68(14), 144001–16pp.
Abstract: Objective. Background events are one of the most relevant contributions to image degradation in Compton camera imaging for hadron therapy treatment monitoring. A study of the background and its contribution to image degradation is important to define future strategies to reduce the background in the system. Approach. In this simulation study, the percentage of different kinds of events and their contribution to the reconstructed image in a two-layer Compton camera have been evaluated. To this end, GATE v8.2 simulations of a proton beam impinging on a PMMA phantom have been carried out, for different proton beam energies and at different beam intensities. Main results. For a simulated Compton camera made of Lanthanum (III) Bromide monolithic crystals, coincidences caused by neutrons arriving from the phantom are the most common type of background produced by secondary radiations in the Compton camera, causing between 13% and 33% of the detected coincidences, depending on the beam energy. Results also show that random coincidences are a significant cause of image degradation at high beam intensities, and their influence in the reconstructed images is studied for values of the time coincidence windows from 500 ps to 100 ns. Significance. Results indicate the timing capabilities required to retrieve the fall-off position with good precision. Still, the noise observed in the image when no randoms are considered make us consider further background rejection methods.
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Grkovski, M., Brzezinski, K., Cindro, V., Clinthorne, N. H., Kagan, H., Lacasta, C., et al. (2015). Evaluation of a high resolution silicon PET insert module. Nucl. Instrum. Methods Phys. Res. A, 788, 86–94.
Abstract: Conventional PET systems can be augmented with additional detectors placed in close proximity of the region of interest. We developed a high resolution PET insert module to evaluate the added benefit of such a combination. The insert module consists of two back-to-back 1 mm thick silicon sensors, each segmented into 1040 1 mm(2) pads arranged in a 40 by 26 array. A set of 16 VATAGP7.1 ASICs and a custom assembled data acquisition board were used to read out the signal from the insert module. Data were acquired in slice (20) geometry with a Jaszczak phantom (rod diameters of 12-4.8 mm) Filled with F-18-FDG and the images were reconstructed with ML-EM method. Both data with full and limited angular coverage from the insert module were considered and three types of coincidence events were combined. The ratio of high-resolution data that substantially improves quality of the reconstructed image for the region near the surface of the insert module was estimated to be about 4%. Results from our previous studies suggest that such ratio could be achieved at a moderate technological expense by using an equivalent of two insert modules (an effective sensor thickness of 4 mm).
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Rodriguez-Alvarez, M. J., Sanchez, F., Soriano, A., & Iborra, A. (2010). Sparse Givens resolution of large system of linear equations: Applications to image reconstruction. Math. Comput. Model., 52(7-8), 1258–1264.
Abstract: In medicine, computed tomographic images are reconstructed from a large number of measurements of X-ray transmission through the patient (projection data). The mathematical model used to describe a computed tomography device is a large system of linear equations of the form AX = B. In this paper we propose the QR decomposition as a direct method to solve the linear system. QR decomposition can be a large computational procedure. However, once it has been calculated for a specific system, matrices Q and R are stored and used for any acquired projection on that system. Implementation of the QR decomposition in order to take more advantage of the sparsity of the system matrix is discussed.
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Brzezinski, K., Oliver, J. F., Gillam, J., Rafecas, M., Studen, A., Grkovski, M., et al. (2016). Experimental evaluation of the resolution improvement provided by a silicon PET probe. J. Instrum., 11, P09016–13pp.
Abstract: A high-resolution PET system, which incorporates a silicon detector probe into a conventional PET scanner, has been proposed to obtain increased image quality in a limited region of interest. Detailed simulation studies have previously shown that the additional probe information improves the spatial resolution of the reconstructed image and increases lesion detectability, with no cost to other image quality measures. The current study expands on the previous work by using a laboratory prototype of the silicon PET-probe system to examine the resolution improvement in an experimental setting. Two different versions of the probe prototype were assessed, both consisting of a back-to-back pair of 1-mm thick silicon pad detectors, one arranged in 32 x 16 arrays of 1.4mm x 1.4mm pixels and the other in 40 x 26 arrays of 1.0mm x 1.0mm pixels. Each detector was read out by a set of VATAGP7 ASICs and a custom-designed data acquisition board which allowed trigger and data interfacing with the PET scanner, itself consisting of BGO block detectors segmented into 8 x 6 arrays of 6mm x 12mm x 30mm crystals. Limited-angle probe data was acquired from a group of Na-22 point-like sources in order to observe the maximum resolution achievable using the probe system. Data from a Derenzo-like resolution phantom was acquired, then scaled to obtain similar statistical quality as that of previous simulation studies. In this case, images were reconstructed using measurements of the PET ring alone and with the inclusion of the probe data. Images of the Na-22 source demonstrated a resolution of 1.5mm FWHM in the probe data, the PET ring resolution being approximately 6 mm. Profiles taken through the image of the Derenzo-like phantom showed a clear increase in spatial resolution. Improvements in peak-to-valley ratios of 50% and 38%, in the 4.8mm and 4.0mm phantom features respectively, were observed, while previously unresolvable 3.2mm features were brought to light by the addition of the probe. These results support the possibility of improving the image resolution of a clinical PET scanner using the silicon PET-probe.
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NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
Abstract: The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.
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