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Carrasco-Ribelles, L. A., Pardo-Mas, J. R., Tortajada, S., Saez, C., Valdivieso, B., & Garcia-Gomez, J. M. (2021). Predicting morbidity by local similarities in multi-scale patient trajectories. J. Biomed. Inform., 120, 103837–9pp.
Abstract: Patient Trajectories (PTs) are a method of representing the temporal evolution of patients. They can include information from different sources and be used in socio-medical or clinical domains. PTs have generally been used to generate and study the most common trajectories in, for instance, the development of a disease. On the other hand, healthcare predictive models generally rely on static snapshots of patient information. Only a few works about prediction in healthcare have been found that use PTs, and therefore benefit from their temporal dimension. All of them, however, have used PTs created from single-source information. Therefore, the use of longitudinal multi-scale data to build PTs and use them to obtain predictions about health conditions is yet to be explored. Our hypothesis is that local similarities on small chunks of PTs can identify similar patients concerning their future morbidities. The objectives of this work are (1) to develop a methodology to identify local similarities between PTs before the occurrence of morbidities to predict these on new query individuals; and (2) to validate this methodology on risk prediction of cardiovascular diseases (CVD) occurrence in patients with diabetes. We have proposed a novel formal definition of PTs based on sequences of longitudinal multi-scale data. Moreover, a dynamic programming methodology to identify local alignments on PTs for predicting future morbidities is proposed. Both the proposed methodology for PT definition and the alignment algorithm are generic to be applied on any clinical domain. We validated this solution for predicting CVD in patients with diabetes and we achieved a precision of 0.33, a recall of 0.72 and a specificity of 0.38. Therefore, the proposed solution in the diabetes use case can result of utmost utility to secondary screening.
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Barrientos, L., Borja-Lloret, M., Casaña, J. V., Dendooven, P., Garcia Lopez, J. G., Hueso-Gonzalez, F., et al. (2024). Gamma-ray sources imaging and test-beam results with MACACO III Compton camera. Phys. Medica, 117, 103199–10pp.
Abstract: Hadron therapy is a radiotherapy modality which offers a precise energy deposition to the tumors and a dose reduction to healthy tissue as compared to conventional methods. However, methods for real-time monitoring are required to ensure that the radiation dose is deposited on the target. The IRIS group of IFIC-Valencia developed a Compton camera prototype for this purpose, intending to image the Prompt Gammas emitted by the tissue during irradiation. The system detectors are composed of Lanthanum (III) bromide scintillator crystals coupled to silicon photomultipliers. After an initial characterization in the laboratory, in order to assess the system capabilities for future experiments in proton therapy centers, different tests were carried out in two facilities: PARTREC (Groningen, The Netherlands) and the CNA cyclotron (Sevilla, Spain). Characterization studies performed at PARTREC indicated that the detectors linearity was improved with respect to the previous version and an energy resolution of 5.2 % FWHM at 511 keV was achieved. Moreover, the imaging capabilities of the system were evaluated with a line source of 68Ge and a point-like source of 241Am-9Be. Images at 4.439 MeV were obtained from irradiation of a graphite target with an 18 MeV proton beam at CNA, to perform a study of the system potential to detect shifts at different intensities. In this sense, the system was able to distinguish 1 mm variations in the target position at different beam current intensities for measurement times of 1800 and 600 s.
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Oliver, S., Rodriguez Bosca, S., & Gimenez-Alventosa, V. (2024). Enabling particle transport on CAD-based geometries for radiation simulations with penRed. Comput. Phys. Commun., 298, 109091–11pp.
Abstract: Geometry construction is a fundamental aspect of any radiation transport simulation, regardless of the Monte Carlo code being used. Typically, this process is tedious, time-consuming, and error-prone. The conventional approach involves defining geometries using mathematical objects or surfaces. However, this method comes with several limitations, especially when dealing with complex models, particularly those with organic shapes. Furthermore, since each code employs its own format and methodology for defining geometries, sharing and reproducing simulations among researchers becomes a challenging task. Consequently, many codes have implemented support for simulating over geometries constructed via Computer-Aided Design (CAD) tools. Unfortunately, this feature is lacking in penRed and other PENELOPE physics-based codes. Therefore, the objective of this work is to implement such support within the penRed framework. New version program summary Program Title: Parallel Engine for Radiation Energy Deposition (penRed) CPC Library link to program files: https://doi.org/10.17632/rkw6tvtngy.2 Developer's repository link: https://github.com/PenRed/PenRed Code Ocean capsule: https://codeocean.com/capsule/1041417/tree Licensing provisions: GNU Affero General Public License v3 Programming language: C++ standard 2011. Journal reference of previous version: V. Gimenez-Alventosa, V. Gimenez Gomez, S. Oliver, PenRed: An extensible and parallel Monte-Carlo framework for radiation transport based on PENELOPE, Computer Physics Communications 267 (2021) 108065. doi:https://doi.org/10.1016/j.cpc.2021.108065. Does the new version supersede the previous version?: Yes Reasons for the new version: Implements the capability to simulate on CAD constructed geometries, among many other features and fixes. Summary of revisions: All changes applied through the code versions are summarized in the file CHANGELOG.md in the repository package. Nature of problem: While Monte Carlo codes have proven valuable in simulating complex radiation scenarios, they rely heavily on accurate geometrical representations. In the same way as many other Monte Carlo codes, penRed employs simple geometric quadric surfaces like planes, spheres and cylinders to define geometries. However, since these geometric models offer a certain level of flexibility, these representations have limitations when it comes to simulating highly intricate and irregular shapes. Anatomic structures, for example, require detailed representations of organs, tissues and bones, which are difficult to achieve using basic geometric objects. Similarly, complex devices or intricate mechanical systems may have designs that cannot be accurately represented within the constraints of such geometric models. Moreover, when the complexity of the model increases, geometry construction process becomes more difficult, tedious, time-consuming and error-prone [2]. Also, as each Monte Carlo geometry library uses its own format and construction method, reproducing the same geometry among different codes is a challenging task. Solution method: To face the problems stated above, the objective of this work is to implement the capability to simulate using irregular and adaptable meshed geometries in the penRed framework. This kind of meshes can be constructed using Computer-Aided Design (CAD) tools, the use of which is very widespread and streamline the design process. This feature has been implemented in a new geometry module named “MESH_BODY” specific for this kind of geometries. This one is freely available and usable within the official penRed package1. It can be used since penRed version 1.9.3b and above.
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Gimenez-Alventosa, V., Gimenez, V., & Oliver, S. (2021). PenRed: An extensible and parallel Monte-Carlo framework for radiation transport based on PENELOPE. Comput. Phys. Commun., 267, 108065–12pp.
Abstract: Monte Carlo methods provide detailed and accurate results for radiation transport simulations. Unfortunately, the high computational cost of these methods limits its usage in real-time applications. Moreover, existing computer codes do not provide a methodology for adapting these kinds of simulations to specific problems without advanced knowledge of the corresponding code system, and this restricts their applicability. To help solve these current limitations, we present PenRed, a general-purpose, standalone, extensible and modular framework code based on PENELOPE for parallel Monte Carlo simulations of electron-photon transport through matter. It has been implemented in C++ programming language and takes advantage of modern object-oriented technologies. In addition, PenRed offers the capability to read and process DICOM images as well as to construct and simulate image-based voxelized geometries, so as to facilitate its usage in medical applications. Our framework has been successfully verified against the original PENELOPE Fortran code. Furthermore, the implemented parallelism has been tested showing a significant improvement in the simulation time without any loss in precision of results. Program summary Program title: PenRed: Parallel Engine for Radiation Energy Deposition. CPC Library link to program files: https://doi .org /10 .17632/rkw6tvtngy.1 Licensing provision: GNU Affero General Public License (AGPL). Programming language: C++ standard 2011. Nature of problem: Monte Carlo simulations usually require a huge amount of computation time to achieve low statistical uncertainties. In addition, many applications necessitate particular characteristics or the extraction of specific quantities from the simulation. However, most available Monte Carlo codes do not provide an efficient parallel and truly modular structure which allows users to easily customise their code to suit their needs without an in-depth knowledge of the code system. Solution method: PenRed is a fully parallel, modular and customizable framework for Monte Carlo simulations of the passage of radiation through matter. It is based on the PENELOPE [1] code system, from which inherits its unique physics models and tracking algorithms for charged particles. PenRed has been coded in C++ following an object-oriented programming paradigm restricted to the C++11 standard. Our engine implements parallelism via a double approach: on the one hand, by using standard C++ threads for shared memory, improving the access and usage of the memory, and, on the other hand, via the MPI standard for distributed memory infrastructures. Notice that both kinds of parallelism can be combined together in the same simulation. Moreover, both threads and MPI processes, can be balanced using the builtin load balance system (RUPER-LB [30]) to maximise the performance on heterogeneous infrastructures. In addition, PenRed provides a modular structure with methods designed to easily extend its functionality. Thus, users can create their own independent modules to adapt our engine to their needs without changing the original modules. Furthermore, user extensions will take advantage of the builtin parallelism without any extra effort or knowledge of parallel programming. Additional comments including restrictions and unusual features: PenRed has been compiled in linux systems withg++ of GCC versions 4.8.5, 7.3.1, 8.3.1 and 9; clang version 3.4.2 and intel C++ compiler (icc) version 19.0.5.281. Since it is a C++11-standard compliant code, PenRed should be able to compile with any compiler with C++11 support. In addition, if the code is compiled without MPI support, it does not require any non standard library. To enable MPI capabilities, the user needs to install whatever available MPI implementation, such as openMPI [24] or mpich [25], which can be found in the repositories of any linux distribution. Finally, to provide DICOM processing support, PenRed can be optionally compiled using the dicom toolkit (dcmtk) [32] library. Thus, PenRed has only two optional dependencies, an MPI implementation and the dcmtk library.
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Plaza, J., Martinez, T., Becares, V., Cano-Ott, D., Villamarin, D., de Rada, A. P., et al. (2023). Thermal neutron background at Laboratorio Subterraneo de Canfranc (LSC). Astropart Phys., 146, 102793–9pp.
Abstract: The thermal neutron background at Laboratorio Subterraneo de Canfranc (LSC) has been determined using several He-3 proportional counter detectors. Bare and Cd shielded counters were used in a series of long measurements. Pulse shape discrimination techniques were applied to discriminate between neutron and gamma signals as well as other intrinsic contributions. Montecarlo simulations allowed us to estimate the sensitivity of the detectors and calculate values for the background flux of thermal neutrons inside Hall-A of LSC. The obtained value is (3.5 +/- 0.8)x10(-6) n/cm(2)s, and is within an order of magnitude compared to similar facilities.
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