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dc.contributor.author | Konstantinou, Georgios | es_ES |
dc.contributor.author | Zhang, Lei | es_ES |
dc.contributor.author | Bonifacio, Daniel | es_ES |
dc.contributor.author | Latella, Riccardo | es_ES |
dc.contributor.author | Benlloch Baviera, Jose María | es_ES |
dc.contributor.author | González Martínez, Antonio Javier | es_ES |
dc.contributor.author | Lecoq, Paul | es_ES |
dc.date.accessioned | 2024-09-05T18:22:35Z | |
dc.date.available | 2024-09-05T18:22:35Z | |
dc.date.issued | 2024-05 | es_ES |
dc.identifier.issn | 2469-7311 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/207438 | |
dc.description.abstract | [EN] In this study, we propose and examine a unique semimonolithic metascintillator (SMMS) detector design, where slow scintillators (BGO or LYSO) are split into thin slabs and read by an array of SiPM, offering depth-of-interaction (DOI) information. These are alternated with thin segmented fast scintillators (plastic EJ232 or EJ232Q), also read by single SiPMs, which provides pixel-level coincidence time resolution (CTR). The structure combines layers of slow scintillators of size 0.3 x 25.5 x (15 or 24) mm(3) with fast scintillators of size 0.1 x 3.1 x (15 or 24) mm(3). We use a Monte Carlo Gate simulation to gauge this novel semimonolithic detector's performance. We found that the time resolution of SMMS is comparable to pixelated metascintillator designs with the same materials. For example, a 15-mm deep LYSO-based SMMS yielded a CTR of 121 ps before applying timewalk correction (after correction, 107-ps CTR). The equivalent BGO-based SMMS presented a CTR of 241 ps, which is a 15% divergence from metascintillator pixel experimental findings from previous works. We also applied neural networks to the photon distributions and timestamps recorded at the SiPM array, following guidelines on semimonolithic detectors. This led to determining the DOI with less than 3-mm precision and a confidence level of 0.85 in the best case, plus more than 2 standard deviations accuracy in reconstructing energy sharing and interaction energy. In summary, neural network prediction capabilities outperform standard energy calculation methods or any analytical approach on energy sharing, thanks to the improved understanding of photon distribution. | es_ES |
dc.description.sponsorship | This work was supported in part by the European Research Council in the framework of the ERC Advanced Grant TICAL under Grant 338953, and in part by the European Research Council (ERC) through the European Union s Horizon 2020 Research and Innovation Program (4DPET) under Grant 695536. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation.ispartof | IEEE Transactions on Radiation and Plasma Medical Sciences | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Depth of interaction | es_ES |
dc.subject | Metascintillators | es_ES |
dc.subject | Positron emission tomography (PET) | es_ES |
dc.subject | Scintillators | es_ES |
dc.subject | Semi-monolithic | es_ES |
dc.subject | Time of flight | es_ES |
dc.title | Semi-Monolithic Meta-Scintillator Simulation Proof-of-Concept, Combining Accurate DOI and TOF | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1109/TRPMS.2024.3368802 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/338953/EU/TICAL: 4D total absorptionTime Imaging CALorimeter/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/695536/EU/Innovative PET scanner for dynamic imaging/ | es_ES |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular | es_ES |
dc.description.bibliographicCitation | Konstantinou, G.; Zhang, L.; Bonifacio, D.; Latella, R.; Benlloch Baviera, JM.; González Martínez, AJ.; Lecoq, P. (2024). Semi-Monolithic Meta-Scintillator Simulation Proof-of-Concept, Combining Accurate DOI and TOF. IEEE Transactions on Radiation and Plasma Medical Sciences. 8(5):482-492. https://doi.org/10.1109/TRPMS.2024.3368802 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/TRPMS.2024.3368802 | es_ES |
dc.description.upvformatpinicio | 482 | es_ES |
dc.description.upvformatpfin | 492 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 8 | es_ES |
dc.description.issue | 5 | es_ES |
dc.relation.pasarela | S\522839 | es_ES |
dc.contributor.funder | European Commission | es_ES |