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Bouziri H, Pepin CM, Koua K, Benhouria M, Paulin C, Ouyang J, Normandin M, Pratte JF, El Fakhri G, Lecomte R, Fontaine R. Investigation of a Model-based Time-over-threshold Technique for Phoswich Crystal Discrimination. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2022; 6:393-403. [PMID: 35372739 PMCID: PMC8974315 DOI: 10.1109/trpms.2021.3077412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The best crystal identification (CI) algorithms proposed so far for phoswich detectors are based on adaptive filtering and pulse shape discrimination (PSD). However, these techniques require free running analog to digital converters, which is no longer possible with the ever increasing pixelization of new detectors. We propose to explore the dual-threshold time-over-threshold (ToT) technique, used to measure events energy and time of occurence, as a more robust solution for crystal identification with broad energy windows in phoswich detectors. In this study, phoswich assemblies made of various combinations of LGSO and LYSO scintillators with decay times in the range 30 to 65 ns were investigated for the LabPET II detection front-end. The electronic readout is based on a 4 × 8 APD array where pixels are individually coupled to charge sensitive preamplifiers followed by first order CR-RC shapers with 75 ns peaking time. Crystal identification data were sorted out based on the measurements of likeliness between acquired signals and a time domain model of the analog front-end. Results demonstrate that crystal identification can be successfully performed using a dual-threshold ToT scheme with a discrimination accuracy of 99.1% for LGSO (30 ns)/LGSO (45 ns), 98.1% for LGSO (65 ns)/LYSO (40 ns) and 92.1% for LYSO (32 ns)/LYSO (47 ns), for an energy window of [350-650] keV. Moreover, the method shows a discrimination accuracy >97% for the two first pairs and ~90% for the last one when using a wide energy window of [250-650] keV.
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Affiliation(s)
- Haithem Bouziri
- Interdisciplinary Institute for Technological Innovation (3IT) and with the Department of Electrical and Computer Engineering, Université de Sherbrooke, Sherbrooke, QC, Canada J1K 0A5
| | - Catherine M Pepin
- Sherbrooke Molecular Imaging Center, Department of Nuclear Medicine and Radiobiology, Université de Sherbrooke, Sherbrooke, QC, Canada J1H 5N4
| | - Konin Koua
- Interdisciplinary Institute for Technological Innovation (3IT) and with the Department of Electrical and Computer Engineering, Université de Sherbrooke, Sherbrooke, QC, Canada J1K 0A5
| | - Maher Benhouria
- Interdisciplinary Institute for Technological Innovation (3IT) and with the Department of Electrical and Computer Engineering, Université de Sherbrooke, Sherbrooke, QC, Canada J1K 0A5
| | - Caroline Paulin
- Interdisciplinary Institute for Technological Innovation (3IT) and with the Department of Electrical and Computer Engineering, Université de Sherbrooke, Sherbrooke, QC, Canada J1K 0A5
| | - Jinsong Ouyang
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114 USA
| | - Marc Normandin
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114 USA
| | - Jean-François Pratte
- Interdisciplinary Institute for Technological Innovation (3IT) and with the Department of Electrical and Computer Engineering, Université de Sherbrooke, Sherbrooke, QC, Canada J1K 0A5
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114 USA
| | - Roger Lecomte
- Sherbrooke Molecular Imaging Center, Department of Nuclear Medicine and Radiobiology, Université de Sherbrooke, Sherbrooke, QC, Canada J1H 5N4
| | - Réjean Fontaine
- Interdisciplinary Institute for Technological Innovation (3IT) and with the Department of Electrical and Computer Engineering, Université de Sherbrooke, Sherbrooke, QC, Canada J1K 0A5
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Zhang X, Yu H, Xie Q, Xie S, Ye B, Guo M, Zhao Z, Huang Q, Xu J, Peng Q. Design study of a PET detector with 0.5 mm crystal pitch for high-resolution preclinical imaging. Phys Med Biol 2021; 66. [PMID: 34130263 DOI: 10.1088/1361-6560/ac0b82] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 06/15/2021] [Indexed: 11/12/2022]
Abstract
Preclinical positron emission tomography (PET) is a sensitive and quantitative molecule imaging modality widely used in characterizing the biological processes and diseases in small animals. The purpose of this study is to investigate the methods to optimize a PET detector for high-resolution preclinical imaging. The PET detector proposed in this study consists of a 28 × 28 array of LYSO crystals 0.5 × 0.5 × 6.25 mm3in size, a wedged lightguide, and a 6 × 6 array of SiPMs 3 × 3 mm2in size. The simulation results showed that the most uniform flood map was achieved when the thickness of the lightguide was 2.35 mm. The quality of the flood map was significantly improved by suppressing the electronics noises using the simple threshold method with a best threshold. The peak-to-valley ratio of flood map improved 25.4% when the algorithm of ICS rejection was applied. An energy resolution (12.96% ± 1.03%) was measured on the prototype scanner constructed with 12 proposed detectors. Lastly, a prototype preclinic PET imager was constructed with 12 optimized detectors. The point source experiment was performed and an excellent spatial resolution (axial: 0.56 mm, tangential: 0.46 mm, radial: 0.42 mm) was achieved with the proposed high-performance PET detectors.
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Affiliation(s)
- Xi Zhang
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, People's Republic of China
| | - Hongsen Yu
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, People's Republic of China
| | - Qiangqiang Xie
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, People's Republic of China
| | - Siwei Xie
- Institute of Biomedical Engineering Shenzhen Bay Laboratory, Shenzhen, 518132, People's Republic of China
| | - Baihezi Ye
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, People's Republic of China
| | - Minghao Guo
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 200240, Shanghai, People's Republic of China
| | - Zhixiang Zhao
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 200240, Shanghai, People's Republic of China
| | - Qiu Huang
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 200240, Shanghai, People's Republic of China
| | - Jianfeng Xu
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, People's Republic of China
| | - Qiyu Peng
- Institute of Biomedical Engineering Shenzhen Bay Laboratory, Shenzhen, 518132, People's Republic of China
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