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Feng Y, Worstell W, Kupinski M, Furenlid LR, Sabet H. Resolution recovery on list mode MLEM reconstruction for dynamic cardiac SPECT system. Biomed Phys Eng Express 2023; 10:10.1088/2057-1976/ad0f40. [PMID: 37995364 PMCID: PMC11162156 DOI: 10.1088/2057-1976/ad0f40] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 11/23/2023] [Indexed: 11/25/2023]
Abstract
The Dynamic Cardiac SPECT (DC-SPECT) system is being developed at the Massachusetts General Hospital, featuring a static cardio focus asymmetrical geometry enabling simultaneous high-resolution and high-sensitivity imaging. Among 14 design iterations of the DC-SPECT with varying number of detector heads, system sensitivity and resolution, the current version under development features 10 mm FWHM geometrical resolution (without resolution recovery) and 0.07% sensitivity at the center of the FOV, this is 1.5× resolution gain and 7× sensitivity gain compared to a conventional dual head gamma camera (0.01% sensitivity and 15-mm resolution). This work presents improvement in imaging resolution by implementing a spatially variant point spread function (SV-PSF) with list mode MLEM reconstruction. A resolution recovery method by PSF deconvolution is validated on list mode MLEM reconstruction for the DC-SPECT. A spatial invariant PSF is included as an additional test to show the influence of the PSF modelling accuracy on reconstructed image quality. We compare the MLEM reconstruction with and without PSF deconvolution; an analytic model is used for the calculation of system response, and the results are compared to the reconstruction with system modelling using Monte Carlo (MC) based methods. Results show that with PSF modelling applied, the quality of the reconstructed image is improved, and the DC-SPECT system can achieve a 4.5 mm central spatial resolution with average 795 counts/Mbq. Both the SV-PSF and the spatial-invariant PSF improve the image quality, and the reconstruction with SV-PSF generates line profiles closer to the ground truth. The results show substantial improvement over the GE Discovery 570c performance (7 mm spatial resolution with an average 460 counts/MBq, 5.8 mm resolution at the FOV center). The impact of PSF deconvolution is significant, improvement of the reconstructed image quality is evident in comparison to MC simulated system matrix with the same sampling size in the simulation.
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Affiliation(s)
- Yuemeng Feng
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Boston, MA, United States of America
| | | | - Matthew Kupinski
- Department of Radiology, and College of Optical Sciences, University of Arizona, Tucson, AZ, United States of America
| | - Lars R Furenlid
- Department of Radiology, and College of Optical Sciences, University of Arizona, Tucson, AZ, United States of America
| | - Hamid Sabet
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Boston, MA, United States of America
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Llosá G, Rafecas M. Hybrid PET/Compton-camera imaging: an imager for the next generation. EUROPEAN PHYSICAL JOURNAL PLUS 2023; 138:214. [PMID: 36911362 PMCID: PMC9990967 DOI: 10.1140/epjp/s13360-023-03805-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
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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Affiliation(s)
- Gabriela Llosá
- Instituto de Física Corpuscular (IFIC), CSIC-UV, Catedrático Beltrán, 2., 46980 Paterna, Valencia, Spain
| | - Magdalena Rafecas
- Institute of Medical Engineering (IMT), Universität zu Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
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Yao Z, Shi C, Tian F, Xiao Y, Geng C, Tang X. Technical note: Rapid and high-resolution deep learning-based radiopharmaceutical imaging with 3D-CZT Compton camera and sparse projection data. Med Phys 2022; 49:7336-7346. [PMID: 35946492 DOI: 10.1002/mp.15898] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 07/05/2022] [Accepted: 07/16/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The Compton camera (CC) has great potential in nuclear medicine imaging due to the high detection efficiency and the ability to simultaneously detect multi-energy radioactive sources. However, the finite resolution of the detectors will degrade the images that the real-world CC can obtain. Besides, the CC sometimes can be limited by the detection efficiency, leading to difficulty in using sparse projection data to realize high-resolution reconstruction with short-time measurement, which limits its clinical application for real-time or rapid radiopharmaceutical imaging. PURPOSE To overcome the difficulty and promote the usage of the CC in radiopharmaceutical imaging, we present a deep learning (DL)-based CC reconstruction method to realize rapid and high-resolution imaging with short-time measurement. METHODS We developed a DL-based algorithm MCBP-CCnet via Monte Carlo sampling-based back projection and a dedicated convolutional neural network, called CC-Net, to realize the rapid and high-resolution reconstruction with sparse projection data. A CC prototype based on a single three-dimensional position-sensitive CdZnTe (3D-CZT) detector was used to demonstrate the feasibility of our proposed method. The simulations and experiments of radiopharmaceutical imaging used the 3D-CZT CC and [18 F]NaF. A 3D-printing mouse phantom was also further used to evaluate the performance of the proposed method in animal molecular imaging. RESULTS The simulation and experimental results showed that the proposed method could realize the images reconstruction within 5 s for list-mode projection data and realized a rapid reconstruction within 35 s for experimental radiopharmaceutical imaging based on the 3D-printing mouse phantom, as well as realized the high-resolution imaging with an accuracy of within 0.78 mm in terms of the sparse projection data that only contained hundreds of events. Besides, the deviations between the reconstructed radiative activities and the exact values were less than 1.51%. CONCLUSION The results demonstrated that the proposed method could realize the rapid and high-resolution CC reconstruction with sparse projection data obtained by the 3D-CZT CC and realize the high-resolution radiopharmaceutical imaging. The study in this paper also demonstrated the potential and feasibility of future applications of a 3D-CZT CC for real-time high-resolution radiopharmaceutical imaging with short-time measurement.
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Affiliation(s)
- Zhiyang Yao
- Department of Engineering Physics, Tsinghua University, Beijing, China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Changrong Shi
- Department of Engineering Physics, Tsinghua University, Beijing, China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Feng Tian
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Yongshun Xiao
- Department of Engineering Physics, Tsinghua University, Beijing, China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Changran Geng
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Xiaobin Tang
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
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Rapid compton camera imaging for source terms investigation in the nuclear decommissioning with a subset-driven origin ensemble algorithm. Radiat Phys Chem Oxf Engl 1993 2022. [DOI: 10.1016/j.radphyschem.2022.110133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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5
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Huang HM. Monte Carlo evaluation of a LYSO-based Compton camera using two origin ensemble algorithms with resolution recovery. Med Phys 2021; 48:5300-5310. [PMID: 34260083 DOI: 10.1002/mp.15092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 06/23/2021] [Accepted: 07/04/2021] [Indexed: 11/05/2022] Open
Abstract
PURPOSE Due to the lack of depth-of-interaction information, a Compton camera made of lutetium-yttrium orthosilicate (LYSO) crystals suffers from poor spatial resolution, which may lead to an unreliable range verification in proton therapy. The aim of this study is to evaluate the performance of a LYSO-based Compton camera using the origin ensemble algorithm with resolution recovery (OE-RR). We also proposed a regularized version of OE-RR called ROE-RR. METHODS We simulated a two-layer LYSO-based Compton camera which was used to detect prompt gammas (PGs) produced by a proton beam irradiated on a water phantom. PG images reconstructed by the OE-RR algorithm were evaluated and compared with those reconstructed by the proposed ROE-RR algorithm. RESULTS Our simulated results show that both the OE-RR and ROE-RR algorithms could provide an accurate estimate of the Bragg peak position, with a mean positioning error of 2.5 mm. Compared to the OE-RR algorithm, the proposed ROE-RR algorithm is less sensitive with respect to initial conditions and requires less iterations for converging to equilibrium. More importantly, the proposed ROE-RR algorithm could provide better image quality than the OE-RR algorithm, especially in low-count data. CONCLUSIONS For LYSO-based Compton cameras, using a resolution-recovery image reconstruction algorithm is essential for reliable range verification.
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Affiliation(s)
- Hsuan-Ming Huang
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei City, Taiwan
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Feng Y, Etxebeste A, Sarrut D, Letang JM, Maxim V. 3-D Reconstruction Benchmark of a Compton Camera Against a Parallel-Hole Gamma Camera on Ideal Data. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2020. [DOI: 10.1109/trpms.2019.2955745] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Kohlhase N, Wegener T, Schaar M, Bolke A, Etxebeste A, Sarrut D, Rafecas M. Capability of MLEM and OE to Detect Range Shifts With a Compton Camera in Particle Therapy. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2020. [DOI: 10.1109/trpms.2019.2937675] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Zheng A, Yao Z, Xiao Y. GPU Accelerated Stochastic Origin Ensemble Method With List-Mode Data for Compton Camera Imaging in Proton Therapy. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2020. [DOI: 10.1109/trpms.2019.2929423] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Yao Z, Xiao Y, Chen Z, Wang B, Hou Q. Compton-based prompt gamma imaging using ordered origin ensemble algorithm with resolution recovery in proton therapy. Sci Rep 2019; 9:1133. [PMID: 30718671 PMCID: PMC6361882 DOI: 10.1038/s41598-018-37623-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 12/06/2018] [Indexed: 11/12/2022] Open
Abstract
Prompt gamma ray (PG) imaging based on Compton camera (CC) is promising to realize in vivo verification during the proton therapy. However, the finite spatial and energy resolution of current CC, as well as the Doppler broaden effect, degrade the quality and resolution of PG images. In addition, due to the inherent geometrical complexity of Compton camera data, PG imaging can be time-consuming and difficult to reconstruct in real-time, while using standard techniques such as filtered back-projection or maximum likelihood-expectation maximization. In this paper, we propose three modifications of origin ensembles with resolution recovery (OE-RR) algorithm based on Markov chains to accelerate the convergence to equilibrium of OE-RR algorithm and improve the image quality. For evaluation, we performed a Monte Carlo simulation of a three-stage CZT Compton camera with resolution loss to detect the PG produced by a proton beam in a water phantom, and evaluate image quality of the gamma rays emitted during proton irradiation. The results show that our ordered OE-RR algorithm realized a good resolution recovery and accurate estimation of the position, including the peak and the distal falloff of the PG emission with remarkably faster reconstruction, thus demonstrating the feasibility of this new method in non-idealized PG-based proton range verification.
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Affiliation(s)
- Zhiyang Yao
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Yongshun Xiao
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Zhiqiang Chen
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China. .,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China.
| | - Bo Wang
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Qinhan Hou
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
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Accuracy of using high-energy prompt gamma to verify proton beam range with a Compton camera: A Monte Carlo simulation study. Appl Radiat Isot 2018; 142:173-180. [PMID: 30326443 DOI: 10.1016/j.apradiso.2018.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Revised: 08/30/2018] [Accepted: 10/06/2018] [Indexed: 11/23/2022]
Abstract
Prompt gamma (PG) rays emitted during proton therapy has been used for proton range verification. Because high-energy PG emission is well correlated to the Bragg peak (BP), high-energy PG rays are well-suited for proton range verification. However, the low production and detection of high-energy PG rays often lead to inaccurate BP position estimates. The aim of this study is to improve the BP position estimates obtained from high-energy PG rays. We propose a BP position estimation method based on the local maximum closest to the distal fall-off region. We present the results of Monte Carlo simulations in which a water phantom was irradiated with a proton beam. Our results show that the BP position estimated from the 6.13 MeV PG rays can be improved using the proposed position estimation method. Moreover, the 6.92 and 7.12 MeV PG rays can be used for predicting the BP position. However, the accuracy of the BP position estimation decreases with decreasing tissue oxygen levels. We also found that the subtraction of the PG images of 6.13 MeV from those of 6.92 and 7.12 MeV can be used to predict the BP position with a mean accuracy of < 2 mm. The accurate estimation of the BP position can be achieved using different high-energy PG rays, but factors including position estimation, irradiated tissue and event selection should be carefully taken into account.
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