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Wang YH, Jin DSC, Wu TY, Shen C, Chen JC, Tseng SH, Liu TY. Cone-beam x-ray luminescence computed tomography (CB-XLCT) prototype development and performance evaluation. Phys Med Biol 2024; 69:035016. [PMID: 38170992 DOI: 10.1088/1361-6560/ad1a25] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 01/03/2024] [Indexed: 01/05/2024]
Abstract
This study developed a prototype for a rotational cone-beam x-ray luminescence computed tomography (CB-XLCT) system, considering its potential application in pre-clinical theranostic imaging. A geometric calibration method applicable to both imaging chains (XL and CT) was also developed to enhance image quality. The results of systematic performance evaluations were presented to assess the feasibility of commercializing XLCT technology. Monte Carlo GATE simulation was performed to determine the optimal imaging conditions for nanophosphor particles (NPs) irradiated by 70 kV x-rays. We acquired a low-dose transmission x-ray tube and designed a prone positioning platform and a rotating gantry, using mice as targets from commercial small animalμ-CT systems. We then employed the image cross-correlation (ICC) automatic geometric calibration method to calibrate XL and CT images. The performance of the system was evaluated through a series of phantom experiments with a linearity of 0.99, and the contrast-to-noise ratio (CNR) between hydroxyl-apatite (HA) and based epoxy resin is 19.5. The XL images of the CB-XLCT prototype achieved a Dice similarity coefficient (DICE) of 0.149 for a distance of 1 mm between the two light sources. Finally, the final XLCT imaging results were demonstrated using the Letter phantoms with NPs. In summary, the CB-XLCT prototype developed in this study showed the potential to achieve high-quality imaging with acceptable radiation doses for small animals. The performance of CT images was comparable to current commercial machines, while the XL images exhibited promising results in phantom imaging, but further efforts are needed for biomedical applications.
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Affiliation(s)
- Yu-Hong Wang
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, 112304 Taipei, Taiwan, ROC
- Institute of Biophotonics, National Yang Ming Chiao Tung University, 112304 Taipei, Taiwan, ROC
| | - David Shih-Chun Jin
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, 112304 Taipei, Taiwan, ROC
- Department of Electro-Optical Engineering, National Taipei University of Technology, 106344 Taipei, Taiwan, ROC
| | - Tian-Yu Wu
- Graduate Institute of Photonics and Optoelectronics, National Taiwan University, 10617 Taipei, Taiwan, ROC
| | - Chieh Shen
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, 112304 Taipei, Taiwan, ROC
| | - Jyh-Cheng Chen
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, 112304 Taipei, Taiwan, ROC
- School of Medical Imaging, Xuzhou Medical University, 221004 Xuzhou, People's Republic of China
- Department of Medical Imaging and Radiological Sciences, China Medical University, Taichung, Taiwan, ROC
| | - Snow H Tseng
- Graduate Institute of Photonics and Optoelectronics, National Taiwan University, 10617 Taipei, Taiwan, ROC
| | - Tse-Ying Liu
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, 112304 Taipei, Taiwan, ROC
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Zhang L, Xu F, Lei T, Zhang X, Lan B, Li T, Yu J, Lu H, Zhang W. Growth Phase Diagram and X-ray Excited Luminescence Properties of NaLuF4:Tb3+ Nanoparticles. ARAB J CHEM 2023. [DOI: 10.1016/j.arabjc.2023.104672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023] Open
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Liu Y, Hu X, Chu M, Guo H, Yu J, He X. A Finite Element Mesh Regrouping Strategy-Based Hybrid Light Transport Model for Enhancing the Efficiency and Accuracy of XLCT. Front Oncol 2022; 11:751139. [PMID: 35111664 PMCID: PMC8801618 DOI: 10.3389/fonc.2021.751139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 12/10/2021] [Indexed: 11/19/2022] Open
Abstract
X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality in optical molecular imaging, which has attracted more attention and has been widely studied. In XLCT, the accuracy and operational efficiency of an optical transmission model play a decisive role in the rapid and accurate reconstruction of light sources. For simulation of optical transmission characteristics in XLCT, considering the limitations of the diffusion equation (DE) and the time and memory costs of simplified spherical harmonic approximation equation (SPN), a hybrid light transport model needs to be built. DE and SPN models are first-order and higher-order approximations of RTE, respectively. Due to the discontinuity of the regions using the DE and SPN models and the inconsistencies of the system matrix dimensions constructed by the two models in the solving process, the system matrix construction of a hybrid light transmission model is a problem to be solved. We provided a new finite element mesh regrouping strategy-based hybrid light transport model for XLCT. Firstly, based on the finite element mesh regrouping strategy, two separate meshes can be obtained. Thus, for DE and SPN models, the system matrixes and source weight matrixes can be calculated separately in two respective mesh systems. Meanwhile, some parallel computation strategy can be combined with finite element mesh regrouping strategy to further save the system matrix calculation time. Then, the two system matrixes with different dimensions were coupled though repeated nodes were processed according to the hybrid boundary conditions, the two meshes were combined into a regrouping mesh, and the hybrid optical transmission model was established. In addition, the proposed method can reduce the computational memory consumption than the previously proposed hybrid light transport model achieving good balance between computational accuracy and efficiency. The forward numerical simulation results showed that the proposed method had better transmission accuracy and achieved a balance between efficiency and accuracy. The reverse simulation results showed that the proposed method had superior location accuracy, morphological recovery capability, and image contrast capability in source reconstruction. In-vivo experiments verified the practicability and effectiveness of the proposed method.
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Affiliation(s)
- Yanqiu Liu
- Key Laboratory for Radiomics and Intelligent Sense of Xi'an, Northwest University, Xi'an, China.,School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Xiangong Hu
- Key Laboratory for Radiomics and Intelligent Sense of Xi'an, Northwest University, Xi'an, China.,Network and Data Center, Northwest University, Xi'an, China
| | - Mengxiang Chu
- Key Laboratory for Radiomics and Intelligent Sense of Xi'an, Northwest University, Xi'an, China.,Network and Data Center, Northwest University, Xi'an, China
| | - Hongbo Guo
- Key Laboratory for Radiomics and Intelligent Sense of Xi'an, Northwest University, Xi'an, China.,School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Jingjing Yu
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an, China
| | - Xiaowei He
- Key Laboratory for Radiomics and Intelligent Sense of Xi'an, Northwest University, Xi'an, China.,School of Information Sciences and Technology, Northwest University, Xi'an, China.,Network and Data Center, Northwest University, Xi'an, China
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Gao P, Cheng K, Schüler E, Jia M, Zhao W, Xing L. Restarted primal-dual Newton conjugate gradient method for enhanced spatial resolution of reconstructed cone-beam x-ray luminescence computed tomography images. Phys Med Biol 2020; 65:135008. [PMID: 32268318 PMCID: PMC7594591 DOI: 10.1088/1361-6560/ab87fb] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Cone-beam x-ray luminescence computed tomography (CB-XLCT) has been proposed as a promising imaging tool, which enables three-dimensional imaging of the distribution of nanophosphors (NPs) in small animals. However, the reconstruction performance is usually unsatisfactory in terms of spatial resolution due to the ill-posedness of the CB-XLCT inverse problem. To alleviate this problem and to achieve high spatial resolution, a reconstruction method consisting of inner and outer iterations based on a restarted strategy is proposed. In this method, the primal-dual Newton conjugate gradient method (pdNCG) is adopted in the inner iterations to get fast reconstruction, which is used for resetting the permission region and increasing the convergence speed of the outer iteration. To assess the performance of the method, both numerical simulation and physical phantom experiments were conducted with a CB-XLCT system. The results demonstrate that compared with conventional reconstruction methods, the proposed re-pdNCG method can accurately and efficiently resolve the adjacent NPs with the least relative error.
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Affiliation(s)
- Peng Gao
- Department of Radiation Oncology, Stanford University, Stanford, CA 94305, United States of America
- School of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, People’s Republic of China
- These authors contributed to this work equally
| | - Kai Cheng
- Department of Radiation Oncology, Stanford University, Stanford, CA 94305, United States of America
- These authors contributed to this work equally
| | - Emil Schüler
- Department of Radiation Oncology, Stanford University, Stanford, CA 94305, United States of America
| | - Mengyu Jia
- Department of Radiation Oncology, Stanford University, Stanford, CA 94305, United States of America
| | - Wei Zhao
- Department of Radiation Oncology, Stanford University, Stanford, CA 94305, United States of America
| | - Lei Xing
- Department of Radiation Oncology, Stanford University, Stanford, CA 94305, United States of America
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Liu T, Rong J, Gao P, Pu H, Zhang W, Zhang X, Liang Z, Lu H. Regularized reconstruction based on joint L 1 and total variation for sparse-view cone-beam X-ray luminescence computed tomography. BIOMEDICAL OPTICS EXPRESS 2019; 10:1-17. [PMID: 30775079 PMCID: PMC6363206 DOI: 10.1364/boe.10.000001] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 11/22/2018] [Accepted: 11/22/2018] [Indexed: 05/22/2023]
Abstract
As an emerging hybrid imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed based on the development of X-ray excitable nanoparticles. Owing to the high degree of absorption and scattering of light through tissues, the CB-XLCT inverse problem is inherently ill-conditioned. Appropriate priors or regularizations are needed to facilitate reconstruction and to restrict the search space to a specific solution set. Typically, the goal of CB-XLCT reconstruction is to get the distributions of nanophosphors in the imaging object. Considering that the distributions of nanophosphors inside bodies preferentially accumulate in specific areas of interest, the reconstruction of XLCT images is usually sparse with some locally smoothed high-intensity regions. Therefore, a combination of the L1 and total variation regularization is designed to improve the imaging quality of CB-XLCT in this study. The L1 regularization is used for enforcing the sparsity of the reconstructed images and the total variation regularization is used for maintaining the local smoothness of the reconstructed image. The implementation of this method can be divided into two parts. First, the reconstruction image was reconstructed based on the fast iterative shrinkage-thresholding (FISTA) algorithm, then the reconstruction image was minimized by the gradient descent method. Numerical simulations and phantom experiments indicate that compared with the traditional ART, ADAPTIK and FISTA methods, the proposed method demonstrates its advantage in improving spatial resolution and reducing imaging time.
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Affiliation(s)
- Tianshuai Liu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Junyan Rong
- Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Peng Gao
- Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Huangsheng Pu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Wenli Zhang
- Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Xiaofeng Zhang
- Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, China
| | - Zhengrong Liang
- Department of Radiology and Biomedical Engineering, State University of New York at Stony Brook, Stony Brook, NY 11794, USA
| | - Hongbing Lu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi 710032, China
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