43
views
0
recommends
+1 Recommend
1 collections
    1
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Feasibility of optimizing acquisition time of 18F-FDG PET with BSREM reconstruction algorithm

      research-article

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective To compare the impact on 18F fluorodeoxyglucose ( 18F-FDG) positron emission tomography (PET) image quality when block sequential regularized expectation maximization (BSREM) algorithm and ordered subset expectation maximization (OSEM) algorithm were used at various acquisition times (ATs), and to discuss the feasibility of AT optimization with BSREM algorithm.

          Methods In the phantom experiment, the NEMA/IEC PET phantom was adopted. In the clinical study, 66 pulmonary nodules with high uptake values from 61 patients who underwent a 18F-FDG PET-CT examination for pulmonary nodules from March to September 2020 were included. PET images were reconstructed according to BSREM algorithm and OSEM algorithm at various ATs in both the phantom experiment and the clinical study. Coefficient of variation, signal-to-noise ratio, contrast-to-noise ratio, and activity values (uptake value in the phantom experiment; standardized uptake value in the clinical study) were compared between the above sequence images for quality evaluation.

          Results The phantom experiment showed that the image quality of 120 s BSREM sequence was superior to that of 120 s OSEM sequence, and the image quality of 75 s BSREM sequence was similar to that of 120 s OSEM sequence. The clinical study showed that the image quality of 120 s BSREM sequence was superior to that of 120 s OSEM sequence, and the image quality of 75 s BSREM sequence was slightly better than that of 120 s OSEM sequence.

          Conclusion In the PET phantom experiment and the clinical study of pulmonary nodules with high uptake values, BSREM algorithm can significantly improve the image quality as compared to OSEM algorithm, and the image quality of 75 s BSREM sequence is slightly better than that of 120 s OSEM sequence.

          Abstract

          摘要: 目的 比较不同采集时间下分块顺序正则化期望最大化(BSREM)算法较有序子集期望最大化(OSEM)算法对 18F-FDG PET图像质量的影响, 探讨其优化采集时间的可行性。 方法 模体实验采用NEMA/IEC PET模体, 临床研宄 中连续收集2020年3—9月因肺结节行 18F-FDG PET-CT检查患者61例(66个高摄取肺结节)。模体实验和临床研宄 均以不同采集时间按BSREM和OSEM算法重建PET图像。比较上述序列的变异系数(CV)、信噪比(SNR)、对比噪 声比(CNR)、活度测量值(模体实验为摄取值UV;临床研宄为标准摄取值SUV)差异。 结果 模体实验显示120 s BSREM序列图像质量优于120 s OSEM序列, 75 s BSREM序列与120 s OSEM序列相仿。临床研宄显示120 s BSREM 序列图像质量优于120 s OSEM序列, 且75 s BSREM序列较120 s OSEM序列略优。 结论 PET模体实验和肺部高 摄取结节临床研宄中, 应用BSREM算法较OSEM算法明显改善图像质量, 75 s BSREM序列图像质量较120 s OSEM 序列略优。

          Related collections

          Author and article information

          Journal
          CJRH
          Chinese Journal of Radiological Health
          Chinese Preventive Medical Association (Ji’an, China )
          1004-714X
          01 April 2022
          01 April 2022
          : 31
          : 2
          : 224-228
          Affiliations
          [1] 1National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116 China
          [2] 2National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021 China
          Author notes
          Corresponding author: LIANG Ying, E-mail: liangy_2000@ 123456sina.com
          Article
          j.issn.1004-714X.2022.02.017
          10.13491/j.issn.1004-714X.2022.02.017
          88055e07-d966-4c17-8489-373f6b491df3
          © 2022 Chinese Journal of Radiological Health

          This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License (CC BY-NC 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc/4.0/.

          History
          Categories
          Journal Article

          Medicine,Image processing,Radiology & Imaging,Bioinformatics & Computational biology,Health & Social care,Public health
          Image quality,Quantitative analysis,Acquisition time,Radiation protection,Reconstruction algorithm,PET-CT

          Comments

          Comment on this article