Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.

Journal: European radiology
Published Date: Mar 28, 2023

Abstract

OBJECTIVES: To evaluate image quality, diagnostic acceptability, and lesion conspicuity in abdominal dual-energy CT (DECT) using deep learning image reconstruction (DLIR) compared to those using adaptive statistical iterative reconstruction-V (Asir-V) at 50% blending (AV-50), and to identify potential factors impacting lesion conspicuity.

Authors

  • Jingyu Zhong
    Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Changning District, Shanghai, 200336, China.
  • Lingyun Wang
    Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, China. wangly@xmu.edu.cn.
  • Hailin Shen
    Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, 215028, Jiangsu, China. hailinshen@163.com.
  • Jianying Li
    CT Research Center, GE Healthcare China, Beijing 100176, China.
  • Wei Lu
    Department of Pharmacy, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
  • Xiaomeng Shi
    From the Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Rd, Shanghai 200080, China (B.J., N.L., X.X.); CT Imaging Research Center, GE Healthcare China, Shanghai, China (X.S., S.Z., J.L.); and Departments of Epidemiology (G.H.d.B.) and Radiology (R.V.), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
  • Yue Xing
    Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Shanghai, 200336, China.
  • Yangfan Hu
    Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China.
  • Xiang Ge
    Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
  • Defang Ding
    Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Shanghai, 200336, China.
  • Fuhua Yan
    Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China. Electronic address: yfh11655@rjh.com.cn.
  • Lianjun Du
    Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. 13601745690@163.com.
  • Weiwu Yao
    Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Changning District, Shanghai, 200336, China. yaoweiwuhuan@163.com.
  • Huan Zhang
    Department of Plant Protection, Zhejiang University, 866 Yuhangtang Road, 5 Hangzhou 310058, China.

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