Application of deep learning reconstruction at prone position chest scanning of early interstitial lung disease.

Journal: BMC medical imaging
Published Date: Aug 19, 2025

Abstract

AIM: Timely intervention of interstitial lung disease (ILD) was promising for attenuating the lung function decline and improving clinical outcomes. The prone position HRCT is essential for early diagnosis of ILD, but limited by its high radiation exposure. This study was aimed to explore whether deep learning reconstruction (DLR) could keep the image quality and reduce the radiation dose compared with hybrid iterative reconstruction (HIR) in prone position scanning for patients of early-stage ILD.

Authors

  • Ruijie Zhao
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
  • Yun Wang
    Department of Anesthesiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, People's Republic of China.
  • Jiaru Wang
    Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No. 1, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
  • Zixing Wang
    Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, School of Basic Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
  • Ran Xiao
  • Ying Ming
    Department of Radiology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
  • Sirong Piao
    Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200000, China.
  • Jinhua Wang
    Department of Pharmacy Intravenous Admixture Service, the First Affiliated Hospital of Harbin Medical University, Harbin, P. R., China.
  • Lan Song
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
  • Yinghao Xu
    Canon Medical System (China), No. 10, Jiuxianqiao North Road, Chaoyang District, Beijing, 100024, China.
  • Zhuangfei Ma
    Canon Medical System (China), No. 10, Jiuxianqiao North Road, Chaoyang District, Beijing, 100024, China.
  • Peilin Fan
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
  • Xin Sui
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
  • Wei Song
    School of Pharmaceutical Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.

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