Prediction of Decompensation and Death in Advanced Chronic Liver Disease Using Deep Learning Analysis of Gadoxetic Acid-Enhanced MRI.

Journal: Korean journal of radiology
Published Date:

Abstract

OBJECTIVE: This study aimed to evaluate the usefulness of quantitative indices obtained from deep learning analysis of gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and their longitudinal changes in predicting decompensation and death in patients with advanced chronic liver disease (ACLD).

Authors

  • Subin Heo
    Department of Radiology, Ajou University School of Medicine, Wonchon-Dong, Yeongtong-Gu, Suwon, 443-380, South Korea.
  • Seung Soo Lee
    From the Department of Computer Science, Hanyang University, Seoul, Republic of Korea (K.J.C.); Department of Radiology and Research Institute of Radiology (J.K.J., S.S.L., Y.S.S., W.H.S., H.S.K., J.Y., J.H.K., S.Y.K.) and Department of Diagnostic Pathology (E.S.Y.), Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea; Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (J.Y.C.); Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Korea (B.K.K.).
  • So Yeon Kim
  • Young-Suk Lim
    Department of Gastroenterology, Asan Medical Center, Seoul, South Korea.
  • Hyo Jung Park
    Department of Radiology and Research Institute of Radiology, Asan Image Metrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Jee Seok Yoon
    Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
  • Heung-Il Suk
    Biomedical Research Imaging Center (BRIC) and Department of Radiology, University of North Carolina, Chapel Hill, NC, 27599, USA, hsuk@med.unc.edu.
  • Yu Sub Sung
    From the Department of Computer Science, Hanyang University, Seoul, Republic of Korea (K.J.C.); Department of Radiology and Research Institute of Radiology (J.K.J., S.S.L., Y.S.S., W.H.S., H.S.K., J.Y., J.H.K., S.Y.K.) and Department of Diagnostic Pathology (E.S.Y.), Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea; Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (J.Y.C.); Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Korea (B.K.K.).
  • Bumwoo Park
    Health Innovation Big Data Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea.
  • Ji Sung Lee
    Clinical Research Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea. (J.S.L.).