Prediction of treatment response and outcome of transarterial chemoembolization in patients with hepatocellular carcinoma using artificial intelligence: A systematic review of efficacy.

Journal: European journal of radiology
PMID:

Abstract

PURPOSE: To perform a systematic literature review of the efficacy of different AI models to predict HCC treatment response to transarterial chemoembolization (TACE), including overall survival (OS) and time to progression (TTP).

Authors

  • Pedram Keshavarz
    Department of Radiological Sciences, David Geffen School of Medicine at The University of California, Los Angeles (UCLA), Los Angeles, CA, USA. Electronic address: Pkeshavarz@mednet.ucla.edu.
  • Nariman Nezami
    Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06520.
  • Fereshteh Yazdanpanah
    Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
  • Maryam Khojaste-Sarakhsi
    Institute for Computing and Information Sciences, Radboud University, Nijmegen, the Netherlands.
  • Zahra Mohammadigoldar
    Department of Radiological Sciences, David Geffen School of Medicine at The University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
  • Mobin Azami
    Department of Diagnostic & Interventional Radiology, New Hospitals Ltd., Tbilisi 0114, Georgia.
  • Azadeh Hajati
    Department of Radiology, Division of Abdominal Imaging, Harvard Medical School, Boston, MA 02114, USA.
  • Faranak Ebrahimian Sadabad
    Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.
  • Jason Chiang
    Department of Radiological Sciences, David Geffen School of Medicine at The University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
  • Justin P McWilliams
    Department of Radiological Sciences, David Geffen School of Medicine at The University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
  • David S K Lu
    Department of Radiologic Sciences David Geffen School of Medicine, University of California Los Angeles CA.
  • Steven S Raman
    Department of Radiologic Sciences David Geffen School of Medicine, University of California Los Angeles CA.