LI-RADS-based hepatocellular carcinoma risk mapping using contrast-enhanced MRI and self-configuring deep learning.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
PMID: 40097992

Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) is often diagnosed using gadoxetate disodium-enhanced magnetic resonance imaging (EOB-MRI). Standardized reporting according to the Liver Imaging Reporting and Data System (LI-RADS) can improve Gd-MRI interpretation but is rather complex and time-consuming. These limitations could potentially be alleviated using recent deep learning-based segmentation and classification methods such as nnU-Net. The study aims to create and evaluate an automatic segmentation model for HCC risk assessment, according to LI-RADS v2018 using nnU-Net.

Authors

  • Róbert Stollmayer
    Department of Radiology, Medical Imaging Centre, Faculty of Medicine, Semmelweis University, Budapest 1083, Hungary.
  • Selda Güven
    Department of Radiology, Diskapi Yildirim Beyazit Training and Research Hospital, University of Health Sciences, Ankara, Turkey.
  • Christian Marcel Heidt
    Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Heidelberg, Germany.
  • Kai Schlamp
  • Pál Novák Kaposi
    Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary.
  • Oyunbileg von Stackelberg
    Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany; Translational Lung Research Center, Member of the German Lung Research Center, Heidelberg, Germany; Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik, Heidelberg University Hospital, Heidelberg, Germany. Electronic address: Oyunbileg.Stackelberg@med.uni-heidelberg.de.
  • Hans-Ulrich Kauczor
    Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
  • Miriam Klauss
    Clinic for Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Heidelberg, Germany.
  • Philipp Mayer
    German Cancer Consortium, Heidelberg, Germany.

Keywords

External Resources

Popular Topics
Recent Journals