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How to utilize LR-M features of the LI-RADS to improve the diagnosis of combined hepatocellular-cholangiocarcinoma on gadoxetate-enhanced MRI?

Hong Seon LeeMyeong Jin KimChansik An
Published in: European radiology (2018)
• Targetoid appearance, including rim APHE, peripheral "washout" appearance, and delayed central enhancement, was the LR-M feature that identified cHCC-CCA as a non-HCC malignancy with the highest sensitivity. • Most cHCC-CCA cases can be properly categorized as LR-M when the presence of any one of the LR-M features was used as the determiner. • Approximately half of HCC cases also showed at least one LR-M feature.
Keyphrases
  • machine learning
  • deep learning
  • contrast enhanced
  • magnetic resonance
  • contrast enhanced ultrasound