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LI-RADS and transplantation: challenges and controversies

  • Guilherme M. CunhaEmail author
  • Dorathy E. Tamayo-Murillo
  • Kathryn J. Fowler
Special Section: Liver Transplantation

Abstract

Patients with early stage hepatocellular carcinoma (HCC) can be cured by liver transplantation. HCC imaging features on CT or MRI are specific enough to allow for definitive diagnosis and treatment without the need of confirmatory biopsy. When applied to the appropriate at-risk population the Liver Imaging Reporting and Data System (LI-RADS) imaging criteria achieve high specificity and positive predictive value for the diagnosis of HCC. The Organ Procurement and Transplantation Network (OPTN) is the United States organization that aims to assure the adequate and fair distribution of livers across candidates. Given the importance of fair organ allocation, OPTN also provides stringent imaging criteria for the diagnosis of HCC aiming to avoid false positive diagnosis. Although most imaging criteria are identical for both systems, discrepancies between LI-RADS and the current OPTN classification system for HCC diagnosis exists. Main differences include, but are not limited to, the binary approach of OPTN to classify lesions as HCC or not, versus the probabilistic algorithmic approach of LI-RADS, technical and interpretation considerations, and the approach towards treated lesions. The purpose of this article is to highlight the similarities and discrepancies between LI-RADS and the current OPTN criteria for HCC diagnosis and the implications that these differences may have on the management of patients who are transplant candidates.

Keywords

Hepatocellular carcinoma Imaging diagnosis Staging Transplantation 

Abbreviations

HCC

Hepatocellular Carcinoma

LT

Liver transplantation

UNOS

United Network for Organ Sharing

OPTN

Organ Procurement and Transplantation Network

MELD

Model for End-Stage Liver Disease

LI-RADS

Liver Imaging Reporting and Data System

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Liver Imaging Group, Department of RadiologyUniversity of CaliforniaSan DiegoUSA
  2. 2.Department of RadiologyUniversity of CaliforniaSan DiegoUSA

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