Hepatocellular carcinoma Liver Imaging Reporting and Data Systems treatment response assessment: Lessons learned and future directions

Anum Aslam*, Richard Kinh Gian Do, Avinash Kambadakone, Bradley Spieler, Frank H. Miller, Ahmed M. Gabr, Resmi A. Charalel, Charles Y. Kirr, David C. Madoff, Mishal Mendiratta-Lala

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of morbidity and mortality worldwide, with rising clinical and economic burden as incidence increases. There are a multitude of evolving treatment options, including locoregional therapies which can be used alone, in combination with each other, or in combination with systemic therapy. These treatment options have shown to be effective in achieving remission, controlling tumor progression, improving disease free and overall survival in patients who cannot undergo resection and providing a bridge to transplant by debulking tumor burden to downstage patients. Following locoregional therapy (LRT), it is crucial to provide treatment response assessment to guide management and liver transplant candidacy. Therefore, Liver Imaging Reporting and Data Systems (LI-RADS) Treatment Response Algorithm (TRA) was created to provide a standardized assessment of HCC following LRT. LI-RADS TRA provides a step by step approach to evaluate each lesion independently for accurate tumor assessment. In this review, we provide an overview of different locoregional therapies for HCC, describe the expected post treatment imaging appearance following treatment, and review the LI-RADS TRA with guidance for its application in clinical practice. Unique to other publications, we will also review emerging literature supporting the use of LI-RADS for assessment of HCC treatment response after LRT.

Original languageEnglish (US)
Pages (from-to)738-753
Number of pages16
JournalWorld Journal of Hepatology
Volume12
Issue number10
DOIs
StatePublished - Oct 27 2020

Funding

Mendiratta-Lala M is funded from National Institute of Health (NIH) PO1 CA59827. Kim CY serves as a consultant for Medical advisory board Boston Scientific, Genentech;

Keywords

  • Arterial phase hyper enhancement
  • Hepatocellular cercinoma
  • Liver Imaging Reporting and Data Systems
  • Liver Imaging Reporting and Data Systems Treatment Response equivocal
  • Locoregional therapy
  • Stereotactic body radiotherapy
  • Treatment Response Algorithm

ASJC Scopus subject areas

  • Hepatology

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