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White paper of the Society of Abdominal Radiology hepatocellular carcinoma diagnosis disease-focused panel on LI-RADS v2018 for CT and MRI

Abdominal Radiology volume 43, pages 2625–2642 (2018)Cite this article

Abstract

The Liver Imaging and Reporting Data System (LI-RADS) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver imaging with the overarching goal of improving communication, clinical care, education, and research relating to patients at risk for or diagnosed with hepatocellular carcinoma (HCC). In 2018, the American Association for the Study of Liver Diseases (AASLD) integrated LI-RADS into its clinical practice guidance for the imaging-based diagnosis of HCC. The harmonization between the AASLD and LI-RADS diagnostic imaging criteria required minor modifications to the recently released LI-RADS v2017 guidelines, necessitating a LI-RADS v2018 update. This article provides an overview of the key changes included in LI-RADS v2018 as well as a look at the LI-RADS v2018 diagnostic algorithm and criteria, technical recommendations, and management suggestions. Substantive changes in LI-RADS v2018 are the removal of the requirement for visibility on antecedent surveillance ultrasound for LI-RADS 5 (LR-5) categorization of 10-19 mm observations with nonrim arterial phase hyper-enhancement and nonperipheral “washout”, and adoption of the Organ Procurement and Transplantation Network definition of threshold growth (≥ 50% size increase of a mass in ≤ 6 months). Nomenclatural changes in LI-RADS v2018 are the removal of -us and -g as LR-5 qualifiers.

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Case courtesy of Dr. Kupa Patel-Lippman

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Acknowledgements

The author(s) are military service members. This work was prepared as part of official duties. Title 17 U.S.C. 105 provides that ‘Copyright protection under this title is not available for any work of the United States Government.’

Disclaimer

The views expressed in this presentation are those of the authors and do not necessarily reflect the official policy or position of the Department of the Navy, Department of Defense or the United States Government.

Author information

Affiliations

  1. Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX, 77030, USA

    Khaled M. Elsayes, Mohab M. Elmohr & Janio Szklaruk

  2. Department of Radiology, University of Toronto, Toronto, ON, Canada

    Ania Z. Kielar

  3. Department of Radiology, Montefiore Medical Center, Bronx, NY, USA

    Victoria Chernyak

  4. Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA

    William R. Masch

  5. Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA

    Alessandro Furlan

  6. Department of Radiology, Naval Medical Center San Diego, Uniformed Services University of the Health Sciences, San Diego, CA, USA

    Robert M. Marks

  7. Department of Radiology, Inland Imaging, Spokane, WA, USA

    Irene Cruite

  8. Department of Radiology, University of California San Diego, San Diego, CA, USA

    Kathryn J. Fowler & Claude B. Sirlin

  9. Department of Radiology, Centre hospitalier de l’Université de Montréal, Montreal, QC, Canada

    An Tang

  10. Department of Radiology, Duke University Medical Center, Durham, NC, USA

    Mustafa R. Bashir

  11. Department of Radiology, Columbia University Medical Center, New York, NY, USA

    Elizabeth M. Hecht

  12. Department of Radiology, Stanford University Medical Center, Stanford, CA, USA

    Aya Kamaya

  13. Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, USA

    Kedar Jambhekar

  14. Department of Radiology, Mount Sinai Health System, New York, NY, USA

    Amita Kamath

  15. Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA

    Sandeep Arora

  16. Department of Radiology, University of California Davis Medical Center, Sacramento, CA, USA

    Bijan Bijan & John P. McGahan

  17. Department of Radiology, University of Kansas, Kansas City, KS, USA

    Ryan Ash

  18. Department of Diagnostic Imaging and Oncology, Schulich School of Medicine, London, ON, Canada

    Zahra Kassam

  19. Department of Radiology, Rutgers-New Jersey Medical School, Newark, NJ, USA

    Humaira Chaudhry

  20. Department of Radiology, Georgetown University School of Medicine, Washington, DC, USA

    Joseph H. Yacoub

  21. Department of Radiology, University of Ottawa, Ottawa, ON, Canada

    Matthew McInnes

  22. Department of Radiology, Oregon Health and Science University, Portland, OR, USA

    Alice W. Fung

  23. Department of Radiology, NYU Langone School of Medicine, New York, NY, USA

    Krishna Shanbhogue

  24. Department of Radiology, University of Kentucky, Lexington, KY, USA

    James Lee

  25. Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA

    Sandeep Deshmukh & Donald G. Mitchell

  26. Department of Radiology, Hospital Sirio-Libanes and University of Sao Paulo, Sao Paulo, Brazil

    Natally Horvat

  27. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Richard K. G. Do

  28. Department of Radiology, University of Texas HSC at Houston, Houston, TX, USA

    Venkateswar R. Surabhi

Authors
  1. Khaled M. Elsayes
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  2. Ania Z. Kielar
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  3. Mohab M. Elmohr
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  4. Victoria Chernyak
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  8. Irene Cruite
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  9. Kathryn J. Fowler
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  10. An Tang
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  20. Humaira Chaudhry
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  21. John P. McGahan
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  22. Joseph H. Yacoub
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  23. Matthew McInnes
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  25. Krishna Shanbhogue
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  26. James Lee
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  27. Sandeep Deshmukh
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  28. Natally Horvat
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  29. Donald G. Mitchell
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  30. Richard K. G. Do
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  31. Venkateswar R. Surabhi
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  32. Janio Szklaruk
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  33. Claude B. Sirlin
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Corresponding author

Correspondence to Khaled M. Elsayes.

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Elsayes, K.M., Kielar, A.Z., Elmohr, M.M. et al. White paper of the Society of Abdominal Radiology hepatocellular carcinoma diagnosis disease-focused panel on LI-RADS v2018 for CT and MRI. Abdom Radiol 43, 2625–2642 (2018). https://doi.org/10.1007/s00261-018-1744-4

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  • DOI: https://doi.org/10.1007/s00261-018-1744-4

Keywords

  • LI-RADS
  • v2018
  • CT
  • MRI
  • HCC