Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients

Published Online:https://doi.org/10.1148/radiol.2018181494

By updating the criteria for small (size range, 10–19 mm) LR-5 observations and simplifying the definition for threshold growth, Liver Imaging Reporting and Data System (LI-RADS) version 2018 achieved consistency with and integration into the American Association for the Study of Liver Diseases 2018 hepatocellular carcinoma (HCC) clinical practice guidance, a major milestone toward establishing a universal approach to the imaging diagnosis of HCC.

The Liver Imaging Reporting and Data System (LI-RADS) is composed of four individual algorithms intended to standardize the lexicon, as well as reporting and care, in patients with or at risk for hepatocellular carcinoma in the context of surveillance with US; diagnosis with CT, MRI, or contrast material–enhanced US; and assessment of treatment response with CT or MRI. This report provides a broad overview of LI-RADS, including its historic development, relationship to other imaging guidelines, composition, aims, and future directions. In addition, readers will understand the motivation for and key components of the 2018 update.

© RSNA, 2018

References

  • 1. Marrero JA, Kulik LM, Sirlin C, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases. Hepatology 2018;68(2):723–750.
  • 2. van der Pol CBLC, Bashir MR, Sirlin CB, et al. What is the percentage of hepatocellular carcinoma and overall malignancy within each LI-RADS category? a systematic review. ILCA 2018: 12th Annual Conference of the International Liver Cancer Association, 2018. London, England: International Liver Cancer Association, 2018.
  • 3. Fowler KJ, Potretzke TA, Hope TA, Costa EA, Wilson SR. LI-RADS M (LR-M): definite or probable malignancy, not specific for hepatocellular carcinoma. Abdom Radiol (NY) 2018;43(1):149–157.
  • 4. Tang A, Hallouch O, Chernyak V, Kamaya A, Sirlin CB. Epidemiology of hepatocellular carcinoma: target population for surveillance and diagnosis. Abdom Radiol (NY) 2018;43(1):13–25.
  • 5. Chernyak V, Santillan CS, Papadatos D, Sirlin CB. LI-RADS® algorithm: CT and MRI. Abdom Radiol (NY) 2018;43(1):111–126.
  • 6. Santillan C, Chernyak V, Sirlin C. LI-RADS categories: concepts, definitions, and criteria. Abdom Radiol (NY) 2018;43(1):101–110.
  • 7. Santillan C, Fowler K, Kono Y, Chernyak V. LI-RADS major features: CT, MRI with extracellular agents, and MRI with hepatobiliary agents. Abdom Radiol (NY) 2018;43(1):75–81.
  • 8. Chernyak V, Tang A, Flusberg M, et al. LI-RADS® ancillary features on CT and MRI. Abdom Radiol (NY) 2018;43(1):82–100.
  • 9. Mitchell DG, Bashir MR, Sirlin CB. Management implications and outcomes of LI-RADS-2, -3, -4, and -M category observations. Abdom Radiol (NY) 2018;43(1):143–148.
  • 10. Sirlin CB, Kielar AZ, Tang A, Bashir MR. LI-RADS: a glimpse into the future. Abdom Radiol (NY) 2018;43(1):231–236.
  • 11. Kambadakone AR, Fung A, Gupta RT, et al. LI-RADS technical requirements for CT, MRI, and contrast-enhanced ultrasound. Abdom Radiol (NY) 2018;43(1):56–74 [Published correction appears in Abdom Radiol (NY) 2018;43(1):240.].
  • 12. Morgan TA, Maturen KE, Dahiya N, Sun MRM, Kamaya A; American College of Radiology Ultrasound Liver Imaging and Reporting Data System (US LI-RADS) Working Group. US LI-RADS: ultrasound Liver Imaging Reporting and Data System for screening and surveillance of hepatocellular carcinoma. Abdom Radiol (NY) 2018;43(1):41–55.
  • 13. Wilson SR, Lyshchik A, Piscaglia F, et al. CEUS LI-RADS: algorithm, implementation, and key differences from CT/MRI. Abdom Radiol (NY) 2018;43(1):127–142.
  • 14. Tang A, Cruite I, Mitchell DG, Sirlin CB. Hepatocellular carcinoma imaging systems: why they exist, how they have evolved, and how they differ. Abdom Radiol (NY) 2018;43(1):3–12.
  • 15. Kielar A, Fowler KJ, Lewis S, et al. Locoregional therapies for hepatocellular carcinoma and the new LI-RADS treatment response algorithm. Abdom Radiol (NY) 2018;43(1):218–230.
  • 16. American College of Radiology. Liver Imaging Reporting and Data System. https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS. Accessed September 2, 2018.
  • 17. Cruite I, Tang A, Sirlin CB. Imaging-based diagnostic systems for hepatocellular carcinoma. AJR Am J Roentgenol 2013;201(1):41–55.
  • 18. Omata M, Lesmana LA, Tateishi R, et al. Asian Pacific Association for the Study of the Liver consensus recommendations on hepatocellular carcinoma. Hepatol Int 2010;4(2):439–474.
  • 19. Kudo M, Matsui O, Izumi N, et al. JSH consensus-based clinical practice guidelines for the management of hepatocellular carcinoma: 2014 update by the Liver Cancer Study Group of Japan. Liver Cancer 2014;3(3-4):458–468.
  • 20. Korean Liver Cancer Study Group (KLCSG); National Cancer Center, Korea (NCC). 2014 Korean Liver Cancer Study Group-National Cancer Center Korea practice guideline for the management of hepatocellular carcinoma. Korean J Radiol 2015;16(3):465–522.
  • 21. Bruix J, Sherman M; American Association for the Study of Liver Diseases. Management of hepatocellular carcinoma: an update. Hepatology 2011;53(3):1020–1022.
  • 22. European Association For The Study Of The Liver; European Organisation For Research And Treatment Of Cancer. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 2012;56(4):908–943.
  • 23. Kudo M, Izumi N, Kokudo N, et al. Management of hepatocellular carcinoma in Japan: consensus-based clinical practice Guidelines proposed by the Japan Society of Hepatology (JSH) 2010 updated version. Dig Dis 2011;29(3):339–364.
  • 24. American College of Radiology. US LI-RADS v2017 Core. https://www.acr.org/-/media/ACR/Files/RADS/LI-RADS/LI-RADS-US-Algorithm-Portrait-2017.pdf?la=en. Accessed 2018.
  • 25. Winkler NS, Raza S, Mackesy M, Birdwell RL. Breast density: clinical implications and assessment methods. RadioGraphics 2015;35(2):316–324.
  • 26. Freer PE. Mammographic breast density: impact on breast cancer risk and implications for screening. RadioGraphics 2015;35(2):302–315.
  • 27. Roberts LR, Sirlin CB, Zaiem F, et al. Imaging for the diagnosis of hepatocellular carcinoma: a systematic review and meta-analysis. Hepatology 2018;67(1):401–421.
  • 28. Hanna RF, Miloushev VZ, Tang A, et al. Comparative 13-year meta-analysis of the sensitivity and positive predictive value of ultrasound, CT, and MRI for detecting hepatocellular carcinoma. Abdom Radiol (NY) 2016;41(1):71–90.
  • 29. Kielar AZ, Chernyak V, Bashir MR, et al. LI-RADS 2017: an update. J Magn Reson Imaging 2018;47(6):1459–1474.
  • 30. Lencioni R, Llovet JM. Modified RECIST (mRECIST) assessment for hepatocellular carcinoma. Semin Liver Dis 2010;30(1):52–60.
  • 31. Bargellini I, Bozzi E, Campani D, et al. Modified RECIST to assess tumor response after transarterial chemoembolization of hepatocellular carcinoma: CT-pathologic correlation in 178 liver explants. Eur J Radiol 2013;82(5):e212–e218.
  • 32. Donati OF, Do RK, Hötker AM, et al. Interreader and inter-test agreement in assessing treatment response following transarterial embolization for hepatocelluar carcinoma. Eur Radiol 2015;25(9):2779–2788.
  • 33. Seyal AR, Gonzalez-Guindalini FD, Arslanoglu A, et al. Reproducibility of mRECIST in assessing response to transarterial radioembolization therapy in hepatocellular carcinoma. Hepatology 2015;62(4):1111–1121.
  • 34. Shim JH, Lee HC, Kim SO, et al. Which response criteria best help predict survival of patients with hepatocellular carcinoma following chemoembolization? a validation study of old and new models. Radiology 2012;262(2):708–718.
  • 35. Vincenzi B, Di Maio M, Silletta M, et al. Prognostic relevance of objective response according to EASL criteria and mRECIST criteria in hepatocellular carcinoma patients treated with loco-regional therapies: a literature-based meta-analysis. PLoS One 2015;10(7):e0133488.
  • 36. Gaba RC, Kallwitz ER, Parvinian A, et al. Imaging surveillance and multidisciplinary review improves curative therapy access and survival in HCC patients. Ann Hepatol 2013;12(5):766–773.
  • 37. Cruite I, Tang A, Mamidipalli A, Shah A, Santillan C, Sirlin CB. Liver Imaging Reporting and Data System: review of major imaging features. Semin Roentgenol 2016;51(4):292–300.
  • 38. Granata V, Fusco R, Avallone A, et al. Critical analysis of the major and ancillary imaging features of LI-RADS on 127 proven HCCs evaluated with functional and morphological MRI: lights and shadows. Oncotarget 2017;8(31):51224–51237.
  • 39. Tang A, Bashir MR, Corwin MT, et al. Evidence supporting LI-RADS major features for CT- and MR imaging-based diagnosis of hepatocellular carcinoma: a systematic review. Radiology 2018;286(1):29–48.
  • 40. Fraum TJ, Tsai R, Rohe E, et al. Differentiation of hepatocellular carcinoma from other hepatic malignancies in patients at risk: diagnostic performance of the Liver Imaging Reporting and Data System version 2014. Radiology 2018;286(1):158–172.
  • 41. Horvat N, Nikolovski I, Long N, et al. Imaging features of hepatocellular carcinoma compared to intrahepatic cholangiocarcinoma and combined tumor on MRI using liver imaging and data system (LI-RADS) version 2014. Abdom Radiol (NY) 2018;43(1):169–178.
  • 42. Cerny M, Bergeron C, Billiard JS, et al. LI-RADS for MR imaging diagnosis of hepatocellular carcinoma: performance of major and ancillary features. Radiology 2018;288(1):118–128.
  • 43. Cruite I, Santillan C, Mamidipalli A, Shah A, Tang A, Sirlin CB. Liver imaging reporting and data system: review of ancillary imaging features. Semin Roentgenol 2016;51(4):301–307.
  • 44. Abd Alkhalik Basha M, Abd El Aziz El Sammak D, El Sammak AA. Diagnostic efficacy of the Liver Imaging-Reporting and Data System (LI-RADS) with CT imaging in categorising small nodules (10-20 mm) detected in the cirrhotic liver at screening ultrasound. Clin Radiol 2017;72(10):901.e1–901.e11.
  • 45. An C, Park S, Chung YE, et al. Curative resection of single primary hepatic malignancy: Liver Imaging Reporting and Data System category LR-M portends a worse prognosis. AJR Am J Roentgenol 2017;209(3):576–583.
  • 46. Cha DI, Jang KM, Kim SH, Kang TW, Song KD. Liver Imaging Reporting and Data System on CT and gadoxetic acid-enhanced MRI with diffusion-weighted imaging. Eur Radiol 2017;27(10):4394–4405.
  • 47. Choi SH, Byun JH, Kim SY, et al. Liver Imaging Reporting and Data System v2014 with gadoxetate disodium-enhanced magnetic resonance imaging: validation of LI-RADS category 4 and 5 criteria. Invest Radiol 2016;51(8):483–490.
  • 48. Joo I, Lee JM, Lee DH, Ahn SJ, Lee ES, Han JK. Liver imaging reporting and data system v2014 categorization of hepatocellular carcinoma on gadoxetic acid-enhanced MRI: comparison with multiphasic multidetector computed tomography. J Magn Reson Imaging 2017;45(3):731–740.
  • 49. Kim BR, Lee JM, Lee DH, et al. Diagnostic performance of gadoxetic acid-enhanced liver MR imaging versus multidetector CT in the detection of dysplastic nodules and early hepatocellular carcinoma. Radiology 2017;285(1):134–146.
  • 50. Kim YY, An C, Kim S, Kim MJ. Diagnostic accuracy of prospective application of the Liver Imaging Reporting and Data System (LI-RADS) in gadoxetate-enhanced MRI. Eur Radiol 2018;28(5):2038–2046.
  • 51. Lee SE, An C, Hwang SH, Choi JY, Han K, Kim MJ. Extracellular contrast agent-enhanced MRI: 15-min delayed phase may improve the diagnostic performance for hepatocellular carcinoma in patients with chronic liver disease. Eur Radiol 2018;28(4):1551–1559.
  • 52. Liu W, Qin J, Guo R, et al. Accuracy of the diagnostic evaluation of hepatocellular carcinoma with LI-RADS. Acta Radiol 2018;59(2):140–146.
  • 53. Ronot M, Fouque O, Esvan M, Lebigot J, Aubé C, Vilgrain V. Comparison of the accuracy of AASLD and LI-RADS criteria for the non-invasive diagnosis of HCC smaller than 3 cm. J Hepatol 2017 Dec 21 [Epub ahead of print].
  • 54. Chernyak V, Flusberg M, Law A, Kobi M, Paroder V, Rozenblit AM. Liver Imaging Reporting and Data System: discordance between computed tomography and gadoxetate-enhanced magnetic resonance imaging for detection of hepatocellular carcinoma major features. J Comput Assist Tomogr 2018;42(1):155–161.
  • 55. Lee KH, O’Malley ME, Haider MA, Hanbidge A. Triple-phase MDCT of hepatocellular carcinoma. AJR Am J Roentgenol 2004;182(3):643–649.
  • 56. Forner A, Vilana R, Ayuso C, et al. Diagnosis of hepatic nodules 20 mm or smaller in cirrhosis: prospective validation of the noninvasive diagnostic criteria for hepatocellular carcinoma. Hepatology 2008;47(1):97–104.
  • 57. Kim TK, Lee KH, Jang HJ, et al. Analysis of gadobenate dimeglumine-enhanced MR findings for characterizing small (1-2-cm) hepatic nodules in patients at high risk for hepatocellular carcinoma. Radiology 2011;259(3):730–738.
  • 58. Rimola J, Forner A, Tremosini S, et al. Non-invasive diagnosis of hepatocellular carcinoma ≤ 2 cm in cirrhosis. diagnostic accuracy assessing fat, capsule and signal intensity at dynamic MRI. J Hepatol 2012;56(6):1317–1323.
  • 59. Sangiovanni A, Manini MA, Iavarone M, et al. The diagnostic and economic impact of contrast imaging techniques in the diagnosis of small hepatocellular carcinoma in cirrhosis. Gut 2010;59(5):638–644.
  • 60. Jang HJ, Kim TK, Khalili K, et al. Characterization of 1-to 2-cm liver nodules detected on hcc surveillance ultrasound according to the criteria of the American Association for the Study of Liver Disease: is quadriphasic CT necessary? AJR Am J Roentgenol 2013;201(2):314–321.
  • 61. Horigome H, Nomura T, Saso K, Itoh M, Joh T, Ohara H. Limitations of imaging diagnosis for small hepatocellular carcinoma: comparison with histological findings. J Gastroenterol Hepatol 1999;14(6):559–565.
  • 62. Yoo HJ, Lee JM, Lee JY, et al. Additional value of SPIO-enhanced MR imaging for the noninvasive imaging diagnosis of hepatocellular carcinoma in cirrhotic liver. Invest Radiol 2009;44(12):800–807.
  • 63. Chen L, Zhang L, Liang M, et al. Magnetic resonance imaging with gadoxetic acid disodium for the detection of hepatocellular carcinoma: a meta-analysis of 18 studies. Acad Radiol 2014;21(12):1603–1613.
  • 64. Khan AS, Hussain HK, Johnson TD, Weadock WJ, Pelletier SJ, Marrero JA. Value of delayed hypointensity and delayed enhancing rim in magnetic resonance imaging diagnosis of small hepatocellular carcinoma in the cirrhotic liver. J Magn Reson Imaging 2010;32(2):360–366.
  • 65. Becker-Weidman DJ, Kalb B, Sharma P, et al. Hepatocellular carcinoma lesion characterization: single-institution clinical performance review of multiphase gadolinium-enhanced MR imaging—comparison to prior same-center results after MR systems improvements. Radiology 2011;261(3):824–833.
  • 66. Liu X, Zou L, Liu F, Zhou Y, Song B. Gadoxetic acid disodium-enhanced magnetic resonance imaging for the detection of hepatocellular carcinoma: a meta-analysis. PLoS One 2013;8(8):e70896.
  • 67. Wu LM, Xu JR, Gu HY, et al. Is liver-specific gadoxetic acid-enhanced magnetic resonance imaging a reliable tool for detection of hepatocellular carcinoma in patients with chronic liver disease? Dig Dis Sci 2013;58(11):3313–3325.
  • 68. Compagnon P, Grandadam S, Lorho R, et al. Liver transplantation for hepatocellular carcinoma without preoperative tumor biopsy. Transplantation 2008;86(8):1068–1076.
  • 69. Chou R, Cuevas C, Fu R, et al. Imaging techniques for the diagnosis of hepatocellular carcinoma: a systematic review and meta-analysis. Ann Intern Med 2015;162(10):697–711.
  • 70. Ohkawa K, Imanaka K, Sakakibara M, et al. Factors related to shift from hepatic borderline lesion to overt HCC diagnosed by CT. Hepatogastroenterology 2014;61(134):1680–1687.
  • 71. Bolondi L, Gaiani S, Celli N, et al. Characterization of small nodules in cirrhosis by assessment of vascularity: the problem of hypovascular hepatocellular carcinoma. Hepatology 2005;42(1):27–34.
  • 72. Kudo M, Tochio H. Intranodular blood supply correlates well with biological malignancy grade determined by tumor growth rate in pathologically proven hepatocellular carcinoma. Oncology 2008;75(Suppl 1):55–64.
  • 73. Fowler KJ, Tang A, Santillan C, et al. Interreader reliability of LI-RADS version 2014 algorithm and imaging features for diagnosis of hepatocellular carcinoma: a large international multireader study. Radiology 2018;286(1):173–185.
  • 74. Barth BK, Donati OF, Fischer MA, et al. Reliability, validity, and reader acceptance of LI-RADS: an in-depth analysis. Acad Radiol 2016;23(9):1145–1153.
  • 75. Bashir MR, Huang R, Mayes N, et al. Concordance of hypervascular liver nodule characterization between the organ procurement and transplant network and Liver Imaging Reporting and Data System classifications. J Magn Reson Imaging 2015;42(2):305–314.
  • 76. Davenport MS, Khalatbari S, Liu PS, et al. Repeatability of diagnostic features and scoring systems for hepatocellular carcinoma by using MR imaging. Radiology 2014;272(1):132–142.
  • 77. Ehman EC, Behr SC, Umetsu SE, et al. Rate of observation and inter-observer agreement for LI-RADS major features at CT and MRI in 184 pathology proven hepatocellular carcinomas. Abdom Radiol (NY) 2016;41(5):963–969.
  • 78. Sofue K, Sirlin CB, Allen BC, Nelson RC, Berg CL, Bashir MR. How reader perception of capsule affects interpretation of washout in hypervascular liver nodules in patients at risk for hepatocellular carcinoma. J Magn Reson Imaging 2016;43(6):1337–1345.
  • 79. Zhang YD, Zhu FP, Xu X, et al. Classifying CT/MR findings in patients with suspicion of hepatocellular carcinoma: comparison of Liver Imaging Reporting and Data System and criteria-free Likert scale reporting models. J Magn Reson Imaging 2016;43(2):373–383.
  • 80. Schellhaas B, Pfeifer L, Kielisch C, Goertz RS, Neurath MF, Strobel D. Interobserver agreement for contrast-enhanced ultrasound (CEUS)-based standardized algorithms for the diagnosis of hepatocellular carcinoma in high-risk patients. Ultraschall Med 2018 Jun 7 [Epub ahead of print].
  • 81. Schellhaas B, Hammon M, Strobel D, et al. Interobserver and intermodality agreement of standardized algorithms for non-invasive diagnosis of hepatocellular carcinoma in high-risk patients: CEUS-LI-RADS versus MRI-LI-RADS. Eur Radiol 2018 Apr 19 [Epub ahead of print].
  • 82. Becker AS, Barth BK, Marquez PH, et al. Increased interreader agreement in diagnosis of hepatocellular carcinoma using an adapted LI-RADS algorithm. Eur J Radiol 2017;86:33–40.
  • 83. Allen BC, Ho LM, Jaffe TA, Miller CM, Mazurowski MA, Bashir MR. Comparison of visualization rates of LI-RADS version 2014 major features with IV gadobenate dimeglumine or gadoxetate disodium in patients at risk for hepatocellular carcinoma. AJR Am J Roentgenol 2018;210(6):1266–1272.
  • 84. Hope TA, Aslam R, Weinstein S, et al. Change in Liver Imaging Reporting and Data System characterization of focal liver lesions using gadoxetate disodium magnetic resonance imaging compared with contrast-enhanced computed tomography. J Comput Assist Tomogr 2017;41(3):376–381.
  • 85. Zhang YD, Zhu FP, Xu X, et al. Liver Imaging Reporting and Data System: substantial discordance between CT and MR for imaging classification of hepatic nodules. Acad Radiol 2016;23(3):344–352.

Article History

Received: June 22 2018
Revision requested: July 16 2018
Revision received: July 22 2018
Accepted: July 30 2018
Published online: Sept 25 2018
Published in print: Dec 2018