Journal of the Korean Society of Radiology (대한영상의학회지)

The Korean Society of Radiology (대한영상의학회)
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CT/MRI Liver Imaging Reporting and Data System (LI-RADS): Standardization, Evidence, and Future Direction

CT/MRI 간영상 판독과 자료체계: 표준화, 근거 및 발전방향

  • Yeun-Yoon Kim (Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine) ;
  • Jin-Young Choi (Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine)
  • 김연윤 (연세대학교 의과대학 세브란스병원 영상의학과) ;
  • 최진영 (연세대학교 의과대학 세브란스병원 영상의학과)
  • Received : 2022.10.26
  • Accepted : 2022.12.27
  • Published : 2023.01.01
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Abstract

The liver imaging reporting and data system (LI-RADS) has been developed with the support of the American College of Radiology to standardize the diagnosis and evaluation of treatment response of hepatocellular carcinoma (HCC). The CT/MRI LI-RADS version 2018 has been incorporated in the American Association for the Study of Liver Diseases guidance. This review examines the effect of CT/MRI LI-RADS on the standardized reporting of liver imaging, and the evidence in diagnosing HCC and evaluating treatment response after locoregional treatment using CT/MRI LI-RADS. The results are compared with other HCC diagnosis guidelines, and future directions are described.

간영상 보고 및 자료체계(liver imaging reporting and data system; 이하 LI-RADS)는 간세포암종 고위험군에서 간세포암종의 진단과 치료반응평가 등을 표준화하기 위해 미국영상의 학회의 후원을 받아 개발되었다. CT/MRI LI-RADS는 2018년 버전이 가장 최근에 개정된 것인데, 미국간학회 가이드라인에 간세포암종 진단기준으로서 통합되었다. 이 종설에서는 CT/MRI LI-RADS가 간영상의 표준화된 보고에 미친 영향을 살펴보고, CT/MRI LI-RADS를 이용한 간세포암종 진단과 국소치료 후의 치료반응평가에 있어 현시점에서 축적된 근거 및 다른 간세포암종 진단가이드라인들과의 비교 결과를 살펴볼 것이며, 추후 발전방향에 대해 기술하고자 한다.

Keywords

References

  1. Mitchell DG, Bruix J, Sherman M, Sirlin CB. LI-RADS (liver imaging reporting and data system): summary, discussion, and consensus of the LI-RADS management working group and future directions. Hepatology 2015;61:1056-1065 
  2. Marrero JA, Kulik LM, Sirlin CB, Zhu AX, Finn RS, Abecassis MM, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the study of liver diseases. Hepatology 2018;68:723-750 
  3. Chernyak V, Fowler KJ, Kamaya A, Kielar AZ, Elsayes KM, Bashir MR, et al. Liver imaging reporting and data system (LI-RADS) version 2018: imaging of hepatocellular carcinoma in at-risk patients. Radiology 2018;289:816-830 
  4. Tang A, Bashir MR, Corwin MT, Cruite I, Dietrich CF, Do RKG, et al. Evidence supporting LI-RADS major features for CT- and MR imaging-based diagnosis of hepatocellular carcinoma: a systematic review. Radiology 2018;286:29-48 
  5. Chernyak V, Tang A, Do RKG, Kamaya A, Kono Y, Santillan CS, et al. Liver imaging: it is time to adopt standardized terminology. Eur Radiol 2022;32:6291-6301 
  6. Ahn Y, Choi SH, Jang JK, Kim SY, Shim JH, Lee SS, et al. Impact of the liver imaging reporting and data system on research studies of diagnosing hepatocellular carcinoma using MRI. Korean J Radiol 2022;23:529-538 
  7. van der Pol CB, Lim CS, Sirlin CB, McGrath TA, Salameh JP, Bashir MR, et al. Accuracy of the liver imaging reporting and data system in computed tomography and magnetic resonance image analysis of hepatocellular carcinoma or overall malignancy-a systematic review. Gastroenterology 2019;156:976-986 
  8. Lee S, Kim SS, Roh YH, Choi JY, Park MS, Kim MJ. Diagnostic performance of CT/MRI liver imaging reporting and data system v2017 for hepatocellular carcinoma: a systematic review and meta-analysis. Liver Int 2020;40:1488-1497 
  9. Lee S, Kim YY, Shin J, Hwang SH, Roh YH, Chung YE, et al. CT and MRI liver imaging reporting and data system version 2018 for hepatocellular carcinoma: a systematic review with meta-analysis. J Am Coll Radiol 2020;17:1199-1206 
  10. Kim YY, Lee S, Shin J, Son WJ, Shin H, Lee JE, et al. Diagnostic performance of liver imaging reporting and data system version 2017 versus version 2018 for hepatocellular carcinoma: a systematic review and meta-analysis of comparative studies. J Magn Reson Imaging 2021;54:1912-1919 
  11. Kim YY, Kim MJ, Kim EH, Roh YH, An C. Hepatocellular carcinoma versus other hepatic malignancy in cirrhosis: performance of LI-RADS version 2018. Radiology 2019;291:72-80 
  12. Choi SH, Lee SS, Park SH, Kim KM, Yu E, Park Y, et al. LI-RADS classification and prognosis of primary liver cancers at gadoxetic acid-enhanced MRI. Radiology 2019;290:388-397 
  13. Jeon SK, Joo I, Lee DH, Lee SM, Kang HJ, Lee KB, et al. Combined hepatocellular cholangiocarcinoma: LIRADS v2017 categorisation for differential diagnosis and prognostication on gadoxetic acid-enhanced MR imaging. Eur Radiol 2019;29:373-382 
  14. Fraum TJ, Cannella R, Ludwig DR, Tsai R, Naeem M, LeBlanc M, et al. Assessment of primary liver carcinomas other than hepatocellular carcinoma (HCC) with LI-RADS v2018: comparison of the LI-RADS target population to patients without LI-RADS-defined HCC risk factors. Eur Radiol 2020;30:996-1007 
  15. van der Pol CB, McInnes MDF, Salameh JP, Levis B, Chernyak V, Sirlin CB, et al. CT/MRI and CEUS LI-RADS major features association with hepatocellular carcinoma: individual patient data meta-analysis. Radiology 2022;302:326-335 
  16. Park JH, Chung YE, Seo N, Choi JY, Park MS, Kim MJ. Should threshold growth be considered a major feature in the diagnosis of hepatocellular carcinoma using LI-RADS? Korean J Radiol 2021;22:1628-1639 
  17. Cerny M, Bergeron C, Billiard JS, Murphy-Lavallee J, Olivie D, Berube J, et al. LI-RADS for MR imaging diagnosis of hepatocellular carcinoma: performance of major and ancillary features. Radiology 2018;288:118-128 
  18. Kim YY, Choi JY, Kim SU, Lee M, Park MS, Chung YE, et al. MRI ancillary features for LI-RADS category 3 and 4 observations: improved categorization to indicate the risk of hepatic malignancy. AJR Am J Roentgenol 2020;215:1354-1362 
  19. Kim YY, Min JH, Hwang JA, Jeong WK, Sinn DH, Lim HK. Second-line Sonazoid-enhanced ultrasonography for liver imaging reporting and data system category 3 and 4 on gadoxetate-enhanced magnetic resonance imaging. Ultrasonography 2022;41:519-529 
  20. Kang JH, Choi SH, Byun JH, Kim DH, Lee SJ, Kim SY, et al. Ancillary features in the liver imaging reporting and data system: how to improve diagnosis of hepatocellular carcinoma ≤ 3 cm on magnetic resonance imaging. Eur Radiol 2020;30:2881-2889 
  21. Cannella R, Vernuccio F, Sagreiya H, Choudhury KR, Iranpour N, Marin D, et al. Liver imaging reporting and data system (LI-RADS) v2018: diagnostic value of ancillary features favoring malignancy in hypervascular observations ≥ 10 mm at intermediate (LR-3) and high probability (LR-4) for hepatocellular carcinoma. Eur Radiol 2020;30:3770-3781 
  22. Lee S, Kim SS, Bae H, Shin J, Yoon JK, Kim MJ. Application of liver imaging reporting and data system version 2018 ancillary features to upgrade from LR-4 to LR-5 on gadoxetic acid-enhanced MRI. Eur Radiol 2021;31:855-863 
  23. Kim HS, Choi JI, Kim BH, Youn SY, Kim H, Kim DH, et al. LI-RADS version 2018 in patients with prior history of hepatocellular carcinoma: are LR4 observations enough for the diagnosis of recurrent HCC? Investig Magn Reson Imaging 2021;25:172-182 
  24. An C, Park S, Chung YE, Kim DY, Kim SS, Kim MJ, 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;209:576-583 
  25. Shin J, Lee S, Kim SS, Chung YE, Choi JY, Park MS, et al. Characteristics and early recurrence of hepatocellular carcinomas categorized as LR-M: comparison with those categorized as LR-4 or 5. J Magn Reson Imaging 2021;54:1446-1454 
  26. Lee S, Kim KW, Jeong WK, Jeong SY, Hwang JA, Choi JS, et al. Liver imaging reporting and data system category on magnetic resonance imaging predicts recurrence of hepatocellular carcinoma after liver transplantation within the Milan criteria: a multicenter study. Ann Surg Oncol 2021;28:6782-6789 
  27. Kim TH, Woo S, Joo I, Bashir MR, Park MS, Burke LMB, et al. LI-RADS treatment response algorithm for detecting incomplete necrosis in hepatocellular carcinoma after locoregional treatment: a systematic review and meta-analysis using individual patient data. Abdom Radiol (NY) 2021;46:3717-3728 
  28. Gupta P, Bansal A, Das GC, Kumar-M P, Chaluvashetty SB, Bhujade H, et al. Diagnostic accuracy of liver imaging reporting and data system locoregional treatment response criteria: a systematic review and meta-analysis. Eur Radiol 2021;31:7725-7733 
  29. Youn SY, Kim DH, Choi SH, Kim B, Choi JI, Shin YR, et al. Diagnostic performance of liver imaging reporting and data system treatment response algorithm: a systematic review and meta-analysis. Eur Radiol 2021;31:4785-4793 
  30. Yoon J, Lee S, Shin J, Kim SS, Kim GM, Won JY. LI-RADS version 2018 treatment response algorithm: diagnostic performance after transarterial radioembolization for hepatocellular carcinoma. Korean J Radiol 2021;22:1279-1288 
  31. Kim YY, Kim MJ, Yoon JK, Shin J, Roh YH. Incorporation of ancillary MRI features into the LI-RADS treatment response algorithm: impact on diagnostic performance after locoregional treatment of hepatocellular carcinoma. AJR Am J Roentgenol 2022;218:484-493 
  32. Youn SY, Kim DH, Choi JI, Choi MH, Kim B, Shin YR, et al. Usefulness of arterial subtraction in applying liver imaging reporting and data system (LI-RADS) treatment response algorithm to gadoxetic acid-enhanced MRI. Korean J Radiol 2021;22:1289-1299 
  33. Kim SW, Joo I, Kim HC, Ahn SJ, Kang HJ, Jeon SK, et al. LI-RADS treatment response categorization on gadoxetic acid-enhanced MRI: diagnostic performance compared to mRECIST and added value of ancillary features. Eur Radiol 2020;30:2861-2870 
  34. Park S, Joo I, Lee DH, Bae JS, Yoo J, Kim SW, et al. Diagnostic performance of LI-RADS treatment response algorithm for hepatocellular carcinoma: adding ancillary features to MRI compared with enhancement patterns at CT and MRI. Radiology 2020;296:554-561 
  35. European Association for the Study of the Liver. EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 2018;69:182-236 
  36. Omata M, Cheng AL, Kokudo N, Kudo M, Lee JM, Jia J, et al. Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma: a 2017 update. Hepatol Int 2017;11:317-370 
  37. Korean Liver Cancer Association (KLCA), National Cancer Center (NCC). 2018 Korean Liver Cancer Association-National Cancer Center Korea practice guidelines for the management of hepatocellular carcinoma. Korean J Radiol 2019;20:1042-1113 
  38. Joo I, Lee JM, Lee DH, Jeon JH, Han JK, Choi BI. Noninvasive diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced MRI: can hypointensity on the hepatobiliary phase be used as an alternative to washout? Eur Radiol 2015;25:2859-2868 
  39. Kim DH, Choi SH, Kim SY, Kim MJ, Lee SS, Byun JH. Gadoxetic acid-enhanced MRI of hepatocellular carcinoma: value of washout in transitional and hepatobiliary phases. Radiology 2019;291:651-657 
  40. Joo I, Lee JM, Lee DH, Jeon JH, Han JK. Retrospective validation of a new diagnostic criterion for hepatocellular carcinoma on gadoxetic acid-enhanced MRI: can hypointensity on the hepatobiliary phase be used as an alternative to washout with the aid of ancillary features? Eur Radiol 2019;29:1724-1732 
  41. Lee S, Kim MJ, Kim SS, Shin H, Kim DY, Choi JY, et al. Retrospective comparison of EASL 2018 and LI-RADS 2018 for the noninvasive diagnosis of hepatocellular carcinoma using magnetic resonance imaging. Hepatol Int 2020;14:70-79 
  42. Min JH, Kim JM, Kim YK, Kim H, Cha DI, Kang TW, et al. EASL versus LI-RADS: Intra-individual comparison of MRI with extracellular contrast and gadoxetic acid for diagnosis of small HCC. Liver Int 2021;41:2986-2996 
  43. Lee S, Kim SS, Chang DR, Kim H, Kim MJ. Comparison of LI-RADS 2018 and KLCA-NCC 2018 for noninvasive diagnosis of hepatocellular carcinoma using magnetic resonance imaging. Clin Mol Hepatol 2020;26:340-351 
  44. Lee SM, Lee JM, Ahn SJ, Kang HJ, Yang HK, Yoon JH. Diagnostic Performance of 2018 KLCA-NCC practice guideline for hepatocellular carcinoma on gadoxetic acid-enhanced MRI in patients with chronic hepatitis B or cirrhosis: comparison with LI-RADS version 2018. Korean J Radiol 2021;22:1066-1076 
  45. Byun J, Choi SH, Byun JH, Lee SJ, Kim SY, Won HJ, et al. Comparison of the diagnostic performance of imaging criteria for HCCs≤ 3.0 cm on gadoxetate disodium-enhanced MRI. Hepatol Int 2020;14:534-543 
  46. Jeon SK, Lee JM, Joo I, Yoo J, Park JY. Comparison of guidelines for diagnosis of hepatocellular carcinoma using gadoxetic acid-enhanced MRI in transplantation candidates. Eur Radiol 2020;30:4762-4771 
  47. Hwang SH, Park MS, Park S, Lim JS, Kim SU, Park YN. Comparison of the current guidelines for diagnosing hepatocellular carcinoma using gadoxetic acid-enhanced magnetic resonance imaging. Eur Radiol 2021;31:4492-4503 
  48. Park SH, Shim YS, Kim B, Kim SY, Kim YS, Huh J, et al. Retrospective analysis of current guidelines for hepatocellular carcinoma diagnosis on gadoxetic acid-enhanced MRI in at-risk patients. Eur Radiol 2021;31:4751-4763 
  49. Kim DH, Kim B, Youn SY, Kim H, Choi JI. Diagnostic performance of KLCA-NCC 2018 criteria for hepatocellular carcinoma using magnetic resonance imaging: a systematic review and meta-analysis. Diagnostics (Basel) 2021;11:1763 
  50. Kwag M, Choi SH, Choi SJ, Byun JH, Won HJ, Shin YM. Simplified LI-RADS for hepatocellular carcinoma diagnosis at gadoxetic acid-enhanced MRI. Radiology 2022;305:614-622 
  51. Jang JK, Choi SH, Byun JH, Park SY, Lee SJ, Kim SY, et al. New strategy for liver imaging reporting and data system category M to improve diagnostic performance of MRI for hepatocellular carcinoma≤ 3.0 cm. Abdom Radiol (NY) 2022;47:2289-2298 
  52. Quaia E. State of the art: LI-RADS for contrast-enhanced US. Radiology 2019;293:4-14 
  53. Kang HJ, Lee JM, Yoon JH, Han JK. Role of contrast-enhanced ultrasound as a second-line diagnostic modality in noninvasive diagnostic algorithms for hepatocellular carcinoma. Korean J Radiol 2021;22:354-365 
  54. Shin J, Lee S, Bae H, Chung YE, Choi JY, Huh YM, et al. Contrast-enhanced ultrasound liver imaging reporting and data system for diagnosing hepatocellular carcinoma: a meta-analysis. Liver Int 2020;40:2345-2352 
  55. Park HJ, Choi BI, Lee ES, Park SB, Lee JB. How to differentiate borderline hepatic nodules in hepatocarcinogenesis: emphasis on imaging diagnosis. Liver Cancer 2017;6:189-203 
  56. Ohama H, Imai Y, Nakashima O, Kogita S, Takamura M, Hori M, et al. Images of Sonazoid-enhanced ultrasonography in multistep hepatocarcinogenesis: comparison with Gd-EOB-DTPA-enhanced MRI. J Gastroenterol 2014;49:1081-1093 
  57. Kudo M. Defect reperfusion imaging with sonazoidⓇ: a breakthrough in hepatocellular carcinoma. Liver Cancer 2016;5:1-7 
  58. King KG. Editorial comment: future incorporation of kupffer cell agents into contrast-enhanced ultrasound LI-RADS may increase sensitivity for HCC without compromising specificity. AJR Am J Roentgenol 2022;219:444 
  59. Kielar AZ, Chernyak V, Bashir MR, Do RK, Fowler KJ, Mitchell DG, et al. LI-RADS 2017: an update. J Magn Reson Imaging 2018;47:1459-1474 
  60. American College of Radiology. Liver imaging reporting and data system version 2014. Available at. http://www.acr.org/Quality-Safety/Resources/LIRADS. Accessed October 1, 2022