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Inter-reader reliability of contrast-enhanced ultrasound Liver Imaging Reporting and Data System: a meta-analysis

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Abstract

Purpose

To systematically determine the inter-reader reliability of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS), with emphasis on its major features for hepatocellular carcinoma (HCC) and LR-M (LI-RADS category M) features for non-HCC malignancy.

Methods

MEDLINE, EMBASE, and Cochrane databases were searched from January 2016 to March 2021 to identify original articles reporting the inter-reader reliability of CEUS LI-RADS. Meta-analytic pooled kappa values (κ) were calculated for major features [nonrim arterial-phase hyperenhancement (APHE), mild and late washout], LR-M features (rim APHE, early washout), and LI-RADS categorization using the DerSimonian-Laird random-effects model. Meta-regression analysis was performed to explore any causes of study heterogeneity.

Results

Twelve studies with a total of 2862 lesions were included. The meta-analytic pooled κ of nonrim APHE, mild and late washout, rim APHE, early washout, and LI-RADS categorization were 0.73 [95% confidence interval (CI), 0.67 − 0.79], 0.69 (95% CI, 0.54–0.84), 0.54 (95% CI, 0.37–0.71), 0.62 (95% CI, 0.45–0.79), and 0.75 (95% CI, 0.64–0.87), respectively. Compared with the major features, LR-M features had a lower meta-analytic pooled κ. Substantial study heterogeneity was noted in the LI-RADS categorization, and lesion size (p = 0.03) and the homogeneity in reader experience (p = 0.03) were significantly associated with study heterogeneity.

Conclusions

CEUS LI-RADS showed substantial inter-reader reliability for major features and LI-RADS categorization, but relatively lower reliability was found for LR-M features. In our opinion, the definitions of imaging features require further refinement to improve the inter-reader reliability of CEUS LI-RADS.

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Abbreviations

HCC:

Hepatocellular carcinoma

LI-RADS:

Liver Imaging Reporting and Data System

CEUS:

Contrast-enhanced ultrasound

CT:

Computed tomography

MRI:

Magnetic resonance imaging

APHE:

Arterial-phase hyperenhancement

κ :

Kappa value

CI:

Confidence interval

References

  1. Marrero JA, Kulik LM, Sirlin CB, et al. (2018) Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases. Hepatology 68:723-750. https://doi.org/10.1002/hep.29913.

    Article  PubMed  Google Scholar 

  2. Mitchell DG, Bruix J, Sherman M, Sirlin CB (2015) LI-RADS (Liver Imaging Reporting and Data System): summary, discussion, and consensus of the LI-RADS Management Working Group and future directions. Hepatology 61:1056-1065. https://doi.org/10.1002/hep.27304.

    Article  PubMed  Google Scholar 

  3. Wilson SR, Lyshchik A, Piscaglia F, et al. (2018) CEUS LI-RADS: algorithm, implementation, and key differences from CT/MRI. Abdom Radiol (NY) 43:127-142. https://doi.org/10.1007/s00261-017-1250-0.

    Article  Google Scholar 

  4. American College of Radiology (2021) CEUS LI-RADS v2017 core. https://www.acr.org/-/media/ACR/Files/RADS/LI-RADS/CEUS-LI-RADS-2017-Core.pdf. Accessed 31 March 2021.

  5. Shin J, Lee S, Bae H, et al. (2020) Contrast-enhanced ultrasound Liver Imaging Reporting and Data System for diagnosing hepatocellular carcinoma: a meta-analysis. Liver Int 40:2345-2352. https://doi.org/10.1111/liv.14617.

    Article  PubMed  Google Scholar 

  6. Son JH, Choi SH, Kim SY, et al. (2020) Accuracy of contrast-enhanced ultrasound Liver Imaging Reporting and Data System: a systematic review and meta-analysis. Hepatol Int 14:1104-1113. https://doi.org/10.1007/s12072-020-10102-5.

    Article  PubMed  Google Scholar 

  7. Li J, Chen M, Wang ZJ, et al. (2020) Interobserver agreement for contrast-enhanced ultrasound of Liver Imaging Reporting and Data System: a systematic review and meta-analysis. World J Clin Cases 8:5589-5602. https://doi.org/10.12998/wjcc.v8.i22.5589.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Li J, Ling W, Chen S, et al. (2019) The interreader agreement and validation of contrast-enhanced ultrasound Liver Imaging Reporting and Data System. Eur J Radiol 120:108685. https://doi.org/10.1016/j.ejrad.2019.108685.

    Article  PubMed  Google Scholar 

  9. Terzi E, Iavarone M, Pompili M, et al. (2018) Contrast ultrasound LI-RADS LR-5 identifies hepatocellular carcinoma in cirrhosis in a multicenter restropective study of 1,006 nodules. J Hepatol 68:485-492. https://doi.org/10.1016/j.jhep.2017.11.007.

    Article  PubMed  Google Scholar 

  10. Kang HJ, Lee JM, Yoon JH, Han JK (2021) Role of contrast-enhanced ultrasound as a second-line diagnostic modality in noninvasive diagnostic algorithms for hepatocellular carcinoma. Korean J Radiol 22:354-365. https://doi.org/10.3348/kjr.2020.0973.

    Article  PubMed  Google Scholar 

  11. Kang HJ, Lee JM, Yoon JH, et al. (2020) Contrast-enhanced US with sulfur hexafluoride and perfluorobutane for the diagnosis of hepatocellular carcinoma in individuals with high risk. Radiology 297:108-116. https://doi.org/10.1148/radiol.2020200115.

    Article  PubMed  Google Scholar 

  12. Li W, Li L, Zhuang BW, et al. (2021) Inter-reader agreement of CEUS LI-RADS among radiologists with different levels of experience. Eur Radiol. https://doi.org/10.1007/s00330-021-07777-1.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Makoyeva A, Kim TK, Jang HJ, et al. (2020) Use of CEUS LI-RADS for the accurate diagnosis of nodules in patients at risk for hepatocellular carcinoma: a validation study. Radiol Imaging Cancer 2:e190014. https://doi.org/10.1148/rycan.2020190014.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Zhou H, Zhang C, Du L, et al. (2020) Contrast-enhanced ultrasound Liver Imaging Reporting and Data System in diagnosing hepatocellular carcinoma: diagnostic performance and interobserver agreement. Ultraschall Med. https://doi.org/10.1055/a-1168-6321.

    Article  PubMed  Google Scholar 

  15. Stroup DF, Berlin JA, Morton SC, et al. (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 283:2008-2012. https://doi.org/10.1001/jama.283.15.2008.

    Article  CAS  PubMed  Google Scholar 

  16. Liberati A, Altman DG, Tetzlaff J, et al. (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ 339:b2700. https://doi.org/10.1136/bmj.b2700.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Moher D, Liberati A, Tetzlaff J, et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339:b2535. https://doi.org/10.1136/bmj.b2535.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Kottner J, Audige L, Brorson S, et al. (2011) Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed. J Clin Epidemiol 64:96-106. https://doi.org/10.1016/j.jclinepi.2010.03.002.

    Article  PubMed  Google Scholar 

  19. IntHout J, Ioannidis JP, Borm GF (2014) The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method. BMC Med Res Methodol 14:25. https://doi.org/10.1186/1471-2288-14-25.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159-174.

    Article  CAS  PubMed  Google Scholar 

  21. Higgins JP, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327:557-560. https://doi.org/10.1136/bmj.327.7414.557.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Ling W, Wang M, Ma X, et al. (2018) The preliminary application of Liver Imaging Reporting and Data System (LI-RADS) with contrast-enhanced ultrasound (CEUS) on small hepatic nodules (</= 2cm). J Cancer 9:2946-2952. https://doi.org/10.7150/jca.25539.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Schellhaas B, Pfeifer L, Kielisch C, et al. (2018) Interobserver agreement for contrast-enhanced ultrasound (CEUS)-based standardized algorithms for the diagnosis of hepatocellular carcinoma in high-risk patients. Ultraschall Med 39:667-674. https://doi.org/10.1055/a-0612-7887.

    Article  PubMed  Google Scholar 

  24. Tan Z, Teoh WC, Wong KM, et al. (2020) Analysis of comparative performance of CEUS and CECT/MR LI-RADS classification: Can CEUS dichotomize LI-RADS indeterminate lesions on CT or MRI? Clin Imaging 62:63-68. https://doi.org/10.1016/j.clinimag.2020.02.002.

    Article  PubMed  Google Scholar 

  25. Wang JY, Feng SY, Xu JW, et al. (2020) Usefulness of the contrast-enhanced ultrasound Liver Imaging Reporting and Data System in diagnosing focal liver lesions by inexperienced radiologists. J Ultrasound Med 39:1537-1546. https://doi.org/10.1002/jum.15242.

    Article  PubMed  Google Scholar 

  26. Wang JY, Feng SY, Yi AJ, et al. (2020) Comparison of contrast-enhanced ultrasound versus contrast-enhanced magnetic resonance imaging for the diagnosis of focal liver lesions using the Liver Imaging Reporting and Data System. Ultrasound Med Biol 46:1216-1223. https://doi.org/10.1016/j.ultrasmedbio.2020.01.023.

    Article  PubMed  Google Scholar 

  27. Kang JH, Choi SH, Lee JS, et al. (2020) Interreader agreement of Liver Imaging Reporting and Data System on MRI: a systematic review and meta-analysis. J Magn Reson Imaging 52:795-804. https://doi.org/10.1002/jmri.27065.

    Article  PubMed  Google Scholar 

  28. Kang JH, Choi SH, Lee JS, et al. (2021) Inter-reader reliability of CT Liver Imaging Reporting and Data System according to imaging analysis methodology: a systematic review and meta-analysis. Eur Radiol. https://doi.org/10.1007/s00330-021-07815-y.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Schellhaas B, Hammon M, Strobel D, et al. (2018) 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 28:4254-4264. https://doi.org/10.1007/s00330-018-5379-1.

    Article  PubMed  Google Scholar 

  30. Jang HJ, Kim TK, Burns PN, Wilson SR (2007) Enhancement patterns of hepatocellular carcinoma at contrast-enhanced US: comparison with histologic differentiation. Radiology 244:898-906. https://doi.org/10.1148/radiol.2443061520.

    Article  PubMed  Google Scholar 

  31. Grimm LJ, Anderson AL, Baker JA, et al. (2015) Interobserver variability between breast imagers using the fifth edition of the BI-RADS MRI lexicon. AJR Am J Roentgenol 204:1120–1124. https://doi.org/10.2214/ajr.14.13047.

    Article  PubMed  Google Scholar 

  32. Greer MD, Shih JH, Lay N, et al. (2019) Interreader variability of Prostate Imaging Reporting and Data System version 2 in detecting and assessing prostate cancer lesions at prostate MRI. AJR Am J Roentgenol 212:1197-1205. https://doi.org/10.2214/ajr.18.20536.

    Article  Google Scholar 

  33. Park KJ, Choi SH, Lee JS, et al. (2020) Interreader agreement with Prostate Imaging Reporting and Data System version 2 for prostate cancer detection: a systematic review and meta-analysis. J Urol 204:661-670. https://doi.org/10.1097/ju.0000000000001200.

    Article  PubMed  Google Scholar 

  34. Bartolotta TV, Taibbi A, Midiri M, Lagalla R (2019) Contrast-enhanced ultrasound of hepatocellular carcinoma: where do we stand? Ultrasonography 38:200-214. https://doi.org/10.14366/usg.18060.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Stevens WR, Gulino SP, Batts KP, et al. (1996) Mosaic pattern of hepatocellular carcinoma: histologic basis for a characteristic CT appearance. J Comput Assist Tomogr 20:337-342. https://doi.org/10.1097/00004728-199605000-00001.

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Sang Hyun Choi.

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Kang, J.H., Choi, S.H., Lee, J.S. et al. Inter-reader reliability of contrast-enhanced ultrasound Liver Imaging Reporting and Data System: a meta-analysis. Abdom Radiol 46, 4671–4681 (2021). https://doi.org/10.1007/s00261-021-03169-7

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