Article Search
검색
검색 팝업 닫기

Metrics

Help

  • 1. Aims and Scope

    Gut and Liver is an international journal of gastroenterology, focusing on the gastrointestinal tract, liver, biliary tree, pancreas, motility, and neurogastroenterology. Gut atnd Liver delivers up-to-date, authoritative papers on both clinical and research-based topics in gastroenterology. The Journal publishes original articles, case reports, brief communications, letters to the editor and invited review articles in the field of gastroenterology. The Journal is operated by internationally renowned editorial boards and designed to provide a global opportunity to promote academic developments in the field of gastroenterology and hepatology. +MORE

  • 2. Editorial Board

    Editor-in-Chief + MORE

    Editor-in-Chief
    Yong Chan Lee Professor of Medicine
    Director, Gastrointestinal Research Laboratory
    Veterans Affairs Medical Center, Univ. California San Francisco
    San Francisco, USA

    Deputy Editor

    Deputy Editor
    Jong Pil Im Seoul National University College of Medicine, Seoul, Korea
    Robert S. Bresalier University of Texas M. D. Anderson Cancer Center, Houston, USA
    Steven H. Itzkowitz Mount Sinai Medical Center, NY, USA
  • 3. Editorial Office
  • 4. Articles
  • 5. Instructions for Authors
  • 6. File Download (PDF version)
  • 7. Ethical Standards
  • 8. Peer Review

    All papers submitted to Gut and Liver are reviewed by the editorial team before being sent out for an external peer review to rule out papers that have low priority, insufficient originality, scientific flaws, or the absence of a message of importance to the readers of the Journal. A decision about these papers will usually be made within two or three weeks.
    The remaining articles are usually sent to two reviewers. It would be very helpful if you could suggest a selection of reviewers and include their contact details. We may not always use the reviewers you recommend, but suggesting reviewers will make our reviewer database much richer; in the end, everyone will benefit. We reserve the right to return manuscripts in which no reviewers are suggested.

    The final responsibility for the decision to accept or reject lies with the editors. In many cases, papers may be rejected despite favorable reviews because of editorial policy or a lack of space. The editor retains the right to determine publication priorities, the style of the paper, and to request, if necessary, that the material submitted be shortened for publication.

Search

Search

Year

to

Article Type

Online first

Split Viewer

Online first

Diagnostic Performance of LI-RADS v2018 versus KLCA-NCC 2018 Criteria for Hepatocellular Carcinoma Using Magnetic Resonance Imaging with Hepatobiliary Agent: A Systematic Review and Meta-Analysis of Comparative Studies

Jaeseung Shin1 , Sunyoung Lee2 , Ja Kyung Yoon2 , Won Jeong Son3 , Yun Ho Roh3 , Yong Eun Chung2 , Jin-Young Choi2 , Mi-Suk Park2

1Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 2Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, and 3Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea

Correspondence to: Sunyoung Lee
ORCID https://orcid.org/0000-0002-6893-3136
E-mail carnival0126@gmail.com

Received: March 22, 2022; Revised: June 12, 2022; Accepted: June 21, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Gut Liver.

Published online November 1, 2022

Copyright © Gut and Liver.

Background/Aims: To compare the performance of the Liver Imaging Reporting and Data System (LI-RADS) v2018 and Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) 2018 criteria for diagnosing hepatocellular carcinoma (HCC) using magnetic resonance imaging (MRI) with hepatobiliary agent (HBA).
Methods: We searched the MEDLINE and EMBASE for studies from January 1, 2018, to October 20, 2021, that compared the diagnostic performance of two imaging criteria on HBA-MRI. A bivariate random-effects model was fitted to calculate the per-observation sensitivity and specificity, and the estimates of paired data were compared. Subgroup analysis was performed based on the observation size. Meta-regression analysis was also performed for study heterogeneity.
Results: Of the six studies included, the pooled sensitivity of the definite HCC category of the KLCA-NCC criteria (82%; 95% confidence interval [CI], 74% to 90%; I2=84%) was higher than that of LR-5 of LI-RADS v2018 (65%; 95% CI, 52% to 77%; I2=96%) for diagnosing HCC (p<0.001), while the specificity was lower for KLCA-NCC criteria (87%; 95% CI, 84% to 91%; I2=0%) than LI-RADS v2018 (93%; 95% CI, 91% to 96%; I2=0%) (p=0.017). For observations sized ≥20 mm, the sensitivity was higher for KLCA-NCC 2018 than for LI-RADS v2018 (84% vs 74%, p=0.012), with no significant difference in specificity (81% vs 85%, p=0.451). The reference standard was a significant factor contributing to the heterogeneity of sensitivities.
Conclusions: The definite HCC category of KLCA-NCC 2018 provided a higher sensitivity and lower specificity than the LR-5 of LI-RADS v2018 for diagnosing HCC using MRI with HBA.

Keywords: Liver neoplasms, Magnetic resonance imaging, Contrast media, Diagnosis, Sensitivity and specificity

Hepatocellular carcinoma (HCC) accounts for the largest proportion of primary hepatic malignancy.1 In clinical practice, noninvasive diagnosis of HCC can be performed in patients at high risk for HCC using medical imaging without pathologic confirmation based on the imaging criteria for diagnosing HCC proposed by several international organizations.2-4 Although these HCC diagnoses are based on a combination of arterial phase hyperenhancement and washout appearance, there are considerable differences in the diagnostic algorithms and detailed definitions of imaging findings across the guidelines, which are largely attributable to the varied prevalence of and treatment approaches for HCC in different geographic regions.5

The Liver Imaging Reporting and Data System (LI-RADS) is a primary diagnostic system which is used worldwide to standardize the interpretation, reporting, and data collection of liver imaging in high-risk patients for HCC.6 Updated in 2018, LI-RADS v2018 was fully integrated into 2018 HCC Practice Guidance by the American Association for the Study of Liver Disease.4,6 LI-RADS was designed to maximize specificity over sensitivity, reflecting clinical management in the United States, where liver transplantation is a common treatment option for early stage HCC.5 Meanwhile, the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) established and revised the KLCA-NCC practice guidelines in 2018 based on data from an Asian, and more specifically, Korean population that exhibits epidemiological and clinical characteristics of HCC, which are very distinct from those of the Western population.3 The KLCA-NCC 2018 practice guideline adopted a non-binary system, categorizing hepatic observations as either indeterminate, probable HCC, or definite HCC after applying the exclusion criteria, such as marked T2 hyperintensity for benign lesions or a targetoid appearance for non-HCC malignancies.3 In contrast to LI-RADS, the KLCA-NCC guidelines focus on the early detection and treatment of HCC with higher sensitivity, as surgical resection and locoregional therapies are more common curative options for HCC in Asian countries.3,5,6

Several meta-analyses have reported on the diagnostic performance of either LI-RADS or KLCA-NCC for diagnosis of HCC;7,8 however, evidence for a direct comparison of the two imaging criteria is lacking. Moreover, several comparative studies have not reached consistent conclusion whether the two imaging criteria differ in their specificity on diagnosing HCC.9-14 Therefore, in the present study, we performed a meta-analysis to compare the performance of LR-5 (i.e., definitely HCC) of LI-RADS v2018 and definite HCC category of KLCA-NCC 2018 criteria to diagnose HCC with contrast-enhanced magnetic resonance imaging (MRI) using hepatobiliary agent (HBA) in high-risk patients using direct comparative studies.

We conducted the present meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies statement.15 This study was registered on the International Prospective Register of Systematic Reviews, PROSPERO (CRD42021277532).

1. Literature search

Computerized searches in the MEDLINE and EMBASE databases were conducted to identify original studies published in English reporting the performance of the LI-RADS v2018 and KLCA-NCC 2018 criteria for diagnosing HCC using MRI. The search was limited to articles published between January 01, 2018, and October 20, 2021, as the present study aimed to compare the performance of LI-RADS v2018 and KLCA-NCC criteria which were updated in 2018. The detailed search term and strategy utilized in the present study are provided in Supplementary Table 1.

2. Study selection

After removing duplicate articles, the articles’ potential eligibility were reviewed as follows: (1) population: patients with risk for HCC; (2) index test: liver MRI with dynamic contrast enhancement using HBA; (3) reference standard: histopathologic diagnosis or composite clinical reference standard (CCRS); (4) diagnostic performance of HCC diagnosis according to the LI-RADS v2018 and KLCA-NCC 2018 criteria; and (5) study design: only direct comparative studies with intra-individual paired comparisons between LR-5 of LI-RADS v2018 and definite HCC category of KLCA-NCC 2018 criteria. Studies were excluded based on the following criteria: (1) studies published only as abstracts, case reports, reviews, animal studies, commentaries, or letters; (2) studies without sufficient information on the diagnostic performance of both imaging criteria and reference standard findings; and (3) studies not within the field of interest. Two independent reviewers (J Shin and JK Yoon, both with 6-year-experience in liver imaging) screened articles by title and abstract and then reviewed the relevant full-text articles. Discrepancies were re-evaluated and confirmed a consensus decision with another reviewer (S Lee, 10-year-experience in liver imaging).

3. Data extraction

Reviewers extracted the following information from the eligible studies: (1) study characteristics, such as author(s), nation, year of publication, types of study design (cohort or case-control, retrospective or prospective), and subject enrollment (selective or consecutive); (2) characteristics of study population (the number of patients, age, sex, and dominant risk factor for HCC); (3) MRI magnet field strength (1.5 or 3 T); (4) reference standards (pathology with CCRS or explanted liver only); and (5) image review methods, including consensus or independent review. If a study reported more than one dataset (e.g., more than one reviewer), the data across all reviewers were averaged. Data extraction was also conducted by the independent reviewers (J Shin and JK Yoon), and disagreements were resolved by the third reviewer (S Lee).

4. Risk of bias and quality assessment

The risk of bias and applicability of the included study were assessed according to the Quality Assessment of Diagnostic Accuracy Studies-2 criteria, which includes four domains: (1) patient and observation selection, (2) index test, (3) reference standard, and (4) flow and timing.16

5. Statistical analysis

For this meta-analysis of comparative studies involving the LI-RADS v2018 and KLCA-NCC 2018 criteria in the same patients (intra-individual design), the bivariate random-effects model was fitted to evaluate the paired sensitivity and specificity for diagnosis of HCC. The pooled sensitivities and specificities of the two imaging criteria were compared using a random-effects model for sensitivity, considering only the correlation for these paired data.17,18 Heterogeneity was evaluated using the Cochran's Q test (p-value) with p<0.10, or the Higgins index (I2), with I2 >50% considered to indicate presence of significant heterogeneity in the study. Linked receiver operating characteristic plots and forest plots were utilized to show the results of the paired studies. We also performed subgroup analyses based on the size of observations (10–19 mm or ≥20 mm). Meta-regression analyses were performed to investigate the potential factors for study heterogeneity. Assessment of publication bias was conducted by funnel plot asymmetry (visual evaluation) and with the Egger’s test. PROC NLMIXED was utilized for all bivariate analyses in SAS version 9.4 (SAS Institute, Cary, NC, USA), while R version 4.0.1 (R Foundation for Statistical Computing, Vienna, Austria) was utilized to analyze heterogeneity and publication bias. p-value less than 0.05 was considered to be statistically significant, except in regard to determining heterogeneity among the studies.

1. Study selection

Of the 39 initially selected studies, 29 were screened by title and abstract after removing duplicates, 10 of which were considered eligible for the full-text review. Four studies were excluded after the full-text review, leaving six eligible for full data inclusion.9-14 The six included studies included 1,409 HCCs among a total of 2,023 observations. Fig. 1 shows a flow diagram of the study selection. We summarized the characteristics of the included studies in Table 1. The methodological quality assessed using Quality Assessment of Diagnostic Accuracy Studies-2 is presented in Supplementary Fig. 1.

Table 1. Summary Characteristics of the Included Primary Studies

Author (year)NationStudy designStudy
type
Subject
enrollment
No. of
patients
Age, yrMen (%)Dominant
etiology
MRI field
strength (T)
Reference standardReviewer
Byun et al. (2020)9KoreaRCohortCons40060 (33–86)*81HBV1.5 or 3Pathology or CCRSIndependent review then, use consensus data
Lee et al. (2020)10KoreaRCohortCons20257±970HBV3Pathology or CCRSIndependent review then, use consensus data
Jeon et al. (2020)11KoreaRCohortCons8154±9 (26–72)83HBV1.5 or 3Explanted liver onlyIndependent review then, use consensus data
Hwang et al. (2021)12KoreaRCohortCons17758 (32–80)*80HBV3Pathology or CCRSIndependent review
Lee et al. (2021)13KoreaRCohortCons38759±1079HBV1.5 or 3Pathology or CCRSIndependent review then, use consensus data
Park et al. (2021)14KoreaRCohortCons38656±1076HBV1.5 or 3Pathology or CCRSIndependent review

R, retrospective; Cons, consecutive; MRI, magnetic resonance imaging; HBV, hepatitis B virus; CCRS, composite clinical reference standard.

*Median (range); Mean±SD; Mean±SD (range).


Figure 1.Flow diagram of study selection.

2. The pooled diagnostic performance of the LI-RADS v2018 and the KLCA-NCC 2018 criteria

The sensitivity and specificity for diagnosing HCC (per-observation) on MRI were 65% (95% confidence interval [CI], 52% to 77%; I2=96%; p<0.001) and 93% (95% CI, 91% to 96%; I2=0%; p=0.873), respectively, for LR-5 in LI-RADS v2018 (Fig. 2A) and 82% (95% CI, 74% to 90%; I2=84%; p<0.001) and 87% (95% CI, 84% to 91%; I2=0%; p=0.579), respectively, for the definite HCC category in KLCA-NCC 2018 criteria (Fig. 2B). The sensitivity of LI-RADS v2018 was lower than that of the KLCA-NCC 2018 (65% vs 82%, p<0.001), while the specificity of LI-RADS v2018 was higher than that of the KLCA-NCC 2018 (93% vs 87%, p=0.017). The linked receiver operating characteristic plot is shown in Fig. 3.

Figure 2.Forest plots of the sensitivity and specificity for diagnosing hepatocellular carcinoma (HCC) with (A) the LR-5 category of the LI-RADS v2018; and (B) the definite HCC category of the KLCA-NCC 2018 criteria.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval.
Figure 3.Linked receiver operating characteristic plot.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center.

3. Subgroup analysis

Forest plots based on the size of observations are shown in Fig. 4. For observations sized ≥20 mm, the sensitivity and specificity (per-observation) of LR-5 of LI-RADS v2018 for diagnosis of HCC on HBA-MRI were 74% (95% CI, 65% to 83%) and 85% (95% CI, 76% to 94%), respectively, whereas those for the definite HCC category in KLCA-NCC 2018 criteria were 84% (95% CI, 78% to 91%) and 81% (95% CI, 72% to 91%), respectively. The sensitivity of LI-RADS v2018 was lower than that of the KLCA-NCC 2018 (74% vs 84%, p=0.012), while any significant difference was not found for the pooled specificity between the two imaging criteria for observations sized ≥20 mm (85% vs 81%, p=0.451).

Figure 4.Forest plots of the sensitivities and specificities for diagnosing hepatocellular carcinoma (HCC) with (A) the LR-5 category of the LI-RADS with observation size ≥20 mm; (B) the LR-5 category with observation size 10–19 mm; (C) the definite HCC category of the KLCA-NCC 2018 criteria with observation size ≥20 mm; and (D) the definite HCC category of KLCA-NCC 2018 criteria with observation size 10–19 mm.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval.

For observations sized 10–19 mm, the per-observation sensitivity and specificity of LR-5 of LI-RADS v2018 for diagnosis of HCC on HBA-MRI were 55% (95% CI, 35% to 74%) and 96% (95% CI, 93% to 99%), respectively, whereas those for the definite HCC category of KLCA-NCC 2018 criteria were 81% (95% CI, 68% to 93%) and 90% (95% CI, 85% to 94%), respectively. The sensitivity of LI-RADS v2018 was lower than that of the KLCA-NCC 2018 (55% vs 81%, p=0.002), whereas the specificity of LI-RADS v2018 was higher than that of the KLCA-NCC 2018 for observations sized 10–19 mm (96% vs 90%, p=0.034).

4. Meta-regression analysis

Among the three included covariates (reviewer, reference standard, and MRI field strength), the reference standard for HCC (pathology or CCRS vs explanted liver only) was the only factor that significantly contributed to the heterogeneity of the sensitivities for both imaging criteria (Table 2). Sensitivity was higher for studies using pathology or CCRS than for those using explanted liver only (LI-RADS v2018, 70% vs 35%, p<0.001; KLCA-NCC 2018, 84% vs 66%, p<0.001).

Table 2. Meta-Regression Analysis of Two Imaging Diagnostic Criteria for Diagnosing Hepatocellular Carcinoma

VariableLI-RADS v2018KLCA-NCC 2018 criteria
Sensitivity, % (95% CI)p-valueSpecificity, % (95% CI)p-valueSensitivity, % (95% CI)p-valueSpecificity, % (95% CI)p-value
Reviewer0.8000.6730.3820.728
Independent review (n=2)67 (58–75)94 (89–96)85 (81–88)87 (82–91)
Consensus (n=4)63 (43–80)95 (90–97)80 (70–87)89 (83–93)
Reference standard<0.0010.365<0.0010.380
Pathology or CCRS (n=5)70 (63–76)94 (91–95)84 (81–86)87 (84–90)
Explanted liver only (n=1)35 (26–44)97 (84–99)66 (56–74)92 (78–97)
MRI field strength0.9260.9090.8960.580
3T only (n=2)66 (59–71)94 (89–97)82 (75–88)91 (80–96)
1.5T or 3T (n=4)64 (43–81)95 (90–97)82 (72–88)87 (83–91)

LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval; CCRS, composite clinical reference standard; MRI, magnetic resonance imaging.



5. Publication bias

There was no significant publication bias for either imaging diagnostic criterion across the studies (LI-RADS v2018, p=0.498; KLCA-NCC 2018 criteria, p=0.969) (Supplementary Fig. 2).

For the meta-analysis of direct comparative studies (with intra-individual paired comparison of two diagnostic criteria for HCC using HBA-MRI), the present study demonstrated that the definite HCC category in KLCA-NCC 2018 criteria provides higher per-observation sensitivity than the LR-5 in LI-RADS v2018 (82% vs 65%, respectively), while the per-observation specificity of KLCA-NCC 2018 was lower than that the specificity of LI-RADS v2018 (87% vs 93%, respectively). However, for observations sized ≥20 mm, the KLCA-NCC 2018 criteria revealed higher sensitivity than LI-RADS v2018 (84% vs 74%, respectively), but the specificity was comparable for both criteria (81% vs 85%, respectively).

Our meta-analysis demonstrated higher sensitivity for the HCC diagnosis on HBA-MRI using the KLCA-NCC 2018 criteria than using LI-RADS v2018. The expanded definition of washout to the transitional or hepatobiliary phase in the KLCA-NCC 2018 criteria is primarily responsible for this higher sensitivity,3 compared to the definition of washout appearance only in the portal venous phase by LI-RADS v2018 using HBA-MRI.6 The diagnostic criteria with higher sensitivity are more suitable for Eastern countries where early diagnosis and early treatment of HCC, including surgical resection and locoregional therapy, are preferable. However, at the expense of higher sensitivity, the KLCA-NCC 2018 criteria showed lower specificity than the LI-RADS v2018, which is due to the basic trade-off relationship between the two diagnostic test measures. Interestingly, for observations sized >20 mm, the KLCA-NCC 2018 criteria showed higher sensitivity, although we found no significant difference in the specificities between the two imaging criteria, which could be evidence that the KLCA-NCC 2018 criteria might be more preferable for Eastern populations than the LI-RADS v2018.

Significant heterogeneity in sensitivity was identified in the six included studies for both imaging criteria. Meta-regression analysis showed that the pooled sensitivities using any of both imaging criteria were higher for studies based on the pathology or CCRS than for those based on explanted liver only. In one study,11 the study population comprised patients with focal liver lesions who underwent liver transplantation. Therefore, selection bias could be introduced in these specific inclusion criteria (e.g., pathology results from explanted liver only), compared with other studies that included patients at high risk of HCC.

The present study had several limitations. First, only six primary studies were eligible for our meta-analysis of direct comparative studies within the same participants. Although fewer studies were included in the present design, this approach is preferred to avoid potential bias and confusion that could arise from indirect comparisons of non-comparative primary studies.19,20 Second, substantial heterogeneity in sensitivity was noted among studies using both imaging criteria, which made it difficult to obtain robust meta-analytic estimates. To explore potential sources that influence heterogeneity, we conducted a meta-regression analysis, which revealed that the selected reference standard was a significant factor. Third, all six studies included were conducted in South Korea and utilized a retrospective design, potentially introducing a major methodological limitation and higher risk of selection bias. In particular, as hepatitis B is the predominant underlying etiology for HCC in South Korea, the results of our meta-analysis cannot be generalized to countries where factors other than hepatitis B virus are predominant, such as the United States. Finally, a subgroup analysis based on contrast agents was not able to be conducted, as most of the studies, with the exception of one, reported the diagnostic performance of both imaging criteria with MRI using only HBA.10

In conclusion, the definite HCC category in KLCA-NCC 2018 provided a higher per-observation sensitivity, but lower per-observation specificity than the LR-5 in LI-RADS v2018 for diagnosing HCC using MRI with HBA. However, for observations sized ≥20 mm, the KLCA-NCC 2018 criteria showed a higher sensitivity, while there is no significant decrease in specificity, than LI-RADS v2018.

No potential conflict of interest relevant to this article was reported.

Study concept and design: J.S., S.L. Acquisition of data: J.S., J.K.Y., S.L. Analysis and interpretation of data: J.S., S.L. Drafting of the manuscript: J.S. Critical revision of the manuscript for important intellectual content: S.L., Y.E.C., J.Y.C., M.S.P. Statistical analysis: W.J.S., Y.H.R. Study supervision: S.L. All authors approved the final version of manuscript.

  1. Asrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. J Hepatol 2019;70:151-171.
    Pubmed CrossRef
  2. EASL Clinical Practice Guidelines: management of hepatocellular carcinoma. J Hepatol 2018;69:182-236.
    Pubmed CrossRef
  3. 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.
    Pubmed KoreaMed CrossRef
  4. Marrero JA, Kulik LM, Sirlin CB, 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.
    Pubmed CrossRef
  5. Kim TH, Kim SY, Tang A, Lee JM. Comparison of international guidelines for noninvasive diagnosis of hepatocellular carcinoma: 2018 update. Clin Mol Hepatol 2019;25:245-263.
    Pubmed KoreaMed CrossRef
  6. American College of Radiology. CT/MRI Liver Imaging Reporting and Data System (LI-RADS) version 2018 [Internet]. Reston: American College of Radiology; c2018 [cited 2022 Feb 15].
    Available from: https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS/LI-RADS-CT-MRI--v2018.
  7. Lee S, Kim YY, Shin J, 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.
    Pubmed CrossRef
  8. 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.
    Pubmed KoreaMed CrossRef
  9. Byun J, Choi SH, Byun JH, 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.
    Pubmed CrossRef
  10. 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.
    Pubmed KoreaMed CrossRef
  11. 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.
    Pubmed CrossRef
  12. 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.
    Pubmed CrossRef
  13. 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.
    Pubmed KoreaMed CrossRef
  14. Park SH, Shim YS, Kim B, 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.
    Pubmed CrossRef
  15. McInnes M, Moher D, Thombs BD, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA Statement. JAMA 2018;319:388-396.
    Pubmed CrossRef
  16. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529-536.
    Pubmed CrossRef
  17. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 2005;58:982-990.
    Pubmed CrossRef
  18. van Houwelingen HC, Arends LR, Stijnen T. Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med 2002;21:589-624.
    Pubmed CrossRef
  19. Takwoingi Y, Leeflang MM, Deeks JJ. Empirical evidence of the importance of comparative studies of diagnostic test accuracy. Ann Intern Med 2013;158:544-554.
    Pubmed CrossRef
  20. Dehmoobad Sharifabadi A, Leeflang M, Treanor L, et al. Comparative reviews of diagnostic test accuracy in imaging research: evaluation of current practices. Eur Radiol 2019;29:5386-5394.
    Pubmed CrossRef

Article

ahead

Gut and Liver

Published online November 1, 2022

Copyright © Gut and Liver.

Diagnostic Performance of LI-RADS v2018 versus KLCA-NCC 2018 Criteria for Hepatocellular Carcinoma Using Magnetic Resonance Imaging with Hepatobiliary Agent: A Systematic Review and Meta-Analysis of Comparative Studies

Jaeseung Shin1 , Sunyoung Lee2 , Ja Kyung Yoon2 , Won Jeong Son3 , Yun Ho Roh3 , Yong Eun Chung2 , Jin-Young Choi2 , Mi-Suk Park2

1Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 2Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, and 3Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea

Correspondence to:Sunyoung Lee
ORCID https://orcid.org/0000-0002-6893-3136
E-mail carnival0126@gmail.com

Received: March 22, 2022; Revised: June 12, 2022; Accepted: June 21, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background/Aims: To compare the performance of the Liver Imaging Reporting and Data System (LI-RADS) v2018 and Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) 2018 criteria for diagnosing hepatocellular carcinoma (HCC) using magnetic resonance imaging (MRI) with hepatobiliary agent (HBA).
Methods: We searched the MEDLINE and EMBASE for studies from January 1, 2018, to October 20, 2021, that compared the diagnostic performance of two imaging criteria on HBA-MRI. A bivariate random-effects model was fitted to calculate the per-observation sensitivity and specificity, and the estimates of paired data were compared. Subgroup analysis was performed based on the observation size. Meta-regression analysis was also performed for study heterogeneity.
Results: Of the six studies included, the pooled sensitivity of the definite HCC category of the KLCA-NCC criteria (82%; 95% confidence interval [CI], 74% to 90%; I2=84%) was higher than that of LR-5 of LI-RADS v2018 (65%; 95% CI, 52% to 77%; I2=96%) for diagnosing HCC (p<0.001), while the specificity was lower for KLCA-NCC criteria (87%; 95% CI, 84% to 91%; I2=0%) than LI-RADS v2018 (93%; 95% CI, 91% to 96%; I2=0%) (p=0.017). For observations sized ≥20 mm, the sensitivity was higher for KLCA-NCC 2018 than for LI-RADS v2018 (84% vs 74%, p=0.012), with no significant difference in specificity (81% vs 85%, p=0.451). The reference standard was a significant factor contributing to the heterogeneity of sensitivities.
Conclusions: The definite HCC category of KLCA-NCC 2018 provided a higher sensitivity and lower specificity than the LR-5 of LI-RADS v2018 for diagnosing HCC using MRI with HBA.

Keywords: Liver neoplasms, Magnetic resonance imaging, Contrast media, Diagnosis, Sensitivity and specificity

INTRODUCTION

Hepatocellular carcinoma (HCC) accounts for the largest proportion of primary hepatic malignancy.1 In clinical practice, noninvasive diagnosis of HCC can be performed in patients at high risk for HCC using medical imaging without pathologic confirmation based on the imaging criteria for diagnosing HCC proposed by several international organizations.2-4 Although these HCC diagnoses are based on a combination of arterial phase hyperenhancement and washout appearance, there are considerable differences in the diagnostic algorithms and detailed definitions of imaging findings across the guidelines, which are largely attributable to the varied prevalence of and treatment approaches for HCC in different geographic regions.5

The Liver Imaging Reporting and Data System (LI-RADS) is a primary diagnostic system which is used worldwide to standardize the interpretation, reporting, and data collection of liver imaging in high-risk patients for HCC.6 Updated in 2018, LI-RADS v2018 was fully integrated into 2018 HCC Practice Guidance by the American Association for the Study of Liver Disease.4,6 LI-RADS was designed to maximize specificity over sensitivity, reflecting clinical management in the United States, where liver transplantation is a common treatment option for early stage HCC.5 Meanwhile, the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) established and revised the KLCA-NCC practice guidelines in 2018 based on data from an Asian, and more specifically, Korean population that exhibits epidemiological and clinical characteristics of HCC, which are very distinct from those of the Western population.3 The KLCA-NCC 2018 practice guideline adopted a non-binary system, categorizing hepatic observations as either indeterminate, probable HCC, or definite HCC after applying the exclusion criteria, such as marked T2 hyperintensity for benign lesions or a targetoid appearance for non-HCC malignancies.3 In contrast to LI-RADS, the KLCA-NCC guidelines focus on the early detection and treatment of HCC with higher sensitivity, as surgical resection and locoregional therapies are more common curative options for HCC in Asian countries.3,5,6

Several meta-analyses have reported on the diagnostic performance of either LI-RADS or KLCA-NCC for diagnosis of HCC;7,8 however, evidence for a direct comparison of the two imaging criteria is lacking. Moreover, several comparative studies have not reached consistent conclusion whether the two imaging criteria differ in their specificity on diagnosing HCC.9-14 Therefore, in the present study, we performed a meta-analysis to compare the performance of LR-5 (i.e., definitely HCC) of LI-RADS v2018 and definite HCC category of KLCA-NCC 2018 criteria to diagnose HCC with contrast-enhanced magnetic resonance imaging (MRI) using hepatobiliary agent (HBA) in high-risk patients using direct comparative studies.

MATERIALS AND METHODS

We conducted the present meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies statement.15 This study was registered on the International Prospective Register of Systematic Reviews, PROSPERO (CRD42021277532).

1. Literature search

Computerized searches in the MEDLINE and EMBASE databases were conducted to identify original studies published in English reporting the performance of the LI-RADS v2018 and KLCA-NCC 2018 criteria for diagnosing HCC using MRI. The search was limited to articles published between January 01, 2018, and October 20, 2021, as the present study aimed to compare the performance of LI-RADS v2018 and KLCA-NCC criteria which were updated in 2018. The detailed search term and strategy utilized in the present study are provided in Supplementary Table 1.

2. Study selection

After removing duplicate articles, the articles’ potential eligibility were reviewed as follows: (1) population: patients with risk for HCC; (2) index test: liver MRI with dynamic contrast enhancement using HBA; (3) reference standard: histopathologic diagnosis or composite clinical reference standard (CCRS); (4) diagnostic performance of HCC diagnosis according to the LI-RADS v2018 and KLCA-NCC 2018 criteria; and (5) study design: only direct comparative studies with intra-individual paired comparisons between LR-5 of LI-RADS v2018 and definite HCC category of KLCA-NCC 2018 criteria. Studies were excluded based on the following criteria: (1) studies published only as abstracts, case reports, reviews, animal studies, commentaries, or letters; (2) studies without sufficient information on the diagnostic performance of both imaging criteria and reference standard findings; and (3) studies not within the field of interest. Two independent reviewers (J Shin and JK Yoon, both with 6-year-experience in liver imaging) screened articles by title and abstract and then reviewed the relevant full-text articles. Discrepancies were re-evaluated and confirmed a consensus decision with another reviewer (S Lee, 10-year-experience in liver imaging).

3. Data extraction

Reviewers extracted the following information from the eligible studies: (1) study characteristics, such as author(s), nation, year of publication, types of study design (cohort or case-control, retrospective or prospective), and subject enrollment (selective or consecutive); (2) characteristics of study population (the number of patients, age, sex, and dominant risk factor for HCC); (3) MRI magnet field strength (1.5 or 3 T); (4) reference standards (pathology with CCRS or explanted liver only); and (5) image review methods, including consensus or independent review. If a study reported more than one dataset (e.g., more than one reviewer), the data across all reviewers were averaged. Data extraction was also conducted by the independent reviewers (J Shin and JK Yoon), and disagreements were resolved by the third reviewer (S Lee).

4. Risk of bias and quality assessment

The risk of bias and applicability of the included study were assessed according to the Quality Assessment of Diagnostic Accuracy Studies-2 criteria, which includes four domains: (1) patient and observation selection, (2) index test, (3) reference standard, and (4) flow and timing.16

5. Statistical analysis

For this meta-analysis of comparative studies involving the LI-RADS v2018 and KLCA-NCC 2018 criteria in the same patients (intra-individual design), the bivariate random-effects model was fitted to evaluate the paired sensitivity and specificity for diagnosis of HCC. The pooled sensitivities and specificities of the two imaging criteria were compared using a random-effects model for sensitivity, considering only the correlation for these paired data.17,18 Heterogeneity was evaluated using the Cochran's Q test (p-value) with p<0.10, or the Higgins index (I2), with I2 >50% considered to indicate presence of significant heterogeneity in the study. Linked receiver operating characteristic plots and forest plots were utilized to show the results of the paired studies. We also performed subgroup analyses based on the size of observations (10–19 mm or ≥20 mm). Meta-regression analyses were performed to investigate the potential factors for study heterogeneity. Assessment of publication bias was conducted by funnel plot asymmetry (visual evaluation) and with the Egger’s test. PROC NLMIXED was utilized for all bivariate analyses in SAS version 9.4 (SAS Institute, Cary, NC, USA), while R version 4.0.1 (R Foundation for Statistical Computing, Vienna, Austria) was utilized to analyze heterogeneity and publication bias. p-value less than 0.05 was considered to be statistically significant, except in regard to determining heterogeneity among the studies.

RESULTS

1. Study selection

Of the 39 initially selected studies, 29 were screened by title and abstract after removing duplicates, 10 of which were considered eligible for the full-text review. Four studies were excluded after the full-text review, leaving six eligible for full data inclusion.9-14 The six included studies included 1,409 HCCs among a total of 2,023 observations. Fig. 1 shows a flow diagram of the study selection. We summarized the characteristics of the included studies in Table 1. The methodological quality assessed using Quality Assessment of Diagnostic Accuracy Studies-2 is presented in Supplementary Fig. 1.

Table 1 . Summary Characteristics of the Included Primary Studies.

Author (year)NationStudy designStudy
type
Subject
enrollment
No. of
patients
Age, yrMen (%)Dominant
etiology
MRI field
strength (T)
Reference standardReviewer
Byun et al. (2020)9KoreaRCohortCons40060 (33–86)*81HBV1.5 or 3Pathology or CCRSIndependent review then, use consensus data
Lee et al. (2020)10KoreaRCohortCons20257±970HBV3Pathology or CCRSIndependent review then, use consensus data
Jeon et al. (2020)11KoreaRCohortCons8154±9 (26–72)83HBV1.5 or 3Explanted liver onlyIndependent review then, use consensus data
Hwang et al. (2021)12KoreaRCohortCons17758 (32–80)*80HBV3Pathology or CCRSIndependent review
Lee et al. (2021)13KoreaRCohortCons38759±1079HBV1.5 or 3Pathology or CCRSIndependent review then, use consensus data
Park et al. (2021)14KoreaRCohortCons38656±1076HBV1.5 or 3Pathology or CCRSIndependent review

R, retrospective; Cons, consecutive; MRI, magnetic resonance imaging; HBV, hepatitis B virus; CCRS, composite clinical reference standard..

*Median (range); Mean±SD; Mean±SD (range)..


Figure 1. Flow diagram of study selection.

2. The pooled diagnostic performance of the LI-RADS v2018 and the KLCA-NCC 2018 criteria

The sensitivity and specificity for diagnosing HCC (per-observation) on MRI were 65% (95% confidence interval [CI], 52% to 77%; I2=96%; p<0.001) and 93% (95% CI, 91% to 96%; I2=0%; p=0.873), respectively, for LR-5 in LI-RADS v2018 (Fig. 2A) and 82% (95% CI, 74% to 90%; I2=84%; p<0.001) and 87% (95% CI, 84% to 91%; I2=0%; p=0.579), respectively, for the definite HCC category in KLCA-NCC 2018 criteria (Fig. 2B). The sensitivity of LI-RADS v2018 was lower than that of the KLCA-NCC 2018 (65% vs 82%, p<0.001), while the specificity of LI-RADS v2018 was higher than that of the KLCA-NCC 2018 (93% vs 87%, p=0.017). The linked receiver operating characteristic plot is shown in Fig. 3.

Figure 2. Forest plots of the sensitivity and specificity for diagnosing hepatocellular carcinoma (HCC) with (A) the LR-5 category of the LI-RADS v2018; and (B) the definite HCC category of the KLCA-NCC 2018 criteria.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval.
Figure 3. Linked receiver operating characteristic plot.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center.

3. Subgroup analysis

Forest plots based on the size of observations are shown in Fig. 4. For observations sized ≥20 mm, the sensitivity and specificity (per-observation) of LR-5 of LI-RADS v2018 for diagnosis of HCC on HBA-MRI were 74% (95% CI, 65% to 83%) and 85% (95% CI, 76% to 94%), respectively, whereas those for the definite HCC category in KLCA-NCC 2018 criteria were 84% (95% CI, 78% to 91%) and 81% (95% CI, 72% to 91%), respectively. The sensitivity of LI-RADS v2018 was lower than that of the KLCA-NCC 2018 (74% vs 84%, p=0.012), while any significant difference was not found for the pooled specificity between the two imaging criteria for observations sized ≥20 mm (85% vs 81%, p=0.451).

Figure 4. Forest plots of the sensitivities and specificities for diagnosing hepatocellular carcinoma (HCC) with (A) the LR-5 category of the LI-RADS with observation size ≥20 mm; (B) the LR-5 category with observation size 10–19 mm; (C) the definite HCC category of the KLCA-NCC 2018 criteria with observation size ≥20 mm; and (D) the definite HCC category of KLCA-NCC 2018 criteria with observation size 10–19 mm.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval.

For observations sized 10–19 mm, the per-observation sensitivity and specificity of LR-5 of LI-RADS v2018 for diagnosis of HCC on HBA-MRI were 55% (95% CI, 35% to 74%) and 96% (95% CI, 93% to 99%), respectively, whereas those for the definite HCC category of KLCA-NCC 2018 criteria were 81% (95% CI, 68% to 93%) and 90% (95% CI, 85% to 94%), respectively. The sensitivity of LI-RADS v2018 was lower than that of the KLCA-NCC 2018 (55% vs 81%, p=0.002), whereas the specificity of LI-RADS v2018 was higher than that of the KLCA-NCC 2018 for observations sized 10–19 mm (96% vs 90%, p=0.034).

4. Meta-regression analysis

Among the three included covariates (reviewer, reference standard, and MRI field strength), the reference standard for HCC (pathology or CCRS vs explanted liver only) was the only factor that significantly contributed to the heterogeneity of the sensitivities for both imaging criteria (Table 2). Sensitivity was higher for studies using pathology or CCRS than for those using explanted liver only (LI-RADS v2018, 70% vs 35%, p<0.001; KLCA-NCC 2018, 84% vs 66%, p<0.001).

Table 2 . Meta-Regression Analysis of Two Imaging Diagnostic Criteria for Diagnosing Hepatocellular Carcinoma.

VariableLI-RADS v2018KLCA-NCC 2018 criteria
Sensitivity, % (95% CI)p-valueSpecificity, % (95% CI)p-valueSensitivity, % (95% CI)p-valueSpecificity, % (95% CI)p-value
Reviewer0.8000.6730.3820.728
Independent review (n=2)67 (58–75)94 (89–96)85 (81–88)87 (82–91)
Consensus (n=4)63 (43–80)95 (90–97)80 (70–87)89 (83–93)
Reference standard<0.0010.365<0.0010.380
Pathology or CCRS (n=5)70 (63–76)94 (91–95)84 (81–86)87 (84–90)
Explanted liver only (n=1)35 (26–44)97 (84–99)66 (56–74)92 (78–97)
MRI field strength0.9260.9090.8960.580
3T only (n=2)66 (59–71)94 (89–97)82 (75–88)91 (80–96)
1.5T or 3T (n=4)64 (43–81)95 (90–97)82 (72–88)87 (83–91)

LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval; CCRS, composite clinical reference standard; MRI, magnetic resonance imaging..



5. Publication bias

There was no significant publication bias for either imaging diagnostic criterion across the studies (LI-RADS v2018, p=0.498; KLCA-NCC 2018 criteria, p=0.969) (Supplementary Fig. 2).

DISCUSSION

For the meta-analysis of direct comparative studies (with intra-individual paired comparison of two diagnostic criteria for HCC using HBA-MRI), the present study demonstrated that the definite HCC category in KLCA-NCC 2018 criteria provides higher per-observation sensitivity than the LR-5 in LI-RADS v2018 (82% vs 65%, respectively), while the per-observation specificity of KLCA-NCC 2018 was lower than that the specificity of LI-RADS v2018 (87% vs 93%, respectively). However, for observations sized ≥20 mm, the KLCA-NCC 2018 criteria revealed higher sensitivity than LI-RADS v2018 (84% vs 74%, respectively), but the specificity was comparable for both criteria (81% vs 85%, respectively).

Our meta-analysis demonstrated higher sensitivity for the HCC diagnosis on HBA-MRI using the KLCA-NCC 2018 criteria than using LI-RADS v2018. The expanded definition of washout to the transitional or hepatobiliary phase in the KLCA-NCC 2018 criteria is primarily responsible for this higher sensitivity,3 compared to the definition of washout appearance only in the portal venous phase by LI-RADS v2018 using HBA-MRI.6 The diagnostic criteria with higher sensitivity are more suitable for Eastern countries where early diagnosis and early treatment of HCC, including surgical resection and locoregional therapy, are preferable. However, at the expense of higher sensitivity, the KLCA-NCC 2018 criteria showed lower specificity than the LI-RADS v2018, which is due to the basic trade-off relationship between the two diagnostic test measures. Interestingly, for observations sized >20 mm, the KLCA-NCC 2018 criteria showed higher sensitivity, although we found no significant difference in the specificities between the two imaging criteria, which could be evidence that the KLCA-NCC 2018 criteria might be more preferable for Eastern populations than the LI-RADS v2018.

Significant heterogeneity in sensitivity was identified in the six included studies for both imaging criteria. Meta-regression analysis showed that the pooled sensitivities using any of both imaging criteria were higher for studies based on the pathology or CCRS than for those based on explanted liver only. In one study,11 the study population comprised patients with focal liver lesions who underwent liver transplantation. Therefore, selection bias could be introduced in these specific inclusion criteria (e.g., pathology results from explanted liver only), compared with other studies that included patients at high risk of HCC.

The present study had several limitations. First, only six primary studies were eligible for our meta-analysis of direct comparative studies within the same participants. Although fewer studies were included in the present design, this approach is preferred to avoid potential bias and confusion that could arise from indirect comparisons of non-comparative primary studies.19,20 Second, substantial heterogeneity in sensitivity was noted among studies using both imaging criteria, which made it difficult to obtain robust meta-analytic estimates. To explore potential sources that influence heterogeneity, we conducted a meta-regression analysis, which revealed that the selected reference standard was a significant factor. Third, all six studies included were conducted in South Korea and utilized a retrospective design, potentially introducing a major methodological limitation and higher risk of selection bias. In particular, as hepatitis B is the predominant underlying etiology for HCC in South Korea, the results of our meta-analysis cannot be generalized to countries where factors other than hepatitis B virus are predominant, such as the United States. Finally, a subgroup analysis based on contrast agents was not able to be conducted, as most of the studies, with the exception of one, reported the diagnostic performance of both imaging criteria with MRI using only HBA.10

In conclusion, the definite HCC category in KLCA-NCC 2018 provided a higher per-observation sensitivity, but lower per-observation specificity than the LR-5 in LI-RADS v2018 for diagnosing HCC using MRI with HBA. However, for observations sized ≥20 mm, the KLCA-NCC 2018 criteria showed a higher sensitivity, while there is no significant decrease in specificity, than LI-RADS v2018.

SUPPLEMENTARY MATERIALS

Supplementary materials can be accessed at https://doi.org/10.5009/gnl220115.

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS

Study concept and design: J.S., S.L. Acquisition of data: J.S., J.K.Y., S.L. Analysis and interpretation of data: J.S., S.L. Drafting of the manuscript: J.S. Critical revision of the manuscript for important intellectual content: S.L., Y.E.C., J.Y.C., M.S.P. Statistical analysis: W.J.S., Y.H.R. Study supervision: S.L. All authors approved the final version of manuscript.

Fig 1.

Figure 1.Flow diagram of study selection.
Gut and Liver 2022; :

Fig 2.

Figure 2.Forest plots of the sensitivity and specificity for diagnosing hepatocellular carcinoma (HCC) with (A) the LR-5 category of the LI-RADS v2018; and (B) the definite HCC category of the KLCA-NCC 2018 criteria.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval.
Gut and Liver 2022; :

Fig 3.

Figure 3.Linked receiver operating characteristic plot.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center.
Gut and Liver 2022; :

Fig 4.

Figure 4.Forest plots of the sensitivities and specificities for diagnosing hepatocellular carcinoma (HCC) with (A) the LR-5 category of the LI-RADS with observation size ≥20 mm; (B) the LR-5 category with observation size 10–19 mm; (C) the definite HCC category of the KLCA-NCC 2018 criteria with observation size ≥20 mm; and (D) the definite HCC category of KLCA-NCC 2018 criteria with observation size 10–19 mm.
LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval.
Gut and Liver 2022; :

Table 1 Summary Characteristics of the Included Primary Studies

Author (year)NationStudy designStudy
type
Subject
enrollment
No. of
patients
Age, yrMen (%)Dominant
etiology
MRI field
strength (T)
Reference standardReviewer
Byun et al. (2020)9KoreaRCohortCons40060 (33–86)*81HBV1.5 or 3Pathology or CCRSIndependent review then, use consensus data
Lee et al. (2020)10KoreaRCohortCons20257±970HBV3Pathology or CCRSIndependent review then, use consensus data
Jeon et al. (2020)11KoreaRCohortCons8154±9 (26–72)83HBV1.5 or 3Explanted liver onlyIndependent review then, use consensus data
Hwang et al. (2021)12KoreaRCohortCons17758 (32–80)*80HBV3Pathology or CCRSIndependent review
Lee et al. (2021)13KoreaRCohortCons38759±1079HBV1.5 or 3Pathology or CCRSIndependent review then, use consensus data
Park et al. (2021)14KoreaRCohortCons38656±1076HBV1.5 or 3Pathology or CCRSIndependent review

R, retrospective; Cons, consecutive; MRI, magnetic resonance imaging; HBV, hepatitis B virus; CCRS, composite clinical reference standard.

*Median (range); Mean±SD; Mean±SD (range).


Table 2 Meta-Regression Analysis of Two Imaging Diagnostic Criteria for Diagnosing Hepatocellular Carcinoma

VariableLI-RADS v2018KLCA-NCC 2018 criteria
Sensitivity, % (95% CI)p-valueSpecificity, % (95% CI)p-valueSensitivity, % (95% CI)p-valueSpecificity, % (95% CI)p-value
Reviewer0.8000.6730.3820.728
Independent review (n=2)67 (58–75)94 (89–96)85 (81–88)87 (82–91)
Consensus (n=4)63 (43–80)95 (90–97)80 (70–87)89 (83–93)
Reference standard<0.0010.365<0.0010.380
Pathology or CCRS (n=5)70 (63–76)94 (91–95)84 (81–86)87 (84–90)
Explanted liver only (n=1)35 (26–44)97 (84–99)66 (56–74)92 (78–97)
MRI field strength0.9260.9090.8960.580
3T only (n=2)66 (59–71)94 (89–97)82 (75–88)91 (80–96)
1.5T or 3T (n=4)64 (43–81)95 (90–97)82 (72–88)87 (83–91)

LI-RADS, Liver Imaging Reporting and Data System; KLCA-NCC, Korean Liver Cancer Association-National Cancer Center; CI, confidence interval; CCRS, composite clinical reference standard; MRI, magnetic resonance imaging.


References

  1. Asrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. J Hepatol 2019;70:151-171.
    Pubmed CrossRef
  2. EASL Clinical Practice Guidelines: management of hepatocellular carcinoma. J Hepatol 2018;69:182-236.
    Pubmed CrossRef
  3. 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.
    Pubmed KoreaMed CrossRef
  4. Marrero JA, Kulik LM, Sirlin CB, 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.
    Pubmed CrossRef
  5. Kim TH, Kim SY, Tang A, Lee JM. Comparison of international guidelines for noninvasive diagnosis of hepatocellular carcinoma: 2018 update. Clin Mol Hepatol 2019;25:245-263.
    Pubmed KoreaMed CrossRef
  6. American College of Radiology. CT/MRI Liver Imaging Reporting and Data System (LI-RADS) version 2018 [Internet]. Reston: American College of Radiology; c2018 [cited 2022 Feb 15]. Available from: https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS/LI-RADS-CT-MRI--v2018.
  7. Lee S, Kim YY, Shin J, 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.
    Pubmed CrossRef
  8. 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.
    Pubmed KoreaMed CrossRef
  9. Byun J, Choi SH, Byun JH, 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.
    Pubmed CrossRef
  10. 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.
    Pubmed KoreaMed CrossRef
  11. 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.
    Pubmed CrossRef
  12. 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.
    Pubmed CrossRef
  13. 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.
    Pubmed KoreaMed CrossRef
  14. Park SH, Shim YS, Kim B, 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.
    Pubmed CrossRef
  15. McInnes M, Moher D, Thombs BD, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA Statement. JAMA 2018;319:388-396.
    Pubmed CrossRef
  16. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529-536.
    Pubmed CrossRef
  17. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 2005;58:982-990.
    Pubmed CrossRef
  18. van Houwelingen HC, Arends LR, Stijnen T. Advanced methods in meta-analysis: multivariate approach and meta-regression. Stat Med 2002;21:589-624.
    Pubmed CrossRef
  19. Takwoingi Y, Leeflang MM, Deeks JJ. Empirical evidence of the importance of comparative studies of diagnostic test accuracy. Ann Intern Med 2013;158:544-554.
    Pubmed CrossRef
  20. Dehmoobad Sharifabadi A, Leeflang M, Treanor L, et al. Comparative reviews of diagnostic test accuracy in imaging research: evaluation of current practices. Eur Radiol 2019;29:5386-5394.
    Pubmed CrossRef
Gut and Liver

Vol.16 No.6
November, 2022

pISSN 1976-2283
eISSN 2005-1212

qrcode
qrcode

Supplementary

Share this article on :

  • line

Popular Keywords

Gut and LiverQR code Download
qr-code

Editorial Office