Is concurrent LR-5 associated with a higher rate of hepatocellular carcinoma in LR-3 or LR-4 observations? An individual participant data meta-analysis.
Concurrent
Hepatocellular carcinoma
LI-RADS
LR-3
LR-4
Positive predictive value
Journal
Abdominal radiology (New York)
ISSN: 2366-0058
Titre abrégé: Abdom Radiol (NY)
Pays: United States
ID NLM: 101674571
Informations de publication
Date de publication:
27 Sep 2024
27 Sep 2024
Historique:
received:
22
07
2024
accepted:
09
09
2024
revised:
09
09
2024
medline:
28
9
2024
pubmed:
28
9
2024
entrez:
27
9
2024
Statut:
aheadofprint
Résumé
The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations. To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis. Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x . Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis. The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.
Sections du résumé
BACKGROUND
BACKGROUND
The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.
PURPOSE
OBJECTIVE
To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.
METHODS
METHODS
Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x . Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).
RESULTS
RESULTS
Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.
CONCLUSION
CONCLUSIONS
The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.
Identifiants
pubmed: 39333410
doi: 10.1007/s00261-024-04580-6
pii: 10.1007/s00261-024-04580-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIH HHS
ID : U01 CA271887
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA283935
Pays : United States
Organisme : the European Union - FESR or FSE, PON Research and Innovation
ID : DM 1062/2021
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Singal AG, Kanwal F, Llovet JM. Global trends in hepatocellular carcinoma epidemiology: implications for screening, prevention and therapy. Nature Reviews Clinical Oncology. 2023;20(12):864-84.
pubmed: 37884736
doi: 10.1038/s41571-023-00825-3
Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians. 2024;74(3):229-63.
pubmed: 38572751
Llovet JM, Kelley RK, Villanueva A, Singal AG, Pikarsky E, Roayaie S, et al. Hepatocellular carcinoma. Nature Reviews Disease Primers. 2021;7(1):6.
pubmed: 33479224
doi: 10.1038/s41572-020-00240-3
Balogh J, Victor D, Asham EH, Burroughs SG, Boktour M, Saharia A, et al. Hepatocellular carcinoma: a review. Journal of Hepatocellular Carcinoma. 2016;3(null):41-53.
pubmed: 27785449
pmcid: 5063561
doi: 10.2147/JHC.S61146
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(3):816-30.
pubmed: 30251931
doi: 10.1148/radiol.2018181494
van der Pol CB, Lim CS, Sirlin CB, McGrath TA, Salameh J-P, 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(4):976-86.
pubmed: 30445016
doi: 10.1053/j.gastro.2018.11.020
Lee T-H, Hirshman N, Cardona DM, Berg CL, Fowler KJ, Bashir MR, et al. LR-3 and LR-4 Lesions Are More Likely to Be Hepatocellular Carcinoma in Transplant Patients with LR-5 or LR–TR Lesions. Digestive Diseases and Sciences. 2022;67:5345 - 52.
pubmed: 35257246
doi: 10.1007/s10620-022-07428-5
Smereka P, Doshi AM, Lavelle LP, Shanbhogue K. New Arterial Phase Enhancing Nodules on MRI of Cirrhotic Liver: Risk of Progression to Hepatocellular Carcinoma and Implications for LI-RADS Classification. AJR Am J Roentgenol. 2020;215(2):382-9.
pubmed: 32432909
doi: 10.2214/AJR.19.22033
Slaughter DP, Southwick HW, Smejkal W. “Field cancerization” in oral stratified squamous epithelium. Clinical implications of multicentric origin. Cancer. 1953;6(5):963-8.
pubmed: 13094644
Lochhead P, Chan AT, Nishihara R, Fuchs CS, Beck AH, Giovannucci E, et al. Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression. Modern Pathology. 2015;28(1):14-29.
pubmed: 24925058
doi: 10.1038/modpathol.2014.81
Ranathunga D, Osman H, Islam N, McInnes MDF, Munir J, Pol CBvd, et al. Progression Rates of LR-2 and LR-3 Observations on MRI to Higher LI-RADS Categories in Patients at High Risk of Hepatocellular Carcinoma: A Retrospective Study. American Journal of Roentgenology. 2022;218(3):462-70.
pubmed: 34643108
doi: 10.2214/AJR.21.26376
Goins SM, Jiang H, Pol CBvd, Salameh J-P, Lam E, Adamo RG, et al. Individual Participant Data Meta-Analysis of LR-5 in LI-RADS Version 2018 versus Revised LI-RADS for Hepatocellular Carcinoma Diagnosis. Radiology. 2023;309(3):e231656.
pubmed: 38112549
doi: 10.1148/radiol.231656
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(2):326-35.
pubmed: 34783596
doi: 10.1148/radiol.2021211244
Goins SM, Jiang H, van der Pol CB, Salameh JP, Lam E, Adamo RG, et al. Comparative performance of 2018 LI-RADS versus Modified LIRADS (mLI-RADS): An Individual Participant Data Meta-Analysis. J Magn Reson Imaging. 2024;60(3):1082-91.
Deeks JJ BP, Leeflang MM, Takwoingi Y (editors). . Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy. Version 2.0 (updated July 2023). Cochrane2023.
McInnes MDF, Moher D, Thombs BD, McGrath TA, Bossuyt PM, Clifford T, et al. Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement. Jama. 2018;319(4):388-96.
pubmed: 29362800
doi: 10.1001/jama.2017.19163
American College of Radiology Liver Reporting and Data System (LI-RADS). .
Kambadakone AR, Fung A, Gupta RT, Hope TA, Fowler KJ, Lyshchik A, et al. LI-RADS technical requirements for CT, MRI, and contrast-enhanced ultrasound. Abdom Radiol (NY). 2018;43(1):56-74.
pubmed: 28940042
doi: 10.1007/s00261-017-1325-y
Riley RD, Levis B, Takwoingi Y. IPD Meta-Analysis for Test Accuracy Research. Individual Participant Data Meta‐Analysis2021. p. 387-420.
doi: 10.1002/9781119333784.ch15
Cohen JF, Deeks JJ, Hooft L, Salameh JP, Korevaar DA, Gatsonis C, et al. Preferred reporting items for journal and conference abstracts of systematic reviews and meta-analyses of diagnostic test accuracy studies (PRISMA-DTA for Abstracts): checklist, explanation, and elaboration. Bmj. 2021;372:n265.
pubmed: 33722791
pmcid: 7957862
doi: 10.1136/bmj.n265
Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software. 2015;67(1):1 - 48.
doi: 10.18637/jss.v067.i01
Kanneganti M, Marrero JA, Parikh ND, Kanwal F, Yokoo T, Mendiratta-Lala M, et al. Clinical outcomes of patients with Liver Imaging Reporting and Data System 3 or Liver Imaging Reporting and Data System 4 observations in patients with cirrhosis: A systematic review. Liver Transpl. 2022;28(12):1865-75.
pubmed: 35980600
pmcid: 9669163
doi: 10.1002/lt.26562
De Muzio F, Grassi F, Dell'Aversana F, Fusco R, Danti G, Flammia F, et al. A Narrative Review on LI-RADS Algorithm in Liver Tumors: Prospects and Pitfalls. Diagnostics (Basel). 2022;12(7).
Mettikanont P, Kalluri A, Bittermann T, Phillips N, Loza BL, Rosen M, et al. The Course of LIRADS 3 and 4 Hepatic Abnormalities as Correlated With Explant Pathology: A Single Center Experience. J Clin Exp Hepatol. 2022;12(4):1048-56.
pubmed: 35814502
pmcid: 9257948
doi: 10.1016/j.jceh.2022.02.005
Singal AG, Llovet JM, Yarchoan M, Mehta N, Heimbach JK, Dawson LA, et al. AASLD Practice Guidance on prevention, diagnosis, and treatment of hepatocellular carcinoma. Hepatology. 2023;78(6).
Kim Y-Y, Choi J-Y, Kim SU, Lee M, Park M-S, Chung YE, et al. MRI Ancillary Features for LI-RADS Category 3 and 4 Observations: Improved Categorization to Indicate the Risk of Hepatic Malignancy. American Journal of Roentgenology. 2020;215(6):1354-62.
pubmed: 33052732
doi: 10.2214/AJR.20.22802
Alhasan A, Cerny M, Olivié D. LI-RADS for CT diagnosis of hepatocellular carcinoma: performance of major and ancillary features. Abdom Radiol. 2019;44(2):517-28.
doi: 10.1007/s00261-018-1762-2
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. American Journal of Roentgenology. 2018;210(6):1266-72.
pubmed: 29629800
doi: 10.2214/AJR.17.18981
Arvind A, Joshi S, Zaki T. Risk of Hepatocellular Carcinoma in Patients With Indeterminate (LI-RADS 3) Liver Observations. Clinical Gastroenterology and Hepatology. 2023;21(4):1091-3.
pubmed: 34902571
doi: 10.1016/j.cgh.2021.11.042
Cannella R, Dioguardi Burgio M, Beaufrère A. Imaging features of histological subtypes of hepatocellular carcinoma: Implication for LI-RADS. JHEP Reports. 2021;3(6).
doi: 10.1016/j.jhepr.2021.100380
Bartnik K, Podgórska J, Rosiak G, Korzeniowski K, Rowiński O. Inter-observer agreement using the LI-RADS version 2018 CT treatment response algorithm in patients with hepatocellular carcinoma treated with conventional transarterial chemoembolization. Abdom Radiol. 2022;47(1):115-22.
doi: 10.1007/s00261-021-03272-9
Cerny M, Bergeron C, Billiard JS. LI-RADS for MR Imaging Diagnosis of Hepatocellular Carcinoma: Performance of Major and Ancillary Features. Radiology. 2018;288(1):118-28.
pubmed: 29634435
doi: 10.1148/radiol.2018171678
Kim DH, Choi SH, Byun JH. Arterial subtraction images of gadoxetate-enhanced MRI improve diagnosis of early-stage hepatocellular carcinoma. Journal of Hepatology. 2019;71(3):534-42.
pubmed: 31108157
doi: 10.1016/j.jhep.2019.05.005
Lee C, Choi SH, Byun JH. Combined computed tomography and magnetic resonance imaging improves diagnosis of hepatocellular carcinoma ≤ 3.0 cm. Hepatol Int. 2021;15(3):676-84.
pubmed: 33956288
doi: 10.1007/s12072-021-10190-x
Choi JY, Ha J, Choi SH, Kang HJ, Kim SY, Kim KW. Comparison of gadoxetate disodium-enhanced MRI sequences for measuring hepatic observation size and its implication of LI-RADS classification. Abdom Radiol. 2022;47(3):1024-31.
doi: 10.1007/s00261-021-03403-2
Choi SJ, Choi SH, Kim DW. Value of threshold growth as a major diagnostic feature of hepatocellular carcinoma in LI-RADS. Journal of Hepatology. 2023;78(3):596-603.
pubmed: 36402451
doi: 10.1016/j.jhep.2022.11.006
Clarke CGD, Albazaz R, Smith CR. Comparison of LI-RADS with other non-invasive liver MRI criteria and radiological opinion for diagnosing hepatocellular carcinoma in cirrhotic livers using gadoxetic acid with histopathological explant correlation. Clinical Radiology. 2021;76(5):333-41.
pubmed: 33461746
doi: 10.1016/j.crad.2020.12.007
Cannella R, Vernuccio F, Sagreiya H. 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(7):3770-81.
pubmed: 32107603
doi: 10.1007/s00330-020-06698-9
Jiang H, Song B, Qin Y. Data‐Driven Modification of the LI‐RADS Major Feature System on Gadoxetate Disodium‐Enhanced MRI : Toward Better Sensitivity and Simplicity. Magnetic Resonance Imaging. 2022;55(2):493-506.
doi: 10.1002/jmri.27824
Ding J, Long L, Zhang X. Contrast-enhanced ultrasound LI-RADS 2017: comparison with CT/MRI LI-RADS. Eur Radiol. 2021;31(2):847-54.
pubmed: 32803416
doi: 10.1007/s00330-020-07159-z
Jeon SK, Joo I, Bae JS, Park SJ, Lee JM. LI-RADS v2018: how to appropriately use ancillary features in category adjustment from intermediate probability of malignancy (LR-3) to probably HCC (LR-4) on gadoxetic acid–enhanced MRI. Eur Radiol. 2022;32(1):46-55.
pubmed: 34132875
doi: 10.1007/s00330-021-08116-0
Kang HJ, Lee JM, Jeon SK. Intra-individual comparison of dual portal venous phases for non-invasive diagnosis of hepatocellular carcinoma at gadoxetic acid–enhanced liver MRI. Eur Radiol. 2021;31(2):824-33.
pubmed: 32845387
doi: 10.1007/s00330-020-07162-4
Kierans AS, Makkar J, Guniganti P. Validation of Liver Imaging Reporting and Data System 2017 (LI‐RADS) Criteria for Imaging Diagnosis of Hepatocellular Carcinoma. Magnetic Resonance Imaging. 2019;49(7).
Lim K, Kwon H, Cho J, Kim D, Kang E, Kim S. Added value of enhanced CT on LR-3 and LR-4 observation of Gd-EOB-DTPA MRI for the diagnosis of HCC: are CT and MR washout features interchangeable? BJR. 2022;95(1132).
doi: 10.1259/bjr.20210738
Min JH, Kim JM, Kim YK. A modified LI-RADS: targetoid tumors with enhancing capsule can be diagnosed as HCC instead of LR-M lesions. Eur Radiol. 2022;32(2):912-22.
pubmed: 34345947
doi: 10.1007/s00330-021-08124-0
Piñero F, Thompson MA, Diaz Telli F. LI-RADS 4 or 5 categorization may not be clinically relevant for decision-making processes: A prospective cohort study. Annals of Hepatology. 2020;19(6):662-7.
pubmed: 32683095
doi: 10.1016/j.aohep.2020.06.007
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. Journal of Hepatology. 2018;68(4):715-23.
pubmed: 29274407
doi: 10.1016/j.jhep.2017.12.014
Paisant A, Vilgrain V, Riou J. Comparison of extracellular and hepatobiliary MR contrast agents for the diagnosis of small HCCs. Journal of Hepatology. 2020;72(5):937-45.
pubmed: 31870951
doi: 10.1016/j.jhep.2019.12.011
Rosiak G, Podgorska J, Rosiak E, Cieszanowski A. Comparison of LI-RADS v.2017 and ESGAR Guidelines Imaging Criteria in HCC Diagnosis Using MRI with Hepatobiliary Contrast Agents. BioMed Research International. 2018;2018:1-6.
doi: 10.1155/2018/7465126
Seo N, Kim MS, Park MS. Optimal criteria for hepatocellular carcinoma diagnosis using CT in patients undergoing liver transplantation. Eur Radiol. 2019;29(2):1022-31.
pubmed: 29974221
doi: 10.1007/s00330-018-5557-1
Song JS, Choi EJ, Hwang SB, Hwang HP, Choi H. LI-RADS v2014 categorization of hepatocellular carcinoma: Intraindividual comparison between gadopentetate dimeglumine-enhanced MRI and gadoxetic acid-enhanced MRI. Eur Radiol. 2019;29(1):401-10.
pubmed: 29922928
doi: 10.1007/s00330-018-5559-z
Stocker D, Becker AS, Barth BK. Does quantitative assessment of arterial phase hyperenhancement and washout improve LI-RADS v2018–based classification of liver lesions? Eur Radiol. 2020;30(5):2922-33.
pubmed: 32020398
doi: 10.1007/s00330-019-06596-9
Pol CBvd, Dhindsa K, Shergill R, Zha N, Ferri M, Kagoma YK, et al. MRI LI-RADS Version 2018: Impact of and Reduction in Ancillary Features. American Journal of Roentgenology. 2021;216(4):935-42.
pubmed: 33534620
doi: 10.2214/AJR.20.23031
Wang W, Yang C, Zhu K, Yang L, Ding Y, Luo R, et al. Recurrence After Curative Resection of Hepatitis B Virus–Related Hepatocellular Carcinoma: Diagnostic Algorithms on Gadoxetic Acid–Enhanced Magnetic Resonance Imaging. Liver Transplantation. 2020;26(6):751-63.
pubmed: 31901208
doi: 10.1002/lt.25713
Zhang L, Kuang S, Chen J. The Role of Preoperative Dynamic Contrast-enhanced 3.0-T MR Imaging in Predicting Early Recurrence in Patients With Early-Stage Hepatocellular Carcinomas After Curative Resection. Front Oncol. 2019;9(1336).