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LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis

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收录情况： ◇ SCIE

作者：
Haben Dawit[1,2] * ; Eric Lam[3] ; Matthew D. F. McInnes[2,4] ; Christian B. van der Pol[5] ; Mustafa R. Bashir[6,7] ; Jean-Paul Salameh[2,8] ; Brooke Levis[9] ; Claude B. Sirlin[10] ; Victoria Chernyak[11] ; Sang Hyun Choi[12] ; So Yeon Kim[12] ; Tyler J. Fraum[13] ; An Tang[14] ; Hanyu Jiang[15] ; Bin Song[15] ; Jin Wang[16] ; Stephanie R. Wilson[17] ; Heejin Kwon[18] ; Andrea S. Kierans[19] ; Ijin Joo[20] ; Maxime Ronot[21,22] ; Ji Soo Song[23] ; Joanna Podgórska[24] ; Grzegorz Rosiak[24] ; Zhen Kang[25] ; Brian C. Allen[6] ; Andreu F. Costa[26] ;
机构： [1]Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada [2]Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada [3]Ottawa Hospital Research Institute, Ottawa, Ontario, Canada [4]Department of Radiology, University of Ottawa, Ottawa, Ontario, Canada [5]Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada [6]Department of Radiology , Duke University Medical Center, Durham, NC [7]Center for Advanced Magnetic Resonance Development ,Duke University Medical Center, Durham, NC [8]Faculty of Health Sciences, Queen’s University, Kingston, Ontario, Canada [9]Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada [10]Liver Imaging Group, Department of Radiology, University of California–San Diego, San Diego, Calif [11]Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY [12]Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea [13]Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo [14]Department of Radiology, Centre Hospitalier de l’Université de Montréal, Montreal, Quebec, Canada [15]Department of Radiology, West China Hospital, Sichuan University, Chengdu, China [16]Department of Radiology, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China [17]University of Calgary Foothills Medical Centre, Calgary, Alberta, Canada [18]Department of Radiology, Dong-A University Hospital, Dong-A University College of Medicine, Busan, Republic of Korea [19]Weill Cornell Medical Center, New York, NY [20]Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea [21]Department of Radiology, Assistance Publique– H.pitaux de Paris, Nord, Université Paris Cité, CRI UMR 1149, Paris, France [22]H.pital Beaujon, Clichy, France [23]Department of Radiology, Chonbuk National University Medical School and Hospital, Jeonju, Republic of Korea [24]Second Radiology Department, Warsaw Medical University, Warsaw, Poland [25]Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China [26]Department of Diagnostic Radiology, Queen Elizabeth II Health Sciences Centre and Dalhousie University, Victoria General Building, 3rd Fl, 1276 S Park St, Halifax, NS, Canada B3H 2Y9
出处：
DOI： 10.1148/radiol.231501
ISSN：

摘要：
Background The independent contribution of each Liver Imaging Reporting and Data System (LI-RADS) CT or MRI ancillary feature (AF) has not been established. Purpose To evaluate the association of LI-RADS AFs with hepatocellular carcinoma (HCC) and malignancy while adjusting for LI-RADS major features through an individual participant data (IPD) meta-analysis. Materials and Methods Medline, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched from January 2014 to January 2022 for studies evaluating the diagnostic accuracy of CT and MRI for HCC using LI-RADS version 2014, 2017, or 2018. Using a one-step approach, IPD across studies were pooled. Adjusted odds ratios (ORs) and 95% CIs were derived from multivariable logistic regression models of each AF combined with major features except threshold growth (excluded because of infrequent reporting). Liver observation clustering was addressed at the study and participant levels through random intercepts. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2. Results Twenty studies comprising 3091 observations (2456 adult participants; mean age, 59 years ± 11 [SD]; 1849 [75.3%] men) were included. In total, 89% (eight of nine) of AFs favoring malignancy were associated with malignancy and/or HCC, 80% (four of five) of AFs favoring HCC were associated with HCC, and 57% (four of seven) of AFs favoring benignity were negatively associated with HCC and/or malignancy. Nonenhancing capsule (OR = 3.50 [95% CI: 1.53, 8.01]) had the strongest association with HCC. Diffusion restriction (OR = 14.45 [95% CI: 9.82, 21.27]) and mild-moderate T2 hyperintensity (OR = 10.18 [95% CI: 7.17, 14.44]) had the strongest association with malignancy. The strongest negative associations with HCC were parallels blood pool enhancement (OR = 0.07 [95% CI: 0.01, 0.49]) and marked T2 hyperintensity (OR = 0.18 [95% CI: 0.07, 0.45]). Seventeen studies (85%) had a high risk of bias. Conclusion Most LI-RADS AFs were independently associated with HCC, malignancy, or benignity as intended when adjusting for major features. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Crivellaro in this issue.

基金：
This international collaborative project was made possible through funding from the following sources: Joan Sealy Trust for Cancer Research, Canadian Institutes of Health Research (grant 469052), RSNA Research Scholar Grant, and Queen Elizabeth II Graduate Scholarship in Science and Technology. A.T. supported by Fonds de Recherche du Québec–Santé and Fondation de l’Association des Radiologistes du Québec (grant 298509). H. J. supported by the National Natural Science Foundation of China (grant 82101997) and the China Postdoctoral Science Foundation (grant 2023T160448). B.S. supported by National Natural Science Foundation of China (grant U22A20343), and the 1.3.5 Project for Disciplines of Excellence at West China Hospital, Sichuan University (grants ZYJC21012 and ZYGD22004).
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大类 | 1 区 医学
小类 | 1 区 核医学
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Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子： 最新[2023版] 最新五年平均 出版当年[2023版] 出版当年五年平均 出版前一年[2023版]

第一作者：
第一作者机构： [1]Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada [2]Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
通讯作者：
推荐引用方式(GB/T 7714)：
Haben Dawit,Eric Lam,Matthew D. F. McInnes,et al.LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis[J].RADIOLOGY.2024,310(2):e231501.doi:10.1148/radiol.231501.
APA：
Haben Dawit,Eric Lam,Matthew D. F. McInnes,Christian B. van der Pol,Mustafa R. Bashir...&Andreu F. Costa.(2024).LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis.RADIOLOGY,310,(2)
MLA：
Haben Dawit,et al."LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis".RADIOLOGY 310..2(2024):e231501

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