Rationale and Objectives
To determine the accuracy of magnetic resonance imaging (MRI) with gadoxetic acid disodium for the detection of hepatocellular carcinoma (HCC).
Materials and Methods
Various databases were searched for original articles published before May 2013. Studies were selected, which performed MRI with gadoxetic acid disodium to detect and diagnose HCC and which presented sufficient data to allow construction of contingency tables. For each study, the true-positive, false-positive, true-negative, and false-negative values were extracted or derived, and 2 × 2 contingency tables were constructed. The heterogeneity test, the threshold effect test, the publication bias analysis, and subgroup analyses were performed.
Results
From 623 citations, 18 were included in the meta-analysis with a total of 2572 lesions. We detected heterogeneity between studies and evidence of publication bias. The methodological quality was moderate. The pooled weighted sensitivity was 0.91 (95% confidence interval [CI], 0.90–0.93), the specificity was 0.94 (95% CI, 0.93–0.96), the positive likelihood ratio was 12.31 (95% CI, 7.66–19.78), the negative likelihood ratio was 0.10 (95% CI, 0.07–0.13), and the diagnostic odds ratio was 159.72 (95% CI, 91.72–276.08). The area under the receiver operating characteristic curve was 0.98 (95% CI, 0.96–0.99).
Conclusions
MRI with gadoxetic acid disodium is a noninvasive and no radiation exposure imaging modality with high sensitivity and specificity for the detection of HCC. Nonetheless, it should be applied cautiously in liver nodule <1 cm, and large-scale well-designed trials are necessary to assess its clinical value.
Hepatocellular carcinoma (HCC) is a major contributor to cancer incidence and mortality worldwide . HCC incidence rates have been increasing in the United States among most racial and ethnic groups . The prognosis for HCC has improved in recent years because more cases are diagnosed at an early stage . To provide better treatment options for patients, it is important to improve the diagnostic accuracy of HCC detection methods, especially at early stages of the disease.
To diagnose HCC, some useful, noninvasive, imaging tests, such as computed tomography (CT) and magnetic resonance imaging (MRI), can be used. In contrast to multidetector CT (MDCT) techniques, MRI has emerged as the preferred radiologic tool for the investigation of HCC. Dynamic contrast-enhanced (DCE) MRI with liver-specific contrast agents, such as gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (gadoxetic acid disodium or Gd-EOB-DTPA, Primovist; Schering, Berlin, Germany) can provide tissue-specific physiological information, thereby facilitating liver cancer characterization . Gadoxetate disodium has several advantageous properties for evaluating liver lesions. After injection, normal areas of the liver exhibit T1 shortening because of specific hepatocyte uptake, whereas most focal liver lesions, such as HCC and hepatic metastases, do not exhibit T1 shortening . Combined with the three-dimensional gradient-echo sequence technique, which provides excellent spatial resolution, gadoxetate disodium–enhanced MRI may be useful in detecting small HCC .
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Materials and methods
Literature Search
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Selection of Articles
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Quality Assessment and Data Extraction
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Meta-analysis
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Results
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Table 1
Characteristics of the Included Studies
Study Year Nation TP FP FN TN Patient Spectrum Disease Spectrum Size Study Design Blind Field Dose Sequence Kim et al. 2009 Korea 77 2 6 47 CLD or not Suspected HCC 2.9 (0.5–10.5) Retrospective Y 3.0 T 0.1 mL/kg w/o DWI Ahn et al. 2010 Korea 75 2 9 27 CLD or not Suspected HCC 2.8 (0.4–11.0) Retrospective Y 1.5/3.0 T 0.1 mL/kg w/o DWI Akai et al. 2010 Japan 45 4 7 41 CLD or not Suspected HCC 2.6 (0.4–15.2) Prospective Y 1.5 T 0.1 mL/kg w/o DWI Di Martino et al. 2010 Italy 74 1 13 21 CLD only Suspected HCC 1.8 (0.3–7.0) Prospective Y 1.5 T 0.1 mL/kg w/o DWI Filippone et al. 2010 Italy 36 1 3 14 CLD only HCC and DN 3.2 (0.8–7.5) Retrospective Y 1.5 T 0.1 mL/kg w/o DWI Kim et al. 2010 Korea 107 2 11 6 CLD or not Suspected HCC 1.5 (0.6–3.0) Retrospective Y 1.5 T 0.1 mL/kg w/o DWI Lee et al. 2010 Korea 37 0 1 18 CLD only Suspected HCC 2.8 (0.8–10.2) Retrospective Y 3.0 T 0.1 mL/kg w/o DWI Sun et al. 2010 Korea 30 3 2 25 CLD only HCC and AEP ≤2 Retrospective Y 3.0 T 10 mL w/o DWI Baek et al. 2011 Korea 65 3 8 35 CLD only Suspected HCC 2.98 (0.2–10) Retrospective Y 3.0 T 0.1 mL/kg w/o DWI Golfieri et al. 2011 Italy 172 2 1 40 CLD or not Suspected HCC 1.6 (0.4–2.0) Prospective Y 1.5 T 0.1 mL/kg w/o DWI Haradome et al. 2011 Italy 52 3 8 36 CLD or not HCC and DN 1.74 (0.5–2.8) Retrospective Y 1.5 T 0.1 mL/kg w/o DWI Lee et al. ∗ 2011 Korea 21 3 10 8 CLD only Well-differentiated HCC 2.4 (1.4–4.4) Retrospective Y 3.0 T 0.1 mL/kg w/DWI Sano et al. 2011 Japan 87 7 4 154 CLD only HCC and DN 1.3 (0.4–2.0) Retrospective Y 1.5 T 0.1 mL/kg w/o DWI Granito et al. 2012 Italy 30 0 8 10 CLD only Suspected HCC 1.8 (1.0–3.0) Prospective Y 1.5 T 0.1 mL/kg w/o DWI Inoue et al. 2012 Japan 75 2 2 7 CLD only HCC and DN 2.1 (0.6–4.0) Retrospective Y 1.5/3.0 T 0.1 mL/kg w/o DWI Ooka et al. 2012 Japan 82 11 5 343 CLD or not Suspected HCC 1.8 (0.3–6.5) Retrospective Y 1.5 T 0.1 mL/kg w/o DWI Park et al. 2012 Korea 147 3 32 141 CLD or not Suspected HCC 1.6 (0.8–2.0) Retrospective Y 3.0 T 0.1 mL/kg w/DWI Bashir et al. 2013 USA 64 14 6 41 CLD only Suspected HCC — Retrospective Y 1.5/3.0 T 10 mL w/o DWI Park et al. 2013 Korea 100 3 2 20 CLD only Suspected HCC 1.3 (0.6–2.0) Retrospective Y 3.0 T 0.1 mL/kg w/DWI
AEP, arterial-enhancing pseudolesions; CLD, chronic liver disease; DN, dysplastic nodule; DWI, diffusion-weighted imaging; HCC, hepatocellular carcinoma; w/o DWI, without DWI; w/DWI, without DWI.
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Table 2
Sensitivity and Specificity Estimates for Each Subgroup
Subgroup Number of Studies Sensitivity (%) Specificity (%) Lesion size ≥20 mm 12 91 (90–93) 94 (93–96) <20 mm 7 85 (82–88) 94 (93–97) <10 mm 2 73 (63–82) 97 (87–100) Reference standard Histopathologic only 9 93 (91–95) 96 (95–97) Histopathologic and other 9 89 (86–91) 88 (83–92) Magnetic field strength 1.5 T 9 91 (90–93) 96 (94–97) 3.0 T 6 90 (88–92) 96 (93–98) 1.5 T/3.0 T 3 92 (90–93) 94 (92–96) Study design Retrospective 12 92 (90–93) 96 (94–97) Prospective 6 91 (88–93) 89 (84–93) Patient spectrum CLD only 10 91 (88–92) 93 (90–95) CLD or not 8 92 (90–94) 95 (93–97) Sequences With DWI 2 89 (85–94) 96 (92–99) Without DWI 17 91 (89–93) 94 (93–96)
CLD, chronic liver disease; DWI, diffusion-weighted imaging.
Numbers in parentheses are the 95% confidence intervals.
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Discussion
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Conclusions
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Appendix
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PRISMA 2009 Checklist
From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA Statement. PLoS Med 6(6): e1000097. http://dx.doi.org/10.1371/journal.pmed1000097 .
Section/topic # Checklist item Reported on page #TITLE Title 1 Identify the report as a systematic review, meta-analysis, or both. TitleABSTRACT Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number. AbstractINTRODUCTION Rationale 3 Describe the rationale for the review in the context of what is already known. Introduction Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS). IntroductionMETHODS Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number. Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale. Selection of articles Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched. Literature search Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated. Literature search Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis). Selection of articles Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators. data extraction Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. data extraction Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis. Quality assessment Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). Meta-analysis Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I 2 ) for each meta-analysis. Meta-analysis Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies). Quality assessment Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified. Meta-analysisRESULTS Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram. Results Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations. Results Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). Results Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot. Results Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. Results Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). Results Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]). ResultsDISCUSSION Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers). Discussion Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias). Discussion Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research. DiscussionFUNDING Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review. Funding Statement
For more information, visit: www.prisma-statement.org .
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