Detection of liver metastases on gadobenate dimeglumine-enhanced MRI: systematic review, meta-analysis, and similarities with gadoxetate-enhanced MRI View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03-26

AUTHORS

Ling Zhang, Xian Yu, Lei Huo, Lun Lu, Xinpeng Pan, Ningyang Jia, Xinxiang Fan, Giovanni Morana, Luigi Grazioli, Guenther Schneider

ABSTRACT

OBJECTIVES: To determine the sensitivity and positive predictive value (PPV) of gadobenate-enhanced MR imaging for the detection of liver metastases. METHODS: This systematic review and meta-analysis was conducted according to PRISMA guidelines. A comprehensive search (EMBASE, PubMed) was performed to identify relevant articles up to December 2017. Studies eligible for inclusion were performed using appropriate methodology with complete verification by means of histopathology, intraoperative observation and/or follow-up, and sufficient information to permit determination of true-positive (TP), false-negative (FN), and false-positive (FP) values. Sources of bias were assessed using the QUADAS-2 tool. An inverse variance-weighted random-effects model was used to obtain sensitivity and PPV estimates. Information was analyzed and presented using Cochran's Q statistic, funnel plots, and modified Deeks' analysis. RESULTS: Ten articles (256 patients, 562 metastases) were included. Sensitivity estimates for pre-contrast (unenhanced) imaging, gadobenate-enhanced dynamic imaging, and combined unenhanced, dynamic, and delayed hepatobiliary phase imaging for detecting liver metastases on a per-lesion basis were 77.8% (95% CI 71.4-84.3%, 7 assessments), 88.1% (95% CI, 84.0-92.2%, 13 assessments), and 95.1% (95% CI 93.1-97.1%, 15 assessments), respectively. The addition of hepatobiliary phase images significantly improved the detection of liver metastases. The overall PPV was 90.9% (95% CI 86.6-95.1%, 11 assessments). Deeks' funnel analysis revealed no association between sample size and sensitivity (β = 0.02, p = 0.814) indicating no significant publication bias. CONCLUSIONS: Gadobenate-enhanced MR imaging has high sensitivity and PPV for the detection of liver metastases on a per-lesion basis. The sensitivity and PPV for detection is comparable to reported values for the pure liver-specific agent gadoxetate. KEY POINTS: • Gadobenate dimeglumine is a hepatobiliary MR contrast agent that permits acquisition of contrast-enhanced liver images during the immediate post-injection dynamic phase, like any extracellular agent, and in the delayed hepatobiliary phase, after specific uptake by the hepatocytes. • The hepatobiliary phase improves detection of liver metastases when compared either to pre-contrast unenhanced images alone or to pre-contrast + gadobenate-enhanced dynamic phase images. • The meta-analysis showed an overall sensitivity of 95.1% and PPV of 90.9% of gadobenate-enhanced MRI for the detection of metastases, when based on the evaluation of all available acquisitions. More... »

PAGES

1-12

References to SciGraph publications

  • 2010-06. Diagnosis of liver metastases: value of diffusion-weighted MRI compared with gadolinium-enhanced MRI in EUROPEAN RADIOLOGY
  • 2016-04. ESGAR consensus statement on liver MR imaging and clinical use of liver-specific contrast agents in EUROPEAN RADIOLOGY
  • 2012-03. MRI of colorectal cancer liver metastases: comparison of orally administered manganese with intravenously administered gadobenate dimeglumine in EUROPEAN RADIOLOGY
  • 2012-09. Preoperative Imaging of Colorectal Liver Metastases After Neoadjuvant Chemotherapy: A Meta-Analysis in ANNALS OF SURGICAL ONCOLOGY
  • 2018-11. Diagnostic accuracy of CE-CT, MRI and FDG PET/CT for detecting colorectal cancer liver metastases in patients considered eligible for hepatic resection and/or local ablation in EUROPEAN RADIOLOGY
  • 2017-04. Comparison of gadoxetic acid-enhanced dynamic MR imaging and contrast-enhanced computed tomography for preoperative evaluation of colorectal liver metastases in JAPANESE JOURNAL OF RADIOLOGY
  • 2004-01. Gadobenate dimeglumine-enhanced liver MR imaging: value of dynamic and delayed imaging for the characterization and detection of focal liver lesions in EUROPEAN RADIOLOGY
  • 2005-02. Detection of liver metastases: gadobenate dimeglumine-enhanced three-dimensional dynamic phases and one-hour delayed phase MR imaging versus superparamagnetic iron oxide-enhanced MR imaging in EUROPEAN RADIOLOGY
  • 2018-10. Accurate IVIM model-based liver lesion characterisation can be achieved with only three b-value DWI in EUROPEAN RADIOLOGY
  • 2011-11. Gd-EOB-DTPA-enhanced 3.0 T MR imaging: quantitative and qualitative comparison of hepatocyte-phase images obtained 10 min and 20 min after injection for the detection of liver metastases from colorectal carcinoma in EUROPEAN RADIOLOGY
  • 2016-11. Comparative diagnostic accuracy of hepatocyte-specific gadoxetic acid (Gd-EOB-DTPA) enhanced MR imaging and contrast enhanced CT for the detection of liver metastases: a systematic review and meta-analysis in INTERNATIONAL JOURNAL OF COLORECTAL DISEASE
  • 2015-03. Hepatobiliary agents and their role in LI-RADS in ABDOMINAL RADIOLOGY
  • 2014-12. Investigation of publication bias in meta-analyses of diagnostic test accuracy: a meta-epidemiological study in BMC MEDICAL RESEARCH METHODOLOGY
  • 2010-12. Characterisation of small hypoattenuating hepatic lesions in multi-detector CT (MDCT) in patients with underlying extrahepatic malignancy: added value of contrast-enhanced MR images in EUROPEAN RADIOLOGY
  • 2016-12. A meta-analysis of diffusion-weighted and gadoxetic acid-enhanced MR imaging for the detection of liver metastases in EUROPEAN RADIOLOGY
  • 2013-08. Preoperative evaluation of colorectal liver metastases: comparison between gadoxetic acid-enhanced 3.0-T MRI and contrast-enhanced MDCT with histopathological correlation in EUROPEAN RADIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00330-019-06110-1

    DOI

    http://dx.doi.org/10.1007/s00330-019-06110-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1113006619

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30915560


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