Evidence map›Paper›PMID 25991488›Full record

ArticleEuropean radiology2016

The diagnostic efficacy of quantitative liver MR imaging with diffusion-weighted, SWI, and hepato-specific contrast-enhanced sequences in staging liver fibrosis--a multiparametric approach.

Diana Feier, Csilla Balassy, Nina Bastati, Romana Fragner, Friedrich Wrba, Ahmed Ba-Ssalamah

Abstract read
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In one paragraph

Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
5.2field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Magnetic Resonance Imaging of Liver Fibrosis, Fat, and Iron.Radiologic clinics of North America · 2022
    Review
  8. Article
  9. Fat- and iron-corrected ADC to assess liver fibrosis in patients with chronic hepatitis B.Diagnostic and interventional radiology (Ankara, Turkey) · 2022
    Article
  10. Consensus report from the 9European radiology · 2021
    Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Imaging of Hepatic Fibrosis.Current gastroenterology reports · 2018
    Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Diana FeierDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, General Hospital of Vienna (AKH), Waehringer Guertel 18-20, A-1090, Vienna, Austria.
Csilla BalassyDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, General Hospital of Vienna (AKH), Waehringer Guertel 18-20, A-1090, Vienna, Austria.
Nina BastatiDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, General Hospital of Vienna (AKH), Waehringer Guertel 18-20, A-1090, Vienna, Austria.
Romana FragnerDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, General Hospital of Vienna (AKH), Waehringer Guertel 18-20, A-1090, Vienna, Austria.
Friedrich WrbaDepartment of Pathology, Medical University of Vienna, General Hospital of Vienna (AKH), Vienna, Austria.
Ahmed Ba-SsalamahDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, General Hospital of Vienna (AKH), Waehringer Guertel 18-20, A-1090, Vienna, Austria. ahmed.ba-ssalamah@meduniwien.ac.at.
Medical University of Vienna · ATIuliu Hațieganu University of Medicine and Pharmacy · ROVienna General Hospital · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the diagnostic efficacy of multiparametric MRI using quantitative measurements of the apparent diffusion coefficient (ADC) of the liver parenchyma on diffusion-weighted imaging (DWI), signal intensity (SI) on susceptibility-weighted imaging (SWI), and gadoxetic acid-enhanced T1-weighted imaging during the hepatobiliary phase for the staging of liver fibrosis. MATERIALS AND

methodsSeventy-seven patients underwent a 3T MRI examination, including DWI/SWI sequences and gadoxetic acid-enhanced T1-weighted MRI. Liver fibrosis according to liver biopsy was staged using the Metavir fibrosis score: F0 (n = 21, 27.3%); F1 (n = 7, 9.1%); F2 (n = 8, 10.4%); F3 (n = 12, 15.6%); and F4 (n = 29, 37.7%). SI of the liver was defined using region-of-interest measurements to calculate the ADC values, the relative enhancement (RE) in the hepatobiliary phase, and the liver-to-muscle ratio (LMR) measurements for SWI.

resultsThe values of RE, LMR, and ADC measurements were statistically significantly different among the five fibrosis stages (p < 0.004). Combining the three parameters in a multiparametric approach, the AUC for detecting F1 stage or greater (≥ F1) was 94%, for F2 or greater (≥F2) was 95%, for F3 or greater (≥F3) was 90%, and for stage F4 was 93%.

conclusionsMultiparametric MRI is an efficient non-invasive diagnostic tool for the staging of liver fibrosis. KEY POINTS: • Multiparametric MRI has high accuracy in predicting moderate or greater liver fibrosis. • Relative enhancement post- gadoxetic acid is an independent predictor of liver fibrosis. • Liver SWI signal intensity and ADC values enhance the diagnostic ability.

Indexed as

Contrast MediaGadolinium DTPAImage EnhancementAdolescentAdultAgedAged, 80 and overDiffusion Magnetic Resonance ImagingFemaleHumansLiverLiver CirrhosisMagnetic Resonance ImagingMaleMiddle AgedPilot ProjectsContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPALiver fibrosisMR imagingMultiparametricQuantitativeStaging

Identifiers

PMID25991488
OpenAlexW312847619

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.