Evidence map›Paper›PMID 37932389›Full record

ArticleEuropean radiology2024

Added value of the EUSOBI diffusion levels in breast MRI.

Chiara Zuiani, Iris Mansutti, Guido Caronia, Anna Linda, Viviana Londero, Rossano Girometti

Open access · hybridAbstract read
In one paragraph

Article in European radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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 2 institutions in 1 country.

Chiara ZuianiInstitute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy.
Iris MansuttiInstitute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy.
Guido CaroniaInstitute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy.
Anna LindaInstitute of Radiology, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy.
Viviana LonderoInstitute of Radiology, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy.
Rossano GiromettiInstitute of Radiology, Department of Medicine, University of Udine, University Hospital S. Maria Della Misericordia, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy. rossano.girometti@uniud.it.ORCID http://orcid.org/0000-0002-0904-5147
University of Udine · ITOspedale Santa Maria della Misericordia di Udine · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate whether using the diffusion levels (DLs) proposed by the European Society of Breast Imaging (EUSOBI) improves the diagnostic accuracy of breast MRI. MATERIALS AND

methodsThis retrospective study included 145 women who, between September 2019 and June 2020, underwent breast 1.5-T MRI with DWI. Reader 1 and reader 2 (R1-R2) independently assessed breast lesions using the BI-RADS on dynamic contrast-enhanced imaging and T2-weighted imaging. DWI was subsequently disclosed, allowing readers able to measure lesions ADC and subjectively express the overall risk of malignancy on a 1-5 Likert scale. ADCs were interpreted as a range of values corresponding to the EUSOBI DLs. The analysis evaluated the inter-reader agreement in measuring ADC and DLs, the per-DL malignancy rate, and accuracy for malignancy using ROC analysis against histological examination or a 3-year follow-up.

resultsLesions were malignant and showed non-mass enhancement in 67.7% and 76.1% of cases, respectively. ADC was measurable in 63.2%/66.7% of lesions (R1/R2), with a minimal discrepancy on Bland-Altman analysis and 0.948 (95%CI 0.925-0.965)/0.989 (95%CI 0.988-0.991) intraclass correlation coefficient in measuring ADC/DLs. The malignancy rate (R1/R2) increased from 0.5/0.5% ("very high" DL) to 96.0/96.8% ("very low" DL), as expected. Likert categorization showed larger areas under the curve than the BI-RADS for both R1 (0.91 versus 0.87; p = 0.0208) and R2 (0.91 versus 0.89; p = 0.1171), with improved specificity (81.5% versus 78.5% for R1 and 84.4% versus 81.2% for R2).

conclusionThough ADC was not measurable in about one-third of lesions, DLs were categorized with excellent inter-reader agreement, improving the specificity for malignancy. CLINICAL RELEVANCE STATEMENT: DLs proposed by the EUSOBI are a reproducible tool to interpret the ADC of breast lesions and, in turn, to improve the specificity of breast MRI and reduce unnecessary breast biopsies. KEY POINTS: • The European Society of Breast Imaging proposed diffusion levels for the interpretation of the apparent diffusion coefficient in diffusion-weighted imaging of the breast. • Adding diffusion levels to the interpretation of magnetic resonance imaging improved the diagnostic accuracy for breast cancer, especially in terms of specificity. • Diffusion levels can favor a more widespread and standardized use of diffusion-weighted imaging of the breast.

Indexed as

Breast NeoplasmsDiffusion Magnetic Resonance ImagingAdultAgedAged, 80 and overBreastContrast MediaFemaleHumansMiddle AgedReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityContrast MediaBreast neoplasmsDiagnosisDiffusion magnetic resonance imaging

Identifiers

PMID37932389
PMCPMC11126436
OpenAlexW4388441937

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.