Evidence map›Paper›PMID 40196314›Full record

ArticlePolish journal of radiology2025

Comparative analysis of diagnostic performance of automatic breast ultrasound and spectral mammography as complementary methods to mammography examination.

Marta Pawlak, Wojciech Rudnicki, Tadeusz Popiela, Lukasz Brandt, Malgorzata Dobrowolska, Milena Lipinska, Elżbieta Łuczyńska

Abstract read
In one paragraph

Article in Polish journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Marta PawlakDepartment of Radiology, University Hospital in Cracow, Cracow, Poland.
Wojciech RudnickiDepartment of Electroradiology, Jagiellonian University Medical College, Cracow, Poland.
Tadeusz PopielaChair of Radiology, Jagiellonian University Medical College, Cracow, Poland.
Lukasz BrandtDepartment of Electroradiology, Jagiellonian University Medical College, Cracow, Poland.
Malgorzata DobrowolskaDepartment of Electroradiology, Jagiellonian University Medical College, Cracow, Poland.
Milena LipinskaDepartment of Radiology, University Hospital in Cracow, Cracow, Poland.
Elżbieta ŁuczyńskaDepartment of Electroradiology, Jagiellonian University Medical College, Cracow, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This single-centre study includes a comparative analysis of the diagnostic performance of contrast-enhanced mammography (CEM) and automatic breast ultrasound (ABUS). The study involved 81 patients with focal breast lesions, who underwent ABUS, full-field digital mammography (FFDM), and CEM. Material and methods: A total of 169 focal lesions were found in 81 patients, of which 110 lesions were histopathologically verified, 92 were malignant, 5 were B3 lesions, and 13 were benign. On CEM 19 additional lesions not visible on other imaging examinations were found, and as many as 36 new lesions were detected on ABUS. The number of lesions detected in patients with multiple lesions were 106 from 169 on ABUS, 65 on FFDM, and 88 on CEM. The highest correlation between the lesion's margin and its histopathological character was found in FFDM ( Results: The sensitivity of ABUS, FFDM, and CEM was, respectively: 80.43, 90.22, and 93.48; specificity: 27.78, 11.11, and 11.11; positive predictive value (PPV): 85.06, 83.84, and 84.31; negative predictive value (NPV): 21.74, 18.18, and 25; and accuracy: 71.82, 77.27, and 80. The sensitivity and accuracy of the combination of FFDM and ABUS were, respectively, 100 ( Conclusions: The study confirms that both ABUS and CEM may serve as a valuable complementary method for FFDM.

Indexed as

ABUSbreast cancerCEMmammography

Identifiers

PMID40196314
PMCPMC11973704

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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.