Evidence map›Paper›PMID 33244075›Full record

ArticleScientific reports2020

Diagnostic accuracy of digital breast tomosynthesis in combination with 2D mammography for the characterisation of mammographic abnormalities.

Vithya Visalatchi Sanmugasiva, Marlina Tanty Ramli Hamid, Farhana Fadzli, Faizatul Izza Rozalli, Chai Hong Yeong, Nazimah Ab Mumin, Kartini Rahmat

Abstract read
In one paragraph

Article in Scientific reports, 2020. 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
–field-weighted citation impact
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.

  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

7 authors.

Vithya Visalatchi SanmugasivaDepartment of Biomedical Imaging, University Malaya Research Imaging Centre, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Marlina Tanty Ramli HamidDepartment of Biomedical Imaging, University Malaya Research Imaging Centre, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Farhana FadzliDepartment of Biomedical Imaging, University Malaya Research Imaging Centre, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Faizatul Izza RozalliDepartment of Biomedical Imaging, University Malaya Research Imaging Centre, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Chai Hong YeongSchool of Medicine, Faculty of Health and Medical Sciences, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia.
Nazimah Ab MuminDepartment of Biomedical Imaging, University Malaya Research Imaging Centre, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Kartini RahmatDepartment of Biomedical Imaging, University Malaya Research Imaging Centre, University of Malaya, 50603, Kuala Lumpur, Malaysia. katt_xr2000@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to assess the diagnostic accuracy of digital breast tomosynthesis in combination with full field digital mammography (DBT + FFDM) in the charaterisation of Breast Imaging-reporting and Data System (BI-RADS) category 3, 4 and 5 lesions. Retrospective cross-sectional study of 390 patients with BI-RADS 3, 4 and 5 mammography with available histopathology examination results were recruited from in a single center of a multi-ethnic Asian population. 2 readers independently reported the FFDM and DBT images and classified lesions detected (mass, calcifications, asymmetric density and architectural distortion) based on American College of Radiology-BI-RADS lexicon. Of the 390 patients recruited, 182 malignancies were reported. Positive predictive value (PPV) of cancer was 46.7%. The PPV in BI-RADS 4a, 4b, 4c and 5 were 6.0%, 38.3%, 68.9%, and 93.1%, respectively. Among all the cancers, 76% presented as masses, 4% as calcifications and 20% as asymmetry. An additional of 4% of cancers were detected on ultrasound. The sensitivity, specificity, PPV and NPV of mass lesions detected on DBT + FFDM were 93.8%, 85.1%, 88.8% and 91.5%, respectively. The PPV for calcification is 61.6% and asymmetry is 60.7%. 81.6% of cancer detected were invasive and 13.3% were in-situ type. Our study showed that DBT is proven to be an effective tool in the diagnosis and characterization of breast lesions and supports the current body of literature that states that integrating DBT to FFDM allows good characterization of breast lesions and accurate diagnosis of cancer.

Indexed as

AdultAgedBreastBreast NeoplasmsCross-Sectional StudiesFemaleHumansMammographyMiddle AgedRadiographic Image EnhancementRetrospective Studies

Identifiers

PMID33244075
PMCPMC7691352

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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.