Evidence map›Paper›PMID 41572981›Full record

ArticleInternational journal of breast cancer2026

Agreement Among Breast Cancer Screening Modalities in Breast Density Assessment and Cancer Risk Prediction.

Areej S Aloufi, Salman M Albeshan, Abdulaziz S Alshabibi, Meaad M Almusined, Lina A Aldibas, Milaf G Alotaibi, Sara Hosawi

Abstract read
In one paragraph

Article in International journal of breast cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Areej S AloufiDepartment of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia, ksu.edu.sa.ORCID https://orcid.org/0000-0002-6646-6378
Salman M AlbeshanDepartment of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia, ksu.edu.sa.ORCID https://orcid.org/0000-0002-8612-1721
Abdulaziz S AlshabibiDepartment of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia, ksu.edu.sa.ORCID https://orcid.org/0000-0003-1954-0034
Meaad M AlmusinedDepartment of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia, ksu.edu.sa.ORCID https://orcid.org/0009-0003-5922-6549
Lina A AldibasDepartment of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia, ksu.edu.sa.ORCID https://orcid.org/0009-0007-8675-7993
Milaf G AlotaibiDepartment of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia, ksu.edu.sa.ORCID https://orcid.org/0009-0002-5921-4719
Sara HosawiDepartment of Radiology, Breast Imaging, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia, kfshrc.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast density is increasingly recognized as a vital risk factor that affects early breast cancer detection. Therefore, this study was aimed at evaluating the agreement between different breast density measurements across multiple imaging modalities and identifying the best breast cancer predictor among these methods. Methods: Data for women over 30 years old who underwent mammography, synthetic mammography of digital breast tomosynthesis (SM-DBT), ultrasound (US), and magnetic resonance imaging (MRI) were collected. Breast density was assessed by two breast radiologists using the American College of Radiology (ACR) categories and the visual analog scale (VAS) for percentage density (%PD). The agreement was calculated using the kappa coefficient ( Results: Among 77 women (mean age 47.34 years), 25 had breast cancer. Categorical breast density assessments showed the highest agreement between mammography and SM-DBT ( Conclusion: The results suggest notable variability in radiologists' breast density assessment across different imaging modalities. MRI showed a greater ability to identify dense breast tissue and demonstrated potential value in breast cancer risk prediction, although these findings should be interpreted cautiously given the limited sample size. Establishing standardized approaches to breast density assessment remains important to improve the accuracy of breast cancer screening and risk prediction, and further research with larger cohorts is warranted.

Indexed as

breast cancerDBTdense breastmammographyMRIultrasound

Identifiers

PMID41572981
PMCPMC12822569

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Registered trials

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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.