Evidence map›Paper›PMID 39953260›Full record

ArticleJournal of imaging informatics in medicine2025

Application of a Commercial Artificial Intelligence Software in Unilateral Mammography: Simulating Total Mastectomy Scenarios.

Ji Yeong An, Janie M Lee, Myoung-Jin Jang, Su Min Ha, Jung Min Chang

Abstract read
In one paragraph

Article in Journal of imaging informatics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

5 authors.

Ji Yeong AnDepartment of Radiology, Seoul National University Hospital, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.ORCID http://orcid.org/0009-0007-0093-2018
Janie M LeeDepartment of Radiology, University of Washington School of Medicine, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-6452-8168
Myoung-Jin JangMedical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0001-8123-5001
Su Min HaDepartment of Radiology, Seoul National University Hospital, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.ORCID http://orcid.org/0000-0002-1833-0919
Jung Min ChangDepartment of Radiology, Seoul National University Hospital, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea. imchangjm@gmail.com.ORCID http://orcid.org/0000-0001-5726-9797

Funding

Seoul National University Hospital grant no. 04-2023-2160.
6 · The paper itself

Abstract

This study was to evaluate the performance of commercially available artificial intelligence (AI) software in unilateral mammograms simulating postmastectomy surveillance compared with AI software used in bilateral mammograms from the same women serving as controls. A retrospective database search identified consecutive women who underwent breast cancer surgery between January 2021 and December 2021. AI software was applied to the mammogram immediately preceding breast cancer diagnosis in two modes: bilateral (the standard bilateral mammography dataset) and unilateral analyses (each breast's craniocaudal and mediolateral oblique views), and their outputs were reviewed. The sensitivity, specificity, and number of marks per breast were compared between the bilateral and unilateral analyses with -5% non-inferiority margin for the difference in sensitivity and specificity between the two modes. A total of 694 women (mean age, 55.2 ± 10.8 years) with unilateral or bilateral breast cancer contributed mammograms for analysis; each breast was then separately evaluated in the unilateral postmastectomy simulation (n = 1388), of which 730 had breast cancer (52.6%) (mean invasive size = 1.5 cm) and compared with bilateral mammography analysis. The sensitivity of unilateral analysis was not inferior to that of bilateral analysis (78.6% vs. 76.7%), with a difference of 1.9%. The specificity of unilateral analysis was inferior to that in the bilateral analysis (81.5% vs. 91.9%), with a difference of -10.5% being lower than the non-inferiority margin. The average number of AI marks per breast was 0.94 (unilateral [1298/1388] and bilateral analyses [1306/1388], respectively). AI software performance in simulated unilateral mammography analysis demonstrated non-inferior sensitivity and inferior specificity compared to bilateral mammography.

Indexed as

Artificial IntelligenceBreast NeoplasmsMammographyMastectomy, SimpleRadiographic Image Interpretation, Computer-AssistedSoftwareAdultAgedFemaleHumansMastectomyMiddle AgedRetrospective StudiesSensitivity and SpecificityArtificial intelligenceMammographyMastectomyNon-inferiority

Identifiers

PMID39953260
PMCPMC12701099

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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.