Evidence map›Paper›PMID 42867734›Full record

ArticleEuropean radiology experimental2026

Comparison of two automated PGMI-based software tools for breast positioning quality assessment in DBT screening.

Gisella Gennaro, Stefano Trazzi, Valentina Bordon, Vania Galli

Abstract readComparative Study
In one paragraph

Article in European radiology experimental, 2026. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Gisella GennaroVeneto Institute of Oncology (IOV), IRCCS, Via Gattamelata 64, 35128, Padua, Italy. gisella.gennaro@iov.veneto.it.ORCID http://orcid.org/0000-0003-2444-1778
Stefano TrazziAzienda USL Bologna, Bologna, Italy.
Valentina BordonULSS 6 "Euganea", Padua, Italy.
Vania GalliAUSL Modena, Modena, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAutomated "Perfect/Good/Moderate/Inadequate" (PGMI)-based tools have been developed to standardize breast positioning quality assessment, but their agreement remains uncertain. This study compared two automated software systems applied to the same digital breast tomosynthesis (DBT) screening cohort. MATERIALS AND

methodsThis retrospective study included 778 women (3,112 views). Two software tools (SW1 and SW2) independently generated PGMI classifications and quality control (QC) feature outputs. Agreement was assessed using exact agreement and quadratic weighted κ. PGMI distributions were compared overall and by view, breast density, and breast volume. Associations between imaging parameters and PGMI scores were evaluated using Spearman correlation and ordinal regression.

resultsSW2 assigned more Inadequate ratings than SW1 (10.9% vs. 0.7%, p < 0.001), whereas SW1 assigned more Perfect (21.9% vs. 12.9%, p < 0.001). Overall agreement was limited (48.2%; κ = 0.044, 95% CI 0.006-0.085). Agreement was higher in mediolateral oblique than in craniocaudal views. Across SW1-derived density strata, SW2 assigned more Inadequate and fewer Perfect ratings in higher density strata, with smaller differences observed at higher breast volume. Higher volumetric breast density and breast thickness were associated with lower PGMI scores, whereas breast volume showed positive associations, with the effect more pronounced for SW2. QC patterns differed markedly: SW1 most frequently flagged inframammary fold and posterior positioning criteria, whereas SW2 identified pectoral muscle and parenchymal coverage issues.

conclusionTwo automated PGMI systems showed limited agreement and systematic differences in classification behavior. These findings indicate a lack of interchangeability and support the need for harmonized definitions and validation frameworks for automated image quality assessment. KEY POINTS: Question Standardized automated assessment of breast positioning quality in digital breast tomosynthesis remains lacking, limiting comparability between different PGMI-based software tools in screening. Findings Two automated PGMI systems showed limited agreement and systematic differences across views, breast density, breast volume, and acquisition-related parameters in DBT screening. Relevance statement Automated PGMI systems are not interchangeable and reflect different operational definitions of image quality. Harmonized standards and rigorous validation are required before implementation in clinical quality assurance workflows.

Indexed as

Breast NeoplasmsMammographyRadiographic Image Interpretation, Computer-AssistedSoftwareAdultAgedBreastBreast DensityFemaleHumansMiddle AgedPatient PositioningQuality ControlRetrospective StudiesAutomationBreast densityDigital breast tomosynthesisMammographyQuality control

Identifiers

PMID42867734
PMCPMC13661857

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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.