ReviewMedical physics2026
CDMAM phantom for Image Quality Assessment and Quality Control in digital mammography: A narrative review.
Review in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe CDMAM (Contrast Detail Mammography) phantom is widely used in European mammography quality control as a subjective observer-based tool for quantitative evaluation of low-contrast detectability. With the evolution of breast imaging technologies and the increasing adoption of automation, a technically focused synthesis addressing phantom design, analysis methodology, metrological performance, and practical limitations is needed. This review provides a concise technical overview of the current state of knowledge on CDMAM-based image quality assessment and quality control in digital mammography.
methodsA structured literature review was conducted covering publications from 1998 to 2025. Relevant studies were identified using PubMed, Web of Science, Scopus, SpringerLink, Elsevier ScienceDirect, and IOPscience. More than 60 scientific articles addressing the CDMAM phantom were analyzed, with emphasis on phantom construction and versions (CDMAM 3.4 vs. 4.0), automated analysis software and metrics (including IQF
resultsThe literature supports CDMAM as a useful and standardized surrogate of low-contrast detectability under controlled conditions; however, its ability to represent clinical lesion detectability is inherently limited by the use of simple test objects in a uniform background. CDMAM 4.0 demonstrates improved metrological performance relative to CDMAM 3.4, including enhanced sensitivity for the smallest details and reduced measurement uncertainty. Automated analysis substantially improves repeatability and enables harmonized long-term trend monitoring; however, software version dependence can bias IQF
conclusionsCDMAM remains a central tool for perceptual image quality evaluation and quality control in digital mammography and provides a practical bridge between physical metrics and detectability-oriented performance assessment. Current evidence supports the preferential use of CDMAM 4.0 in modern quality control programs, emphasizes the need for software harmonization in longitudinal analyses, and highlights the growing role of hybrid CDMAM-model observer-AI pipelines for automated, metrologically consistent quality assurance across emerging breast imaging modalities.
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Registered trials
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.