Evidence map›Paper›PMID 38546790›Full record

ArticleEuropean radiology2024

Optimized signal of calcifications in wide-angle digital breast tomosynthesis: a virtual imaging trial.

Liesbeth Vancoillie, Lesley Cockmartin, Ferdinand Lueck, Nicholas Marshall, Machteld Keupers, Ralf Nanke, Steffen Kappler, Chantal Van Ongeval, Hilde Bosmans

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Article in European radiology, 2024. 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. Black-box Optimization of CT Acquisition and Reconstruction Parameters: A Reinforcement Learning Approach.Proceedings of SPIE--the International Society for Optical Engineering · 2025
    Article
  2. Journal of medical imaging (Bellingham, Wash.) · 2025
    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

9 authors.

Liesbeth VancoillieDepartment of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium. Liesbeth.vancoillie@duke.edu.ORCID http://orcid.org/0000-0002-5103-0758
Lesley CockmartinDepartment of Radiology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium.
Ferdinand LueckSiemens Healthcare GmbH, Siemensstraße 1, 91301, Forchheim, Germany.
Nicholas MarshallDepartment of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
Machteld KeupersDepartment of Radiology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium.
Ralf NankeSiemens Healthcare GmbH, Siemensstraße 1, 91301, Forchheim, Germany.
Steffen KapplerSiemens Healthcare GmbH, Siemensstraße 1, 91301, Forchheim, Germany.
Chantal Van OngevalDepartment of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
Hilde BosmansDepartment of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesEvaluate microcalcification detectability in digital breast tomosynthesis (DBT) and synthetic 2D mammography (SM) for different acquisition setups using a virtual imaging trial (VIT) approach. MATERIALS AND

methodsMedio-lateral oblique (MLO) DBT acquisitions on eight patients were performed at twice the automatic exposure controlled (AEC) dose. The noise was added to the projections to simulate a given dose trajectory. Virtual microcalcification models were added to a given projection set using an in-house VIT framework. Three setups were evaluated: (1) standard acquisition with 25 projections at AEC dose, (2) 25 projections with a convex dose distribution, and (3) sparse setup with 13 projections, every second one over the angular range. The total scan dose and angular range remained constant. DBT volume reconstruction and synthetic mammography image generation were performed using a Siemens prototype algorithm. Lesion detectability was assessed through a Jackknife-alternative free-response receiver operating characteristic (JAFROC) study with six observers.

resultsFor DBT, the area under the curve (AUC) was 0.97 ± 0.01 for the standard, 0.95 ± 0.02 for the convex, and 0.89 ± 0.03 for the sparse setup. There was no significant difference between standard and convex dose distributions (p = 0.309). Sparse projections significantly reduced detectability (p = 0.001). Synthetic images had a higher AUC with the convex setup, though not significantly (p = 0.435). DBT required four times more reading time than synthetic mammography. DISCUSSION: A convex setup did not significantly improve detectability in DBT compared to the standard setup. Synthetic images exhibited a non-significant increase in detectability with the convex setup. Sparse setup significantly reduced detectability in both DBT and synthetic mammography. CLINICAL RELEVANCE STATEMENT: This virtual imaging trial study allowed the design and efficient testing of different dose distribution trajectories with real mammography images, using a dose-neutral protocol. KEY POINTS: • In DBT, a convex dose distribution did not increase the detectability of microcalcifications compared to the current standard setup but increased detectability for the SM images. • A sparse setup decreased microcalcification detectability in both DBT and SM images compared to the convex and current clinical setups. • Optimal microcalcification cluster detection in the system studied was achieved using either the standard or convex dose setting, with the default number of projections.

Indexed as

Breast NeoplasmsCalcinosisMammographyAlgorithmsFemaleHumansMiddle AgedRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedBreast neoplasmsComputer simulationMammography

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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.