ArticleTomography (Ann Arbor, Mich.)2026
Can AI Detect What Is Not Injected? Evaluation of Lesion Detection in Virtual Contrast-Enhanced Breast MRI Using a Large-Scale AI Model Trained on GBCA-Enhanced Data.
Shirin Heidarikahkesh, Hannes Schreiter, Aju George, Tri-Thien Nguyen, Dominika Skwierawska, Luise Brock, Dominique Hadler, Michael Uder, Frederik B Laun, Chris Ehring and 7 more
Abstract read
In one paragraphArticle in Tomography (Ann Arbor, Mich.), 2026. 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
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0citing papers in PubMed
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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 registryThe 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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3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
17 authors.
Shirin HeidarikahkeshInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0009-0002-7479-693X Hannes SchreiterInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.
Aju GeorgeInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.
Tri-Thien NguyenInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.
Dominika SkwierawskaInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0002-6531-4049 Luise BrockInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0002-4591-4354 Dominique HadlerInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0002-7334-8855 Michael UderInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.
Frederik B LaunInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0002-9269-5609 Chris EhringInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0009-0002-4910-0937 Johanna GraberInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.
Lorenz DöppmannInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0009-0000-0854-0640 Ihor HorishnyiInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0002-9306-4702 Lorenz A KapsnerInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0003-1866-860X Sabine OhlmeyerInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0001-9163-8840 Andrzej LiebertInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.ORCID 0000-0002-8450-3021 Sebastian BickelhauptInstitute of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany.
Funding
Bavarian Ministry of Economic Affairs and Media, Energy and Technology MVA2023
6 · The paper itselfAbstract
BACKGROUND/
objectivesArtificial intelligence (AI) can support lesion detection in gadolinium-based contrast agent-enhanced (GBCA-enhanced) breast MRI. However, its effectiveness on virtual contrast-enhanced (vCE) images remains unclear. This feasibility study evaluated the publicly available MAMA-MIA nnU-Net model trained on GBCA-enhanced data using an independent cohort of both GBCA-enhanced and vCE breast MRI.
methodsThis IRB-approved retrospective study included the publicly available nnU-Net model trained on
resultsThe final test set comprised
conclusionsA GBCA-trained algorithm demonstrated some cross-domain transferability to vCE images, albeit with a reduced case-level sensitivity of 84% (95% CI: 73.7-90.9%) vs. 91% (95% CI: 82.3-96.0%). Based on these preliminary results, further research, including larger cohorts and more diverse datasets, is warranted.
Indexed as
Artificial IntelligenceBreast NeoplasmsContrast MediaGadoliniumImage Interpretation, Computer-AssistedMagnetic Resonance ImagingAdultBreastFeasibility StudiesFemaleGenerative Adversarial NetworksHumansMiddle AgedRetrospective StudiesContrast MediaGadoliniumgadolinium-enhanced MRIlesion detectionvirtual contrast enhancement
Identifiers
PMID42506870
PMCPMC13417500
What OpenQuestion holds
Textmetadata
LicenceCC BY
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