Evidence map›Paper›PMID 40506431›Full record

ArticleNature communications2025

AI-Based screening for thoracic aortic aneurysms in routine breast MRI.

Dimitrios Bounias, Tobit Führes, Luise Brock, Johanna Graber, Lorenz A Kapsner, Andrzej Liebert, Hannes Schreiter, Jessica Eberle, Dominique Hadler, Dominika Skwierawska and 8 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

18 authors.

Dimitrios BouniasGerman Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Im Neuenheimer Feld 280, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-3361-1698
Tobit FühresRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.
Luise BrockRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.
Johanna GraberRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.
Lorenz A KapsnerRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.ORCID http://orcid.org/0000-0003-1866-860X
Andrzej LiebertRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.ORCID http://orcid.org/0000-0002-8450-3021
Hannes SchreiterRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.ORCID http://orcid.org/0000-0002-4373-6996
Jessica EberleRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.ORCID http://orcid.org/0009-0007-5030-1134
Dominique HadlerRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.ORCID http://orcid.org/0000-0002-7334-8855
Dominika SkwierawskaRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.ORCID http://orcid.org/0000-0002-6531-4049
Ralf FlocaGerman Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Im Neuenheimer Feld 280, Heidelberg, Germany.ORCID http://orcid.org/0000-0003-3218-3377
Peter NeherGerman Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Im Neuenheimer Feld 280, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-5285-7554
Balint KovacsGerman Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Im Neuenheimer Feld 280, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-1191-0646
Evelyn WenkelRadiologie München, Burgstraße 7, München, Germany.
Sabine OhlmeyerRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.
Michael UderRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany.
Klaus Maier-HeinGerman Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Im Neuenheimer Feld 280, Heidelberg, Germany.
Sebastian BickelhauptRadiological Institute, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, Erlangen, Germany. sebastian.bickelhaupt@uk-erlangen.de.ORCID http://orcid.org/0000-0003-1043-4462

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prognosis for thoracic aortic aneurysms is significantly worse for women than men, with a higher mortality rate observed among female patients. The increasing use of magnetic resonance breast imaging (MRI) offers a unique opportunity for simultaneous detection of both breast cancer and thoracic aortic aneurysms. We retrospectively validate a fully-automated artificial neural network (ANN) pipeline on 5057 breast MRI examinations from public (Duke University Hospital/EA1141 trial) and in-house (Erlangen University Hospital) data. The ANN, benchmarked against 3D-ground-truth segmentations, clinical reports, and a multireader panel, demonstrates high technical robustness (dice/clDice 0.88-0.91/0.97-0.99) across different vendors and field strengths. The ANN improves aneurysm detection rates by 3.5-fold compared with routine clinical readings, highlighting its potential to improve early diagnosis and patient outcomes. Notably, a higher odds ratio (OR = 2.29, CI: [0.55,9.61]) for thoracic aortic aneurysms is observed in women with breast cancer or breast cancer history, suggesting potential further benefits from integrated simultaneous assessment for cancer and aortic aneurysms.

Indexed as

Aortic Aneurysm, ThoracicBreastBreast NeoplasmsMagnetic Resonance ImagingAdultAgedFemaleHumansMaleMass ScreeningMiddle AgedNeural Networks, ComputerRetrospective Studies

Identifiers

PMID40506431
PMCPMC12162828

What OpenQuestion holds

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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.