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

Author

Listed:
  • Dimitrios Bounias

    (Im Neuenheimer Feld 280
    Im Neuenheimer Feld 672)

  • Tobit Führes

    (Maximiliansplatz 3)

  • Luise Brock

    (Maximiliansplatz 3)

  • Johanna Graber

    (Maximiliansplatz 3)

  • Lorenz A. Kapsner

    (Maximiliansplatz 3
    Wetterkreuz 15)

  • Andrzej Liebert

    (Maximiliansplatz 3)

  • Hannes Schreiter

    (Maximiliansplatz 3)

  • Jessica Eberle

    (Maximiliansplatz 3)

  • Dominique Hadler

    (Maximiliansplatz 3)

  • Dominika Skwierawska

    (Maximiliansplatz 3)

  • Ralf Floca

    (Im Neuenheimer Feld 280
    Im Neuenheimer Feld 280)

  • Peter Neher

    (Im Neuenheimer Feld 280
    Im Neuenheimer Feld 280
    Im Neuenheimer Feld 400
    Im Neuenheimer Feld 460)

  • Balint Kovacs

    (Im Neuenheimer Feld 280
    Im Neuenheimer Feld 672)

  • Evelyn Wenkel

    (Burgstraße 7)

  • Sabine Ohlmeyer

    (Maximiliansplatz 3)

  • Michael Uder

    (Maximiliansplatz 3)

  • Klaus Maier-Hein

    (Im Neuenheimer Feld 280
    Im Neuenheimer Feld 672
    Im Neuenheimer Feld 280
    Im Neuenheimer Feld 400)

  • Sebastian Bickelhaupt

    (Maximiliansplatz 3)

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.

Suggested Citation

  • Dimitrios Bounias & Tobit Führes & Luise Brock & Johanna Graber & Lorenz A. Kapsner & Andrzej Liebert & Hannes Schreiter & Jessica Eberle & Dominique Hadler & Dominika Skwierawska & Ralf Floca & Peter, 2025. "AI-Based screening for thoracic aortic aneurysms in routine breast MRI," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59694-2
    DOI: 10.1038/s41467-025-59694-2
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