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

Bounias D, Führes T, Brock L, Graber J, Kapsner L, Liebert A, Schreiter H, Eberle J, Hadler D, Skwierawska D, Floca R, Neher P, Kovacs B, Wenkel E, Ohlmeyer S, Uder M, Maier-Hein K, Bickelhaupt S (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Nature Communications Nature Publishing Group: Nature Communications

Book Volume: 16

Article Number: 5299

Journal Issue: 1

DOI: 10.1038/s41467-025-59694-2

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.

Authors with CRIS profile

Tobit Führes Institute of Radiology Luise Brock Institute of Radiology Johanna Graber Professur für Experimentelle Nieren- und Kreislaufforschung Lorenz Kapsner Institute of Radiology Andrzej Liebert Institute of Radiology Hannes Schreiter Institute of Radiology Jessica Eberle Institute of Radiology Dominique Hadler Institute of Radiology Dominika Skwierawska Professur für quantitative MR-Bildgebung Sabine Ohlmeyer Institute of Radiology Michael Uder Lehrstuhl für Diagnostische Radiologie Sebastian Bickelhaupt Institute of Radiology

Involved external institutions

Deutsches Krebsforschungszentrum (DKFZ) DE Germany (DE)

How to cite

APA:

Bounias, D., Führes, T., Brock, L., Graber, J., Kapsner, L., Liebert, A.,... Bickelhaupt, S. (2025). AI-Based screening for thoracic aortic aneurysms in routine breast MRI. Nature Communications, 16(1). https://doi.org/10.1038/s41467-025-59694-2

MLA:

Bounias, Dimitrios, et al. "AI-Based screening for thoracic aortic aneurysms in routine breast MRI." Nature Communications 16.1 (2025).

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