Association Between Aortic Imaging Features and Impaired Glucose Metabolism: A Deep Learning Population Phenotyping Approach
Aortic features showed a glucose level dependent increase from normoglycemic individuals to those with prediabetes and diabetes. Total aortic length and volume were independently and inversely associated with impaired glucose metabolism beyond traditional CV risk factors.
Authors
- Jakob Weiß
- Susanne Rospleszcz (ORCID: https://orcid.org/0000-0002-4788-2341)
- Lea Michel (ORCID: https://orcid.org/0000-0001-6104-4646)
- Fabian Bamberg (ORCID: https://orcid.org/0000-0002-7460-3942)
- Jana Taron (ORCID: https://orcid.org/0000-0002-1388-7531)
- Maximilian Frederik Russe (ORCID: https://orcid.org/0000-0003-3187-2429)
- Marco Reisert (ORCID: https://orcid.org/0000-0003-2742-1940)
- Sabrina Schlesinger (ORCID: https://orcid.org/0000-0003-4244-0832)
- Alexander Rau (ORCID: https://orcid.org/0000-0001-5881-6043)
- Annette Peters (ORCID: https://orcid.org/0000-0001-6645-0985)
- Christopher L. Schlett (ORCID: https://orcid.org/0000-0002-1576-1481)
Institutions
- University of Freiburg (DE)
- University Medical Center Freiburg (DE)
- Helmholtz Zentrum München (DE)
- German Centre for Cardiovascular Research (DE)
- Deutsches Diabetes-Zentrum e.V. (DE)
- German Center for Diabetes Research (DE)
- Heinrich Heine University Düsseldorf (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Academic Radiology
- Published
- 2025-02-10
- DOI
- https://doi.org/10.1016/j.acra.2025.01.032
- Primary Topic
- Cardiovascular Health and Disease Prevention
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Albert-Ludwigs-Universität Freiburg
- Medizinische Fakultät der Albert-Ludwigs-Universität Freiburg