Artificial intelligence-based machine learning protocols enable quicker assessment of aortic biomechanics: A case study
Analyzing aortic biomechanical wall stresses for abdominal aortic aneurysms remains challenging. Clinical applications of biomechanical and morphological image-based analysis protocols have limited adoption owing to the time and expertise required. Our multidisciplinary and multi-institute team has demonstrated the feasibility of expediting advanced aortic image analysis on a single patient tracked longitudinally. We also demonstrate the utility of a previously trained artificial intelligence-based classifier that accurately predicts patient outcomes, a potential alternative to serial surveillance. This paper describes the overall workflow and processes performed in a 70-year-old man who was incidentally diagnosed to have a 5.4-cm juxtarenal aortic aneurysm in 2016 with successful fenestrated endovascular repair in 2023.
Authors
- Nathan L. Liang (ORCID: https://orcid.org/0000-0003-2863-4008)
- Pete H. Gueldner (ORCID: https://orcid.org/0000-0002-9177-8162)
- David A. Vorp (ORCID: https://orcid.org/0000-0002-6467-2151)
- Tiziano Tallarita (ORCID: https://orcid.org/0000-0001-6262-0246)
- Katherine E. Kerr (ORCID: https://orcid.org/0000-0003-1238-6564)
- Timothy K. Chung
- Jason Beckermann (ORCID: https://orcid.org/0000-0002-4162-4237)
- Indrani Sen
- Joseph C. Wildenberg (ORCID: https://orcid.org/0000-0001-5489-8467)
Institutions
- University of Pittsburgh (US)
- Magee-Womens Research Institute (US)
- Mayo Clinic Health System (US)
- University of Pittsburgh Medical Center (US)
- McGowan Institute for Regenerative Medicine (US)
Publication Details
- Journal
- Journal of Vascular Surgery Cases and Innovative Techniques
- Published
- 2025-04-14
- DOI
- https://doi.org/10.1016/j.jvscit.2025.101806
- Citations
- 1
- Primary Topic
- Aortic aneurysm repair treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.52
Funders
- National Science Foundation
- American Heart Association
- Nvidia
- University of Pittsburgh
- Jewish Healthcare Foundation
- National Institutes of Health