Key result
An artificial intelligence-based machine learning protocol demonstrated feasibility in expediting advanced aortic image analysis and predicting outcomes in a patient tracked longitudinally.
Why the study?
Clinical applications of biomechanical and morphological image-based analysis protocols for abdominal aortic aneurysms have limited adoption due to the time and expertise required.
Case Report (n=1)
Yes
AI-based machine learning protocols can expedite advanced aortic image analysis and predict outcomes in patients with abdominal aortic aneurysms, potentially offering an alternative to serial surveillance.
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.
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Gueldner et al. (2025) conducted a case report in Juxtarenal aortic aneurysm (n=1). Artificial intelligence-based machine learning protocols was evaluated on Feasibility of expediting advanced aortic image analysis and predicting patient outcomes. An artificial intelligence-based machine learning protocol demonstrated feasibility in expediting advanced aortic image analysis and predicting outcomes in a patient tracked longitudinally.
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