Modern diagnostic approach to patients with abdominal aortic aneurysm.

Abstract

Abdominal aortic aneurysm (AAA) is a relatively frequent and serious condition in vascular surgery. The diagnostic and indication process and its treatment are driven by the guidelines which dictate an intervention when the maximum AAA diameter is more than 55 mm. Nevertheless, this approach is not fully sufficient in all AAA cases and thus we have been seeking to develop a modern diagnostic tool using computer modeling and vascular wall stress analysis. The project has been ongoing in cooperation with engineers from VUT Brno (Brno University of Technology) and VŠB Ostrava (Technical University of Ostrava) for ten years. The design of the analytical tool was created during the first, experimental period of the project; this tool is able to assess vascular wall stress from regular CT scans using the finite element method. This primary model was gradually altered and its precision was increased considerably in the course of the years using data from mechanical and histological tests of AAA wall specimens harvested during open repairs. Additionally, other patient specific data are included in the analysis such as blood pressure, gender and material characteristics. The effectiveness of the method was evaluated in a pseudo-prospective study, showing clear superiority of the vascular wall stress analysis over the maximum diameter approach. The method was used in clinical practice for the first time during restrictions due to the COVID-19 pandemic; based on the analysis we were able to assess which AAA cases can be postponed and which had a high risk of rupture and an intervention was required despite the restrictions. The method achieved 100% sensitivity, and its specificity was also much better compared to the maximum diameter approach. The vascular wall stress analysis of AAA seems to be much more precise than the classic indication approach based only on the maximum diameter, and it can be used to determine the therapy based on patient specific parameters.