Arterial aneurysms represent a significant cause of morbidity and mortality worldwide; therefore, there is a growing need for the rapid and precise tool or method enabling to predict aneurysm emergence. The objective of this study was to develop a computer-aided method for aneurism prediction. Here we utilized a computer-based approach to establish a non-invasive, high-resolution and rapid method for the prediction of aneurysm-prone arterial segments based on combining microcomputed tomography (microCT) scanning with finite element analysis (FEA). We performed a microCT image binarization and designed a computing algorithm for FEA mesh construction, followed by application of gradient mapping and stress modeling to identify thin-walled high-stress areas responsible for the development of aneurysms. The fidelity of our computing algorithm for FEA mesh construction was similar to the commercially available software. The maximum possible error of our approach did not exceed that of either microCT or clinically available multislice computed tomography angiography scanning. Our computational approach revealed thin-walled arterial segments under a high stress, therefore potentially predicting aneurysm-prone sites. Here we demonstrate our approach for the prediction of arterial segments under a high risk of aneurysm occurrence, which should be further validated in pre-clinical models to be translated into the clinical practice.
ASJC Scopus subject areas
- Biomedical Engineering