Informace o publikaci
Tension-based abdominal aortic aneurysm rupture risk assessment improves its accuracy and reduces the time of analysis
Autoři | |
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Rok publikování | 2024 |
Druh | Článek v odborném periodiku |
Časopis / Zdroj | JOURNAL OF BIOMECHANICS |
Fakulta / Pracoviště MU | |
Citace | |
www | https://www.sciencedirect.com/science/article/pii/S0021929024004068?via%3Dihub |
Doi | http://dx.doi.org/10.1016/j.jbiomech.2024.112328 |
Klíčová slova | Abdominal aortic aneurysms; Rupture risk assessment; Finite element analysis; Wall tension |
Popis | The biomechanical rupture risk assessment (BRRA) of abdominal aortic aneurysms (AAA) has higher sensitivity than maximal diameter criterion (DSEX) but its estimation is time-consuming and relies on an uncertain estimation of wall thickness. The aim of this study is to test tension-based criterion in the BRRA of AAA which removes the necessity of wall thickness measurement and should be faster. For that, we retrospectively analyzed 99 patients with intact AAA (25 females). Nineteen of them experienced a rupture later. BRRA was performed with wall tension PRRIT as a primary criterion. The ability of criterion to separate intact and ruptured AAAs at 1,3,6,9 and 12 months was estimated. Next, the receiver operating characteristics and the percentage of true negative cases for a different time to an outcome were estimated. Finally, the computational time was recorded. The results were compared to stress-based criterion PRRI and D-SEX which served as a reference. All three criterions were able to discriminate between intact and ruptured AAAs up to 9 months (p < 0.05) while none of them could do for a 12 month prediction. PRRIT exhibited a significantly higher percentage of true negatives for 12 and 9 month predictions (45 % and 20 % respectively) and similar to other criteria for other prediction times. The mean computational time for estimating PRRIT was 19 h per patient compared to 67 h for PRRI. The tension- based BRRA of AAA leads to better outcomes for a 9 and 12 month prediction while the computational time drops by more than 70 % compared to PRRI. |