ArticleScientific reports2025
Morphology and biomechanical index predict the rupture location and rupture risk of abdominal aortic aneurysm.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Predictive Value of Imaging-Based Classifications for Conservative Management Failure in Isolated Superior Mesenteric Artery Dissection.JACC. Asia · 2026Article
- A multimodal deep learning model for predicting impending rupture in symptomatic abdominal aortic aneurysms using CTA and clinical data.Frontiers in cardiovascular medicine · 2026Article
- Article
- [Efficacy and prognostic factors of open surgical repair and endovascular repair in patients with ruptured abdominal aortic aneurysm].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- Cracking the Kinase Code: Urinary Biomarkers as Early Alarms for AAA Rupture-A Pilot Study.Journal of clinical medicine · 2025Article
- Developing a LASSO Regression-Based Nomogram to Predict Outcomes in Abdominal Aortic Aneurysm Patients Post-Endovascular Aneurysm Repair.Clinical interventions in aging · 2025Article
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11 authors.
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Abstract
The integration of biomechanical and morphological analyses holds tremendous potential for assessing the rupture risk of abdominal aortic aneurysms (AAA). We employed a one-way fluid-structure interaction (FSI) model to distinguish between ruptured AAA (RAAA) and asymptomatic intact AAA (IAAA), focusing on morphological and computational fluid dynamics (CFD) indices. Patient groups with ruptured RAAA and asymptomatic IAAA were matched by diameter, age, and sex. AAA morphology was analyzed via CT segmentation, and biomechanical indices-including wall shear stress (WSS), peak wall stress (PWS), maximum deformation (MD), and other indices-were determined using FSI analysis. Statistical comparisons were performed using paired t-tests or Wilcoxon rank sum tests. Multivariate and LASSO regression analyses identified predictive factors, and a nomogram was developed. Model accuracy was assessed using the area under the curve (AUC). In our study with 66 RAAA and 66 asymptomatic IAAA patients, the tortuosity of the RAAAs was 1.4 times that of the asymptomatic IAAAs (P = 0.0005). The PWS, MD and peak wall rupture index (PWRI) of the RAAAs was 1.18, 1.32 and 1.27 times that of the asymptomatic IAAAs (P = 0.0158, 0.0036, 0.0071). The MD position demonstrated high consistency with RAAA rupture locations (94.12%). Four variables were selected for a nomogram, predicting AAA rupture with an AUC of 0.7604 (95% CI 0.6653-0.8556) and an internal validation AUC of 0.8051 (95% CI 0.6400-0.9703). In this study, we demonstrated that the location of MD is valuable for predicting the rupture location of AAA. We constructed a nomogram incorporating four key predictors-aortic neck length (ANL), intraluminal thrombus volume relative to AAA volume (VILT/VAAA), tortuosity, and MD-that enhances the prediction of AAA rupture risk, offering a more personalized assessment beyond traditional diameter-based methods.
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