ArticleActa neurochirurgica2018
Development of a statistical model for discrimination of rupture status in posterior communicating artery aneurysms.
Article in Acta neurochirurgica, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 32 citations in OpenAlex.
- Computational Fluid Dynamics Analysis of Cerebrovascular Hemodynamic Differences in Adults with Sickle Cell Disease: Comparing Stroke and Non-Stroke Cohorts.Annals of biomedical engineering · 2026Article
- Machine Learning-based Prediction of Temporal Velocity-Informatics (TVI) Variables for Accelerated Characterization of Intracranial Aneurysms' Rupture Status.Journal of cardiovascular translational research · 2025Article
- Improving Prediction of Intracranial Aneurysm Rupture Status Using Temporal Velocity-Informatics.Annals of biomedical engineering · 2025Article
- Improving rupture status prediction for intracranial aneurysms using wall shear stress informatics.Acta neurochirurgica · 2025Article
- Fluid structure Interaction analysis for rupture risk assessment in patients with middle cerebral artery aneurysms.Scientific reports · 2025Article
- Computational fluid dynamics and shape analysis enhance aneurysm rupture risk stratification.International journal of computer assisted radiology and surgery · 2025Article
- Rupture risk assessment for AComA aneurysms with morphological, hemodynamic and structural mechanical analysis.PloS one · 2025Article
- Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study.Scientific reports · 2024Article
- Fluid-Structure Interaction Simulations of the Initiation Process of Cerebral Aneurysms.Brain sciences · 2024Article
- Augmenting Prediction of Intracranial Aneurysms' Risk Status Using Velocity-Informatics: Initial Experience.Journal of cardiovascular translational research · 2023Article
- Characterizing Intracranial Hemodynamics in Sickle Cell Anemia: Impact of Patient-Specific Viscosity.Cardiovascular engineering and technology · 2022Article
- An Integrated Model Combining Machine Learning and Deep Learning Algorithms for Classification of Rupture Status of IAs.Frontiers in neurology · 2022Article
- Hemodynamics of Cerebral Aneurysms: Connecting Medical Imaging and Biomechanical Analysis.Annual review of biomedical engineering · 2020Review
- Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-phase II: rupture risk assessment.International journal of computer assisted radiology and surgery · 2019Article
- Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): uncertainty quantification of geometric rupture risk parameters.Biomedical engineering online · 2019Article
- Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-Phase Ib: Effect of morphology on hemodynamics.PloS one · 2019Article
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Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundIntracranial aneurysms at the posterior communicating artery (PCOM) are known to have high rupture rates compared to other locations. We developed and internally validated a statistical model discriminating between ruptured and unruptured PCOM aneurysms based on hemodynamic and geometric parameters, angio-architectures, and patient age with the objective of its future use for aneurysm risk assessment.
methodsA total of 289 PCOM aneurysms in 272 patients modeled with image-based computational fluid dynamics (CFD) were used to construct statistical models using logistic group lasso regression. These models were evaluated with respect to discrimination power and goodness of fit using tenfold nested cross-validation and a split-sample approach to mimic external validation.
resultsThe final model retained maximum and minimum wall shear stress (WSS), mean parent artery WSS, maximum and minimum oscillatory shear index, shear concentration index, and aneurysm peak flow velocity, along with aneurysm height and width, bulge location, non-sphericity index, mean Gaussian curvature, angio-architecture type, and patient age. The corresponding area under the curve (AUC) was 0.8359. When omitting data from each of the three largest contributing hospitals in turn, and applying the corresponding model on the left-out data, the AUCs were 0.7507, 0.7081, and 0.5842, respectively.
conclusionsStatistical models based on a combination of patient age, angio-architecture, hemodynamics, and geometric characteristics can discriminate between ruptured and unruptured PCOM aneurysms with an AUC of 84%. It is important to include data from different hospitals to create models of aneurysm rupture that are valid across hospital populations.
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