ArticleInternational journal of computer assisted radiology and surgery2018
Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics.
Article in International journal of computer assisted radiology and surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.
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Who cites it
55 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Algorithms to Predict the Risk of Rupture of Intracranial Aneurysms: a Systematic Review.Clinical neuroradiology · 2025Pooled it
- Insights into the Mechanisms Underlying the Lower Rupture Risk of Paraclinoid Aneurysms: a Comparative Analysis with Other Aneurysm Locations.Clinical neuroradiology · 2026Article
- GN-Net: A Geometric and Neighborhood-Aware Network for Predicting Intracranial Aneurysm Rupture Risk and Assisting Clinical Decision-Making.Interdisciplinary sciences, computational life sciences · 2026Article
- Investigation of Contrast Retention in PCOM Aneurysms as a Possible Marker for Instability and Rupture.International journal for numerical methods in biomedical engineering · 2026Article
- Computational Framework for Modeling Effects of Brain Collateral Circulation.International journal for numerical methods in biomedical engineering · 2025Article
- Predicting Cerebral Aneurysm Rupture: The Role of Computational Fluid Dynamics.Neuroimaging clinics of North America · 2025Review
- Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture.Scientific reports · 2025Article
- Imaging of Intracranial Aneurysms: A Review of Standard and Advanced Imaging Techniques.Translational stroke research · 2025Review
- Discriminators of Paraclinoid Aneurysm Rupture Based On Morphological Computer-Assisted Semiautomated Measurement (CASAM) and Hemodynamic Analysis.Clinical neuroradiology · 2025Article
- Hemodynamic analysis of thrombosed intracranial aneurysms: a comparative correlation study.Neurosurgical review · 2025Article
- Investigating the role of blood models in predicting rupture status of intracranial aneurysms.Biomedical physics & engineering express · 2025Article
- Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks.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
- Predictions of Small Intracranial Aneurysms' Rupture Risk with Ensemble Machine Learning Model (Super Learner): A Retrospective Study in Two Tertiary Hospitals in China.International journal of general medicine · 2025Article
- Rupture risk assessment for AComA aneurysms with morphological, hemodynamic and structural mechanical analysis.PloS one · 2025Article
- Computational fluid dynamics and shape analysis enhance aneurysm rupture risk stratification.International journal of computer assisted radiology and surgery · 2025Article
- Comparison of Flow Reduction Efficacy of Nominal and Oversized Flow Diverters Using a Novel Measurement-assisted in Silico Method.Clinical neuroradiology · 2024Article
- A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning.Scientific reports · 2024Article
- Image-based hemodynamic simulations for intracranial aneurysms: the impact of complex vasculature.International journal of computer assisted radiology and surgery · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
purposeUnruptured cerebral aneurysms pose a dilemma for physicians who need to weigh the risk of a devastating subarachnoid hemorrhage against the risk of surgery or endovascular treatment and their complications when deciding on a treatment strategy. A prediction model could potentially support such treatment decisions. The aim of this study was to develop and internally validate a model for aneurysm rupture based on hemodynamic and geometric parameters, aneurysm location, and patient gender and age.
methodsCross-sectional data from 1061 patients were used for image-based computational fluid dynamics and shape characterization of 1631 aneurysms for training an aneurysm rupture probability model using logistic group Lasso regression. The model's discrimination and calibration were internally validated based on the area under the curve (AUC) of the receiver operating characteristic and calibration plots.
resultsThe final model retained 11 hemodynamic and 12 morphological variables, aneurysm location, as well as patient age and gender. An adverse hemodynamic environment characterized by a higher maximum oscillatory shear index, higher kinetic energy and smaller low shear area as well as a more complex aneurysm shape, male gender and younger age were associated with an increased rupture risk. The corresponding AUC of the model was 0.86 (95% CI [0.85, 0.86], after correction for optimism 0.84).
conclusionThe model combining variables from various domains was able to discriminate between ruptured and unruptured aneurysms with an AUC of 86%. Internal validation indicated potential for the application of this model in clinical practice after evaluation with longitudinal data.
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