ArticleActa neurochirurgica2021
Quantitative analysis of flow vortices: differentiation of unruptured and ruptured medium-sized middle cerebral artery aneurysms.
Article in Acta neurochirurgica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Radiomics and Artificial Intelligence in Intracranial Aneurysm Management.Journal of neuroimaging : official journal of the American Society of NeuroimagingPooled it
- Predictive models for trans-stenotic pressure gradient in the transverse sinus based on multimodal correlates.Quantitative imaging in medicine and surgery · 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
- Machine learning models for predicting transstenotic pressure gradient based on computed tomography angiography features.Quantitative imaging in medicine and surgery · 2025Article
- Correlations between hemodynamics and radiomic features in thrombosed intracranial aneurysms.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
- Improving Prediction of Intracranial Aneurysm Rupture Status Using Temporal Velocity-Informatics.Annals of biomedical engineering · 2025Article
- Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study.Scientific reports · 2024Article
- Computational Hemodynamics-Based Growth Prediction for Small Abdominal Aortic Aneurysms: Laminar Simulations Versus Large Eddy Simulations.Annals of biomedical engineering · 2024Article
- Augmenting Prediction of Intracranial Aneurysms' Risk Status Using Velocity-Informatics: Initial Experience.Journal of cardiovascular translational research · 2023Article
- Deep-learning-based image segmentation for image-based computational hemodynamic analysis of abdominal aortic aneurysms: a comparison study.Biomedical physics & engineering express · 2023Article
- Computerized Differentiation of Growth Status for Abdominal Aortic Aneurysms: A Feasibility Study.Journal of cardiovascular translational research · 2023Article
- USING CONVOLUTIONAL NEURAL NETWORK-BASED SEGMENTATION FOR IMAGE-BASED COMPUTATIONAL FLUID DYNAMICS SIMULATIONS OF BRAIN ANEURYSMS: INITIAL EXPERIENCE IN AUTOMATED MODEL CREATION.Journal of mechanics in medicine and biology · 2023Article
- Can we explain machine learning-based prediction for rupture status assessments of intracranial aneurysms?Biomedical physics & engineering express · 2023Article
- Impact of spatial and temporal stability of flow vortices on vascular endothelial cells.Biomechanics and modeling in mechanobiology · 2023Article
- An attention residual u-net with differential preprocessing and geometric postprocessing: Learning how to segment vasculature including intracranial aneurysms.Medical image analysis · 2023Article
- S-Net: a multiple cross aggregation convolutional architecture for automatic segmentation of small/thin structures for cardiovascular applications.Frontiers in physiology · 2023Article
- Disturbed flow's impact on cellular changes indicative of vascular aneurysm initiation, expansion, and rupture: A pathological and methodological review.Journal of cellular physiology · 2022Review
- An Integrated Model Combining Machine Learning and Deep Learning Algorithms for Classification of Rupture Status of IAs.Frontiers in neurology · 2022Article
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7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSurgical intervention for unruptured intracranial aneurysms (IAs) carries inherent health risks. The analysis of "patient-specific" IA geometric and computational fluid dynamics (CFD) simulated wall shear stress (WSS) data has been investigated to differentiate IAs at high and low risk of rupture to help clinical decision making. Yet, outcomes vary among studies, suggesting that novel analysis could improve rupture characterization. The authors describe a CFD analytic method to assess spatiotemporal characteristics of swirling flow vortices within IAs to improve characterization.
methodsCFD simulations were performed for 47 subjects harboring one medium-sized (4-10 mm) middle cerebral artery (MCA) aneurysm with available 3D digital subtraction angiography data. Alongside conventional indices, quantified IA flow vortex spatiotemporal characteristics were applied during statistical characterization. Statistical supervised machine learning using a support vector machine (SVM) method was run with cross-validation (100 iterations) to assess flow vortex-based metrics' strength toward rupture characterization.
resultsRelying solely on vortex indices for statistical characterization underperformed compared with established geometric characteristics (total accuracy of 0.77 vs 0.80) yet showed improvements over wall shear stress models (0.74). However, the application of vortex spatiotemporal characteristics into the combined geometric and wall shear stress parameters augmented model strength for assessing the rupture status of middle cerebral artery aneurysms (0.85).
conclusionsThis preliminary study suggests that the spatiotemporal characteristics of flow vortices within MCA aneurysms are of value to improve the differentiation of ruptured aneurysms from unruptured ones.
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