ArticleFrontiers in physiology2021
Prediction of Cerebral Aneurysm Hemodynamics With Porous-Medium Models of Flow-Diverting Stents via Deep Learning.
Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Systematic Review of Radiomics and Artificial Intelligence in Intracranial Aneurysm Management.Journal of neuroimaging : official journal of the American Society of NeuroimagingPooled it
- Optimizing flow-diverting stent configurations for aneurysm treatment: a computational approach integrating deep learning and differential evolution optimization.Physical and engineering sciences in medicine · 2026Article
- Physics constrained graph neural network for real time prediction of intracranial aneurysm hemodynamics.NPJ digital medicine · 2026Article
- Improving rupture status prediction for intracranial aneurysms using wall shear stress informatics.Acta neurochirurgica · 2025Article
- Prediction of time averaged wall shear stress distribution in coronary arteries' bifurcation varying in morphological features via deep learning.Frontiers in physiology · 2025Article
- Accelerated simulation methodologies for computational vascular flow modelling.Journal of the Royal Society, Interface · 2024Review
- Pulse wave-based evaluation of the blood-supply capability of patients with heart failure via machine learning.Biomedical engineering online · 2024Article
- Assessment of intracranial aneurysm rupture risk using a point cloud-based deep learning model.Frontiers in physiology · 2024Article
- Symptom clusters and unplanned hospital readmission in Chinese patients with acute myocardial infarction on admission.Frontiers in cardiovascular medicine · 2024Article
- Fluid dynamics in intracranial aneurysms treated with flow-diverting stents: effect of multiple geometrical parameters.Journal of fluid mechanics · 2023Article
- An artificial intelligence-based platform for automatically estimating time-averaged wall shear stress in the ascending aorta.European heart journal. Digital health · 2022Article
- Deep learning-based hemodynamic prediction of carotid artery stenosis before and after surgical treatments.Frontiers in physiology · 2022Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The interventional treatment of cerebral aneurysm requires hemodynamics to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in calculating cerebral aneurysm hemodynamics before and after flow-diverting (FD) stent placement. However, the complex operation (such as the construction and placement simulation of fully resolved or porous-medium FD stent) and high computational cost of CFD hinder its application. To solve these problems, we applied aneurysm hemodynamics point cloud data sets and a deep learning network with double input and sampling channels. The flexible point cloud format can represent the geometry and flow distribution of different aneurysms before and after FD stent (represented by porous medium layer) placement with high resolution. The proposed network can directly analyze the relationship between aneurysm geometry and internal hemodynamics, to further realize the flow field prediction and avoid the complex operation of CFD. Statistical analysis shows that the prediction results of hemodynamics by our deep learning method are consistent with the CFD method (error function <13%), but the calculation time is significantly reduced 1,800 times. This study develops a novel deep learning method that can accurately predict the hemodynamics of different cerebral aneurysms before and after FD stent placement with low computational cost and simple operation processes.
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