ArticleNeurosurgery2020
A Simple Flow Classification Parameter Can Discriminate Rupture Status in Intracranial Aneurysms.
Article in Neurosurgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 10 citations in OpenAlex.
- Verification of a simplified aneurysm dimensionless flow parameter to predict intracranial aneurysm rupture status.The British journal of radiology · 2024Article
- Bio-inspired microfluidics: A review.Biomicrofluidics · 2023Review
- Patient-Specific Cerebral Blood Flow Simulation Based on Commonly Available Clinical Datasets.Frontiers in bioengineering and biotechnology · 2022Article
- Mesenchymal stem cell spheroids alleviate neuropathic pain by modulating chronic inflammatory response genes.Frontiers in immunology · 2022Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
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Abstract
backgroundA simple dimensionless aneurysm number ($An$), which depends on geometry and flow pulsatility, was previously shown to distinguish the flow mode in intracranial aneurysms (IA): vortex mode with a dynamic vortex formation/evolution if $An > 1$, and cavity mode with a steady shear layer if $An < 1$.
objectiveTo hypothesize that $An\ > \ 1$ can distinguish rupture status because vortex mode is associated with high oscillatory shear index, which, in turn, is statistically associated with rupture.
methodsThe above hypothesis is tested on a retrospective, consecutively collected database of 204 patient-specific IAs. The first 119 cases are assigned to training and the remainder to testing dataset. $An$ is calculated based on the pulsatility index (PI) approximated either from the literature or solving an optimization problem (denoted as$\ \widehat {PI}$). Student's t-test and logistic regression (LR) are used for hypothesis testing and data fitting, respectively.
results$An$ can significantly discriminate ruptured and unruptured status with 95% confidence level (P < .0001). $An$ (using PI) and $\widehat {An}$ (using $\widehat {PI}$) significantly predict the ruptured IAs (for training dataset $An\!:\ $AUC = 0.85, $\widehat {An}\!:\ $AUC = 0.90, and for testing dataset $An\!:\ $sensitivity = 94%, specificity = 33%, $\widehat {An}\!:\ $sensitivity = 93.1%, specificity = 52.85%).
conclusion$An > 1$ predicts ruptured status. Unlike traditional hemodynamic parameters such as wall shear stress and oscillatory shear index, $An$ has a physical threshold of one (does not depend on statistical analysis) and does not require time-consuming flow simulations. Therefore, $An$ is a simple, practical discriminator of IA rupture status.
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