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Towards Prediction of Blood Flow in Coiled Aneurysms Before Treatment: A Porous Media Approach
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Towards Prediction of Blood Flow in Coiled Aneurysms Before Treatment: A Porous Media Approach
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Journal Article
Towards Prediction of Blood Flow in Coiled Aneurysms Before Treatment: A Porous Media Approach
2023
Overview
Modeling blood flow in aneurysms treated with coils could be used to understand the complete embolization of the aneurysm, through thrombus formation that fills the entire sac. Modeling of the endovascular coil mass as a porous medium is a technique that allows for study of aneurysm hemodynamics, efficiently for patient-specific treatment outcome predictions. Models in the literature use mean porosity of coils in the aneurysmal volume, proving inadequate for outcome prediction. However, models that consider heterogeneous porosity distribution have shown more accurate hemodynamics. We recently published the porous crown model, considering the heterogeneous coil mass distribution, validated on two patients. This study aims (i) to validate the porous crown model for a larger cohort (eight patients), and (ii) to propose a porous medium model translatable to clinical practice in treatment planning. We analyzed the porosity distribution of the endovascular coils deployed inside the cerebral aneurysm phantoms of eight patients using 3D x-ray synchrotron images. The permeability and inertial factor of the porous crown model are calculated using previously published methodology. We propose a new “bilinear” porous model, that uses the same hypothesis, but the permeability and inertial factor can be defined from just basic information available in the neuro-suite, i.e., the aneurysmal sac volume and the coil volume fraction targeted by the neurosurgeon. These two models are compared to the coil-resolved simulations, considered as the gold standard. The results show that both the porous crown model and the bilinear model produce similarly accurate hemodynamics in the aneurysm. The error in the standard (mean porosity) porous model is 66%, whereas the error of the bilinear model is 26%, compared to the coil-resolved. The bilinear model is promising as a means of treatment outcome prediction at time of intervention.
Publisher
Springer Nature B.V
Subject
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