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Computational Fluid Dynamics‐based Virtual Angiograms for the Detection of Flow Stagnation in Intracranial Aneurysms by Sara Hadad; Yogesh Karnam; Fernando Mut; Rainald Lohner; Anne M. Robertson; Naoki Kaneko; Juan R. Cebral is a Medicine article available to read on EtoBox.
What is Computational Fluid Dynamics‐based Virtual Angiograms for the Detection of Flow Stagnation in Intracranial Aneurysms about?
## Abstract The goal of this study was to test if CFD‐based virtual angiograms could be used to automatically discriminate between intracranial aneurysms (IAs) with and without flow stagnation. Time density curves (TDC) were extracted from patient digital subtraction angiography (DSA) image sequences by computing the average gray level intensity inside the aneurysm region and used to define injection profiles for each subject. Subject‐specific 3D models were reconstructed from 3D rotational angiography (3DRA) and computational fluid dynamics (CFD) simulations were performed to simulate the blood flow inside IAs. Transport equations were solved numerically to simulate the dynamics of contrast injection into the parent arteries and IAs and then the contrast retention time (RET) was calculated. The importance of gravitational pooling of contrast agent within the aneurysm was evaluated by modeling contrast agent and blood as a mixture of two fluids with different densities and viscosities. Virtual angiograms can reproduce DSA sequences if the correct injection profile is used. RET can identify aneurysms with significant flow stagnation even when the injection profile is not known. Usin
Who reads Computational Fluid Dynamics‐based Virtual Angiograms for the Detection of Flow Stagnation in Intracranial Aneurysms?
It is typically read by researchers, students, and practitioners in Medicine.
- Author
- Sara Hadad; Yogesh Karnam; Fernando Mut; Rainald Lohner; Anne M. Robertson; Naoki Kaneko; Juan R. Cebral
- Publisher
- Wiley
- Published
- 2023
- Language
- EN
- Field
- Medicine (Health Sciences)