Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/98386
Title: | Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images |
Author(s): | Niemann, Annika Voß, Samuel Tulamo, Riikka Weigand, Simon Preim, Bernhard Berg, Philipp Saalfeld, Sylvia |
Issue Date: | 2021 |
Type: | Article |
Language: | English |
URN: | urn:nbn:de:gbv:ma9:1-1981185920-1003427 |
Subjects: | Intracranial aneurysms Aneurysm wall Histologic images Structural simulation |
Abstract: | Purpose For the evaluation and rupture risk assessment of intracranial aneurysms, clinical,morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall. Methods In this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations. Result We presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious. Conclusion The presented approach enables the creation of a geometricmodel with differentiatedwall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy. |
URI: | https://opendata.uni-halle.de//handle/1981185920/100342 http://dx.doi.org/10.25673/98386 |
Open Access: | Open access publication |
License: | (CC BY 4.0) Creative Commons Attribution 4.0 |
Sponsor/Funder: | Projekt DEAL 2021 |
Journal Title: | International journal of computer assisted radiology and surgery |
Publisher: | Springer |
Publisher Place: | Berlin |
Volume: | 16 |
Issue: | 4 |
Original Publication: | 10.1007/s11548-021-02334-z |
Page Start: | 597 |
Page End: | 607 |
Appears in Collections: | Fakultät für Informatik (OA) |
Files in This Item:
File | Description | Size | Format | |
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Niemann et al._Complex wall_2021.pdf | Zweitveröffentlichung | 3.4 MB | Adobe PDF | View/Open |