Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study

Abstract Intracranial aneurysms (IA) pose significant health risks and are often challenging to manage. Computational fluid dynamics (CFD) simulation has emerged as a powerful tool for understanding lesion-specific hemodynamics in and around IAs, aiding in the clinical management of patients with an...

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Main Authors: Mostafa Rezaeitaleshmahalleh, Nan Mu, Zonghan Lyu, Joseph Gemmete, Aditya Pandey, Jingfeng Jiang
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-024-80891-4
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author Mostafa Rezaeitaleshmahalleh
Nan Mu
Zonghan Lyu
Joseph Gemmete
Aditya Pandey
Jingfeng Jiang
author_facet Mostafa Rezaeitaleshmahalleh
Nan Mu
Zonghan Lyu
Joseph Gemmete
Aditya Pandey
Jingfeng Jiang
author_sort Mostafa Rezaeitaleshmahalleh
collection DOAJ
description Abstract Intracranial aneurysms (IA) pose significant health risks and are often challenging to manage. Computational fluid dynamics (CFD) simulation has emerged as a powerful tool for understanding lesion-specific hemodynamics in and around IAs, aiding in the clinical management of patients with an IA. However, the current workflow of CFD simulations is time-consuming, complex, and labor-intensive and, thus, does not fit the clinical environment. To address these challenges, we have developed a semi-automated pipeline integrating multiple open-source software packages to streamline the CFD simulation process. Specifically, the study utilized medical angiography data from 18 patients. An in-house open-source DL image segmentation model (ARU-Net) was employed to generate 3D computer models of the anterior circulation. The segmented intracranial vasculature models, including IAs, were further refined using the Vascular Modeling Toolkit (VMTK), an open-source Python package. This step involved smoothing the surface of the models and extending the inlet and outlet regions to ensure a realistic representation of the vascular geometry. The refined vascular models were then converted into computational meshes using an open-source mesh generator known as TetGen. This process was nearly automated and required minimal user interaction(s). Blood flow simulations of the cerebral vascular models were performed using established SimVascular solvers (an open-source finite element platform for vascular applications) through an application programming interface (API). The CFD simulation process was also conducted using the manual workflow for comparative purposes. The initial assessment compared the geometries derived from manual and DL-based segmentation. The DL-based segmentation demonstrated reliable performance, closely aligning with manually segmented results, evidenced by excellent Pearson correlation coefficient (PCC) values and low relative difference (RD) values ranging from 3% to 10% between the computed geometrical variables derived from both methods. The statistical analysis of the computed hemodynamic variables, including velocity informatics and WSS-related variables, indicated good to excellent reliability for most parameters (e.g., ICC of 0.85–0.95). Given the data investigated, the proposed automated workflow streamlines the process of conducting CFD simulations. It generates results consistent with the current standard manual CFD protocol while minimizing dependence on user input.
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spelling doaj-art-b203e6766cae47b49b5427bda1b2d7212024-12-08T12:26:08ZengNature PortfolioScientific Reports2045-23222024-12-0114112110.1038/s41598-024-80891-4Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility studyMostafa Rezaeitaleshmahalleh0Nan Mu1Zonghan Lyu2Joseph Gemmete3Aditya Pandey4Jingfeng Jiang5Department of Biomedical Engineering, Michigan Technological UniversityDepartment of Biomedical Engineering, Michigan Technological UniversityDepartment of Biomedical Engineering, Michigan Technological UniversityDepartment of Radiology, University of Michigan Medical CenterDepartment of Radiology, University of Michigan Medical CenterDepartment of Biomedical Engineering, Michigan Technological UniversityAbstract Intracranial aneurysms (IA) pose significant health risks and are often challenging to manage. Computational fluid dynamics (CFD) simulation has emerged as a powerful tool for understanding lesion-specific hemodynamics in and around IAs, aiding in the clinical management of patients with an IA. However, the current workflow of CFD simulations is time-consuming, complex, and labor-intensive and, thus, does not fit the clinical environment. To address these challenges, we have developed a semi-automated pipeline integrating multiple open-source software packages to streamline the CFD simulation process. Specifically, the study utilized medical angiography data from 18 patients. An in-house open-source DL image segmentation model (ARU-Net) was employed to generate 3D computer models of the anterior circulation. The segmented intracranial vasculature models, including IAs, were further refined using the Vascular Modeling Toolkit (VMTK), an open-source Python package. This step involved smoothing the surface of the models and extending the inlet and outlet regions to ensure a realistic representation of the vascular geometry. The refined vascular models were then converted into computational meshes using an open-source mesh generator known as TetGen. This process was nearly automated and required minimal user interaction(s). Blood flow simulations of the cerebral vascular models were performed using established SimVascular solvers (an open-source finite element platform for vascular applications) through an application programming interface (API). The CFD simulation process was also conducted using the manual workflow for comparative purposes. The initial assessment compared the geometries derived from manual and DL-based segmentation. The DL-based segmentation demonstrated reliable performance, closely aligning with manually segmented results, evidenced by excellent Pearson correlation coefficient (PCC) values and low relative difference (RD) values ranging from 3% to 10% between the computed geometrical variables derived from both methods. The statistical analysis of the computed hemodynamic variables, including velocity informatics and WSS-related variables, indicated good to excellent reliability for most parameters (e.g., ICC of 0.85–0.95). Given the data investigated, the proposed automated workflow streamlines the process of conducting CFD simulations. It generates results consistent with the current standard manual CFD protocol while minimizing dependence on user input.https://doi.org/10.1038/s41598-024-80891-4Computational fluid dynamicsIntracranial aneurysmSimVascularVelocity-informatics
spellingShingle Mostafa Rezaeitaleshmahalleh
Nan Mu
Zonghan Lyu
Joseph Gemmete
Aditya Pandey
Jingfeng Jiang
Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study
Scientific Reports
Computational fluid dynamics
Intracranial aneurysm
SimVascular
Velocity-informatics
title Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study
title_full Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study
title_fullStr Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study
title_full_unstemmed Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study
title_short Developing a nearly automated open-source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature: a feasibility study
title_sort developing a nearly automated open source pipeline for conducting computational fluid dynamics simulations in anterior brain vasculature a feasibility study
topic Computational fluid dynamics
Intracranial aneurysm
SimVascular
Velocity-informatics
url https://doi.org/10.1038/s41598-024-80891-4
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