Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms

This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in “patient-specific” geometries, using computational fluid dynami...

Full description

Bibliographic Details
Main Authors: Kevin Sunderland, Christopher Haferman, Gouthami Chintalapani, Jingfeng Jiang
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Computational and Mathematical Methods in Medicine
Online Access:http://dx.doi.org/10.1155/2016/7406215
id doaj-8c7c7ec651ab457289af798ba518e70f
record_format Article
spelling doaj-8c7c7ec651ab457289af798ba518e70f2020-11-24T23:18:47ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182016-01-01201610.1155/2016/74062157406215Vortex Analysis of Intra-Aneurismal Flow in Cerebral AneurysmsKevin Sunderland0Christopher Haferman1Gouthami Chintalapani2Jingfeng Jiang3Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USADepartment of Biomedical Engineering, Michigan Technological University, Houghton, MI, USASiemens Medical Solution USA, Inc., Heffernan Estate, IL, USADepartment of Biomedical Engineering, Michigan Technological University, Houghton, MI, USAThis study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in “patient-specific” geometries, using computational fluid dynamics (CFD) simulations. Modified versions of known λ2 and Q-criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments.http://dx.doi.org/10.1155/2016/7406215
collection DOAJ
language English
format Article
sources DOAJ
author Kevin Sunderland
Christopher Haferman
Gouthami Chintalapani
Jingfeng Jiang
spellingShingle Kevin Sunderland
Christopher Haferman
Gouthami Chintalapani
Jingfeng Jiang
Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms
Computational and Mathematical Methods in Medicine
author_facet Kevin Sunderland
Christopher Haferman
Gouthami Chintalapani
Jingfeng Jiang
author_sort Kevin Sunderland
title Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms
title_short Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms
title_full Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms
title_fullStr Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms
title_full_unstemmed Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms
title_sort vortex analysis of intra-aneurismal flow in cerebral aneurysms
publisher Hindawi Limited
series Computational and Mathematical Methods in Medicine
issn 1748-670X
1748-6718
publishDate 2016-01-01
description This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in “patient-specific” geometries, using computational fluid dynamics (CFD) simulations. Modified versions of known λ2 and Q-criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments.
url http://dx.doi.org/10.1155/2016/7406215
work_keys_str_mv AT kevinsunderland vortexanalysisofintraaneurismalflowincerebralaneurysms
AT christopherhaferman vortexanalysisofintraaneurismalflowincerebralaneurysms
AT gouthamichintalapani vortexanalysisofintraaneurismalflowincerebralaneurysms
AT jingfengjiang vortexanalysisofintraaneurismalflowincerebralaneurysms
_version_ 1725580094870650880