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Parametric Model of Human Cerebral Aneurysms
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]The goal of this work was to create a more realistic idealized model of human cerebral aneurysms that captures all features common to arterial bifurcations and can accurately reproduce patient specific geometries. This idealized model can then be used both for parametric studies in representative cerebral aneurysm as well as for computationally efficient studies of cerebral aneurysm in specific patients. The model was extended from our previous work on parametric model of arterial bifurcations by adding the aneurysm geometry to the apex of bifurcation where it is most likely to occur. The true ‘reference’ geometry was reconstructed from CT medical images of two patients that had been diagnosed with cerebral aneurysm. The idealized model can be viewed as of the joining of two daughter vessels and a shape of an aneurysm at its apex point. The idealized model was generated via Solidworks (SolidWorks Co.). The ability of the idealized model to ‘accurately’ reproduce the geometry of a real human cerebral aneurysm was evaluated using a point wise geometric error, defined as the distance between the true and idealized model divided by the parent diameter. The maximum geometric error was less than 17.5% while the average geometric error was less than 5.8%. The distribution of WSS, wall pressure and the flow structures was qualitatively similar. © 2009 International Federation of Medical and Biological Engineering.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Arterial bifurcations,Cerebral Aneurysms,Computationally efficient,Geometric errors,Idealized models,Parametric modeling,Parametric study,Patient specific[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Cerebral Aneurysm,CFD,Parametric Model[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1007/978-3-540-92841-6_518[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]