Document Detail


In silico vascular modeling for personalized nanoparticle delivery.
MedLine Citation:
PMID:  23199308     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
AIMS: To predict the deposition of nanoparticles in a patient-specific arterial tree as a function of the vascular architecture, flow conditions, receptor surface density and nanoparticle properties.
MATERIALS & METHODS: The patient-specific vascular geometry is reconstructed from computed tomography angiography images. The isogeometric analysis framework integrated with a special boundary condition for the firm wall adhesion of nanoparticles is implemented. A parallel plate flow chamber system is used to validate the computational model in vitro.
RESULTS: Particle adhesion is dramatically affected by changes in patient-specific attributes, such as branching angle and receptor density. The adhesion pattern correlates well with the spatial and temporal distribution of the wall shear rates. For the case considered, the larger (2.0 µm) particles adhere two-times more in the lower branches of the arterial tree, whereas the smaller (0.5 µm) particles deposit more in the upper branches.
CONCLUSION: Our computational framework in conjunction with patient-specific attributes can be used to rationally select nanoparticle properties to personalize, and thus optimize, therapeutic interventions.
Authors:
Shaolie S Hossain; Yongjie Zhang; Xinghua Liang; Fazle Hussain; Mauro Ferrari; Thomas J R Hughes; Paolo Decuzzi
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2012-12-02
Journal Detail:
Title:  Nanomedicine (London, England)     Volume:  8     ISSN:  1748-6963     ISO Abbreviation:  Nanomedicine (Lond)     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-03-12     Completed Date:  2013-09-04     Revised Date:  2014-02-04    
Medline Journal Info:
Nlm Unique ID:  101278111     Medline TA:  Nanomedicine (Lond)     Country:  England    
Other Details:
Languages:  eng     Pagination:  343-57     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Arteries / drug effects*
Computer Simulation*
Drug Delivery Systems*
Humans
Individualized Medicine
Nanoparticles / administration & dosage*,  chemistry
Grant Support
ID/Acronym/Agency:
U54 CA143837/CA/NCI NIH HHS; U54 CA151668/CA/NCI NIH HHS; U54CA143837/CA/NCI NIH HHS; U54CA151668/CA/NCI NIH HHS
Comments/Corrections

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