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Nanoparticle transport and delivery in a heterogeneous pulmonary vasculature

Abstract Quantitative understanding of nanoparticles delivery in a complex vascular networks is very challenging because it involves interplay of transport, hydrodynamic force, and multivalent interactions across different scales. Heterogeneous pulmonary network includes up to 16 generations of vess... Full description

Journal Title: Journal of biomechanics 2016, Vol.50, p.240-247
Main Author: Sohrabi, Salman
Other Authors: Wang, Shunqiang , Tan, Jifu , Xu, Jiang , Yang, Jie , Liu, Yaling
Format: Electronic Article Electronic Article
Language: English
Subjects:
DNA
Quelle: Alma/SFX Local Collection
Publisher: United States: Elsevier Ltd
ID: ISSN: 0021-9290
Link: https://www.ncbi.nlm.nih.gov/pubmed/27863742
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title: Nanoparticle transport and delivery in a heterogeneous pulmonary vasculature
format: Article
creator:
  • Sohrabi, Salman
  • Wang, Shunqiang
  • Tan, Jifu
  • Xu, Jiang
  • Yang, Jie
  • Liu, Yaling
subjects:
  • Adhesion
  • Adhesion probability function
  • Air flow
  • Alveoli
  • Analysis
  • Animal models
  • Arteries
  • Article
  • Asymmetry
  • Biological Transport
  • Blood
  • Blood flow
  • Blood pressure
  • Blood vessels
  • Blood Vessels - physiology
  • Boundary conditions
  • Branches
  • Capillaries
  • Computer applications
  • Computer Simulation
  • Cystic fibrosis
  • Deoxyribonucleic acid
  • Deposition
  • DNA
  • Drug delivery
  • Drug delivery systems
  • Drugs
  • Fluid dynamics
  • Fluid flow
  • Fluids
  • Geometry
  • Hemodynamics
  • Heterogeneity
  • Heterogeneous vasculature
  • Human lung
  • Humans
  • Hydrodynamics
  • Impedance
  • Inhalation
  • Lung - blood supply
  • Lung cancer
  • Lung diseases
  • Mathematical models
  • Mathematics
  • Mechanical engineering
  • Medical imaging
  • Models, Biological
  • Nanoparticle delivery
  • Nanoparticles
  • Nanoparticles - administration & dosage
  • Nanoparticles - chemistry
  • Nanotechnology
  • Organ level drug delivery
  • Particle Size
  • Permeability
  • Physical Medicine and Rehabilitation
  • Placenta
  • Pressure distribution
  • Pulmonary arteries
  • Respiratory tract
  • Rheology
  • Simulation
  • Statistics
  • Studies
  • Tissue Distribution
  • Truncated Model
  • Vascular system
  • Vehicles
ispartof: Journal of biomechanics, 2016, Vol.50, p.240-247
description: Abstract Quantitative understanding of nanoparticles delivery in a complex vascular networks is very challenging because it involves interplay of transport, hydrodynamic force, and multivalent interactions across different scales. Heterogeneous pulmonary network includes up to 16 generations of vessels in its arterial tree. Modeling the complete pulmonary vascular system in 3D is computationally unrealistic. To save computational cost, a model reconstructed from MRI scanned images is cut into an arbitrary pathway consisting of the upper 4-generations. The remaining generations are represented by an artificially rebuilt pathway. Physiological data such as branch information and connectivity matrix are used for geometry reconstruction. A lumped model is used to model the flow resistance of the branches that are cut off from the truncated pathway. Moreover, since the nanoparticle binding process is stochastic in nature, a binding probability function is used to simplify the carrier attachment and detachment processes. The stitched realistic and artificial geometries coupled with the lumped model at the unresolved outlets are used to resolve the flow field within the truncated arterial tree. Then, the biodistribution of 200 nm, 700 nm and 2 µm particles at different vessel generations is studied. At the end, 0.2–0.5% nanocarrier deposition is predicted during one time passage of drug carriers through pulmonary vascular tree. Our truncated approach enabled us to efficiently model hemodynamics and accordingly particle distribution in a complex 3D vasculature providing a simple, yet efficient predictive tool to study drug delivery at organ level.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 0021-9290
fulltext: fulltext
issn:
  • 0021-9290
  • 1873-2380
url: Link


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descriptionAbstract Quantitative understanding of nanoparticles delivery in a complex vascular networks is very challenging because it involves interplay of transport, hydrodynamic force, and multivalent interactions across different scales. Heterogeneous pulmonary network includes up to 16 generations of vessels in its arterial tree. Modeling the complete pulmonary vascular system in 3D is computationally unrealistic. To save computational cost, a model reconstructed from MRI scanned images is cut into an arbitrary pathway consisting of the upper 4-generations. The remaining generations are represented by an artificially rebuilt pathway. Physiological data such as branch information and connectivity matrix are used for geometry reconstruction. A lumped model is used to model the flow resistance of the branches that are cut off from the truncated pathway. Moreover, since the nanoparticle binding process is stochastic in nature, a binding probability function is used to simplify the carrier attachment and detachment processes. The stitched realistic and artificial geometries coupled with the lumped model at the unresolved outlets are used to resolve the flow field within the truncated arterial tree. Then, the biodistribution of 200 nm, 700 nm and 2 µm particles at different vessel generations is studied. At the end, 0.2–0.5% nanocarrier deposition is predicted during one time passage of drug carriers through pulmonary vascular tree. Our truncated approach enabled us to efficiently model hemodynamics and accordingly particle distribution in a complex 3D vasculature providing a simple, yet efficient predictive tool to study drug delivery at organ level.
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subjectAdhesion ; Adhesion probability function ; Air flow ; Alveoli ; Analysis ; Animal models ; Arteries ; Article ; Asymmetry ; Biological Transport ; Blood ; Blood flow ; Blood pressure ; Blood vessels ; Blood Vessels - physiology ; Boundary conditions ; Branches ; Capillaries ; Computer applications ; Computer Simulation ; Cystic fibrosis ; Deoxyribonucleic acid ; Deposition ; DNA ; Drug delivery ; Drug delivery systems ; Drugs ; Fluid dynamics ; Fluid flow ; Fluids ; Geometry ; Hemodynamics ; Heterogeneity ; Heterogeneous vasculature ; Human lung ; Humans ; Hydrodynamics ; Impedance ; Inhalation ; Lung - blood supply ; Lung cancer ; Lung diseases ; Mathematical models ; Mathematics ; Mechanical engineering ; Medical imaging ; Models, Biological ; Nanoparticle delivery ; Nanoparticles ; Nanoparticles - administration & dosage ; Nanoparticles - chemistry ; Nanotechnology ; Organ level drug delivery ; Particle Size ; Permeability ; Physical Medicine and Rehabilitation ; Placenta ; Pressure distribution ; Pulmonary arteries ; Respiratory tract ; Rheology ; Simulation ; Statistics ; Studies ; Tissue Distribution ; Truncated Model ; Vascular system ; Vehicles
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descriptionAbstract Quantitative understanding of nanoparticles delivery in a complex vascular networks is very challenging because it involves interplay of transport, hydrodynamic force, and multivalent interactions across different scales. Heterogeneous pulmonary network includes up to 16 generations of vessels in its arterial tree. Modeling the complete pulmonary vascular system in 3D is computationally unrealistic. To save computational cost, a model reconstructed from MRI scanned images is cut into an arbitrary pathway consisting of the upper 4-generations. The remaining generations are represented by an artificially rebuilt pathway. Physiological data such as branch information and connectivity matrix are used for geometry reconstruction. A lumped model is used to model the flow resistance of the branches that are cut off from the truncated pathway. Moreover, since the nanoparticle binding process is stochastic in nature, a binding probability function is used to simplify the carrier attachment and detachment processes. The stitched realistic and artificial geometries coupled with the lumped model at the unresolved outlets are used to resolve the flow field within the truncated arterial tree. Then, the biodistribution of 200 nm, 700 nm and 2 µm particles at different vessel generations is studied. At the end, 0.2–0.5% nanocarrier deposition is predicted during one time passage of drug carriers through pulmonary vascular tree. Our truncated approach enabled us to efficiently model hemodynamics and accordingly particle distribution in a complex 3D vasculature providing a simple, yet efficient predictive tool to study drug delivery at organ level.
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abstractAbstract Quantitative understanding of nanoparticles delivery in a complex vascular networks is very challenging because it involves interplay of transport, hydrodynamic force, and multivalent interactions across different scales. Heterogeneous pulmonary network includes up to 16 generations of vessels in its arterial tree. Modeling the complete pulmonary vascular system in 3D is computationally unrealistic. To save computational cost, a model reconstructed from MRI scanned images is cut into an arbitrary pathway consisting of the upper 4-generations. The remaining generations are represented by an artificially rebuilt pathway. Physiological data such as branch information and connectivity matrix are used for geometry reconstruction. A lumped model is used to model the flow resistance of the branches that are cut off from the truncated pathway. Moreover, since the nanoparticle binding process is stochastic in nature, a binding probability function is used to simplify the carrier attachment and detachment processes. The stitched realistic and artificial geometries coupled with the lumped model at the unresolved outlets are used to resolve the flow field within the truncated arterial tree. Then, the biodistribution of 200 nm, 700 nm and 2 µm particles at different vessel generations is studied. At the end, 0.2–0.5% nanocarrier deposition is predicted during one time passage of drug carriers through pulmonary vascular tree. Our truncated approach enabled us to efficiently model hemodynamics and accordingly particle distribution in a complex 3D vasculature providing a simple, yet efficient predictive tool to study drug delivery at organ level.
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