A computational modeling of blood flow in asymmetrically bifurcating microvessels and its experimental validation

2018 ◽  
Vol 34 (6) ◽  
pp. e2981
Author(s):  
Tae-Rin Lee ◽  
Ji-Ah Hong ◽  
Sung Sic Yoo ◽  
Do Wan Kim
Keyword(s):  
Blood Flow ◽  
Computational Modeling ◽  
Experimental Validation

scholarly journals Computational modeling of PET tracer distribution in solid tumors integrating microvasculature

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Niloofar Fasaeiyan ◽  
M. Soltani ◽  
Farshad Moradi Kashkooli ◽  
Erfan Taatizadeh ◽  
Arman Rahmim
Keyword(s):  
Blood Flow ◽  
Computational Modeling ◽  
Interstitial Fluid ◽  
Diffusion Reaction ◽  
Surrounding Tissue ◽  
Tissue Type ◽  
Computational Domain ◽  
Interstitial Pressure ◽  
Coupled Modeling ◽  
Tumor Region

Abstract Background We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection–Diffusion–Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues. Results Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal). Conclusion Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.

scholarly journals Metformin Is a Direct SIRT1-Activating Compound: Computational Modeling and Experimental Validation

2018 ◽  
Vol 9 ◽  
Author(s):  
Elisabet Cuyàs ◽  
Sara Verdura ◽  
Laura Llorach-Parés ◽  
Salvador Fernández-Arroyo ◽  
Jorge Joven ◽  
...  
Keyword(s):  
Computational Modeling ◽  
Experimental Validation

Numerical Simulation and Experimental Validation of Blood Flow in Arteries with Structured-Tree Outflow Conditions

2000 ◽  
Vol 28 (11) ◽  
pp. 1281-1299 ◽  
Author(s):  
Mette S. Olufsen ◽  
Charles S. Peskin ◽  
Won Yong Kim ◽  
Erik M. Pedersen ◽  
Ali Nadim ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Blood Flow ◽  
Experimental Validation

Hemodynamic analysis of blood flow in umbilical artery using computational modeling

Placenta ◽  
2017 ◽  
Vol 57 ◽  
pp. 9-12 ◽  
Author(s):  
Ruchit G. Shah ◽  
Theresa Girardi ◽  
George Merz ◽  
Phillip Necaise ◽  
Carolyn M. Salafia
Keyword(s):  
Blood Flow ◽  
Computational Modeling ◽  
Umbilical Artery

Abstract A48: Computational modeling of vessel growth and blood flow in the tumor microvasculature

2017 ◽  
Author(s):  
Tae-Rin Lee ◽  
Sung Sic Yoo ◽  
Junhong Jo ◽  
Anna Go ◽  
Hyung-Kwon Seo
Keyword(s):  
Blood Flow ◽  
Computational Modeling ◽  
Tumor Microvasculature ◽  
Vessel Growth
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