Blood Flow Modeling in a Synthetic Cylindrical Vessel for Validating Methods of Vessel Segmentation in MRA Images

2013 ◽  
pp. 601-610
Author(s):  
Grzegorz Dwojakowski ◽  
Artur Klepaczko ◽  
Andrzej Materka
Keyword(s):  
Blood Flow ◽  
Vessel Segmentation ◽  
Cylindrical Vessel ◽  
Flow Modeling ◽  
Blood Flow Modeling

scholarly journals Dynamics of blood flow: modeling of the Fåhræus–Lindqvist effect

2015 ◽  
Vol 41 (3) ◽  
pp. 313-326 ◽  
Author(s):  
Rachid Chebbi
Keyword(s):  
Blood Flow ◽  
Flow Modeling ◽  
Blood Flow Modeling

Abstract 16856: Mathematical Modeling of Blood Flow to Evaluate the Hemodynamic Significance of Peripheral Vascular Lesions

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Seyed Mehran Mirramezani ◽  
Paul Cimadomo ◽  
Ernie Ahsan ◽  
David Shavelle ◽  
Leonardo Clavijo ◽  
...  
Keyword(s):  
Blood Flow ◽  
Pressure Gradient ◽  
Ankle Brachial Index ◽  
Peripheral Arteries ◽  
Flow Modeling ◽  
Peripheral Vascular ◽  
Blood Flow Modeling ◽  
Resting Pressure ◽  
Grade Iii ◽  
Significant Lesion

Introduction: Evaluating the severity of lesions in peripheral arteries is challenging. Image-based blood flow modeling from peripheral computed tomographic angiography (pCTA) may provide a non-invasive method to determine the hemodynamic significance of lesions. The objective of this study was to evaluate the diagnostic performance of a trans-lesion pressure drop computed from pCTA-based blood flow modeling in the peripheral arteries. Methods: Ten patients undergoing digital subtraction angiography (DSA) and pCTA were included. The peripheral arteries were divided into 8 segments per extremity and stenosis severity was visually graded by DSA as non-stenosed (grade 0), mild (grade I), moderate (grade II), severe (grade III), occluded (grade IV) or non-evaluable. A functionally significant lesion was defined as grade III or IV by DSA. Independent from the DSA review, a resting pressure gradient (rPG) and exercise PG (ExPG) for each segment was calculated from pCTA-based blood flow modeling (Figure), and a functionally significant lesion was defined as having an rPG > 5 mm Hg or an ExPG > 20 mm Hg. Results: Mean age was 52±16 years, 4 patients (40%) were male, 8 patients (80%) presented with critical limb ischemia, mean ankle brachial index was 0.60±0.29 and 66 arterial segments were available for both assessment methods. Twenty-two segments had functionally significant lesions by DSA. For rPG, sensitivity was 80%, specificity was 85% and accuracy was 79% with DSA as the standard; for ExPG, sensitivity was 84%, specificity was 89% and accuracy was 88%. Conclusions: Use of a resting pressure gradient > 5 mm Hg and an exercise pressure gradient > 20 mm Hg measured by peripheral computed tomography-based blood flow modeling accurately identifies functionally significant stenosis in patients with advanced peripheral vascular disease. These results support a prospective imaging trial to further validate this novel approach.

scholarly journals Blood flow modeling with a gemo-library in the FlowVision software complex

2020 ◽  
Vol 747 ◽  
pp. 012071
Author(s):  
E E Ovsyannikova ◽  
D P Silaev ◽  
V S Kashirin
Keyword(s):  
Blood Flow ◽  
Flow Modeling ◽  
Software Complex ◽  
Blood Flow Modeling

scholarly journals Experimental Validation of Microvasculature Blood Flow Modeling by Diffuse Correlation Spectroscopy

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 15945-15951
Author(s):  
Yanwen Zhu ◽  
Zhiguo Gui ◽  
Bing Xue ◽  
Yu Shang
Keyword(s):  
Blood Flow ◽  
Experimental Validation ◽  
Correlation Spectroscopy ◽  
Flow Modeling ◽  
Diffuse Correlation Spectroscopy ◽  
Blood Flow Modeling

Blood Flow Modeling with Microcapsular Suspensions

1969 ◽  
Vol 8 (4) ◽  
pp. 615-620 ◽  
Author(s):  
R. M. Navari ◽  
J. L. Gainer ◽  
O. L. Updike
Keyword(s):  
Blood Flow ◽  
Flow Modeling ◽  
Blood Flow Modeling

Metabolic and hormonal blood flow modeling in patients with coronary heart disease: In vitro and clinical study

2007 ◽  
Vol 22 (3) ◽  
pp. 173-184 ◽  
Author(s):  
Lidia I. Malinova ◽  
Georgy V. Simonenko ◽  
Tatyana P. Denisova ◽  
Valery V. Tuchin
Keyword(s):  
Coronary Heart Disease ◽  
Blood Flow ◽  
Heart Disease ◽  
Clinical Study ◽  
Flow Modeling ◽  
Blood Flow Modeling

scholarly journals Cerebral Blood Flow Modeling in Primate Cortex

2010 ◽  
Vol 30 (11) ◽  
pp. 1860-1873 ◽  
Author(s):  
Romain Guibert ◽  
Caroline Fonta ◽  
Franck Plouraboué
Keyword(s):  
Blood Flow ◽  
Phase Separation ◽  
Boundary Conditions ◽  
Blood Rheology ◽  
Detailed Comparison ◽  
Flow Modeling ◽  
Separation Effect ◽  
Essential Components ◽  
Blood Flow Modeling ◽  
The Impact

We report new results on blood flow modeling over large volumes of cortical gray matter of primate brain. We propose a network method for computing the blood flow, which handles realistic boundary conditions, complex vessel shapes, and complex nonlinear blood rheology. From a detailed comparison of the available models for the blood flow rheology and the phase separation effect, we are able to derive important new results on the impact of network structure on blood pressure, hematocrit, and flow distributions. Our findings show that the network geometry (vessel shapes and diameters), the boundary conditions associated with the arterial inputs and venous outputs, and the effective viscosity of the blood are essential components in the flow distribution. In contrast, we show that the phase separation effect has a minor function in the global microvascular hemodynamic behavior. The behavior of the pressure, hematocrit, and blood flow distributions within the network are described through the depth of the primate cerebral cortex and are discussed.

scholarly journals From whole-organ imaging to in-silico blood flow modeling: A new multi-scale network analysis for revisiting tissue functional anatomy

2020 ◽  
Vol 16 (2) ◽  
pp. e1007322
Author(s):  
Pol Kennel ◽  
Jules Dichamp ◽  
Corinne Barreau ◽  
Christophe Guissard ◽  
Lise Teyssedre ◽  
...  
Keyword(s):  
Blood Flow ◽  
Network Analysis ◽  
In Silico ◽  
Functional Anatomy ◽  
Flow Modeling ◽  
Multi Scale ◽  
Blood Flow Modeling ◽  
Scale Network
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