Hematocrit Distribution and Tissue Oxygenation in Large Microcirculatory Networks

Gould, Ian Gopal; Linninger, Andreas A.

doi:10.1111/micc.12156

Cited by 81 publications

(140 citation statements)

References 69 publications

Supporting

Mentioning

135

Contrasting

Order By: Relevance

“…However, an investigation and verification of the usefulness of Voronoi tessellations to describe oxygenation volumes in 3D problems has not yet been conducted and remains to be shown. Most image-based models of tissue oxygen perfusion are based on 2D image data, and namely on histological images [65,139,142]. This is mainly due to the lack of relevant 3D datasets and/or efforts to reduce computing time.…”

Section: Image-based Modellingmentioning

confidence: 99%

“…In theoretical mathematical modelling the important role of the RBCs has long been taken into account; some models consider RBCs as point-like oxygen sources [14], while others assume separate homogeneous flowing regions of plasma and RBCs [149,150]. Gould & Linninger [65] reviewed such existing models against morphological data of vascular trees and as a result, presented a working model of haematocrit distribution. For image-based modelling of oxygen supply in tissue, this leaves two alternatives: firstly, to image the blood vessel structure and to employ a haematocrit distribution model to correctly predict oxygen delivery; or secondly, in addition to imaging the vascular structure, using an imaging technique capable of identifying RBCs within the vasculature.…”

Section: Limitation 1: Role Of the Haematocritmentioning

confidence: 99%

See 1 more Smart Citation

Image-based modelling of skeletal muscle oxygenation

Zeller‐Plumhoff

Roose

Clough

et al. 2017

J. R. Soc. Interface.

View full text Add to dashboard Cite

The supply of oxygen in sufficient quantity is vital for the correct functioning of all organs in the human body, in particular for skeletal muscle during exercise. Disease is often associated with both an inhibition of the microvascular supply capability and is thought to relate to changes in the structure of blood vessel networks. Different methods exist to investigate the influence of the microvascular structure on tissue oxygenation, varying over a range of application areas, i.e. biological in vivo and in vitro experiments, imaging and mathematical modelling. Ideally, all of these methods should be combined within the same framework in order to fully understand the processes involved. This review discusses the mathematical models of skeletal muscle oxygenation currently available that are based upon images taken of the muscle microvasculature in vivo and ex vivo. Imaging systems suitable for capturing the blood vessel networks are discussed and respective contrasting methods presented. The review further informs the association between anatomical characteristics in health and disease. With this review we give the reader a tool to understand and establish the workflow of developing an image-based model of skeletal muscle oxygenation. Finally, we give an outlook for improvements needed for measurements and imaging techniques to adequately investigate the microvascular capability for oxygen exchange.

show abstract

Section: Image-based Modellingmentioning

confidence: 99%

Section: Limitation 1: Role Of the Haematocritmentioning

confidence: 99%

Image-based modelling of skeletal muscle oxygenation

Zeller‐Plumhoff

Roose

Clough

et al. 2017

J. R. Soc. Interface.

View full text Add to dashboard Cite

show abstract

“…While there are other plasma skimming models [25,27], the model developed by Gould and Linninger [26] is considered due to its easy extensibility. The model is as follows:…”

mentioning

confidence: 99%

“…In order to validate the fractional blood flow model, plasma skimming at single bifurcation is computed and compared with in vivo experimental data [24], along with the model developed by Gould and Linninger [26]. Logit model [24,25] is not considered for single bifurcation since this model was developed based on curve fitting of the same experimental data [24].…”

mentioning

confidence: 99%

See 1 more Smart Citation

Effect of fractional blood flow on plasma skimming in the microvasculature

2017

View full text Add to dashboard Cite

Although redistribution of red blood cells at bifurcated vessels is highly dependent on flow rate, it is still challenging to quantitatively express the dependency of flow rate in plasma skimming due to nonlinear cellular interactions. We suggest a plasma skimming model that can involve the effect of fractional blood flow at each bifurcation point. For validating the new model, it is compared with in vivo data at single bifurcation points, as well as microvascular network systems. In the simulation results, the exponential decay of plasma skimming parameter, M , along fractional flow rate shows the best performance in both cases.Red blood cells (RBCs) in microvessels are concentrated on the vessel core. Subsequently, a cell-free layer (CFL) with a few micrometer thickness is observed on the vessel wall. The CFL leads asymmetric redistribution of hematocrit at each bifurcation, called plasma skimming effect. As a continuous process of plasma skimming in microvascular networks, the average hematocrit in capillary beds is lower than the systemic hematocrit as reported in many previous studies [1][2][3][4][5][6][7][8]. Interestingly, the plasma skimming is recently revisited to develop new microchannels for detecting specific DNAs, proteins and cells by efficiently separating plasma from whole blood [9][10][11]. Also, it has been highlighted to accurately predict drug carrier distribution in the microvasculature [12][13][14][15][16][17][18]. For utilizing the plasma skimming to new applications in vitro and in vivo, it is crucial to quantitatively predict the redistribution of RBCs and plasma at bifurcations.From the early 70s, several experiments for quantifying the plasma skimming were performed [2,[19][20][21][22][23] In this paper, we aim to mathematically model fractional blood flow in a simple and generalized manner in order to computationally study its significance in plasma skimming, and also to accurately predict plasma skimming in the microvasculature. For this task, a recently developed plasma skimming model [26] is taken, and extended to take into account the effect of fractional blood flow. This new model is then validated with experimental data at single bifurcation level, and also at microvascular network level.While there are other plasma skimming models [25,27], the model developed by Gould and Linninger [26] is considered due to its easy extensibility. The model is as follows:where H is the hematocrit, M is the plasma skimming parameter, ζ is the hematocrit change coefficient due to plasma skimming, Q is the flow rate, A is the crosssectional area of each vessel, and subscript 0, 1, and 2 indicate the parent, and two daughter vessels, respectively. Specifically, the plasma skimming parameter M is related to the cross-sectional distribution of RBCs near bifurcation. Small M represents that RBCs are highly concentrated on the vessel core. In other words, plasma dominant region, or CFL, is developed on the near wall region. The two separated regions, expressed as RBCs and plasma areas, lead to strong...

show abstract

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

Lee

Hong

Yoo

et al. 2018

Numer Methods Biomed Eng

View full text Add to dashboard Cite

Microvascular transport is complex due to its heterogeneity. Many researchers have been developing mathematical and computational models in predicting microvascular geometries and blood transport. However, previous works were focused on developing simulation models, not on validating suggested models with microvascular geometry and blood flow in the real microvasculature. In this paper, we suggest a computational model for microvascular transport with experimental validation in its geometry and blood flow. The geometry is generated by controlling asymmetric conditions of microvascular network. Also, the blood flow in microvascular networks is predicted by considering in vivo viscosity, Poiseuille flow model, and hematocrit redistribution by plasma skimming. The suggested model is validated by the measured data in rat mesentery. Also, the microvascular transport in a case of mouse cortex is predicted and compared against experimental data to check applicability of the suggested model.

show abstract

Hematocrit Distribution and Tissue Oxygenation in Large Microcirculatory Networks

Cited by 81 publications

References 69 publications

Image-based modelling of skeletal muscle oxygenation

Image-based modelling of skeletal muscle oxygenation

Effect of fractional blood flow on plasma skimming in the microvasculature

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

Contact Info

Product

Resources

About