Evidence map›Paper›PMID 39546289›Full record

ArticleInvestigative ophthalmology & visual science2024

A High-Fidelity Computational Model for Predicting Blood Cell Trafficking and 3D Capillary Hemodynamics in Retinal Microvascular Networks.

Saman Ebrahimi, Phillip Bedggood, Yifu Ding, Andrew Metha, Prosenjit Bagchi

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Article in Investigative ophthalmology & visual science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Saman EbrahimiMechanical and Aerospace Engineering Department, Rutgers, The State University of New Jersey, Piscataway, New Jersey, United States.
Phillip BedggoodDepartment of Optometry and Vision Sciences, University of Melbourne, Melbourne, Australia.
Yifu DingDepartment of Optometry and Vision Sciences, University of Melbourne, Melbourne, Australia.
Andrew MethaDepartment of Optometry and Vision Sciences, University of Melbourne, Melbourne, Australia.
Prosenjit BagchiMechanical and Aerospace Engineering Department, Rutgers, The State University of New Jersey, Piscataway, New Jersey, United States.

Funding

Development and application of a high-fidelity computational model of diabetic retinopathy hemodynamics: Coupling single-cell biophysics with retinal vascular network topology and complexityR01EY033003 · NEI · RUTGERS, THE STATE UNIV OF N.J. · PI BAGCHI, PROSENJIT · 2021 to 2024
$1.5M
NEI NIH HHS R01 EY033003
6 · The paper itself

Abstract

Purpose: To present a first principle-based, high-fidelity computational model for predicting full three-dimensional (3D) and time-resolved retinal microvascular hemodynamics taking into consideration the flow and deformation of individual blood cells. Methods: The computational model is a 3D fluid-structure interaction model based on combined finite volume/finite element/immersed-boundary methods. Three in silico microvascular networks are built from high-resolution in vivo motion contrast images of the superficial capillary plexus in the parafoveal region of the human retina. The maximum tissue area represented in the model is approximately 500 × 500 µm2, and vessel lumen diameters ranged from 5.5 to 25 µm covering capillaries, arterioles, and venules. Blood is modeled as a suspension of individual blood cells, namely, erythrocytes (RBC), leukocytes (WBC), and platelets in plasma. An accurate and detailed biophysical modeling of each blood cell and their flow-induced deformation is considered. A physiological, pulsatile boundary condition corresponding to an average cardiac cycle of 0.9 second is used. Results: Detailed quantitative data and analysis of 3D retinal microvascular hemodynamics are presented, and their relationship to RBC flow dynamics is illustrated. Blood velocity is shown to have temporal oscillations superimposed on the background pulsatile variation, which arise because of the way RBCs partition at vascular junctions, causing repeated clogging and unclogging of vessels. Temporal variations in RBC velocity and hematocrit are anti-correlated in a given vessel, but their time-averaged distributions are positively correlated across the network. Whole blood velocity is 65% to 85% of RBC velocity, with the discrepancy related to the formation of an RBC-free region, adjacent to the vascular endothelium and typically 0.8 to 1.8 µm thick. The 3D velocity and RBC concentration profiles are shown to be oppositely skewed with respect to each other, because of the way that RBCs "hug" the apex of each bifurcation. RBC deformation is predicted to have biphasic behavior with respect to vessel diameter, with minimal cell length for vessels approximately 7 µm in diameter. The wall shear stress (WSS) exhibits a strongly 3D distribution with local regions of high value and gradient spanning a range of 10 to 80 dyn/cm2. WSS is highest where there is faster flow, greater curvature of the vessel wall, capillary bifurcations, and at locations of RBC crowding and associated thinning of the cell-free layer. Conclusions: This study highlights the usefulness of high-fidelity cell-resolved modeling to obtain accurate and detailed 3D, time-resolved retinal hemodynamic parameters that are not readily available through noninvasive imaging approaches. The results presented are expected to complement and enhance the interpretation of in vivo data, as well as open new avenues to study retinal hemodynamics in health and disease.

Indexed as

CapillariesComputer SimulationErythrocytesHemodynamicsRetinal VesselsBlood Flow VelocityCell MovementHumansImaging, Three-DimensionalLeukocytesMicrocirculationMicrovesselsModels, Cardiovascular

Identifiers

PMID39546289
PMCPMC11580294

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.