grant

Development and application of a high-fidelity computational model of diabetic retinopathy hemodynamics: Coupling single-cell biophysics with retinal vascular network topology and complexity

Organization RUTGERS, THE STATE UNIV OF N.J.Location PISCATAWAY, UNITED STATESPosted 1 Sept 2021Deadline 31 Jul 2026
NIHUS FederalResearch GrantFY202421+ years old3-D3-Dimensional3DAdministrative SupplementAdultAdult HumanAffectAgeAppearanceAutoregulationBioavailabilityBiological AvailabilityBiophysicsBleedingBlindnessBloodBlood CellsBlood Reticuloendothelial SystemBlood VesselsBlood capillariesBlood erythrocyteBlood flowBody TissuesCell BodyCellsClinical EvaluationClinical TestingClinical TreatmentComplexComputer ModelsComputer SystemsComputerized ModelsCouplingDataDetectionDevelopmentDiabetes MellitusDiabetic RetinopathyDiseaseDisorderEndogenous Nitrate VasodilatorEndothelial CellsEndothelium-Derived Nitric OxideErythrocytesErythrocyticExposure toGasesGeometryHemorrhageHeterogeneityHigh Performance ComputingHomeostasisHypoxiaHypoxicImageImaging ProceduresImaging TechnicsImaging TechniquesIndividualMarrow erythrocyteMeasurementMediatingModelingMononitrogen MonoxideMorphologyNatureNitric OxideNitrogen MonoxideNitrogen ProtoxideOxygen DeficiencyPathogenesisPathogenicity FactorsPathway interactionsPeripheral Blood CellPhysiologic AvailabilityPhysiological HomeostasisPropertyRed Blood CellsRed CellRegulationRetinaRetinal Blood VesselsRetinal DiseasesRetinal DisorderRetinal VesselsRheologyRoleSeverity of illnessStructureStudy modelsTissuesVariantVariationVirulence Factorsadulthoodagesbiophysical characteristicsbiophysical characterizationbiophysical foundationbiophysical measurementbiophysical parametersbiophysical principlesbiophysical propertiesbiophysical sciencesblood corpusclesblood losscapillaryclinical diagnosisclinical testcomputational modelingcomputational modelscomputer based modelscomputer based predictioncomputerized modelingcomputing systemdevelopmentaldiabetesdiabeticdisease severityendothelial cell derived relaxing factorhemodynamicshigh end computerhigh performance computerhigh-end computinghuman imagingimagingimaging in vivoin silicoin vivo imaginginnovateinnovationinnovativeinsightmulti-scale computational modelingmulti-scale mathematical modelingmulti-scale modelingmultiscale computational modelingmultiscale mathematical modelingmultiscale modelingnovelpathwaypredictive modelingresearch clinical testingretina blood vessel structureretina diseaseretina disorderretina imagingretinal imagingretinopathysimulationsocial rolethree dimensionaltissue oxygen saturationtissue oxygenationtrial regimentrial treatmentvascularvascular abnormalityvision lossvisual loss
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Full Description

An administrative Supplement is requested to purchase a high-performance computer system to simulate and
generate data for predicting diabetic retinopathy hemodynamics.

Pathogenesis of diabetic retinopathy is characterized by the appearance of morphological abnormalities in the

retinal capillary vessels. Although such abnormalities are used in the clinical evaluation of the disease severity,

the hemodynamic mechanisms underlying their development and progression remain unknown. These

morphological abnormalities are highly localized in specific regions of the retinal vascular network, and may

correlate with the local variations of the hemodynamic parameters and forces. Diabetic conditions significantly

alter the biophysical properties of the blood cells, however the influence of such altered biophysical properties

on the retinal hemodynamics and pathogenesis of retinopathy are not known. Existing in vivo imaging

techniques have limitations in terms of the hemodynamic measurements in the topologically complex and multi-

plexus retinal vasculature. Additionally, tissue hypoxia and the loss of blood flow autoregulation are pathogenic

factors in retinopathy. No study exists that correlates diabetes-mediated altered biophysics of the individual

blood cell to the loss of retinal tissue oxygenation and flow regulation. Our underlying hypotheses are: (i)

altered biophysics of diabetic red blood cells (RBC) alone can mediate vascular abnormalities by altering the

hemodynamic parameters and forces; and (ii) such changes are spatially heterogeneous across the retinal

vascular network, and correlate with the focal and heterogeneous nature of vascular abnormalities. The broad

objective of this project is to understand the relationship between the hemodynamics of diabetic blood cells,

retinal vascular network topology, and pathogenesis of retinopathy, using a high-fidelity, predictive

computational modeling study. Specific aims are: 1) To develop a multiscale computational model of the

diabetic retinopathy hemodynamics taking into consideration the precise microstructural and geometric details

of the 3D vascular networks as obtained from in vivo images of the human retina, and 3D deformation of every

single blood cell with altered biophysical properties representing diabetic conditions. 2) To predict diabetic

RBC-mediated alteration in the retinal hemodynamics, and how such changes are correlated to the formation

and heterogeneity of microvascular abnormalities and vascular adaptation at different stages of progressive

retinopathy. 3) To evaluate the significance of diverse cellular-scale hemodynamic pathways involved. 4) To

predict the role of RBC hemodynamics on retinal hypoxia and loss of nitric oxide bioavailability as pathogenic

factors in retinopathy. This study is significant and innovative because it will (i) develop the first high-fidelity,

predictive computational model that combines the exact 3D geometry of ultra-large-scale and multi-plexus in

silico retinal vasculature, and 3D deformation and rheology of every blood cell, (ii) provide a rheology-

topology coupling mechanism as a basis of hemodynamics-mediated initiation and progression of vascular

abnormalities, (ii) directly model heterotypic individual cell-cell and cell-endothelium interactions, and (iv)

couple individual RBC transient deformation with blood and retinal tissue gas transport.

Acquisition of the high-performance computer system will enable us to perform the simulations and generate

data to accomplish the Specific Aims.

Grant Number: 3R01EY033003-04S1
NIH Institute/Center: NIH

Principal Investigator: Prosenjit Bagchi

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