ArticleMicrocirculation (New York, N.Y. : 1994)2025
Blood Flow Simulation and Uncertainty Quantification in Extensive Microvascular Networks: Application to Brain Cortical Networks.
Article in Microcirculation (New York, N.Y. : 1994), 2025. 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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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.
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Who cites it
1 citing paper in PubMed.
- Blood Flow Simulation and Uncertainty Quantification in Extensive Microvascular Networks: Application to Brain Cortical Networks.Microcirculation (New York, N.Y. : 1994) · 2025Article
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Authors and funding
1 author.
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Abstract
objectiveMicrovascular blood flow simulations enhance understanding of microcirculatory phenomena at the micrometer scale by capturing heterogeneity in blood flow. However, imaged areas often only partially represent tissue regions, leading to numerous vessels crossing boundaries and strongly influencing simulated blood flows through imposed boundary conditions.
methodsTwo key methodological aspects of blood flow simulations are addressed: selecting appropriate boundary conditions and quantifying the inevitable impact of boundary condition uncertainties on model simulations. An adaptive method for pressure boundary conditions is proposed and rigorously evaluated in extensive brain cortical microvascular networks. The adaptive method is integrated into a Bayesian calibration framework, inferring distributions over thousands of unknown pressure boundary conditions and providing uncertainty estimates for model simulations.
resultsThe adaptive method produces simulations consistent with reference data, yielding depth-dependent pressure drop profiles and layer-wise capillary blood flow profiles consistent with previous analysis. These hemodynamic phenomena generalize to biphasic blood flow simulation models incorporating in vivo viscosity formulations. Uncertainty quantification reveals a novel spatially heterogeneous and depth-dependent pattern in blood flow uncertainty.
conclusionsThe adaptive method for pressure boundary conditions will be useful in future applications of both forward and inverse blood flow simulations. Uncertainty quantification complements hemodynamic predictions with associated uncertainties.
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