ArticleFrontiers in physics2021
Poroelasticity as a Model of Soft Tissue Structure: Hydraulic Permeability Reconstruction for Magnetic Resonance Elastography in Silico.
Article in Frontiers in physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review.Frontiers in physiology · 2021Pooled it
- Shear Mechanics of Articular Cartilage and Cartilage-Inspired Materials.Annual review of condensed matter physics · 2026Article
- Patient-specific numerical simulation of compression therapy effects on interstitial fluid motion in lower limb lymphedema.Biomechanics and modeling in mechanobiology · 2025Article
- Evaluating the Performance and Repeatability of Poroelastic and Poroviscoelastic Models in Intrinsic MR Elastography.NMR in biomedicine · 2025Article
- Article
- Tissue-scale in vitro epithelial wrinkling and wrinkle-to-fold transition.Nature communications · 2024Article
- Estimating the viscoelastic properties of the human brain at 7 T MRI using intrinsic MRE and nonlinear inversion.Human brain mapping · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Magnetic Resonance Elastography allows noninvasive visualization of tissue mechanical properties by measuring the displacements resulting from applied stresses, and fitting a mechanical model. Poroelasticity naturally lends itself to describing tissue - a biphasic medium, consisting of both solid and fluid components. This article reviews the theory of poroelasticity, and shows that the spatial distribution of hydraulic permeability, the ease with which the solid matrix permits the flow of fluid under a pressure gradient, can be faithfully reconstructed without spatial priors in simulated environments. The paper describes an in-house MRE computational platform - a multi-mesh, finite element poroelastic solver coupled to an artificial epistemic agent capable of running Bayesian inference to reconstruct inhomogenous model mechanical property images from measured displacement fields. Building on prior work, the domain of convergence for inference is explored, showing that hydraulic permeabilities over several orders of magnitude can be reconstructed given very little prior knowledge of the true spatial distribution.
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Registered trials
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.