Poroelastic Imaging Techniques in Biological Tissues

Poroelastic imaging exploits the coupled mechanical response of fluid‐filled soft tissues to mechanical loading, offering quantitative insight into both solid matrix properties and interstitial fluid dynamics. In poroelastic media, mechanical compression or shear induces fluid flow through the porous matrix, producing time‐dependent strain and pressure fields that reflect tissue permeability, stiffness and fluid volume fractions. Imaging approaches translate these biomechanical signatures into spatial maps of parameters such as aggregate modulus, permeability, extracellular volume fraction and interstitial hydraulic conductivity. Modalities include ultrasound poroelastography, magnetic resonance elastography with poroelastic models, optical coherence poroelastography and coupled finite‐element–imaging inversions. Such techniques have proven valuable in oncology for mapping tumour interstitial fluid transport, in musculoskeletal research for assessing cartilage health and in lymphatic disorders for evaluating tissue oedema. By linking microstructural fluid‐solid interactions with macroscopic mechanical behaviour, poroelastic imaging promises enhanced diagnosis, treatment monitoring and mechanobiological understanding across a range of clinical and research contexts.

Research from Nature Portfolio

Recent studies have introduced non-invasive ultrasound-based methods to quantify key interstitial fluid transport parameters in tumours in vivo. One approach models a tumour as a biphasic poroelastic composite to estimate extracellular volume fraction, interstitial fluid volume fraction and interstitial hydraulic conductivity, validating accuracy against scanning electron microscopy and demonstrating in vivo sensitivity to treatment-induced changes in breast cancer models. A complementary development enables simultaneous reconstruction of Young’s modulus and Poisson’s ratio maps from axial and lateral strain data, employing axisymmetric and ellipsoidal inclusion assumptions. Finite‐element simulations and phantom experiments confirm high spatial resolution and accuracy above 90 % under a variety of geometries, while in vivo studies in orthotopic tumour models illustrate clinical feasibility for detecting early mechanical alterations in cancerous tissue.

Poroelastic Imaging Techniques in Biological Tissues publication trend

The graph below shows the total number of articles in poroelastic imaging techniques in biological tissues across all publications each year (not limited to Nature Index journals).

Technical terms

Poroelasticity: Mechanical behaviour arising from interaction between a deformable solid matrix and interstitial fluid in a porous medium.

Ultrasound poroelastography: Imaging modality that tracks time-dependent tissue deformation under compression to infer poroelastic properties.

Extracellular volume fraction (EVF): Proportion of tissue volume occupied by solid matrix excluding fluid.

Interstitial fluid volume fraction (IFVF): Proportion of tissue volume occupied by interstitial fluid.

Interstitial hydraulic conductivity (IHC): Measure of ease with which fluid flows through the tissue’s porous matrix.

Young’s modulus: Elastic modulus quantifying tissue stiffness under uniaxial loading.

Poisson’s ratio: Ratio of transverse to axial strain under uniaxial stress.

Stress relaxation: Decrease of stress over time under constant strain in a poroelastic material.

Strain relaxation: Increase of strain over time under constant stress in a poroelastic material.

References

1. Non-invasive imaging of interstitial fluid transport parameters in solid tumors in vivo. Scientific Reports (2023).
2. Non-invasive imaging of Young’s modulus and Poisson’s ratio in cancers in vivo. Scientific Reports (2020).
3. On the Comparative Suitability of Strain Relaxation and Stress Relaxation Compression for Ultrasound Poroelastic Tissue Characterization. Frontiers in Physics (2021).
4. A stochastic filtering approach to recover strain images from quasi-static ultrasound elastography. BioMedical Engineering OnLine (2014).