Kai Willner | Searcharxiv

arXiv2026

Crossover Frequency as a Model-Independent Viscoelastic Constant for Soft Tissue Biomechanics

Magnetic resonance elastography (MRE) and related elastography techniques are emerging as quantitative diagnostic tools for assessing tissue microstructure and pathology. To determine descriptive parameters of the tissues' properties, a frequency-dependent viscoelastic material model is required, which is calibrated to the measured response in a parameter identification process. However, the selection of this model and the fitting strategy is challenging, since it may influence the identified viscoelastic parameters notably. Here, we address this limitation by proposing the crossover frequency (fc, defined as the frequency at which storage and loss moduli intersect G'(fc) = G''(fc)) as a model-independent viscoelastic constant for soft tissues. Fresh porcine specimens of the corona radiata, the putamen, the thalamus, and the liver were investigated using tabletop MRE and the frequency-dependent viscoelasticity was characterized with a fractional Kelvin-Voigt model. By validating the crossover frequency against the viscoelastic parameters, we demonstrated that the crossover frequency accurately reflects the viscoelastic behavior, independent of the material model or the fitting strategy. Across all samples, fc distinguished brain regions and separated brain from liver tissue by median frequencies of 85Hz (95% CI: 69-269Hz) in the corona radiata, 423Hz (95% CI: 316-575Hz) in the putamen, 426Hz (95% CI: 302-601Hz) in the thalamus and 1174Hz (95% CI: 1074-1300Hz) in the liver (p<0.001). These results suggest that crossover frequencies capture distinct viscoelastic fingerprints without requiring viscoelastic model selection. The crossover frequency may therefore serve as a practical, model-independent biomaterial constant to improve comparability of viscoelastic measurements across elastography studies.

physics.med-ph↗

arXiv2026

Combining quasi-static and high frequency experiments for the viscoelastic characterization of brain tissue

Mechanical models of brain tissue are a beneficial tool to simulate neurosurgical interventions, disease progression, or brain development. However, the accuracy and predictive capacity of such a model relies on a precise experimental characterization of the tissue's mechanical behavior. Such a characterization is yet limited by inconsistent or contradictory experimental responses reported in the literature, particularly when measurements are performed in different time or length scales. Although brain tissue has been extensively investigated in previous studies, the combination of experimental findings from different scales has received limited attention. In this study, we combine ex vivo mechanical responses of porcine brain tissue obtained at different time scales in a mechanical model. We investigated the mechanical behavior of three different brain regions in the quasi-static domain with multi-modal large strain rheometer measurements and at high frequencies with magnetic resonance elastography (MRE). A comparative analysis of the mechanical parameters obtained from both experimental techniques demonstrated consistent regional variations in the viscoelastic behavior across the two domains. However, the mechanical behavior changes from a higher elasticity in the quasi-static and low frequency domain to a dominating viscosity at high frequencies. Based on the quasi-static and the high frequency behavior, we calibrated a fractional Kelvin-Voigt model and consequently unified the two responses in a single mechanical model to obtain a comprehensive characterization of the tissue's mechanical behavior.

physics.med-ph↗