Characterizing brain tissue viscoelasticity using air-coupled ultrasound transducer-based optical coherence elastography with power-law-constrained Kelvin-Voigt fractional derivative model☆★

Viscoelastic properties of pathological changes in brain tissue are key biomarkers for clinical neurological diseases. Clinically, shear wave elastography is an ultrasound technique capable of quantitatively assessing tissue elasticity, however, its application is limited by submillimeter spatial resolution. In this work, we developed an air-coupled ultrasound transducer-based optical coherence elastography system (AcUT-OCE), which enables non-contact quantitative elastography of brain tissue with micrometer-scale resolution. A Kelvin-Voigt fractional derivative model (KVFD) incorporating a power-law- constraint (PC-KVFD) was established to quantitatively evaluate the viscoelasticity of brain tissue. The results of the phantom experiment demonstrate that the phase velocity corrected using the PC-KVFD model exhibits a power-law relationship, with its magnitude being higher than the uncorrected measured values. The storage modulus and loss modulus of the phantom were calculated to be within the ranges of 6.1–10.3 kPa and 1.8–4.6 kPa, respectively. Then, an in ex vivo porcine brain experiment was conducted, in which the storage modulus and loss modulus of the brain tissue were estimated to be in the ranges of 4.5–8 kPa and 2–4 kPa, respectively. Subsequently, we compared the accuracies of the linear model, KVFD model, and PC-KVFD model in calculating viscoelasticity. The PC-KVFD model exhibits superior performance in terms of viscoelastic frequency dependence curves, with R 2 (coefficient of determination) values exceeding 0.99 for the storage modulus and 0.98 for the loss modulus, indicating an excellent goodness of fit. Overall, the AcUT-OCE technique combined with the PC-KVFD model, enables non-contact, high-resolution, and quantitative assessment of brain tissue viscoelasticity.