In dynamic optical coherence elastography (OCE), surface acoustic waves are the predominant perturbations. They constrain the quantification of elastic modulus to the direction of wave propagation only along the surface of tissues, and disregard elasticity gradients along depth. Longitudinal shear waves (LSW), on the other hand, can be generated at the surface of the tissue and propagate through depth with desirable properties for OCE: (1) LSW travel at the shear wave speed and can discriminate elasticity gradients along depth, and (2) the displacement of LSW is longitudinally polarized along the direction of propagation; therefore, it can be measured by a phase-sensitive optical coherence tomography system. In this study, we explore the capabilities of LSW generated by a circular glass plate in contact with a sample using numerical simulations and tissue-mimicking phantom experiments. Results demonstrate the potential of LSW in detecting an elasticity gradient along axial and lateral directions simultaneously. Finally, LSW are used for the elastography of ex vivo mouse brain and demonstrate important implications in in vivo and in situ measurements of local elasticity changes in brain and how they might correlate with the onset and progression of degenerative brain diseases.

As elastography of the brain finds increasing clinical applications, fundamental questions remain about baseline viscoelastic properties of the brain in vivo. Furthermore, the underlying mechanisms of how and why elastographic measures can change over time are still not well understood. To study these issues, reverberant shear wave elastography using an optical coherence tomography scanner is implemented on a mouse model, both under awake conditions and in a sleep state where there are known changes in the glymphatic fluid flow system in the brain. We find that shear wave speed, a measure of stiffness, changes by approximately 12% between the two states, sleep vs awake, in the entire cortical brain imaging volume. Our microchannel flow model of biphasic (fluid plus solid) tissue provides a plausible rheological model based on the fractal branching vascular and perivascular system, plus a second parallel system representing the finer scale glymphatic fluid microchannels. By adjusting the glymphatic system fluid volume proportional to the known wake/sleep changes, we are able to approximately predict the measured shear wave speeds and their change with the state of the glymphatic system. The advantages of this model are that its main parameters are derived from anatomical measures and are linked to other major derivations of branching fluid structures including Murray’s Law. The implications for clinical studies are that elastography of the brain is strongly influenced by the regulation or dysregulation of the vascular, perivascular, and glymphatic systems.

No abstract

Abstract. The H-scan analysis of ultrasound images is a matched-filter approach derived from analysis of scattering from incident pulses in the form of Gaussian-weighted Hermite polynomial functions. This framework is applied in a preliminary study of thyroid lesions to examine the H-scan outputs for three categories: normal thyroid, benign lesions, and cancerous lesions within a total group size of 46 patients. In addition, phantoms comprised of spherical scatterers are analyzed to establish independent reference values for comparison. The results demonstrate a small but significant difference in some measures of the H-scan channel outputs between the different groups.

The speckle statistics of optical coherence tomography images of biological tissue have been studied using several historical probability density functions. A recent hypothesis implies that underlying power-law distributions in the medium structure, such as the fractal branching vasculature, will contribute to power-law probability distributions of speckle statistics. Specifically, these are the Burr type XII distribution for speckle amplitude, the Lomax distribution for intensity, and the generalized logistic distribution for log amplitude. In this study, these three distributions are fitted to histogram data from nine optical coherence tomography scans of various biological tissues and samples. The distributions are also compared with conventional distributions such as the Rayleigh, K, and gamma distributions. The results indicate that these newer distributions based on power laws are, in general, more appropriate models and support the plausibility of their use for characterizing biological tissue. Potentially, the governing power-law parameter of these distributions could be used as a biomarker for tissue disease or pathology.