Ultrasound poroelastography aims at assessing the poroelastic behavior of biological tissues via estimation of the local temporal axial strains and effective Poisson's ratios (EPR). Currently, reliable estimation of EPR using ultrasound is a challenging task due to the limited quality of lateral strain estimation. In this paper, we propose a new two-step EPR estimation technique based on dynamic programming elastography (DPE) and Horn-Schunck (HS) optical flow estimation. In the proposed method, DPE is used to estimate the integer axial and lateral displacements while HS is used to obtain subsample axial and lateral displacements from the motion-compensated pre-compressed and post-compressed radio frequency data. Axial and lateral strains are then calculated using Kalman filter-based least square estimation. The proposed two-step technique was tested using finite-element simulations, controlled experiments and in vivo experiments, and its performance was statistically compared with that of analytic minimization (AM) and correlation-based method (CM). Our results indicate that our technique provides EPR elastograms of higher quality and accuracy than those produced by AM and CM. Regarding signal-to-noise ratio and elastographic contrast-to-noise ratio, in simulated data, the proposed method provides an average improvement of 30% and 75%, respectively, with respect to AM and of 100% and 169%, respectively, with respect to CM, whereas, in experiments, the proposed approach provides an average improvement of 30% and 67% with respect to AM and of 230% and 525% with respect to CM. Based on these results, the proposed method may be the preferred one in experimental poroelastography applications.

Ultrasound methods to image the time constant (TC) of elastographic tissue parameters have been recently developed. Elastographic TC images from creep or stress relaxation tests have been shown to provide information on the viscoelastic and poroelastic behavior of tissues. However, the effect of temporal ultrasonic acquisition parameters and input noise on the image quality of the resultant strain TC elastograms has not been fully investigated yet. Understanding such effects could have important implications for clinical applications of these novel techniques. This work reports a simulation study aimed at investigating the effects of varying windows of observation, acquisition frame rate, and strain signal-to-noise ratio (SNR) on the image quality of elastographic TC estimates. A pilot experimental study was used to corroborate the simulation results in specific testing conditions. The results of this work suggest that the total acquisition time necessary for accurate strain TC estimates has a linear dependence to the underlying strain TC (as estimated from the theoretical strain-vs.-time curve). The results also indicate that it might be possible to make accurate estimates of the elastographic TC (within 10% error) using windows of observation as small as 20% of the underlying TC, provided sufficiently fast acquisition rates (>100 Hz for typical acquisition depths). The limited experimental data reported in this study statistically confirm the simulation trends, proving that the proposed model can be used as upper bound guidance for the correct execution of the experiments.

The mechanical behavior of biological tissues has been studied using a number of mechanical models. Due to the relatively high fluid content and mobility, many biological tissues have been modeled as poroelastic materials. Diseases such as cancers are known to alter the poroelastic response of a tissue. Tissue poroelastic properties such as compressibility, interstitial permeability and fluid pressure also play a key role for the assessment of cancer treatments and for improved therapies. At the present time, however, a limited number of poroelastic models for soft tissues are retrievable in the literature, and the ones available are not directly applicable to tumors as they typically refer to uniform tissues. In this paper, we report the analytical poroelastic model for a non-uniform tissue under stress relaxation. Displacement, strain and fluid pressure fields in a cylindrical poroelastic sample containing a cylindrical inclusion during stress relaxation are computed. Finite element simulations are then used to validate the proposed theoretical model. Statistical analysis demonstrates that the proposed analytical model matches the finite element results with less than 0.5% error. The availability of the analytical model and solutions presented in this paper may be useful to estimate diagnostically relevant poroelastic parameters such as interstitial permeability and fluid pressure, and, in general, for a better interpretation of clinically-relevant ultrasound elastography results.

The mechanical behavior of long bones and fractures has been under investigation for many decades due to its complexity and clinical relevance. In this paper, we report a new subject-specific methodology to predict and analyze the mechanical behavior of the soft tissue at a bone interface with the intent of identifying the presence and location of bone abnormalities with high accuracy, spatial resolution, and contrast. The proposed methodology was tested on both intact and fractured rabbit femur samples with finite element-based 3-D simulations, created from actual femur computed tomography data, and ultrasound elastography experiments. The results included in this study demonstrate that elastographic strains at the bone/soft tissue interface can be used to differentiate fractured femurs from the intact ones on a distribution level. These results also demonstrate that coronal plane axial shear strain creates a unique contrast mechanism that can be used to reliably detect fractures (both complete and incomplete) in long bones. Kruskal-Wallis test further demonstrates that the contrast measure for the fracture group (simulation: 2.1286±0.2206; experiment: 2.7034 ± 1.0672) is significantly different from that for the intact group (simulation: 0 ± 0; experiment: 1.1540±0.6909) when using coronal plane axial shear strain elastography ( < 0.01). We conclude that: 1) elastography techniques can be used to accurately identify the presence and location of fractures in a long bone and 2) the proposed model-based approach can be used to predict and analyze strains at a bone fracture site and to better interpret experimental elastographic data.

We report on the use of elastographic imaging techniques to assess the bone/soft tissue interface, a region that has not been previously investigated but may provide important information about fracture and bone healing. The performance of axial strain elastograms and axial shear strain elastograms at the bone/soft tissue interface was studied ex vivo on intact and fractured canine and ovine tibias. Selected ex vivo results were corroborated on intact sheep tibias in vivo. The elastography results were statistically analyzed using elastographic image quality tools. The results of this study demonstrate distinct patterns in the distribution of the normalized local axial strains and axial shear strains at the bone/soft tissue interface with respect to the background soft tissue. They also show that the relative strength and distribution of the elastographic parameters change in the presence of a fracture and depend on the degree of misalignment between the fracture fragments. Thus, elastographic imaging modalities might be used in the future to obtain information regarding the integrity of bones and to assess the severity of fractures, alignment of bone fragments as well as to follow bone healing.