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Lymphedema is a common condition involving an abnormal accumulation of lymphatic fluid in the interstitial space that causes swelling, most often in the arm(s) and leg(s). Lymphedema is a significant lifelong concern that can be congenital or develop following cancer treatment or cancer metastasis. Common methods of evaluation of lymphedema are mostly qualitative making it difficult to reliably assess the severity of the disease, a key factor in choosing the appropriate treatment. In this paper, we investigate the feasibility of using novel elastographic techniques to differentiate between lymphedematous and normal tissues. This study represents the first step of a larger study aimed at investigating the combined use of elastographic and sonographic techniques for the detection and staging of lymphedema. In this preliminary study, poroelastographic images were generated from the leg (8) and arm (4) subcutis of five normal volunteers and seven volunteers having lymphedema, and the results were compared using statistical analyses. The preliminary results reported in this paper suggest that it may be feasible to perform poroelastography in different lymphedematous tissues in vivo and that poroelastography techniques may be of help in differentiating between normal and lymphedematous tissues. [ABSTRACT FROM AUTHOR]

Ultrasound elastography produces strain images of compliant tissues under quasi-static compression. In axial-shear strain elastography, the local axial-shear strain resulting from application of quasi-static axial compression to an inhomogeneous material is imaged. The overall hypothesis of this work is that the pattern of axial-shear strain distribution around the inclusion/background interface is completely determined by the bonding at the interface after normalization for inclusion size and applied strain levels, and that it is feasible to extract certain features from the axial-shear strain elastograms to quantify this pattern. The mechanical model used in this study consisted of a single stiff circular inclusion embedded in a homogeneous softer background. First, we performed a parametric study using finite-element analysis (FEA) (no ultrasound involved) to identify possible features that quantify the pattern of axial-shear strain distribution around an inclusion/background interface. Next, the ability to extract these features from axial-shear strain elastograms, estimated from simulated pre- and post-compression noisy RF data, was investigated. Further, the feasibility of extracting these features from in vivobreast data of benign and malignant tumors was also investigated. It is shown using the FEA study that the pattern of axial-shear strain distribution is determined by the degree of bonding at the inclusion/background interface. The results suggest the feasibility of using normalized features that capture the region of positive and negative axial-shear strain area to quantify the pattern of the axial-shear strain distribution. The simulation results showed that it was feasible to extract the features, as identified in the FEA study, from axial-shear strain elastograms. However, an effort must be made to obtain axial-shear strain elastograms with the highest signal-to-noise ratio (SNRasse) possible, without compromising the resolution. The in vivoresults demonstrated the feasibility of producing and extracting features from the axial-shear strain elastograms from breast data. Furthermore, the in vivoaxial-shear strain elastograms suggest an additional feature not identified in the simulations that may potentially be used for distinguishing benign from malignant tumors-the proximity of the axial-shear strain regions to the inclusion/background interface identified in the sonogram. [ABSTRACT FROM AUTHOR]

In axial-shear strain elastography, the local axial-shear strain resulting from the application of quasi-static axial compression to an inhomogeneous material is imaged. In this paper, we investigated the image quality of the axial-shear strain estimates in terms of the signal-to-noise ratio (SNRasse) and contrast-to-noise ratio (CNRasse) using simulations and experiments. Specifically, we investigated the influence of the system parameters (beamwidth, transducer element pitch and bandwidth), signal processing parameters (correlation window length and axial window shift) and mechanical parameters (Young's modulus contrast, applied axial strain) on the SNRasseand CNRasse. The results of the study show that the CNRasse(SNRasse) is maximum for axial-shear strain values in the range of 0.005-0.03. For the inclusion/background modulus contrast range considered in this study (<10), the CNRasse(SNRasse) is maximum for applied axial compressive strain values in the range of 0.005%-0.03%. This suggests that the RF data acquired during axial elastography can be used to obtain axial-shear strain elastograms, since this range is typically used in axial elastography as well. The CNRasse(SNRasse) remains almost constant with an increase in the beamwidth while it increases as the pitch increases. As expected, the axial shift had only a weak influence on the CNRasse(SNRasse) of the axial-shear strain estimates. We observed that the differential estimates of the axial-shear strain involve a trade-off between the CNRasse(SNRasse) and the spatial resolution only with respect to pitch and not with respect to signal processing parameters. Simulation studies were performed to confirm such an observation. The results demonstrate a trade-off between CNRasseand the resolution with respect to pitch. [ABSTRACT FROM AUTHOR]