Abstract

It is well known that some diseases, such as cancer, lead to a change of tissue hardness (i.e. the so-called elasticity modulus). The reconstruction of tissue elasticity provides the sonographer with important additional information which can be applied for the diagnosis of these diseases. Elasticity imaging has recently attracted attention as a technique which directly reveals the physical property of tissue and enables us to determine the change of tissue hardness caused by diseases. The elasticity modulus, i.e. the tissue elasticity distribution can be calculated from the strain and the stress of the examined structures. While the strain field can be estimated from the RF signals returned from tissue structures before and after compression, it is impossible to measure the stress field directly within the tissue. Another problem is that the compression of harder tissue structures is often followed by a lateral displacement of these structures. It is nearly impossible to represent the volume of this sideslip with conventional 2D methods but its calculation is indispensable for an accurate determination of the tissue elasticity of the examined structures. To overcome these problems, we propose the so-called Extended CA-method (Extended Combined Autocorrelation Method) which allows the reconstruction of the tissue elasticity of the examined structures on the basis of the 3-dimensional finite element model. The new technique enables a highly accurate estimation of the tissue elasticity distribution and the adequate compensation of sideslips. The realtime elasticity imaging described in this article, can easily be performed with the SonoElastography module that can be integrated into the platform of the HITACHI EUB-8500 system. Like colour Doppler examinations, tissue elasticity imaging can easily be performed with conventional ultrasound probes and does not require additional instruments (e.g. for measuring pressure or vibrations). The calculation of tissue elasticity distribution is performed in realtime and the examination results are represented in colour over the conventional B-mode image. The results of the simulations and phantom experiments performed verify that with the information obtained by the new realtime elasticity imaging method, lesions can be detected and represented more rapidly and with higher accuracy than with conventional methods based on the 2D Model, and that even lesions invisible on B-mode images can be detected.

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