Ultrasonic strain imaging and reconstructive elastography for biological tissue

Abstract

In the field of medical diagnosis, there is a strong need to determine mechanical properties of biological tissue, which are of histological and pathological relevance. In order to obtain non-invasively mechanical properties of tissue, we developed a real-time strain imaging system for clinical applications. The output data of this system allows an inverse approach leading to the spatial distribution of the relative elastic modulus of tissue. The internal displacement field of biological tissue is determined by applying quasi-static compression to the considered tissue. Axial displacements are calculated by comparing echo signal sets obtained prior to and immediately following a small compression, using a cross-correlation technique. Strain images representing mechanical tissue properties in a non quantitative manner are displayed in real time mode. For additional quantitative imaging, the stiffness distribution is calculated from the displacement field assuming the investigated material to be elastic, isotropic, and nearly incompressible. Different inverse problem approaches for calculating the shear modulus distribution using the internal displacement field have been implemented and compared using tissue-like phantoms. One of the important applications for diagnosis using ultrasound elastography is the coronary atherosclerosis, which is a common disease in industrialized countries. In this work some clinical in-vivo results are presented using intravascular ultrasound elastography. In the field of tumor diagnosis, the results of an ongoing clinical study with more than 200 patients show, that our real time strain imaging system is able to differentiate malignant and benign tissue areas in the prostate with a high degree of accuracy (Sensitivity=76% and Specificity=89%). The reconstruction approaches applied to the strain image data deliver quantitative tissue information and seem promising for an additional differential diagnosis of lesions in biological tissue. © 2008 Springer-Verlag.