首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Ultrasonic strain imaging and reconstructive elastography for biological tissue
Authors:Khaled Walaa  Reichling Stefan  Bruhns Otto T  Ermert Helmut
Institution:Institute of High Frequency Engineering, Ruhr-University Bochum, Building IC 6/132, D-44780 Bochum, Germany. Walaa.Khaled@rub.de
Abstract:Mechanical properties of biological tissue represent important diagnostic information and 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 also allow an inverse elastography approach leading to the spatial distribution of the relative elastic modulus of tissue. The internal displacement field of biological tissue is determined using the above mentioned strain imaging system by applying quasi-static compression to the considered tissue. Axial displacements are calculated by comparing echo signal sets obtained prior to and immediately following less than 0.1% compression, using the fast root seeking 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. 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. Our real-time system has the potential of improving diagnosis of prostate and breast cancer.
Keywords:
本文献已被 PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号