Three-dimensional ultrasound elasticity imaging on an automated breast volume scanning system

摘要

Ultrasound elasticity imaging has demonstrated utility in breast imaging, but it is typically performed with handheld transducers and two-dimensional imaging. Two-dimensional (2D) elastography images tissue stiffness of only a plane and hence suffers from errors due to out-of-plane motion, whereas three-dimensional (3D) data acquisition and motion tracking can be used to track out-of-plane motion that is lost in 2D elastography systems. A commercially-available automated breast volume scanning system that acquires 3D ultrasound data with precisely controlled elevational movement of the 1D array ultrasound transducer was employed in this study. A hybrid, guided 3D motion tracking algorithm was developed that first estimated the displacements in one plane using a modified quality-guided search method, and then performed an elevational guided-search for displacement estimation in adjacent planes. To assess the performance of the method, 3D radiofrequency echo data were acquired with this system from a phantom and from an in vivo human breast. For both experiments, the axial displacement fields were smooth and high cross-correlation coefficients were obtained in most of the tracking region. The motion tracking performance of the new method was compared with a correlation-based exhaustive search method on six consecutive volumes (five consecutive volume pairs) of radiofrequency echo data acquired during in vivo scanning of the breast of one subject. For all five motion tracking volume pairs, the average motion-compensated cross-correlation values (between pre-deformation and motion-compensated post-deformation echo fields) obtained by the guided-search motion tracking method were equivalent to those by the exhaustive search method, and the computation time was about a factor of 10 less. Therefore, the proposed 3D ultrasound elasticity imaging method was a more efficient approach to produce a high quality of 3D ultrasound strain image.