Performance optimization of lateral displacement estimation with spatial angular compounding

Elastography provides tissue mechanical information to differentiate normal and disease states. Nowadays, axial displacement and strain are usually estimated in clinical practice whereas lateral estimation is rarely used given that its accuracy is typically one order of magnitude worse than that of axial estimation. To improve the performance of lateral estimation, spatial angular compounding of multiple axial displacements along ultrasound beams transmitting in different steering angles was previously proposed. However, few studies have been conducted to evaluate the influence of key factors such as grating lobe noise (GLN), the number of steering angles (NSA) and maximum steering angle (MSA) in terms of performance optimization. The aim of this study was thus to investigate the effects of these factors through both computer simulations and phantom experiments. Only lateral rigid motion was considered in this study to separate its effects from those of axial and lateral strains on lateral displacement estimation. The performance as indicated by the root mean square error (RMSE) and standard deviation (SD) of the estimated lateral displacements validates the capability of spatial angular compounding in improving the performance of lateral estimation. It is necessary to filter the GLN for better estimation, and better performance is associated with a larger NSA and bigger MSA in both simulations and experiments, which is in agreement with the theoretical analysis. As indicated by the RMSE and SD, two steering angles with a larger steering angle are recommended. These results could provide insights into the performance optimization of lateral displacement estimation with spatial angular compounding.