Reverse Time Migration and Genetic Algorithms combined for reconstruction in transluminal shear wave elastography: An in silico case study

Abstract

A new reconstruction approach that combines Reverse Time Migration (RTM) and Genetic Algorithms (GAs) is proposed for solving the inverse problem associated with transluminal shear wave elastography. The transurethral identification of the first thermal lesion generated by transrectal High Intensity Focused Ultrasound (HIFU) for the treatment of prostate cancer, was used to preliminarily test in silico the combined reconstruction method. The RTM method was optimised by comparing reconstruction images from several cross-correlation techniques, including a new proposed one, and different device configurations in terms of the number and arrangement of emitters and receivers of the conceptual transurethral probe. The best results were obtained for the new proposed cross-correlation method and a device configuration with 3 emitters and 32 receivers. The RTM reconstructions did not completely contour the shape of the HIFU lesion, however, as planned for the combined approach, the areas in the RTM images with high level of correlation were used to narrow down the search space in the GA-based technique. The GA-based technique was set to find the location of the HIFU lesion and the increment in stiffness and viscosity due to thermal damage. Overall, the combined approach achieves lower level of error in the reconstructed values, and in a shorter computational time, compared to the GA-based technique alone. The lowest errors were accomplished for the location of HIFU lesion, followed by the contrast ratio of stiffness between thermally treated tissue and non-treated normal tissue. The homologous ratio of viscosity obtained higher level of error. Further investigation considering diverse scenarios to be reconstructed and with experimental data is required to fully evaluate the feasibility of the combined approach.