Online 4D Ultrasound-Guided Robotic Tracking Enables 3D Ultrasound Localisation Microscopy with Large Tissue Displacements

TL;DR

This paper presents a real-time ultrasound-guided robotic tracking system that enables super-resolution ultrasound imaging of moving tissues, overcoming challenges posed by large displacements such as respiration, and achieving high frame-rate imaging in dynamic conditions.

Contribution

The study introduces an integrated high-frame-rate ultrasound and robotic probe control approach for super-resolution imaging during large tissue movements, demonstrated on a moving phantom.

Findings

Achieved real-time tracking of tissue displacements up to 20 mm.

Successfully reconstructed super-resolution images of moving microvasculature.

Maintained imaging volume rate at 85 Hz during large tissue motions.

Abstract

Super-Resolution Ultrasound (SRUS) imaging through localising and tracking microbubbles, also known as Ultrasound Localisation Microscopy (ULM), has demonstrated significant potential for reconstructing microvasculature and flows with sub-diffraction resolution in clinical diagnostics. However, imaging organs with large tissue movements, such as those caused by respiration, presents substantial challenges. Existing methods often require breath holding to maintain accumulation accuracy, which limits data acquisition time and ULM image saturation. To improve image quality in the presence of large tissue movements, this study introduces an approach integrating high-frame-rate ultrasound with online precise robotic probe control. Tested on a microvasculature phantom with translation motions up to 20 mm, twice the aperture size of the matrix array used, our method achieved real-time tracking of the moving phantom and imaging volume rate at 85 Hz, keeping majority of the target volume in the imaging field of view. ULM images of the moving cross channels in the phantom were successfully reconstructed in post-processing, demonstrating the feasibility of super-resolution imaging under large tissue motions. This represents a significant step towards ULM imaging of organs with large motion.