Organ Shape Sensing using Pneumatically Attachable Flexible Rails in Robotic-Assisted Laparoscopic Surgery
This work addresses the problem of reducing surgeon cognitive load and improving patient outcomes in partial nephrectomy, representing an incremental advancement in surgical automation.
The researchers tackled the challenge of autonomously moving an ultrasound probe on a kidney surface during robotic-assisted surgery by integrating shape-sensing into a soft robotic rail system, achieving autonomous ultrasound scans on a kidney phantom.
In robotic-assisted partial nephrectomy, surgeons remove a part of a kidney often due to the presence of a mass. A drop-in ultrasound probe paired to a surgical robot is deployed to execute multiple swipes over the kidney surface to localise the mass and define the margins of resection. This sub-task is challenging and must be performed by a highly skilled surgeon. Automating this sub-task may reduce cognitive load for the surgeon and improve patient outcomes. The overall goal of this work is to autonomously move the ultrasound probe on the surface of the kidney taking advantage of the use of the Pneumatically Attachable Flexible (PAF) rail system, a soft robotic device used for organ scanning and repositioning. First, we integrate a shape-sensing optical fibre into the PAF rail system to evaluate the curvature of target organs in robotic-assisted laparoscopic surgery. Then, we investigate the impact of the stiffness of the material of the PAF rail on the curvature sensing accuracy, considering that soft targets are present in the surgical field. Finally, we use shape sensing to plan the trajectory of the da Vinci surgical robot paired with a drop-in ultrasound probe and autonomously generate an Ultrasound scan of a kidney phantom.