Organ Shape Sensing using Pneumatically Attachable Flexible Rails in Robotic-Assisted Laparoscopic Surgery

TL;DR

This paper introduces a novel organ shape sensing method using a shape-sensing optical fiber integrated into a pneumatically attachable flexible rail system, enabling autonomous ultrasound scanning in robotic-assisted laparoscopic surgery.

Contribution

It demonstrates the integration of shape sensing into a soft robotic rail for organ curvature measurement and autonomous ultrasound scanning in surgical settings.

Findings

Shape sensing accuracy depends on the rail's material stiffness.

The system successfully autonomously scans a kidney phantom.

Material stiffness impacts curvature sensing precision.

Abstract

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.