CathSim: An Open-source Simulator for Autonomous Cannulation

Abstract

Autonomous robots in endovascular operations have the potential to navigate circulatory systems safely and reliably while decreasing the susceptibility to human errors. However, there are numerous challenges involved with the process of training such robots such as long training duration due to sample inefficiency of machine learning algorithms and safety issues arising from the interaction between the catheter and the endovascular phantom. Physics simulators have been used in the context of endovascular procedures, but they are typically employed for staff training and generally do not conform to the autonomous cannulation goal. Furthermore, most current simulators are closed-source which hinders the collaborative development of safe and reliable autonomous systems. In this work, we introduce CathSim, an open-source simulation environment that accelerates the development of machine learning algorithms for autonomous endovascular navigation. We first simulate the high-fidelity catheter and aorta with the state-of-the-art endovascular robot. We then provide the capability of real-time force sensing between the catheter and the aorta in the simulation environment. We validate our simulator by conducting two different catheterisation tasks within two primary arteries using two popular reinforcement learning algorithms, Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC). The experimental results show that using our open-source simulator, we can successfully train the reinforcement learning agents to perform different autonomous cannulation tasks. Our CathSim simulator is publicly available at https://github.com/tudorjnu/cathsim.

A haptic guidance system for simulated catheter navigation with different kinaesthetic feedback profiles

“…This simulation takes a practical approach diverging from comparable simulations that initiate from points unrelated to the intervention, such as starting at the aortic valve and progressing towards the subclavian arteries. 39,40 Moreover, while some studies confine the workspace to a solitary vein or artery, 16,21 A modified version of the segmentation method used by koc et al, 31 is employed in this study to have four regions roughly the same length. This modification makes it easier to compare the performances of the regions.…”