Toward Fluoroscopy Guided Robotic Needle Insertion for Radio Frequency Ablation

Abstract

This article presents a fluoroscopy image-based registration method along with a comprehensive protocol for robotic needle insertion in radiofrequency ablation (RFA) to treat liver cancer. The proposed method uses real-time fluoroscopic images acquired from a C-ARM system and integrates an inverse finite element (FE) simulation to compute robotic commands for accurate and adaptive needle steering. The registration procedure is fully automated and involves the injection of multiple radiopaque markers into the liver, enabling precise anatomical registration and targeted tumor localization. A key challenge addressed in this work is the integration of this image-based registration with the inverse biomechanical simulation used to guide the robot during insertion. We describe how registration constraints can be mapped onto the surface of the biomechanical model to ensure consistent alignment between image data and robotic actuation. Designed to be adaptable to varying levels of radiologist expertise and applicable across a wide range of tumor locations, this method provides a robust and versatile solution for improving the accuracy and safety of minimally invasive liver cancer treatments.