Robot-Assisted Reduction of the Ankle Joint via Multi-Body 3D–2D Image Registration

Abstract

Robot-assisted orthopaedic joint reduction offers enhanced precision and control across multiple axes of motion, enabling precise realignment according to predefined plans. However, the high levels of forces encountered may induce unintended anatomical motion and flex mechanical components. To address this, this work presents an approach that uses 2D fluoroscopic imaging to verify and readjust the 3D reduction path by tracking deviations from the planned trajectory. The proposed method involves a 3D-2D registration algorithm using a pair of fluoroscopic images, along with prior models of each body in the radiographic scene. This objective is formulated to couple and constrain multiple object poses (fibula, tibia, talus, and robot end effector), and incorporate novel methods for automatic view and hyperparameter selection to improve robustness. The algorithms were refined through cadaver studies and evaluated in a preclinical trial, employing a robotic system to manipulate a dislocated fibula. Studies with cadaveric specimens highlighted the joint-specific formulation’s high registration accuracy ( $\Delta _{x} {=} 0.3~\pm ~1$ .5 mm), further improved with the use of automatic view and hyperparameter selection ( $\Delta _{x} {=} 0.2~\pm ~0$ .8 mm). Preclinical studies demonstrated a high deviation between the intended and the actual path of the robotic system, which was accurately captured ( $\Delta _{x}$ 1 mm) using the proposed techniques. The solution offers to close the loop on image-based guidance of robot-assisted joint reduction by tracking the robot and bones to dynamically correct the course. The approach uses standard clinical images and is expected to lower radiation exposure by providing 3D information and allowing the staff to stay clear of the x-ray beam.