Real-Time 3D Guidewire Reconstruction from Intraoperative DSA Images for Robot-Assisted Endovascular Interventions

2025-06-24

AI Summary

In robot-assisted endovascular interventions, the lack of depth information in intraoperative 2D digital subtraction angiography (DSA) impedes accurate spatial perception of guidewires. To address this, we propose a DSA-driven real-time 3D guidewire reconstruction method. Our approach introduces a novel multimodal real-time registration and inverse-projection framework that jointly fuses preoperative CTA-derived 3D vascular models with intraoperative 2D DSA images. To our knowledge, this is the first method achieving sub-pixel accuracy (projection error: 1.76 ± 0.08 pixels) and high geometric fidelity (length deviation: 2.93 ± 0.15%) in 3D guidewire deformation reconstruction at clinical-grade frame rates (39.3 ± 1.5 FPS). The method significantly enhances the robot’s spatial awareness and navigation precision, providing robust, real-time 3D guidance for minimally invasive endovascular procedures.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: 3D Computer Vision
• Planning, Routing, and Scheduling: Model-Based Reasoning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

Abstract

Accurate three-dimensional (3D) reconstruction of guidewire shapes is crucial for precise navigation in robot-assisted endovascular interventions. Conventional 2D Digital Subtraction Angiography (DSA) is limited by the absence of depth information, leading to spatial ambiguities that hinder reliable guidewire shape sensing. This paper introduces a novel multimodal framework for real-time 3D guidewire reconstruction, combining preoperative 3D Computed Tomography Angiography (CTA) with intraoperative 2D DSA images. The method utilizes robust feature extraction to address noise and distortion in 2D DSA data, followed by deformable image registration to align the 2D projections with the 3D CTA model. Subsequently, the inverse projection algorithm reconstructs the 3D guidewire shape, providing real-time, accurate spatial information. This framework significantly enhances spatial awareness for robotic-assisted endovascular procedures, effectively bridging the gap between preoperative planning and intraoperative execution. The system demonstrates notable improvements in real-time processing speed, reconstruction accuracy, and computational efficiency. The proposed method achieves a projection error of 1.76$pm$0.08 pixels and a length deviation of 2.93$pm$0.15%, with a frame rate of 39.3$pm$1.5 frames per second (FPS). These advancements have the potential to optimize robotic performance and increase the precision of complex endovascular interventions, ultimately contributing to better clinical outcomes.

Problem

• Real-time 3D guidewire reconstruction for robot-assisted interventions
• Overcoming 2D DSA limitations in depth perception
• Enhancing spatial accuracy in endovascular procedures

Innovation

• Combines preoperative 3D CTA with intraoperative 2D DSA
• Uses deformable image registration for alignment
• Employs inverse projection for 3D reconstruction