FBG-driven simulation for virtual augmentation of fluoroscopic images during endovascular interventions

Area of Science:

• Medical Imaging
• Interventional Cardiology
• Surgical Technology

Background:

• Endovascular interventions utilize catheters for diagnosing and treating vascular diseases.
• Clinicians face challenges with small artery cannulation, requiring specialized skills and significant X-ray use.
• Current solutions like simulators or basic augmented reality lack predictive capabilities for catheter-guidewire dynamics.

Purpose of the Study:

• To develop and evaluate a novel system for real-time enhancement of fluoroscopic 2D images during endovascular procedures.
• To provide clinicians with predictive visualization of catheter and guidewire configurations, particularly for challenging aortic branch access.
• To reduce the difficulty and improve the efficiency of endovascular interventions.

Main Methods:

• A novel predictive simulation system was developed to visualize virtual catheter and guidewire configurations in real-time.
• The system predicts the final catheter shape after guidewire withdrawal without manual intervention.
• Performance was assessed using 3D error metrics and a user study evaluating intervention time and X-ray exposure.

Main Results:

• The system demonstrated accurate shape prediction with a mean 3D error of 2.4 ± 1.3 mm and a mean 2D error of 1.1 ± 0.7 mm.
• A user study showed an average reduction in intervention time of 56%.
• Adoption of the system led to decreased overall X-ray exposure for clinicians.

Conclusions:

• The proposed predictive simulation system significantly enhances fluoroscopic guidance for endovascular interventions.
• This technology offers a valuable tool for improving procedural efficiency and reducing radiation exposure.
• The system addresses a critical challenge in accessing difficult vascular anatomies, improving patient care.