Robot-assisted catheter navigation using learning from demonstration (LfD) and non-rigid registration of anatomical data to generate patient-specific catheter trajectories
Target Population
Patients undergoing endovascular procedures, particularly with type I aortic arch anatomy
Care Setting
Interventional radiology or endovascular surgical suites with robotic catheterization platforms
Key Highlights
Robot-assisted catheterization systems improve stability, precision, operator comfort, and reduce radiation exposure compared to manual catheterization.
Learning-based techniques enable semiautonomous robotic catheter navigation by encoding expert motion patterns and adapting trajectories to patient-specific vascular anatomies.
The proposed method integrates preoperative imaging and non-rigid registration to generate patient-specific catheter trajectories, reducing catheter contact forces and potential vascular complications.
Guideline-Based Recommendations
Diagnosis
Utilize preoperative imaging to obtain detailed anatomical information for surgical planning.
Management
Incorporate robot-assisted catheter navigation systems that leverage learned expert motion patterns for endovascular interventions.
Apply non-rigid registration techniques to adapt robotic catheter trajectories to individual patient anatomies.
Monitoring & Follow-up
Assess catheter path smoothness and contact forces during procedures to minimize risk of vascular injury.
Use flow simulation models to validate catheterization success and safety preoperatively.
Risks
Monitor for complications such as vessel perforation, embolization, and dissection caused by excessive catheter-vessel interaction.
Be aware of variability in vascular anatomy that may affect catheter navigation and require trajectory adaptation.
Patient & Prescribing Data
Patients undergoing endovascular catheterization, especially those with type I aortic arch anatomy
Robotic catheterization guided by learned expert trajectories and anatomical data can improve procedural success and reduce vascular trauma compared to manual techniques.
Clinical Best Practices
Integrate preoperative imaging data into robotic navigation systems for patient-specific trajectory planning.
Utilize learning from demonstration frameworks to encode expert catheter manipulation skills for robotic assistance.
Employ shared control navigation to balance operator input and robotic automation for enhanced safety and efficiency.
Validate robotic catheter trajectories with flow simulation prior to clinical application.
