Learning Needle Placement in Soft Tissue With Robot-assisted Navigation

Area of Science:

• Medical robotics
• Medical imaging technology
• Surgical simulation

Background:

• Novice practitioners require effective training methods for complex procedures.
• Robotic assistance systems (RAS) offer potential for enhanced precision and control in interventions.
• Cone-beam computed tomography (CBCT) provides real-time imaging guidance for needle placement.

Purpose of the Study:

• To evaluate the learning curves of novices using a novel RAS for CBCT-guided needle placement.
• To assess the impact of RAS on precision, intervention duration, autonomy, and confidence.
• To determine the feasibility of RAS in training for image-guided procedures.

Main Methods:

• Ten novice participants performed 18 CBCT-guided needle punctures each in a phantom model.
• Training and practice were conducted over three days with RAS support.
• Key performance metrics included needle tip deviation, total intervention time, needle placement duration, autonomy, and self-reported confidence.

Main Results:

• No significant difference in needle tip deviation was observed across trial days (Day 1: 2.82 mm vs. Day 3: 3.07 mm).
• Significant reductions in total intervention duration (Day 1: 11:22 min vs. Day 3: 07:39 min) and needle placement duration (Day 1: 03:17 min vs. Day 3: 02:11 min) were recorded.
• Participant autonomy (Day 1: 94% vs. Day 3: 99%) and confidence (Day 1: 78% vs. Day 3: 91%) significantly increased.

Conclusions:

• Novices achieved precise CBCT-guided needle interventions with RAS support from the first day.
• The RAS facilitated significant improvements in procedural efficiency and participant confidence over the trial period.
• The study demonstrates the potential of RAS to accelerate the learning curve for image-guided interventions.