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Endpoint Accuracy in Manual Control of a Steerable Needle
Nick J van de Berg1, Jenny Dankelman1, John J van den Dobbelsteen1
1Department of Biomechanical Engineering, Delft University of Technology, Faculty of Mechanical, Maritime and Materials Engineering, Mekelweg 2, Delft 2628CD, The Netherlands.
Journal of Vascular and Interventional Radiology : JVIR
|October 11, 2016
Summary
Human operators can manually steer a novel steerable needle to precise targets without withdrawing it. This active needle technology offers improved accuracy over automated systems in tissue simulations.
Area of Science:
- Medical Devices
- Robotics
- Surgical Navigation
Background:
- Minimally invasive procedures require precise instrument control.
- Steerable needles offer enhanced maneuverability for targeted interventions.
- Manual control of steerable needles is an area of active research.
Purpose of the Study:
- To evaluate the capability of human operators to manually correct needle insertion path errors.
- To assess the performance of an active, tip-articulated steerable needle in reaching predefined targets.
- To investigate needle steering without requiring partial withdrawal.
Main Methods:
- A steerable needle with a flexure joint and retractable stylet was used.
- Manual insertions were performed under camera-based image guidance in tissue simulants.
- Steering tasks involved reaching targets with a 20 mm lateral displacement in 5 directions.
- Automated insertions were conducted for repeatability assessment.
Main Results:
- Manual steering achieved a targeting error of 0.5 mm ± 1.1 mm in stiff tissue.
- Manual steering variability (1.1 mm) was lower than automated insertions (1.4 mm).
- Increased tissue stiffness correlated with greater lateral tip displacement.
- Tip angle control was user-driven and independent of tissue stiffness.
Conclusions:
- Human operators can effectively steer needles to target locations using image guidance.
- The active, tip-articulated steerable needle enables precise manual navigation.
- This technology shows promise for improving accuracy in image-guided interventions.
