Toward FBG-Sensorized Needle Shape Detection in Real Tissue Insertions.

Area of Science:

• Medical Devices
• Surgical Robotics
• Biomedical Engineering

Background:

• Accurate determination of flexible needle shape is crucial for minimally invasive surgical procedures.
• Existing methods may lack precision for real-time shape sensing during insertion.
• Novel sensor technologies are needed to improve planning and validation.

Purpose of the Study:

• To validate a novel needle shape-sensing method using fiber Bragg grating (FBG) sensors.
• To assess the accuracy of the FBG sensor system in both phantom and real biological tissues.
• To establish a reliable 3D needle shape reconstruction model for percutaneous procedures.

Main Methods:

• Development of a flexible needle equipped with four active-area fiber Bragg grating (FBG) sensors.
• Sequential insertion of the FBG-sensorized needle into gel phantoms and animal tissue models.
• Utilizing computed tomography (CT) as the ground truth for needle shape determination.
• Comparison of needle shapes reconstructed from FBG data against CT-derived shapes.

Main Results:

• The FBG sensor-based method demonstrated consistent accuracy in determining needle shape across various insertion depths.
• Shape sensing accuracy in real animal tissue was comparable to that observed in gel phantoms.
• The study successfully validated a 3D needle shape-sensing model and reconstruction technique.

Conclusions:

• The fiber Bragg grating (FBG) sensor system provides a viable and accurate method for real-time flexible needle shape determination.
• This technology has significant potential for enhancing the planning, guidance, and validation of minimally invasive surgical interventions.
• The validated model supports improved safety and efficacy in percutaneous procedures requiring precise needle insertion.