A Novel Sensor for Tissue Mechanical Property Detection During Robotic Surgery.

Area of Science:

• Biomedical Engineering
• Surgical Robotics
• Sensing Technologies

Background:

• Haptic feedback is crucial for surgeons to discern tissue mechanical properties during open surgery.
• This vital sensory information is lost in Robot-assisted Minimally Invasive Surgery (RMIS).
• Current RMIS systems lack the ability to relay tissue characteristics to the surgeon.

Purpose of the Study:

• To develop and validate a novel instrument-integrated sensor for tissue identification based on mechanical properties in RMIS.
• To overcome the loss of haptic feedback in robot-assisted surgery.
• To enhance surgical precision and decision-making during RMIS procedures.

Main Methods:

• Integration of fiber Bragg grating (FBG) arrays into a surgical instrument.
• Development of an automated analysis system for sensor data.
• Experimental validation using tissue phantoms with varying hardness.
• Comparison of sensor performance against conventional robotic surgery and direct palpation.

Main Results:

• Novice and expert users had significant errors (22.5% and 12.5%) sorting phantoms with conventional robots.
• Direct palpation reduced errors to 2.5% and 0% for novices and experts, respectively.
• The sensorized instrument with automated analysis achieved 0% error across all trials, demonstrating superior performance.

Conclusions:

• The developed FBG-based sensor effectively identifies tissues by their mechanical properties.
• This technology has the potential to restore crucial sensory information in RMIS.
• The sensor can aid in characterizing tumors and other structures, improving surgical outcomes and enabling autonomous surgery.