Pedicle Screw Insertion Surgical Simulator

Abstract

Scoliosis is a sideway spinal deformity. If the curvature is measured to be more than 50 ∘, surgery is required to straighten the spine. Pedicle screw insertion is a procedure that requires the placement of screws from the pedicle into the vertebral body. A rod is used to connect all the pedicle screws. The spine is straightened during the connection process. One of the most common techniques used for pedicle screw insertion is called the free hand technique, where the surgeon creates a screw channel by manually probing into the spine. The surgeon relies strongly on haptics feedback. However, small changes in force or direction can cause the probe to breach out of the spine. If the breach reaches the spine medial, the spinal cord could be damaged. Even experienced surgeons can not prevent breach. In this paper, a pedicle screw insertion simulator is developed which combines visual and haptics sensation to recreate the channel creation process of the surgery. The device includes a linear actuator and a rotary motor. The simulator is tuned to four different surgical scenarios by 2 expert surgeons. Ten additional surgeons are asked to participate in the clinical study. Four research questions were examined: 1. Can experience help the surgeon improve correct breach recognition rate? 2. Can experience help the surgeon improve overall correct scenario recognition rate? 3. Is there any performance difference between surgeons with different experience levels? 4. Can the simulation trials become a learning tool for the simulation tasks? It was concluded that there is no statistically significant relationship between the wrong breach or total wrong recognition rate and surgical experience. Furthermore, there is statistical significance in the hard probing scenario between surgical experience and vertical force variance. Lastly, ANOVA analysis is used to examine breach force and velocity performance between three trials to evaluate learning with increase trials. The results are close to being statistical significant.