The Association Between Trajectory-Skull Angle and Accuracy of Stereoelectroencephalography Electrode Implantation in Drug-Resistant Epilepsy.
World Neurosurg 2024;
184:e408-e416. [PMID:
38309654 DOI:
10.1016/j.wneu.2024.01.139]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 01/24/2024] [Indexed: 02/05/2024]
Abstract
OBJECTIVE
To analyze the relationship between trajectory-skull angle and stereoelectroencephalography electrode implantation accuracy in drug-resistant epilepsy patients, aiming to guide clinical electrode placement and enhance surgical precision and safety.
METHODS
We conducted a retrospective analysis of medical records and surgical characteristics of 32 consecutive patients diagnosed with drug-resistant epilepsy, who underwent stereoelectroencephalography procedures at our center from June 2020 to June 2023. To evaluate the accuracy of electrode implantation, we utilized preoperative and postoperative computed tomography scans fused with SinoPlan software-planned trajectories. Entry radial error and target vector error were assessed as measurements of electrode implantation accuracy.
RESULTS
After adjusting for confounders, we found a significant positive correlation between trajectory-skull angle and entry radial error (β = 0.02, 95% CI: 0.01-0.03, P < 0.001). Likewise, a significant positive correlation existed between trajectory-skull angle and target vector error in all three models (β = 0.03, 95% CI: 0.01-0.04, P < 0.001). Additionally, a U-shaped relationship between trajectory-skull angle and target vector error was identified using smooth curve fitting. This U-shaped pattern persisted in both frame-based and robot-guided stereotactic techniques. According to the two-piecewise linear regression model, the inflection points were 9° in the frame-based group and 16° in the robot-guided group.
CONCLUSIONS
This study establishes a significant positive linear correlation between trajectory-skull angle and entry radial error, along with a distinctive U-shaped pattern in the relationship between trajectory-skull angle and target vector error. Our findings suggest that trajectory-skull angles of 9° (frame-based) and 16° (robot-guided) may optimize the accuracy of target vector error.
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