Objective:

To determine the optimal incision placement for uniportal spinal endoscopic fusion to maximize disc and endplate preparation, enhance surgical access, and improve the feasibility of larger grafts.

Key Findings:

• Optimal incision placement significantly enhances disc and endplate preparation, leading to improved surgical outcomes.
• Increased graft-bone interface correlates with improved fusion success rates, with specific metrics indicating a higher likelihood of successful fusion.
• Machine learning models can accurately predict optimal incision sites from MRI data, demonstrating a high degree of reliability.

Interpretation:

Computationally optimized incision placement can significantly improve surgical outcomes in uniportal spinal endoscopic fusion by maximizing access and preparation capacity, ultimately enhancing patient recovery.

Limitations:

• Study is retrospective and may not account for all variables affecting surgical outcomes, including potential biases.
• Findings are based on a specific cohort and may not generalize to all patient populations.

Conclusion:

Optimizing incision placement through advanced modeling techniques can enhance surgical efficacy in lumbar endoscopic fusion procedures.