The aim of the study was to investigate the correlation between the extent of decompression and patient follow-up metrics at 1 year postoperatively by analysing data from a real-world, multicentre cohort of patients, and to clarify the precise extent of decompression for endoscopic spine surgery.

In recent years, endoscopic spine surgery has developed rapidly, especially in the treatment of degenerative spinal diseases. Minimally invasive endoscopic spine surgery has been widely implemented and promoted in hospitals at all levels. The learning curve of endoscopic spinal surgery is steep because it is performed in a narrow space adjacent to sensitive structures such as nerves and blood vessels. The surgical effect completely depends on the experience of the surgeon. How to break through the bottleneck and forbidden zone of endoscopic spine surgery and establish a perfect treatment system for endoscopic spine surgery has become one of the urgent problems and challenges in current spine surgery. At present, enabling technologies such as artificial intelligence, computer-assisted surgical navigation and robotics have been applied in spinal surgery, but their functions are limited to stereotactic orientation. Endoscopic spinal surgery robots that can meet the needs of intelligent surgical planning, precise decompression and flexible micromanipulation under endoscope are still lacking in the world. It is of great practical significance to develop an endoscopic spinal surgery robot platform with artificial intelligence characteristics, and based on this, establish an endoscopic spinal surgery treatment system oriented by accurate, safe and effective improvement of patient clinical outcomes, which is expected to improve the level of diagnosis and treatment of spinal surgery and promote the transformation and industrialization of a new generation of surgical technology. The objectives of this project include: 1) to conduct a real-world study on the precise decompression range of endoscopic spine surgery, to investigate the artificial intelligence-assisted spinal segmentation and automatic decompression planning for endoscopic spine surgery; 2) Develop a new generation of small interactive intelligent endoscopic robot system and supporting new minimally invasive surgical instruments, and study the human-computer interaction control strategy suitable for narrow space; 3) Carry out the effectiveness and safety research of the endoscopic spinal surgery robot, and verify it in model bones, animal bones and humans in general. The products are approved and clinical trials are completed after the relevant parts are filed. Finally, a small interactive endoscopic surgery robot platform and an intelligent decompression planning system were successfully developed, which clarified the scope and operation specification of accurate endoscopic decompression, provided guidance for the popularization of endoscopic surgery, and formed the operation process specification of small interactive minimally invasive endoscopic surgery.

Inclusion Criteria:

1. Patients with lumbar spinal stenosis or lumbar disc herniation with narrow central canal and lateral recess of single lumbar vertebra;
2. formal conservative treatment is ineffective for at least 3 months;
3. Voluntary surgery and follow-up for more than 6 months;
4. Sign informed consent.
5. The patient is > 18 years old and has the ability to act autonomously.

Exclusion Criteria:

1. Previous history of lumbar surgery; 2, combined with lumbar spondylolisthesis, lumbar instability or spinal deformity; 3, there are surgical contraindications, can not perform surgery; 4, can not follow up on time after surgery or lost visitors.

According to the inclusion and exclusion criteria, the number of patients with lumbar spinal stenosis or lumbar disc herniation who underwent endoscopic spinal surgery during 2021-2023 was determined, and the number of patients in the multi-center was not less than 1000