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Full-Endoscopic Spine Surgery for Adjacent Segment Disease Using Artificial Intelligence-Assisted 3-Dimensional
Koyo Koizumi1, Daisuke Ukeba1, Ken Nagahama1,2
1Department of Orthopaedic Surgery, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
JBJS Case Connector
|January 23, 2026
Summary
Full-endoscopic spine surgery (FESS) effectively treated adjacent segment disease (ASD) in an 82-year-old woman. AI-assisted 3D imaging enhanced surgical planning, leading to long-term pain relief and no symptom recurrence.
Area of Science:
- Neurosurgery
- Spinal Surgery
- Medical Imaging
Background:
- Adjacent segment disease (ASD) is a potential complication following lumbar fusion surgery.
- L3 radiculopathy can cause significant medial thigh pain.
- Previous lumbar decompression and fusion surgeries increase the risk of ASD.
Purpose of the Study:
- To evaluate the efficacy of Full-Endoscopic Spine Surgery (FESS) for treating adjacent segment disease (ASD).
- To assess the role of AI-assisted 3D imaging in preoperative planning for FESS in ASD patients.
Main Methods:
- A case study of an 82-year-old female patient with L3 radiculopathy secondary to ASD.
- Preoperative planning utilized AI-assisted 3D magnetic resonance imaging (MRI)/computed tomography (CT) fusion images.
- Targeted decompression was performed using FESS under local anesthesia.
Main Results:
- The patient experienced immediate postoperative pain relief.
- At a 3-year follow-up, the patient remained asymptomatic.
- No recurrence of symptoms was observed during the follow-up period.
Conclusions:
- FESS is a viable treatment option for adjacent segment disease (ASD).
- AI-assisted 3D MRI/CT fusion imaging significantly aids in detailed surgical planning for FESS.
- This combined approach offers an effective strategy for managing ASD and improving patient outcomes.
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