The ARAI is an advanced digital surgery platform that combines 3D visualisation, data analytics, and machine learning to improve outcomes, reduce surgical time, and decrease surgical complications. The clinically-tested ARAI surgical guidance system provides real-time, patient-specific, 3D anatomical visualisation for pre-surgical planning, real-time intraoperative guidance, and postsurgical data analytics. The system:
- Provides surgeons with “X-ray-like vision”, allowing them to “see” the colour-coded organs as if they were not covered by the skin, muscles and connective tissue
- Utilises artificial intelligence to autonomously segment and analyse patient anatomy and identify (by colour coding) key anatomical landmarks in real time
- Utilises artificial intelligence to autonomously plan the surgical procedure in seconds, including implant size and position; avoids inadvertent injury to critical structures (such as nerves and vessels); and offers real-time “smart guidance” during the surgery.
- Utilises augmented reality to allow surgeons to visualise internal anatomical structures such as nerves, vessels, joints, and bones in 3D without making incisions and without looking at a monitor—thus, away from the surgical field
- Increases surgical accuracy and precision by offering surgeons real-time interactive guidance and providing alerts and suggestions throughout the surgical procedure
- Reduces operating time, cost, and complications caused by suboptimal surgical execution
The case, a lumbar decompression and fusion procedure, was performed on a 61-year-old male suffering from severe back and leg pain as a result of a grade 2 spondylolisthesis, a degenerative spinal condition resulting in spinal stenosis. The surgery was performed in a minimally invasive fashion and the ARAI system was flawlessly incorporated into the surgeon’s regular work-flow.
During the procedure, the ARAI system automatically identified relevant anatomical structures and colour coded them, presented a treatment plan, and guided the surgeon to place the implant using augmented reality-based 3D visualisation.