SpineYOYO is a prospective, multi-center clinical research project developing an AI-driven framework to objectively measure the deviation between pre-operative surgical plans and actual intraoperative execution in spinal deformity correction.
Despite meticulous pre-operative planning, there is currently no standardized method to quantify how accurately a spinal deformity surgery follows the original plan. Surgeons rely on subjective post-operative assessment, and the literature shows significant discrepancy between planned and achieved correction.
Develop and validate a novel quantitative metric that expresses surgical plan adherence as a single percentage score through automated DICOM comparison.
Build an ensemble AI system for automated vertebral segmentation, Cobb angle measurement, and pedicle screw trajectory assessment from pre-op and post-op imaging.
Integrate low-cost IMU/BLE inertial sensors for real-time angular guidance during instrumentation, enabling objective intraoperative deviation tracking.
Conduct a prospective clinical study across 3-5 centers to validate the Stick2Plan metric's reliability, reproducibility, and clinical significance.
Automated vertebral segmentation via TotalSegmentator and MONAI deep learning pipelines
Multi-model consensus for critical measurements ensuring clinical-grade accuracy
Universal digital metric calibration using smartphone screens for standardized measurement
6-axis inertial measurement units with BLE connectivity for real-time angular tracking
We welcome collaboration from spine surgeons, biomedical engineers, AI researchers, and clinical centers interested in surgical quality metrics.
Contact Us — info@spineyoyo.com