Spinal Alignment Registration With Camera Arrays During Surgery
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Solution Overview
Problem
Existing navigation systems for spine deformity surgery rely on manual interpretation of exposed physical anatomy or 2D/3D radiographs, which are imprecise and interfere with surgical workflow, exposing patients and surgeons to radiation.
Innovation Solution
A camera array system that captures real-time images and registers them with preoperative data to determine spinal alignment parameters in real-time, using a synthetic augmented reality system to overlay and update surgical plans without radiation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual interpretation of 2D/3D radiographs is used to assess spinal correction, then measurement precision is improved, but productivity deteriorates due to workflow interruption and radiation exposure
Solution Approach 1:
The patent replaces the mechanical/radiographic imaging system with an optical camera array system. Instead of using X-ray or CT imaging to capture spinal anatomy, the system uses multiple optical cameras to capture images of the spine and surgical instruments, eliminating radiation exposure while maintaining real-time visualization capability.
Solution Approach 2:
The patent creates a virtual copy of the spinal anatomy by registering preoperative 3D imaging data (CT or MRI) with intraoperative optical images. This virtual model allows surgeons to assess spinal alignment and correction without repeatedly exposing the patient to radiation from radiographic imaging.
2Measurement precision
If intraoperative radiographic imaging is used to monitor spinal alignment, then measurement precision is improved, but object-affected harmful factors worsen due to ionizing radiation exposure
Solution Approach 1:
The patent substitutes radiographic imaging systems (X-ray, fluoroscopy) with an optical imaging system consisting of multiple cameras. This replacement eliminates ionizing radiation exposure to both the patient and surgical team while providing real-time visual feedback on spinal alignment during surgery.
Solution Approach 2:
The patent introduces a virtual 3D model as an intermediary between the physical spine and the surgeon's assessment. By registering preoperative imaging data with intraoperative optical images, the system provides accurate alignment information without requiring direct radiographic exposure of the patient.
3Device complexity
If subjective mental assessment of exposed anatomy is used, then device complexity is reduced, but measurement precision deteriorates due to subjectivity and irrepeatability
Solution Approach 1:
The patent creates a virtual copy of the spinal anatomy from preoperative 3D imaging data and registers it with intraoperative optical images. This virtual model provides an objective, quantifiable representation of spinal alignment that eliminates subjective interpretation while maintaining relative system simplicity.
Solution Approach 2:
The patent implements a feedback system that continuously updates the virtual 3D model with intraoperative optical images, allowing real-time assessment of spinal alignment. This provides objective, repeatable measurements while maintaining manageable system complexity through automated image processing and registration algorithms.
Data Source
AI summary
Methods and systems for intraoperatively determining alignment parameters of a spine during a spinal surgical procedure are disclosed herein. In some embodiments, a method of intraoperatively determining an alignment parameter of a spine during a surgical procedure includes receiving initial image data of the spine including multiple vertebrae and identifying a geometric feature associated with each vertebra in the initial image data. The geometric features each have a pose in the initial image data and characterize a three-dimensional (3D) shape of the associated vertebra. The method further comprises receiving intraoperative image data of the spine and registering the initial image data to the intraoperative image data. The method can then update the pose of each geometric feature based on the registration and the intraoperative image data, and determine the alignment parameter based on the updated poses of the geometric features associated with two or more of the vertebrae.