Pelvic Rotation Detection for Accurate Hip Implant Placement
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Solution Overview
Problem
In total hip replacement surgeries, radiographs are affected by patient positioning, leading to misleading measurements and inaccurate implant placement due to changes in pelvic alignment over time, particularly in determining absolute axial rotation and sagittal inclination.
Innovation Solution
A system and method using computing devices to process pelvic images from radiography or fluoroscopy, identifying anatomical landmarks to calculate absolute axial rotation, change in axial rotation, and sagittal inclination, employing machine learning and artificial intelligence for accurate predictions based on preoperative and intraoperative images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radiographs are used for implant placement guidance, then implant positioning can be achieved, but measurement accuracy deteriorates due to patient positioning changes affecting pelvic alignment
Solution Approach 1:
The system performs preoperative planning and establishes reference measurements before the patient's position can change during surgery. By determining the ideal implant position and creating a reference framework beforehand, the system compensates for subsequent positioning variations that occur during the surgical procedure
Solution Approach 2:
The system continuously compares intraoperative radiograph measurements against the preoperative reference measurements to detect deviations caused by patient positioning changes. This feedback loop enables real-time correction of measurement errors and maintains accuracy despite positioning variations
2Manufacturing precision
If multiple pelvic images are processed to determine positioning changes, then accuracy of implant placement improves, but system complexity increases
Solution Approach 1:
The system divides the complex task of implant placement into distinct phases: preoperative planning phase where reference measurements are established, and intraoperative execution phase where images are processed and compared. This segmentation allows each phase to be optimized independently, reducing overall system complexity while maintaining precision
Solution Approach 2:
The system introduces a computational intermediary that automatically processes and compares multiple pelvic images, extracting positioning information and correcting for rotation and inclination changes. This intermediary handles the complex image processing tasks, reducing the burden on the surgical team while improving placement accuracy
Data Source
AI summary
Image-guided implant placement as a function of a determined axial rotation of a pelvis. At least one pelvic image presenting a two-dimensional lateral view of a pelvis and at least one pelvic image presenting a 2-D antero-posterior view of the pelvis are processed, including to measure at least one of distances, angles, and areas based on a plurality of identified anatomical landmarks. Pelvic axial rotation at the time of the 2-D AP image is determined, as a function of calculations associated with the at least one of distances, angles, and areas. Information associated with the determined pelvic axial rotation is provided.