Hip Prosthesis Alignment Check Using 3D-2D Superimposition
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Solution Overview
Problem
Current 2D-2D methods for checking hip prosthesis alignment are inaccurate due to reliance on manual estimation of anteversion, leading to potential errors in positioning that can cause hip dislocation, premature wear, and inflammation.
Innovation Solution
A computer-based method using 3D models of the pelvic bone and 2D images to accurately superimpose and measure the alignment of the acetabular cup, providing precise anteversion and inclination values by aligning the central symmetry axis of the acetabular cup with the axis passing through the center of the ellipse projection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2D-2D methodology with manual estimation is used to check hip prosthesis alignment, then the procedure is simple and quick, but the measurement precision and reliability of anteversion and inclination values are poor
Solution Approach 1:
The patent transitions from 2D-2D image comparison to 2D-3D hybrid methodology. A 3D model of the acetabular cup is generated from preoperative CT scans, and this 3D model is superimposed on postoperative 2D radiographs. This dimensional change enables accurate measurement of anteversion and inclination by utilizing the spatial information from the 3D model, resolving the inaccuracy inherent in manual 2D estimation while maintaining practical applicability.
Solution Approach 2:
The 3D model of the acetabular cup is prepared in advance from preoperative CT images before the surgery. This preliminary creation of the digital model allows for accurate reference data to be established beforehand, which is then used during postoperative assessment to determine the actual position and orientation of the implanted cup, thereby improving measurement precision without adding complexity to the intraoperative process.
2Reliability
If manual superimposition of 2D images is used, then the operation is straightforward, but the reliability of positioning checks is insufficient leading to potential dislocation and wear
Solution Approach 1:
The patent replaces manual mechanical superimposition with an automated computer-based system. The 3D model is digitally generated and automatically superimposed on the 2D radiograph using image processing algorithms. This substitution of manual operations with automated digital processing significantly improves the reliability and objectivity of positioning checks, eliminating human error while maintaining ease of operation through user-friendly software interfaces.
Solution Approach 2:
A digital copy (3D model) of the acetabular cup is created from preoperative CT data. This virtual replica serves as an accurate reference that can be precisely superimposed on postoperative images. The use of this digital copy enables reliable measurement of cup position and orientation without requiring complex manual procedures, thereby improving reliability while maintaining operational simplicity.
3Manufacturing precision
If 2D image superimposition without 3D reference is used, then the system remains simple, but measurement precision of spatial parameters deteriorates
Solution Approach 1:
The patent introduces a 3D dimension to the measurement system by generating a 3D model of the acetabular cup from preoperative CT scans. This 3D reference model provides accurate spatial information about cup orientation and position, enabling precise measurement of anteversion and inclination angles. The integration of 3D modeling with 2D image analysis achieves manufacturing precision for spatial parameters while the automated processing keeps system complexity manageable.
Data Source
AI summary
A computer-implemented method for checking the correct alignment of a hip prosthesis, includes: detecting a 3D model of the pelvic bone of a patient in a preoperative phase, detecting at least one 2D image of the pelvic bone in post-implant situation, selecting an image of the 3D model according to a first inclination thereof and detecting a reference element on said selected image of the 3D model, identifying a plurality of reference points on the 2D image, superimposing the 2D image on said selected image of the 3D model, checking the correct superimposition and correspondence of the reference points of the 2D image with the reference element with said image of the 3D model, and detecting possible differences in the positioning of the pelvic bone in post-implant configuration with respect to the preoperative situation.