Hip Arthroplasty Registration Using CT-Point Cloud Acetabulum Isolation
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Solution Overview
Problem
Conventional surgical navigation systems face challenges in accurately registering the pelvic operating area (acetabulum) during total hip arthroplasty due to anatomical features that complicate imaging and limited surgical access, particularly in isolating the acetabulum from non-target regions like the femur.
Innovation Solution
A system that utilizes pre-operative CT images and intra-operative fluoroscopy or point cloud data to isolate the pelvic operating area by applying merge rules to exclude non-target regions, and employs a navigated ball tip stylus for surface painting and palpation to define bone surfaces and determine the acetabulum's center of rotation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional imaging methods are used to capture the pelvic region, then the entire pelvic area is imaged, but non-target regions (such as the femur) are included which complicates the isolation of the acetabulum
Solution Approach 1:
The imaging data is segmented into target and non-target regions using merge rules. The system divides the pelvic region imaging into distinct anatomical structures, identifying the acetabulum as the target surgical area and excluding non-target regions like the femur through automated segmentation algorithms that process CT and fluoroscopy images.
Solution Approach 2:
Non-target regions are extracted and removed from the imaging data using merge rules. The system identifies and excludes non-target anatomical structures (such as the femur) from the combined image set, leaving only the relevant acetabular region for surgical navigation and registration.
2Loss of information
If multiple imaging modalities (CT and fluoroscopy) are combined, then more comprehensive anatomical data is obtained, but the complexity of merging and registering these images increases
Solution Approach 1:
CT and fluoroscopy images are merged into a single composite image using merge rules. The system combines pre-operative CT data with intra-operative fluoroscopy images to create a unified anatomical representation that preserves information from both modalities while enabling comprehensive surgical navigation.
Solution Approach 2:
Merge rules act as an intermediary mechanism to bridge different imaging modalities. These rules provide a standardized method for integrating CT and fluoroscopy images, handling coordinate transformations, image alignment, and data fusion to reduce the complexity of multi-modal image registration.
3Measurement precision
If the acetabulum is not properly isolated from non-target regions, then registration accuracy is compromised, but achieving precise isolation requires advanced image processing techniques
Solution Approach 1:
The merge rules are applied in advance to pre-process and isolate the acetabulum from non-target regions before the surgical registration process begins. This preliminary isolation of the target anatomical structure ensures that subsequent registration operations work with clean, pre-segmented data, improving accuracy without adding complexity during the critical surgical phase.
Data Source
AI summary
A system for computer assisted navigation during surgery includes a computer platform that operates to register a target surgical area of a patient. In certain cases, a process includes: obtaining a pre-op CT image of a pelvic region of a patient and intra-operatively obtaining a point cloud data about the pelvic region with a navigated instrument, generating a 3D bone model which excludes non-targeted area such as a femur, and then merging the 3D bone model to the point cloud to register the target surgical area.