CT Soft Tissue Modeling for Marker-Free Surgical Planning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current surgical joint repair procedures face challenges in accurately selecting and positioning prosthetics due to the lack of consideration for soft tissue structures, which affect joint function and surgical outcomes.
Innovation Solution
Systems and methods that determine soft tissue dimensions and characteristics from patient imaging data to suggest appropriate surgical interventions, such as shoulder replacement types, and recommend implant types based on bone density metrics, using mixed reality visualization for preoperative planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surgical planning uses only bone structure visualization, then the surgical process is simple, but the accuracy of prosthetic selection and positioning is insufficient
Solution Approach 1:
The patent combines bone structure visualization with soft tissue structure visualization into a single integrated 3D model. The system processes CT images to generate both bone models and soft tissue models, then merges them into a unified visualization that displays both structures simultaneously with different transparency levels, allowing surgeons to see both hard and soft tissues in one view without switching between separate systems.
Solution Approach 2:
The patent transitions from 2D CT images to 3D visualizations of both bone and soft tissue structures. By creating three-dimensional models that incorporate spatial relationships and volumetric data, the system provides depth and contextual information that cannot be obtained from traditional 2D imaging, enabling more accurate prosthetic planning.
2Measurement precision
If soft tissue structures are included in the 3D model, then surgical planning accuracy improves, but the time required for image processing increases
Solution Approach 1:
The system performs preliminary segmentation and classification of soft tissue structures during the initial image processing phase. By identifying and categorizing different soft tissue types (muscle, fat, connective tissue) upfront based on intensity values, the system prepares the data for rapid visualization and analysis during surgical planning, reducing the time needed during the actual surgical workflow.
3Measurement precision
If intensity-based soft tissue segmentation is used, then soft tissue boundaries are clearly defined, but the method fails when intensity values are similar between different tissues
Solution Approach 1:
The system dynamically adjusts segmentation parameters based on the specific tissue being analyzed. Different intensity thresholds, range values, and classification criteria are applied depending on the tissue type (muscle, fat, connective tissue). The system also incorporates spatial context and anatomical position information to refine boundary detection when intensity values alone are insufficient.
Data Source
AI summary
A surgical planning system for use in surgical procedures to repair an anatomy of interest includes a preplanning system to generate a virtual surgical plan and a mixed reality system that includes a visualization device wearable by a user to view the virtual surgical plan projected in a real environment. The virtual surgical plan includes a 3D virtual model of the anatomy of interest. When wearing the visualization device, the user can align the 3D virtual model with the real anatomy of interest, thereby achieving a registration between details of the virtual surgical plan and the real anatomy of interest. The registration enables a surgeon to implement the virtual surgical plan on the real anatomy of interest without the use of tracking markers.