Ligament Strain Imaging for Guided Pie-Crusting in Knee Arthroplasty
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Solution Overview
Problem
Conventional methods for soft tissue balancing in total knee arthroplasty, particularly in patients with varus and valgus knee deformities, lack objective and reproducible techniques for determining ligament strain, leading to subjective and inconsistent results in soft tissue release procedures.
Innovation Solution
The use of digital image correlation (DIC) to analyze image data from a ligament, combined with a template-assisted perforation method, provides quantitative guidance for controlled and repeatable soft tissue release by determining fiber strain and guiding the location and number of perforations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensor-based techniques are used to measure stiffness and elongation at a single location, then the measurement process is simple, but the results do not account for spatial variations of fiber strain and lack local change information
Solution Approach 1:
The patent replaces traditional mechanical sensor-based measurement systems with an optical imaging system. Digital image correlation (DIC) technology uses captured images to compute strain fields, substituting mechanical contact sensors with non-contact optical methods. This enables full-field spatial strain measurement without physical sensors on the ligament, resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
The patent creates a digital copy of the ligament's surface using captured images. By applying a speckle pattern and capturing its deformation through imaging, the system creates a virtual representation that can be analyzed computationally. This digital twin approach allows detailed spatial strain analysis without requiring complex physical sensor arrays on the actual ligament.
2Reliability
If pie-crusting is performed based on surgeon discretion and interpretation, then the procedure is simple to perform, but the results are highly subjective and not controlled or repeatable
Solution Approach 1:
The patent implements real-time feedback by continuously monitoring ligament strain through DIC during the pie-crusting procedure. The system provides quantitative strain data that feeds back to the surgeon, allowing adjustment of perforation strategy based on actual measured response. This closed-loop feedback replaces subjective judgment with objective measurement, ensuring repeatable and reliable results.
Solution Approach 2:
The patent performs preliminary strain assessment and planning before the actual pie-crusting procedure. By capturing baseline images and computing initial strain fields, the system establishes a reference state that guides subsequent perforation decisions. This preliminary characterization enables controlled and repeatable intervention based on pre-established objective criteria rather than intraoperative subjectivity.
3Measurement precision
If conventional methods are used for soft tissue balancing in varus and valgus deformities, then the procedure follows traditional protocols, but the results lack objectivity and reproducibility
Solution Approach 1:
The patent introduces a template with marked aperture locations as an intermediary tool between the complex DIC system and the surgeon's hands. The template translates detailed image analysis results into simple, pre-determined perforation sites that are easy to execute. This intermediary device bridges the gap between sophisticated measurement and simple surgical action, maintaining both precision and ease of operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach yields quantifiable, objective, and reproducible results in soft tissue balancing, improving clinical outcomes by ensuring accurate and consistent ligament release.
Implementation Method 1
determining, by one or more processors, a fiber strain of at least a portion of the ligament by analyzing the image data using digital image correlation (DIC)
Data Source
AI summary
Systems and methods for determining the fiber strain of a subject's ligament are provided. An example method may include capturing, via an imaging device, image data comprising two or more images of the ligament. The method may include determining, by one or more processors, a fiber strain of at least a portion of the ligament by analyzing the image data using digital image correlation, and based on the fiber strain, providing, by the one or more processors, guidance for performing a guided release of the ligament. The guided release may be performed using a template having a plurality of apertures, via which one or more perforations to the ligament of the subject are made using a perforation device. When applied to total knee replacement (TKA) procedures, the guided release techniques ensure optimal balance in the knee throughout both flexion and extension movements and enhances overall functionality of the knee joint.