Personalized Meniscus Scaffold Weaving for Consistent Implant Geometry
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Solution Overview
Problem
Current methods for fabricating personalized fiber-reinforced scaffolds for meniscal tissue replacement are labor-intensive, prone to human error, and yield inconsistent results due to inter- and intra-operator variability, failing to match the patient's specific needs and geometry of the damaged meniscus.
Innovation Solution
A system and method using a processor to generate data for a target soft tissue implant, including a scaffold and reinforcing matrix, with optimized weaving or printing paths based on patient-specific dimensions, and employing a root-mean-square error algorithm to minimize fabrication errors, resulting in a personalized fibrocartilage implant.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Strength
If manual weaving of continuous fiber in distinct patterns is used, then the scaffold can bear circumferential tensile loads, but the fabrication process is labor-intensive and yields inconsistent results due to inter- and intra-operator variability
Solution Approach 1:
The patent replaces manual mechanical weaving with automated robotic arm systems that precisely deposit continuous fibers according to pre-programmed paths. The robotic system uses computer-controlled mechanisms to lay fibers in specific patterns (e.g., orthogonal, concentric, or user-defined patterns) with consistent spacing and tension, eliminating operator variability while maintaining the mechanical strength properties of the scaffold.
Solution Approach 2:
The patent implements computer-controlled parameters for fiber deposition including precise control of fiber tension, deposition speed, spacing, and path trajectories. These parameters can be programmatically adjusted to optimize scaffold mechanical properties while ensuring reproducible fabrication across different operators and batches, directly addressing the consistency issue.
2Shape
If manual weaving process is used, then the scaffold can be fabricated with intricate internal shape, but the process is limited to lab processes and is not capable of personalizing the artificial meniscus matching the geometry of a native meniscus
Solution Approach 1:
The patent employs pre-computed fiber deposition paths and patterns that are programmed into the robotic system before fabrication begins. These pre-planned trajectories allow the system to accurately reproduce complex meniscus geometries and enable easy personalization by simply updating the digital model and corresponding deposition paths, without requiring manual reconfiguration.
Solution Approach 2:
The system allows modification of geometric parameters (dimensions, curvature, thickness) of the scaffold model to match patient-specific meniscus anatomy. By changing these digital parameters and re-running the automated deposition process, personalized scaffolds can be fabricated consistently, transitioning from lab-only processes to scalable personalized manufacturing.
3Manufacturing precision
If manual fabrication process is used, then the scaffold can be created, but the quality of the scaffold is difficult to control and is subject to human errors
Solution Approach 1:
The patent replaces manual fabrication operations with automated robotic systems that execute pre-programmed deposition sequences. This substitution eliminates operator-dependent variations in technique, ensures consistent fiber placement precision, and provides digital traceability of the fabrication process, thereby improving manufacturing precision while reducing operator dependency.
Solution Approach 2:
The system incorporates sensors and control systems that monitor fiber deposition in real-time, verifying that fibers are placed according to the planned paths with correct spacing and tension. This feedback mechanism enables automatic correction of deviations and ensures consistent scaffold quality independent of operator skill level.
Data Source
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AI summary
Systems (500, 1000) and methods (1700) for fabricating a soft tissue implant (100, 400). The methods generally involve: receiving implant data representative of the target implant; determining a planned weaving path for forming the soft tissue implant; and communicating the planned weaving path to an output device.