Authored by: Edited by Leslie Gordon Resources: |
Under normal conditions, the organs of the human body self-regulate and heal when damaged. But when the damage is more severe, it is not always easy in today’s rapidly paced society for patients to get enough rest for the body to heal fully. This is certainly the case when soft tissue such as the ligaments around joints is damaged. In these instances, it is best to implant ligament-augmentation systems to stabilize the joint, allowing the body to heal fully. Some of these implants are only needed for short periods until they have served their purpose. This leaves the problem of what to do with the implant when it hinders full motion in the joint at a later stage. It is almost impossible to remove soft-tissue implants, which are traditionally made of fabrics or biotextiles. However, the development of specialized hyperelastic polymers makes possible soft-tissue implants which perform mechanically as required for a short period of time to stabilize the joint. They then biodegrade naturally, eliminating the need for surgical removal.
For many of these implants, a single elastomeric material is not sufficient. Consider, for instance, a rotator-cuff-ligament replacement and augmentation system (LARS). The implant must be flexible enough to let the patient easily move their arm without restriction. At the same time, it must make the joint stable enough for patients to support objects and hold them steady.
One of our customers has developed an innovative method of injecting multiple slow-curing polymers into a mold to create a one-piece 3D implant with specific anisotropic hyperelastic material properties. Simulating the molding process in Comsol Multiphysics software let us determine how to best manufacture the device in a single production process. The next step would be to add polymers with the required biodegradable properties.
Initial prototype molds had areas consisting of two elastomers, with the regions between being a continuous blend or mix of the two elastomers. In order to get the needed mix and final cured anisotropic material properties, it was necessary to control several parameters including the injection sites, the temperatures of the injected polymers, the mold, and specific faces of the mold. Other aspects included the rate at which the individual polymers entered the mold and the combined volumes of these materials.
Needless to say, it can be difficult to determine the proper parameters for all these variables. Fortunately, Comsol Multiphysics has the capabilities to model this phenomena fully.
Simulating the implant mold process
The Comsol multiphysics model of the LARS implant consisted of three domains: a solid region for the mold walls, a liquid region for the injected polymers, and a gas region for the air in the cavity. The coinjected polymers mix prior to entering the mold. This was simulated by the use of a boundary condition that described the volume fractions of the two polymers as a function of the injection rate. The description was easily defined in Comsol with the use of functions.
To handle the complex interactions of the polymers with each other and their surroundings, we coupled three transient physics interfaces. First, a two-phase flow-field interface simulated the liquid flow front as it evacuated the air from the mold cavity. Another interface simulated the mixing of the two injected polymers in the liquid phase and their interactions with each other. Lastly, the convection and conduction application mode modeled the thermal interaction in and between the fluid, solid, and gas regions. When the injection process came to a stop, the filled cavity was cooled and the polymers cured. During this curing process, the polymers’ densities and viscosities varied with temperature and time, with fluid-fluid interaction continuing until high viscosities were reached and all flow stopped. These changes were also captured with Comsol Multiphysics.
Validating the multiphysics model
To validate the multiphysics model, we qualitatively evaluated the model by comparing video footage of the liquid-air flow front during the filling process with the same process modelled in Comsol. The model gave an excellent representation of the fluid-air interface and the observed flow around various 3D features, such as walls and curved surfaces, including flow baffles in the mold cavity, at different injection rates.
In addition, we placed virtual thermocouples inside the model at the top, bottom, and sides of the mold cavity to measure the temperature of the polymers as they flowed into the cavity and cooled. The readings closely corresponded with the physical test data obtained. The model used an ideal smooth flow function for the injection process, which was deemed suitable for our purposes. In reality, there are discontinuities in the physical injection profile that result from the switching of the solenoids that control the polymer flow rates into the mold.
Once the mold had cooled and the polymer cured, sectional cuts were made in sample devices to assess and compare the boundary regions between the two polymers with the model. Once again, the model gave good comparisons to the actual makeup of the implants.
Without the model, finding the critical parameters that control polymer location would have taken much longer and cost almost 20 times more. The polymers we used made it extremely difficult to define and observe the boundaries and graduated regions in physical samples. To do so would require adding microbubbles or additive dyes to the polymers to differentiate the regions. However, this changes their flow qualities and the results. Another option was to use mechanical-indent techniques and analysis to map physical material differences at points throughout the mold, which is a costly exercise. The Comsol model gave far better insight into what was happening during the mold process.
With the validated model in hand, we plan on introducing more biodegradable products using the multipolymer injection process. In addition, we intend to implement multiple injections to allow for a diverse range of shaped products. Perhaps most ambitious of all, though, is to add parameterization to the Comsol multiphysics model, which will let us quickly account for different anatomies, joint complications, and diseases. We plan on creating an optimization process to the multiphysics model which will let us merely describe the end product’s needed geometry and regions, and the model will solve for the best number of injection sites, polymer flow rates, and process parameters to obtain the required product.