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Spinal fusion — the merging of two vertebrae — could treat an extensive range of spinal disorders.
Frequently, surgeons will utilize a cage to offer support where the disk once was present between the vertebrae. However, what if those cages could aid the spine’s healing in more ways than one?
At the University of Pittsburgh Swanson School of Engineering, scientists are engineering patient-specific 3D-printed smart metamaterial implants to double as sensors to supervise spinal healing.
A study elaborating on their work was reported recently in the Advanced Functional Materials journal.
Smart implants can provide real-time biofeedback and offer many therapeutic and diagnostic benefits. But it is very challenging to integrate bulky circuits or power sources into the small area of implants. The solution is to use the implant matrix as an active sensing and energy harvesting medium. That’s what we’ve been focused on.
Amir Alavi, Assistant Professor, Civil and Environmental Engineering, Swanson School of Engineering, University of Pittsburgh
Alavi's iSMaRT Lab headed the study.
The Intelligent Structural Monitoring and Response Testing (iSMaRT) Lab has come up with a new type of multifunctional mechanical metamaterials, which serve as their sensors, recording and relaying significant data regarding the stresses and pressure on its structure.
The alleged “meta-tribomaterials,” also known as self-aware metamaterials, produce their power and could be utilized for an extensive range of sensing and monitoring applications.
The material has been developed such that under pressure, contact-electrification happens between its conductive and dielectric microlayers, thereby making an electric charge that relays data regarding the condition of the material matrix.
It also naturally inherits the excellent mechanical tunability of standard metamaterials.
The power produced by making its built-in triboelectric nanogenerator mechanism removes the requirement for an individual power source, and a small chip records data regarding the pressure on the cage, which is a significant indicator of healing. Further, the data can be read noninvasively with the help of a portable ultrasound scanner.
Not only is the suggested cage special in its sensing abilities, but it is also made of a highly tunable material that could be tailored to the requirements of patients.
Spinal fusion cages are being widely used in spinal fusion surgeries, but they’re usually made of titanium or PEEK polymer materials (a semi-crystalline, high-performance engineering thermoplastic) with certain mechanical properties.
Amir Alavi, Assistant Professor, Civil and Environmental Engineering, Swanson School of Engineering, University of Pittsburgh
Alavi added, “The stiffness of our metamaterial interbody cages can be readily tuned. The implant can be 3D-printed based on the patient’s specific anatomy before surgery, making it a much more natural fit.”
The team has been successful in testing the device in human cadavers and is searching for ways to move on to animal models next. Since the material itself is unbelievably scalable and tunable, the smart sensor design could be suitable for several other medical applications in the future, like cardiovascular stents or components for hip or knee replacements.
This is a first-of-its-kind implant that leverages advances in nanogenerators and metamaterial to build multifunctionality into the fabric of medical implants. This technological advancement is going to play a major part in the future of implantable devices.
Amir Alavi, Assistant Professor, Civil and Environmental Engineering, Swanson School of Engineering, University of Pittsburgh
The study was co-authored by scientists and surgeons at the University of Pittsburgh, Georgia Institute of Technology, the Beijing Institute of Nanoenergy and Nanosystems, and the Allegheny Health Network Department of Neurosurgery.
Barri, K., et al. (2022) Patient-Specific Self-Powered Metamaterial Implants for Detecting Bone Healing Progress. Advanced Functional Materials. doi.org/10.1002/adfm.202203533.
Source: https://www.engineering.pitt.edu/
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