There are several advantages to being able to use this technology in medical applications. For example, current knee implants for treating knee arthritis are manufactured in a limited number of shapes and sizes. Although new 3D printing techniques are starting to be employed to make implants designed to an individual patient’s shape, this doesn’t take into account the constraints imposed by surgical planning, as well as the patient’s weight or activity levels. These are important elements to understand how a patient’s anatomy and a knee implant will interact and are crucial to the implant design and post-surgical rehabilitation.
Generative design allows the implants to be biomechanically specific, so the implant is tailored to the load it will be bearing. This also allows the end product to be lighter, less prominent and minimally invasive, which means the patient will heal more quickly and is also less likely to need revision surgery.
In the new study, the researchers set out how the design produced by Autodesk’s software can be manufactured and processed into a functional prototype, including how much of the process can be automated.
Postgraduate and lead researcher, Mr Sanjeevan Kanagalingam, of the University of Birmingham, said: “The ‘one-size-fits-all’ approach used in knee surgery to treat osteoarthritis can result in major complications, primarily due to overengineered implant designs and therefore limits surgical adoption and patient outcomes. This AI integrated design interface allows us to configure tailored surgical planning parameters and take personal biomechanical information into account, and synergistically combine it with the embedded manufacturing intelligence to model medical-grade titanium implants that are specific to each patient.”
Principal Investigator and Senior Lecturer, Dr Lauren Thomas-Seale, also at the University of Birmingham, added: “The combination of the academic, industrial and clinical knowledge of the team working on this project, and the vast design space offered by Generative Design, has yielded implant designs beyond anything that has been seen before. Such an approach, noting the diversity of the project team, has enabled the development of a design process which can take into account the many differences between patients, for example the variation between male and female body mass.”
The next steps will be to mechanically test the devices to see how much they bend and flex under loads. If successful, the team will eventually move on to clinical testing.
Kanagalingam concluded: “This generative design approach not only increases the patient-specificity of bone fixations but also serve as a novel, versatile framework in the design of load-bearing patient-specific implants for the hips, shoulders and maxillofacial surgeries”
