Pre-Clinical Virtual Testing and Finite Element Modeling is Gaining Traction with Engineers, Surgeons and Regulators
The International Society for Technology in Arthroplasty (ISTA) is one of the leading international conferences about innovation in orthopedics. One of the best aspects about the conference is the mix of orthopedic surgeons, academics and representatives from the industry, who come together for fruitful discussions about new and ongoing topics in arthroplasty. We look back at the highlights and the insights we gained.
In the 'Computational Modeling in Arthroplasty' session, seven renowned speakers were invited to present their view on how modeling, if used in a sensible way, can help drive good decisions. The speakers discussed this topic from the viewpoint of an engineer, a surgeon, and a regulator.
From an engineer’s perspective, there are still a number of challenges when it comes to Finite Element Analysis (FEA) of bone-implant interactions. Constructing reliable models for individual patients requires specialized knowledge and still takes a lot of time. Therefore it is important to streamline such processes. Furthermore, in the case of bone-implant interactions, not all constraints and material properties are known in detail, unlike that of a new car door design for example. Therefore, the old adagio of ‘garbage in, garbage out’ remains true. For example, it is important to choose the appropriate failure criteria for each particular situation (e.g. max. values or peak stress), to ensure that the right boundary conditions are chosen, and that the models are not made overly complicated.
From the surgeon’s perspective, the focal point was on making sure the model was constructed correctly, and to challenge each of its fundamental assumptions. For example, many of the first Charnley hip replacements led to hip fractures, which was initially difficult to predict with FEA models1. The reasons were not well understood, until researchers realized that traditional elastic FEA models that did not allow for geometrical changes could be invalid. After all, when the surgeon hammers a femur stem into the femoral canal, the geometry of the trabecular bone is altered, which as it turned out, was better captured with a model that had collapsible elements in it.
From a regulator’s perspective, the FDA has traditionally been somewhat apprehensive when it comes to computational modeling as a supporting tool for new (510k) medical device applications. This perspective is changing, and a steering committee with representatives from the FDA, clinicians, and the industry has been established. The committee is working on guidelines for the industry on how computational models can be used in support of new medical device applications. One key word in the guidelines will be ‘Model Credibility’ (of which validation is only one aspect). Guidelines from both the FDA, as well as the American Society of Mechanical Engineers (ASME), are expected to come out in 2018.
An aspect that came back several times was that most computational modeling studies still use only one or a few bones to perform virtual implantation and FEA modeling. The call for larger studies when doing pre-clinical testing for new implants or fixation methods echoed throughout the room, not just in this session but also in others. As a believer of patient-specific computational modeling to improve patient care, Materialise has recently decided to allow more flexibility and automation in the software tools it provides to engineers and researchers. Through new scripting functionalities, users can now create their own workflows and make the link to finite element packages much easier. An example of how this is leading to new insights was shown in a joint presentation by the KU Leuven and Materialise. In the study, KU Leuven investigated how a new calcar guided short hip stem would perform in terms of stress shielding in a large population of femurs in an automated manner2. The study analyzed 96 femurs using the new Scripting module in the Mimics Innovation Suite.
Would you like to see more examples of how Scripting can help you automate repetitive tasks, improve consistency between operators, and reduce processing time for your medical image processing workflows? Visit our Mimics Innovation Suite 20 new release webpage to learn more!
1 Should a Surgeon Trust the Model? Assessing the Clinical Relevance of Computational Models, Hirotaka Iguchi, ISTA 2017.
2 Effect of Anatomical Variation of the Proximal Femur on Stress Shielding Induced by a Calcar Guided Short Stem: An Automated Finite Element Analysis Study, Amelie Sas; Sjoerd Kolk; Pim Pellikaan; Thierry Scheerlinck; Harry Van Lenthe, ISTA 2017.