Review demonstrates personalized spinal fusion design can improve biomechanical outcomes, suggesting a method to integrate AI and modeling.
There is great potential for engineering design approaches in medicine to personalize treatments according to unique patient physiology and needs. However, it is challenging to optimize solutions such as medical implants given the complex biomechanical interactions between the body and implant. Here, we review personalization for clinical needs, biomechanical modelling, and computational design for interbody spinal cage implants. By reviewing relevant literature, research suggests specific clinical needs are addressable by redesigning cages with multi-objective optimization or artificial intelligence methods integrated with finite element modelling of the spine. Such an approach is generalizable to further biomechanical design cases, where personalized design provides promise to deliver higher quality solutions for the clinic.
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Karki et al. (2025) studied this question.
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