Journal
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
Volume 38, Issue 10, Pages -Publisher
WILEY
DOI: 10.1002/cnm.3637
Keywords
biological modelling; bone growth; computational biology; computational modelling; finite element analysis; mechanobiological modelling
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Funding
- SPARC, MHRD, Government of India [SPARC/P705]
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This article provides a comprehensive review of the development of mathematical models of tissue-differentiation and bone adaptation for orthopaedic implant design optimization. Despite the existence of various mechanoregulatory models, none of them has been widely accepted. The lack of research involving clinically relevant animal models has hindered the development of mathematical formulations in this field.
Post-operative bone growth and long-term bone adaptation around the orthopaedic implants are simulated using the mechanoregulation based tissue-differentiation and adaptive bone remodelling algorithms, respectively. The primary objective of these algorithms was to assess biomechanical feasibility and reliability of orthopaedic implants. This article aims to offer a comprehensive review of the developments in mathematical models of tissue-differentiation and bone adaptation and their applications in studies involving design optimization of orthopaedic implants over three decades. Despite the different mechanoregulatory models developed, existing literature confirm that none of the models can be highly regarded or completely disregarded over each other. Not much development in mathematical formulations has been observed from the current state of knowledge due to the lack of in vivo studies involving clinically relevant animal models, which further retarded the development of such models to use in translational research at a fast pace. Future investigations involving artificial intelligence (AI), soft-computing techniques and combined tissue-differentiation and bone-adaptation studies involving animal subjects for model verification are needed to formulate more sophisticated mathematical models to enhance the accuracy of pre-clinical testing of orthopaedic implants.
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