Analysis of the Osteogenic Effects of Biomaterials Using Numerical Simulation.
Lan WangJie ZhangWen ZhangHui-Lin YangZong-Ping LuoPublished in: BioMed research international (2017)
We describe the development of an optimization algorithm for determining the effects of different properties of implanted biomaterials on bone growth, based on the finite element method and bone self-optimization theory. The rate of osteogenesis and the bone density distribution of the implanted biomaterials were quantitatively analyzed. Using the proposed algorithm, a femur with implanted biodegradable biomaterials was simulated, and the osteogenic effects of different materials were measured. Simulation experiments mainly considered variations in the elastic modulus (20-3000 MPa) and degradation period (10, 20, and 30 days) for the implanted biodegradable biomaterials. Based on our algorithm, the osteogenic effects of the materials were optimal when the elastic modulus was 1000 MPa and the degradation period was 20 days. The simulation results for the metaphyseal bone of the left femur were compared with micro-CT images from rats with defective femurs, which demonstrated the effectiveness of the algorithm. The proposed method was effective for optimization of the bone structure and is expected to have applications in matching appropriate bones and biomaterials. These results provide important insights into the development of implanted biomaterials for both clinical medicine and materials science.
Keyphrases
- bone regeneration
- bone mineral density
- deep learning
- tissue engineering
- machine learning
- mesenchymal stem cells
- finite element
- bone marrow
- postmenopausal women
- soft tissue
- randomized controlled trial
- drug delivery
- public health
- computed tomography
- magnetic resonance imaging
- neural network
- convolutional neural network
- magnetic resonance
- positron emission tomography