8:00 PM - SB06.04.12
Design of Novel Scaffolds for Effective Healing of Bone Fractures Using Topology Optimization Based on Mechano-Biological Model, Angiogenesis and Scaffold Degradation
Mervenaz Sahin1,Mehmet Serhat Aydin1,Gullu Kiziltas Sendur1,2
Sabanci University1,Sabanci University Nanotechnology Research and Application Center2
Show Abstract
Bone repair is known to be a complex process affected by many parameters such as fracture size. 3D composite porous tissue scaffolds loaded with bioactive molecules and cells are being developed to offer a better solution for bone fracture healing. Accordingly, an ideal bone tissue scaffold should provide the following functions: a. mechanical support for the growth and functioning of new tissue, b. adequate porosity and permeability for nutrients and oxygen supply, waste removal and growth factors release, c. suitable surface for cell attachment, differentiation and growth, and d. controlled degradation. Therefore, an optimal bone tissue scaffold should have a multi-functional structure with desired mechanical, biological and chemical properties. However, it is still unclear what kind of properties optimal bone scaffolds should provide leading to effective tissue repair. Thus, there is a critical need to find methods suitable for designing novel bone scaffolds and the investigation of structure-function relationships for optimal tissue regeneration. Existing experimental studies are usually very time and cost ineffective.
Most of the computational design studies in literature that target ideal scaffold geometries with desired functional properties do not account for dynamic effects within the scaffold-tissue-cell environment. Among these, topology optimization based studies offer promise to design novel architectures of bone tissue scaffolds1 but mostly have neglected the dynamic mechano-biological nature of regenerative healing2. Unlike topology optimization, scaffold design studies based on parametric size optimization3 and mechano-biological regeneration models offer limited design freedom, hence resulting designs are not necessarily the best candidates to ensure effective healing. Moreover, angiogenesis - a critical part of the regeneration process- and scaffold degradation are not considered in any of these studies together despite their known coupled effect in healing. To address these limitations, we propose, for the first time, a computational framework to design the optimal microstructure of scaffolds that maximize bone formation considering mechano-biology, angiogenesis and scaffold degradation simultaneously. Thus, our model includes the following 4 parts in an integrated fashion: 1. Mechano-biological model describing tissue differentiation, 2. Angiogenesis, 3. Topology optimization targeting maximum bone formation, and 4. Time dependent degradation of the bone scaffold.
The proposed computational design framework is developed in a MATLAB GUI as an integration of above computational modules with a FEA software, namely COMSOL Multiphysics, a SIMP based topology optimization method and a random walk approach for angiogenesis modeling. The computationally designed scaffolds are compared with existing designs and fabricated based on a recently introduced phase separation technique. Morphological and mechanical characterization techniques will be performed to validate bone regeneration performance of designed bone tissue scaffolds. Integration of the proposed computational framework to existing experimental studies should pave the way for more efficient and low-cost solutions in bone tissue engineering.
Keywords: Tissue engineering, bone tissue scaffold, topology optimization, mechano-biology, angiogenesis, scaffold degradation.
References
[1] Wang, Y., Luo, Z., Zhang, N., & Qin, Q. 2016, Structural and Multidisciplinary Optimization, 54(2), 333-347.
[2] Geris, L., Vander Sloten, J., & Van Oosterwyck, H. 2010, Biomechanics and modeling in mechanobiology, 9(6), 713-724.
[3] Boccaccio, A., Uva, A. E., Fiorentino, M., Lamberti, L., & Monno, G. 2016, International journal of biological sciences, 12(1), 1.