Biomineralization Induction for 3D Bioprinted Osteogenic Structures Informed by Bioimaging-Biomodelling Techniques Through Geometrical Efficiency, and Hydrogel Optimization

The Current work presents an interdisciplinary study with the objective to design and fabricate acellular chemically mineralized biomimetic osteo-structures of multi applications. Inspired by the Cancellous-Cortical hierarchical level in bone tissue and by the bone biomineralization process. By combining organic and mineral components to achieve mineralized material for bone replacement material application or as a mineralized architectural material. This was tackled through a customized methodology to address the different disciplines included in the current study. First, analysing bone tissue on the cancellous-cortical level in terms of morphometric parameters correlation with the universal mechanical properties of bone, as an informative model for biomimetic design of bone-like optimized structures and bioengineered materials. Discussed in Chapter 1. Second, a biomimetic approach to synthesize an optimized and sustainable acellular chemically mineralizing hydrogel from Calcium phosphate dibasic enhanced sodium alginate-gelatine hydrogel without and with integrating living cells to achieve enhanced hydrogel stability, antimicrobial resistance, mineralization and enhanced mechanical properties for both proposed applications. Discussed in Chapter 2. Third, by employing Deep Learning generative design tools (CNN, Diffusion Models, and transformers based on NL Processing) to generate 2D sequence Images for data augmentation and design generation as well as 3D voxel and mesh models for direct integration in the biomimetic design to fabrication process informed by the first two chapters to design and fabricate bone-like structures on the cancellous-cortical bone level. Discussed in Chapter 3, and Chapter 4. The results revealed a strong correlation between the Young ́s modulus and the Trabecular bone volume and Trabecular Structure thickness. In addition to dependency of the maximum strain on the Cortical parameters as Cortical Bone Volume, and Cortical structure density. The 6% CPDB enhanced SA-Gelatine based hydrogel achieved the best rheological properties in terms of equilibrium between elasticity and rigidity. The SEM images of the hydrogel and bioink; proved the significant potency of the hydrogel to mineralize through forming hydroxyapatite platelets when incubated in the open air in non-sterile conditions, as well as when incubated in FBS for a duration of up to 14 days, with a congruent increase in mineralization over time. Finally, the results revealed that 2D μ-CT images are less efficient when employed as input for a 2D-CNN convolution generative process in data augmentation or in biomimetic design generation, in comparison to the AI-Diffusion generated 2D images. Furthermore, the results revealed possible integration of text-to-3D model in direct rapid prototyping as well as a volumetric unlimited rapid and open access AI generative biomimetic design to fabrication tool. However, it is proved the need for increasing the training data set of 3D reconstructs representing the various scale lengths and fine resolution details of the bone tissue, as well as in increasing the capacity of the text-to-3D model in learning from 2D text-to-image diffusion models in understanding intricate scales and morphologies of bone tissue. The results revealed the significance and novelty of the study in relating these three aspects combining advanced bone imaging and mechanical testing in informing biomimetic material and structural design. While emphasizing on the potential of AI-DL generative design tools in accelerating, facilitating and augmenting the feasibility of biomimetic design to fabrication of bone inspired hybrid-hierarchical structures that can serve as bone replacement materials and grafts or as architectural materials and structures.