Closed-loop vasculature network design for bioprinting large, solid tissue scaffolds.

Area of Science:

• Biomedical Engineering
• Tissue Engineering
• Computational Modeling

Background:

• Fabricating large solid tissues requires functional vascularization, which is challenging with current bioprinting technology.
• Existing bioprinted vascular networks are often too simple to support large tissues, while natural vasculature is too complex to replicate.
• Developing methods to create complex, functional vascular networks is crucial for advancing tissue engineering and regenerative medicine.

Purpose of the Study:

• To propose a generalized and adaptable numerical model for designing vascular networks based on patient-specific anatomy.
• To simulate nutrient transport within designed vascular networks and iteratively optimize them for improved tissue viability.
• To enhance the design of vascular scaffolds for guiding cell growth and maturation in bioprinted tissues.

Main Methods:

• Processing medical images (e.g., MRI) to extract organ structure and vascular cues.
• Utilizing a mathematical model to guide the formation of arterial and venous networks.
• Simulating mass transport of nutrients (glucose, amino acids, oxygen) and consumption within the designed vasculature.
• Iteratively optimizing the vascular network based on nutrient-deprived regions.

Main Results:

• The numerical model successfully designed complex 3D vascular networks.
• Simulations showed that iterative optimization significantly reduced nutrient-deprived regions within the engineered tissue.
• The efficacy of nutrient transport improved as the vascular structure became more complex.

Conclusions:

• The proposed numerical method is a valuable tool for designing vascular scaffolds in bioprinting.
• This approach can guide cell growth and maturation, leading to faster regeneration of bioprinted tissues.
• The model's adaptability allows for patient-specific vascular network design, improving the potential for organ fabrication.