Modular scaffolds with intelligent visual guidance system for in situ bone tissue repair

In clinical practice, the irregular shapes of traumas pose a significant challenge in rapidly manufacturing personalized scaffolds. To address these challenges, inspired by LEGO^Ⓡ bricks, this study proposed a novel concept of modular scaffolds and developed an innovative system based on machine vision for their rapid and intelligent assembly tailored to defect shapes. Trapezoidal interfaces effectively connect standardized bone units based on magnesium-doped silicate calcium, ensuring high stability of the modular scaffolds, with compressive strength up to 135 MPa and bending strength up to 17 MPa. Through self-developed defect recognition and reconstruction algorithms, defect recognition and personalized assembly schemes for bone scaffolds can be achieved autonomously. Modular scaffolds seamlessly integrate with surrounding bone tissue, promoting new bone growth, with no apparent differences compared to fully 3D printed integral scaffolds in the skull and femur repair experiments. In summary, the adoption of modular scaffolds not only integrates personalization and standardization but also satisfies the optimal treatment window.