Customized Scaffold Design Based on Natural Peripheral Nerve Fascicle Characteristics for Biofabrication in Tissue Regeneration

基于天然周围神经束特征的定制支架设计用于组织再生生物制造

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Abstract

OBJECTIVE: The use of a biofabrication nerve scaffold, which mimics the nerve microstructure, as an alternative for autologous nerve transplantation is a promising strategy for treating peripheral nerve defects. This study aimed to design a customized biofabrication scaffold model with the characteristics of human peripheral nerve fascicles. METHODS: We used Micro-MRI technique to obtain different nerve fascicles. A full-length 28 cm tibial nerve specimen was obtained and was divided into 14 two-centimetre nerve segments. 3D models of the nerve fascicles were obtained by three-dimensional reconstruction after image segmentation. The central line of the nerve fascicles was fitted, and the aggregation of nerve fascicles was analysed quantitatively. The nerve scaffold was designed by simulating the clinical nerve defect and extracting information from the acquired nerve fascicle data; the scaffold design was displayed by 3D printing to verify the accuracy of the model. RESULT: The microstructure of the sciatic nerve, tibial nerve, and common peroneal nerve in the nerve fascicles could be obtained by three-dimensional reconstruction. The number of cross fusions of tibial nerve fascicles from proximal end to distal end decreased gradually. By designing the nerve graft in accordance with the microstructure of the nerve fascicles, the 3D printed model demonstrated that the two ends of the nerve defect can be well matched. CONCLUSION: The microstructure of the nerve fascicles is complicated and changeable, and the spatial position of each nerve fascicle and the long segment of the nerve fascicle aggregation show great changes at different levels. Under the premise of the stability of the existing imaging techniques, a large number of scanning nerve samples can be used to set up a three-dimensional database of the peripheral nerve fascicle microstructure, integrating the gross imaging information, and provide a template for the design of the downstream nerve graft model.

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