Griffin Meghan Rochelle, Bertram Spencer E, Robison Noah P, Panoskaltsis-Mortari Angela, Janardan Ravi, McAlpine Michael C
Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA.
Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN, USA.
Commun Eng. 2025 Aug 14;4(1):154. doi: 10.1038/s44172-025-00489-0.
Complex fibrous microarchitectures are common in biology, with fiber orientation playing a key role in the structure-function relationships that govern tissue behavior. Directional imaging modalities, such as diffusion tensor magnetic resonance imaging (DTMRI), can be used to derive a 3D vector map of fiber orientation. Incorporating this alignment information into engineered tissues remains a challenging and evolving area of research, with direct incorporation of directional imaging data into engineered tissue structures yet to be achieved. Here we describe an algorithmic framework, entitled Nonplanar, Architecture-Aligned Toolpathing for In Vitro 3D bioprinting (NAATIV3), which processes DTMRI data to map tissue fibers, reduce them to a representative subset, remove conflicting fibers, select a printable sequence, and output a G-code file. DTMRI data from a human left ventricle was used to 3D print fibered models with high accuracy. It is anticipated that NAATIV3 is generalizable beyond the cardiac application demonstrated here. Directional imaging data from a variety of organs, disease states, and developmental timepoints may be processible by NAATIV3, enabling the creation of models for understanding development, physiology, and pathophysiology. Furthermore, the NAATIV3 framework could be extended to bioengineered food manufacturing, plant engineering, and beyond.
复杂的纤维微结构在生物学中很常见,纤维取向在控制组织行为的结构-功能关系中起着关键作用。定向成像模态,如扩散张量磁共振成像(DTMRI),可用于生成纤维取向的三维矢量图。将这种排列信息整合到工程组织中仍然是一个具有挑战性且不断发展的研究领域,将定向成像数据直接整合到工程组织结构中尚未实现。在此,我们描述了一种算法框架,名为用于体外3D生物打印的非平面、结构对齐刀具路径规划(NAATIV3),它处理DTMRI数据以绘制组织纤维,将其简化为一个代表性子集,去除冲突纤维,选择可打印序列,并输出一个G代码文件。来自人类左心室的DTMRI数据被用于高精度地3D打印纤维模型。预计NAATIV3可推广到此处展示的心脏应用之外。NAATIV3可能能够处理来自各种器官、疾病状态和发育时间点的定向成像数据,从而创建用于理解发育、生理学和病理生理学的模型。此外,NAATIV3框架可扩展到生物工程食品制造、植物工程等领域。