Peng Xuqi, Tang Haitian, Zhao Zhenwen, Zheng Yating, Gui Xiran, Jiang Aijun, He Pan, Wen Xiaofei, Zhang Qian, Mei Ziyang, Shi Yesi, Chu Chengchao, Zhang Yang, Liu Gang
State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, State Key Laboratory of Vaccines for Infectious Diseases, Center for Molecular Imaging and Translational Medicine, Xiang An Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen, 361102, China.
Department of General Surgery, Naval Medical Center of PLA, Naval Medical University, Shanghai, 200052, China.
Small. 2024 Dec 15:e2408613. doi: 10.1002/smll.202408613.
Microrobots for endovascular embolization face challenges in precise delivery within dynamic blood vessels. Here, an intelligent generic high-throughput oscillatory shear technology (iGHOST) is proposed to fabricate diversely programmable, multifunctional microrobots capable of real-time visual guidance for in vivo endovascular embolization. Leveraging machine learning (ML), key synthesis parameters affecting the success and sphericity of the microrobots are identified. Therefore, the ML-optimized iGHOST enables continuous production of uniform microrobots with programmable sizes (400-1000 µm) at an ultrahigh rate exceeding 240 mL h by oscillatory segmenting fluid into droplets before ionic cross-linking, and without requiring purification. Particularly, the iGHOST-fabricated magnetically responsive lipiodol-calcium alginate (MagLiCA) microrobots are highly distinguishable under X-ray imaging, which allows for precise navigation in fluid flows of up to 4 mL min and accurate embolization in liver and kidney blood vessels, thus addressing the current issues. Crucially, MagLiCA microrobots possess drug-loading capabilities, enabling simultaneous embolization and site-specific treatment. The iGHOST process is an intelligent, rapid, and green manufacturing method, which can produce size-controllable, multifunctional microrobots with the potential for precise drug delivery and treatment under real-time imaging across various medical applications.
用于血管内栓塞的微型机器人在动态血管内的精确输送方面面临挑战。在此，我们提出了一种智能通用高通量振荡剪切技术（iGHOST），以制造能够为体内血管内栓塞提供实时视觉引导的多种可编程多功能微型机器人。利用机器学习（ML），确定了影响微型机器人成功制造和球形度的关键合成参数。因此，经过ML优化的iGHOST能够通过在离子交联前将振荡流体分割成液滴，以超过240 mL/h的超高速度连续生产尺寸可编程（400 - 1000 µm）的均匀微型机器人，且无需纯化。特别地，通过iGHOST制造的磁响应性碘油 - 海藻酸钙（MagLiCA）微型机器人在X射线成像下具有高度可区分性，这使得它们能够在高达4 mL/min的流体流动中精确导航，并在肝脏和肾脏血管中实现精确栓塞，从而解决了当前的问题。至关重要的是，MagLiCA微型机器人具有载药能力，能够实现同时栓塞和位点特异性治疗。iGHOST工艺是一种智能、快速且绿色的制造方法，它可以生产尺寸可控的多功能微型机器人，具有在各种医学应用中进行实时成像下精确药物递送和治疗的潜力。
