Khodayari Amirreza, Ebrahimi Sina, Topaheidari Mohammadmahdi, Shamloo Amir
School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran; Stem Cell and Regenerative Medicine Center, Sharif University of Technology, Tehran, Iran.
School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran; Stem Cell and Regenerative Medicine Center, Sharif University of Technology, Tehran, Iran.
Talanta. 2025 Oct 1;293:128022. doi: 10.1016/j.talanta.2025.128022. Epub 2025 Mar 27.
The precise separation and focusing of circulating tumor cells (CTCs) from blood cells are crucial for advancing cancer diagnosis, optimizing therapeutic strategies, and fostering progress in cellular research. Inertial microfluidics offers an efficient, label-free solution with high throughput and simple design. However, challenges remain in improving separation efficiency, purity, and throughput while minimizing fabrication costs. This study introduces an optimized triangular microchannel design to enhance CTC separation performance. A Gaussian Process Regression (GPR) model was developed to predict the separation efficiency and purity of the microchannel based on key design parameters, significantly reducing computational costs and enabling rapid optimization. The simulation results indicated that a 60° triangular microchannel geometry with a curvature radius of R=200μm emerged as the optimal configuration, achieving 100% separation efficiency and purity at an inlet flow rate of 2mL/min. Experimental validation of the fabricated microchip using cultured MCF-7 (CTC) and white blood cell (WBC) demonstrated its remarkable performance, achieving a separation efficiency of 95.7% and a purity of 93.3% for low concentration (1:30) and efficiency of 93.2% and a purity of 92.5% for high concentration (1:5000) at the same flow rate. The integration of machine learning-based modeling with inertial microfluidics in this work provides a powerful approach for optimizing microchannel designs while maintaining high efficiency and purity. The proposed microchip represents a significant advancement in inertial microfluidics, offering a reliable and scalable solution for biomedical and clinical applications, particularly in CTC isolation and enrichment from complex biological samples.
从血细胞中精确分离和富集循环肿瘤细胞(CTC)对于推动癌症诊断、优化治疗策略以及促进细胞研究进展至关重要。惯性微流控技术提供了一种高效、无需标记的解决方案,具有高通量和设计简单的特点。然而,在提高分离效率、纯度和通量的同时将制造成本降至最低仍面临挑战。本研究引入了一种优化的三角形微通道设计,以提高CTC的分离性能。开发了一种高斯过程回归(GPR)模型,基于关键设计参数预测微通道的分离效率和纯度,显著降低了计算成本并实现了快速优化。模拟结果表明,曲率半径R = 200μm的60°三角形微通道几何结构是最优配置,在入口流速为2mL/min时实现了100%的分离效率和纯度。使用培养的MCF - 7(CTC)和白细胞(WBC)对制造的微芯片进行实验验证,结果表明在相同流速下,低浓度(1:30)时分离效率为95.7%,纯度为93.3%;高浓度(1:5000)时分离效率为93.2%,纯度为92.5%,展现出卓越性能。本工作中将基于机器学习的建模与惯性微流控技术相结合,为优化微通道设计提供了一种强大的方法,同时保持了高效率和高纯度。所提出的微芯片代表了惯性微流控技术的重大进展,为生物医学和临床应用,特别是从复杂生物样品中分离和富集CTC提供了一种可靠且可扩展的解决方案。