Ultrasound-assisted microfluidic cell separation: A study on microparticles for enhanced cancer diagnosis

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Cancer continues to pose significant challenges globally, especially in developed countries, largely due to delayed diagnosis and limited therapeutic options. Early detection of circulating tumor cells (CTCs) in peripheral blood has emerged as a critical factor in enhancing treatment efficacy, despite the inherent difficulty in controllable target cell separation. To address this challenge, this study introduces an innovative acoustofluidic system designed for the separation of CTCs from red blood cells. Leveraging the principles of standing surface acoustic waves (SSAWs) and novel microfluidic channel design, this system promises significant advancements in CTC isolation efficiency. The integration of Multiphysics Finite Element Method and multivariate surrogate modeling, which contribute to generate datasets that predict the performance of the proposed acoustic micro-electro-mechanical system in explaining the cell migration phenomena. These mathematical models serve as the foundation for applying two machine learning algorithms, differential evolution, and multi-objective particle swarm optimization. The proposed integrated intelligent framework balances the interplay of variables, sheath flow rates, and peak-to-peak voltage (Vpp). SSAW and cell interaction times and cell trajectory patterns are analyzed through the controlled generation of acoustic pressures within the microchannel, enhancing efficiency while reducing energy consumption and maximizing cell recovery rates. Precision in cell manipulation is achieved by combining analyzed surface acoustic waves with optimized curved microchannel geometry design, developing a dualized active acoustic zone with improved control mechanisms for cell movement. A 35% increase in acoustic energy consumption occurs when voltage increases from 10 V to 15 V in constant IDT (interdigital transducer) aperture. Additionally, a 72% increase in energy consumption is observed when IDT aperture increases from 10° to 40° under constant voltage. Optimal cell recovery is achieved with 200 mm/s sheath flowrate, 10 V voltage, and 0.32 MPa acoustic pressure, resulting in a 100% recovery rate. Furthermore, increasing IDT aperture from 10° to 40° reduces cell distance by 30 μm, while a maximum lateral displacement of 45 μm is achieved at 120 mm/s. By integrating computational simulations, experimental verifications, and machine learning algorithms, the research unveils transformative potential for miniaturized diagnostic platforms in cancer therapeutics. This innovative approach in laboratory-on-chip technology paves the way for personalized medicine, real-time molecular analysis, and point-of-care diagnostics.