Researchers have introduced an innovative system that utilizes standing surface acoustic waves to effectively isolate circulating tumor cells from red blood cells with unmatched accuracy and efficiency. This platform combines cutting-edge computational modeling, experimental studies, and artificial intelligence algorithms to explore intricate acoustofluidic behaviors. As part of their approach, the researchers employed a creative application of dualized pressure acoustic fields, strategically positioning them at key geometric locations within a lithium niobate substrate. The design enables the generation of consistent datasets through the application of acoustic pressure within a microchannel.
In 2020, cancer was responsible for nearly 10 million fatalities, accounting for approximately one in every six global deaths, according to the World Health Organization. The challenge is that the detection of abnormal cell growth often happens too late, making swift cancer diagnosis a critical and challenging medical aim. Recent studies have concentrated on identifying rare circulating tumor cells (CTCs) in peripheral blood, which act as noninvasive indicators for improving diagnostic accuracy.
Separating specific target cells for examination poses significant challenges. Conventional techniques require complex sample preparation, specialized equipment, and large sample sizes, which complicates the efficient separation of targeted cells.
In Physics of Fluids published by AIP Publishing, researchers Afshin Kouhkord and Naser Naserifar from K. N. Toosi University of Technology in Tehran, Iran, have proposed a revolutionary system using standing surface acoustic waves to effectively isolate CTCs from red blood cells with remarkable accuracy and efficiency. Their developed platform fuses advanced computational modeling, experimental work, and machine learning algorithms to analyze complex acoustofluidic interactions.
“By merging machine learning techniques with data-driven models and computational inputs, we optimized recovery and cell separation rates,” explained Naserifar. “Our system achieves a recovery rate of 100% under optimal conditions while significantly lowering energy consumption by precisely controlling acoustic pressures and flow rates.”
Among the various methods for enhancing particle separation in microfluidics, acoustofluidic techniques stand out as particularly promising due to their biocompatibility, capacity to generate high forces at MPa pressure ranges, and production of cell-sized wavelengths.
In their innovative technique, the researchers integrated dualized pressure acoustic fields, which amplify the effect on target cells, placing them at critical geometric locations in a lithium niobate substrate. The application of acoustic pressure within the microchannel allows for the creation of reliable datasets that display cell interaction durations and movement patterns, aiding in the prediction of tumor cell migration.
“We have developed an advanced lab-on-chip platform that facilitates real-time, energy-efficient, and highly precise cell separation,” Kouhkord stated. “This technology significantly improves CTC separation efficiency and opens new avenues for earlier and more effective cancer diagnoses. It also lays the groundwork for using microengineering and applied AI in personalized medicine and cancer diagnostics.”
