Simulating Dielectrophoretic Separation of CCRF-CEM Leukemic Cells on Interdigitated Electrodes
Year: 2026
Type: article
Abstract: Targeted malignant cell separation from peripheral blood is crucial for early detection of leukemia. Dielectrophoresis (DEP) offers an effective, label-free method to differentiate cells using intrinsic dielectric properties. This study developed a finite-element model to evaluate a planar interdigitated electrodes (IDE) microfluidic device for selectively capturing CCRF-CEM leukemic cells from co-present red blood cells (RBCs) and T-Cells. At 4.6 MHz, all cell types display positive dielectrophoresis (pDEP) responses. However, CCRF-CEM blasts experience a stronger pDEP force due to their larger radius. This size-amplified mechanism yields a DEP factor approximately 3.5- and 6.6-fold higher than T-cells and RBCs respectively enabling selective capture. Field mapping across electrode gaps (100–300 µm) and voltages (5–25 V) confirmed field scales directly with voltages and inversely with gap width. Retention evaluations across flow rates (250–1000 µm/s) revealed peak immobilization at lower flows, minimal gaps, and higher voltages. Six parameters achieved the ideal selective regime (100 µm, 10 V, 250 µm/s; 100 µm, 15 V, 500 µm/s; 100 µm, 15 V, 750 µm/s; 100 µm, 20 V, 1000 µm/s; 200 µm, 25 V, 500 µm/s; and 300 µm, 25 V, 250 µm/s). Under these conditions, simulated CCRF-CEM trapping and healthy cell passage efficiencies both reached 100%, reflecting deterministic idealized threshold behavior rather than experimentally validated yields. Targeted analytical sensitivity analysis verified system robustness while optimizing computational costs, confirming the size-amplified selectivity margin remains intact against variances in medium conductivity and intrinsic cellular properties, even under severe worst-case geometric configuration. This numerical study verifies the multi-parameter operational boundaries required to isolate CCRF-CEM targets from healthy-cell background, offering robust design benchmarks for DEP-based diagnostic microchips.
Institution: Institut Teknologi Sepuluh Nopember
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $100
OpenAlex ID: W7225260917