Magnetic-Assisted Manipulation of Rare Blood Cells for Diagnosis: A Systematic Review.

Journal: Biotechnology and bioengineering
Published Date: Jun 26, 2025

Abstract

The precise isolation and analysis of rare cells from blood are crucial for biomedical research and clinical diagnostics. This review examines recent advancements in magnetic-based separation techniques, focusing on their efficiency in capturing rare cells such as circulating tumor cells (CTCs), circulating fetal cells, and diseased red blood cells (RBCs). These methods use magnetophoresis under external magnetic fields for highly specific isolation with minimal contamination, offering advantages over traditional techniques in speed, cost-effectiveness, and robustness. Magnetic separation is categorized into label-based methods, which use immunomagnetic nanoparticles (IMNs) to target specific cell markers, and label-free methods, which exploit differences in magnetic susceptibility. Both approaches have achieved up to 99% efficiency in isolating diseased RBCs and CTCs. However, challenges remain in improving purity, scalability, and clinical applicability. A key limitation of label-based methods is the need to detach cells from magnetic beads without compromising viability. Label-free technologies, such as magnetic levitation, enable ligand-free separation based on density and susceptibility. Future research should focus on optimizing paramagnetic media, integrating machine learning for enhanced accuracy, and developing high-gradient magnetic fields (~1000 T/m) to improve efficiency. Advancements in IMNs with stronger magnetic properties will further enhance separation performance, driving clinical translation.

Authors

  • Poornima Ramesh Iyer
    William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio, USA.
  • Xian Wu
    Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Hyeon Choe
    William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio, USA.
  • Linh Nguyen T Tran
    Department of Chemical Engineering, Texas Tech University, Lubbock, Texas, USA.
  • Karla Mercedes Paz González
    Department of Chemical Engineering, Texas Tech University, Lubbock, Texas, USA.
  • Bahareh Rezaei
    Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
  • Shahriar Mostufa
    Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
  • Ebrahim Azizi
    Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
  • Ioannis H Karampelas
    Nemak USA, Inc., Sheboygan, Wisconsin, USA.
  • Kai Wu
  • Jeffrey Chalmers
    William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio, USA.
  • Jenifer Gomez-Pastora
    Department of Chemical Engineering, Texas Tech University, Lubbock, Texas, USA.

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