title: Magnetic Levitation Coupled with Portable Imaging and Analysis for Disease Diagnostics.
abstract: Currently, many clinical diagnostic procedures are complex, costly, inefficient, and inaccessible to a large population in the world. The requirements for specialized equipment and trained personnel require that many diagnostic tests be performed at remote, centralized clinical laboratories. Magnetic levitation is a simple yet powerful technique and can be applied to levitate cells, which are suspended in a paramagnetic solution and placed in a magnetic field, at a position determined by equilibrium between a magnetic force and a buoyancy force. Here, we present a versatile platform technology designed for point-of-care diagnostics which uses magnetic levitation coupled to microscopic imaging and automated analysis to determine the density distribution of a patient's cells as a useful diagnostic indicator. We present two platforms operating on this principle: (i) a smartphone-compatible version of the technology, where the built-in smartphone camera is used to image cells in the magnetic field and a smartphone application processes the images and to measures the density distribution of the cells and (ii) a self-contained version where a camera board is used to capture images and an embedded processing unit with attached thin-film-transistor (TFT) screen measures and displays the results. Demonstrated applications include: (i) measuring the altered distribution of a cell population with a disease phenotype compared to a healthy phenotype, which is applied to sickle cell disease diagnosis, and (ii) separation of different cell types based on their characteristic densities, which is applied to separate white blood cells from red blood cells for white blood cell cytometry. These applications, as well as future extensions of the essential density-based measurements enabled by this portable, user-friendly platform technology, will significantly enhance disease diagnostic capabilities at the point of care.
authors.affiliation: Biomedical Engineering Department, University of Connecticut.
authors.forename: Stephanie M
authors.initials: SM
authors.lastname: Knowlton
authors.affiliation: Mechanical Engineering Department, University of Connecticut.
authors.forename: Bekir
authors.initials: B
authors.lastname: Yenilmez
authors.affiliation: Mechanical Engineering Department, University of Connecticut.
authors.forename: Reza
authors.initials: R
authors.lastname: Amin
authors.affiliation: Biomedical Engineering Department, University of Connecticut; Mechanical Engineering Department, University of Connecticut; savas@engr.uconn.edu.
authors.forename: Savas
authors.initials: S
authors.lastname: Tasoglu
mesh_terms: D000755:Anemia, Sickle Cell / Q000175:diagnosis*; D004912:Erythrocytes / Q000737:chemistry / Q000166:cytology; D005682:Gadolinium / Q000737:chemistry; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007962:Leukocytes / Q000737:chemistry / Q000166:cytology; D008280:Magnetics; D019095:Point-of-Care Systems; D000068997:Smartphone; D014584:User-Computer Interface
chemical_list: D005682:Gadolinium