Measuring Red Blood Cell Deformability Using LabVIEW 7 Express and Machine Vision Hardware

Author(s):
Max Hardeman - University of Amsterdam
Iwan Dobbe - University of Amsterdam

Industry:
University/Education, Life Science

Products:
LabVIEW, Vision, PXI/CompactPCI, Motion Control

The Challenge:
Automating the measurement of red blood cell deformability under shear flow from microscopic observations.

The Solution:
Performing advanced image acquisition and analysis using National Instrument IMAQ-1408 and LabVIEW 7 Express, as well as flow control using a PCI-ValueMotion-4A board.

Red blood cells (RBCs) can be thought of as small bags, partly filled with the red-colored hemoglobin. The cells must deform markedly when traveling through the microcirculation and fulfilling their primary job – transporting oxygen from the lungs to the tissues. A reduced deformability is considered to block capillary flow in sickle-cell anemia causing severe pain during crises that these patients experience. Available techniques for measuring RBC deformability often provide an indication of the mean deformability, which may hardly reduce if only a small subpopulation of cells is affected by the presence of parasites, such as in the case of malaria. By measuring the deformability of individual cells, we can select cells that may include a parasite. We use computerized analysis to quickly measure the RBC-deformability, or deformability distribution, of a blood sample from which we can distinguish subpopulations.

Instrument Control
We suspend the RBCs in a high viscous medium, and then insert this medium between two counter-rotating glass plates. The shear stress causes the cells to deform into ellipsoids and orients them in the direction of the streamlines. The deformation is dependent on the shear stress and cell characteristics. DC-type motors and NI motion boards drive and control the glass plates of the flow chamber. A microscope focuses midway between the plates, where the velocity of the cells is practically zero. We use stroboscopic illumination to eliminate residual motion blur. We can store cell images to disk for off-line analysis. We used an IMAQ machine vision board to perform image acquisition and trigger the stroboscope in the integration time of the camera.


Software Implementation
The analysis software loads prerecorded images from disk and performs cell localization, edge detection, and an advanced ellipse fitting procedure – an ellipse best describes the shape of an elongated cell. The ratio of the major and minor axes serves as the deformability index per cell. We manually evaluate the graphically superimposed results of the analysis and tabulate the data for quantitative inspection. The operator can reject misinterpreted or irrelevant cells and analyze a series of images in a single session. The deformability distribution results from all accepted cells in an analysis session.

We wrote our latest program, the Automated Rheoscope and Cell Analyzer (ARCA), using LabVIEW 7 Express. We implemented the basic program functions without the details of driver programming using LabVIEW 7 Express, a Windows 98 operating system, and motion and vision hardware. We quickly and easily programmed a professional and friendly GUI. We wrote our advanced image analysis procedure as a Dynamic Link Library (DLL) in C++ as part of a research program. The ability to import these nonstandard algorithms into LabVIEW 7 Express using the Call Library Function Node was one of the primary reasons that we choose this programming environment.

Conclusion
By using LabVIEW 7 Express in combination with the motion and vision boards, we set up our system quickly and easily. This accurate and user-friendly instrument is extremely beneficial for the study of many diseases prevalent in altered RBC mechanical properties.

For more information, contact:
Iwan Dobbe or Max Hardeman
Academic Medical Center
University of Amsterdam
P.O. Box 22700, 1100 DE Amsterdam
The Netherlands
tel (31) 20 566 69 89 or (31) 20 566 91 11
e-mail j.g.dobbe@amc.uva.nl or m.r.hardeman@amc.uva.nl

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