1Electrical Engineering Department, University of California, Los Angeles, 2California NanoSystems Institute, University of California, Los Angeles
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Mudanyali, O., Erlinger, A., Seo, S., Su, T., Tseng, D., Ozcan, A. Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics. J. Vis. Exp. (34), e1650, doi:10.3791/1650 (2009).
Here we discuss the experimental procedures that are involved in LUCAS [1-3]. To illustrate the proof of concept of LUCAS we will describe the imaging process for a whole blood sample.
A. Imaging Set-up
The LUCAS Imaging platform exhibits significant advantages to provide a cost-effective and compact alternative to existing point-of-care cytometry and medical diagnostic tools, especially for resource-limited settings. Rather than detecting the image of the cells, LUCAS instead captures digital holograms of the cells that are created by the interference of the scattered light from each cell with the background light. Careful control of the partial spatial coherence of the illumination is critical to enable holographic recording.
1. Digital Sensor Array
The LUCAS platform utilizes an optoelectronic sensor array to digitally record individual cell holograms. For this purpose, charged couple devices (CCD; Sample Models: KAI-11002, KAF-39000, from Kodak) or complementary metal-oxide-semiconductor chips (CMOS, Sample Model: MT9P031, Micron) can be used. Pixel sizes for the Kodak charged couple devices, KAI-11002, KAF-39000, and Micron CMOS image sensors are 9 μm, 6.8 μm and 2.2 μm, with an active FOV of 10 cm2, 18 cm2, and 24.4 mm2, respectively. [1-2].
2. Light Source
Unlike most other microscopic imaging modalities, LUCAS does not require a laser and therefore even a simple light emitting diode (LED) can be used for illumination. In order to enable tunable wavelength illumination, we can also utilize a monochromator with a Xenon Lamp (Cornerstone T260, Newport Corp.) along with a standard grade fused silica fiber which consists of a bundle of fibers (77564, Newport) and pinhole of ~100 μm diameter located at ~5-10 cm above the sensor surface. This tunable wavelength illumination configuration provides a flexible platform where the holographic signatures of the cells can be adjusted, and hybrid digital signatures can be synthesized to improve the signal to noise ratio for better characterization accuracy and specificity. 
B. Sample Preparation and Imaging
A proof of concept of LUCAS based on-chip imaging will be demonstrated using a heterogeneous solution as described below. A similar protocol could be applied for various other cell types [1-3].
1. Whole blood dilution and preparation of the heterogeneous solution
2. Whole Blood Staining
Figure 1: LUCAS enables accurate counting and digital differentiation of various cells and micro-objects based on their 2D holographic signatures without using any lenses, lasers or other bulky optical components. Characteristic LUCAS signatures of various micro-objects are illustrated in this figure and are compared against a conventional microscope image obtained with a 40X objective lens. Please click here to see a larger version of figure 1.
Figure 2: (Left) Raw image of a heterogeneous mixture containing red blood cells, 10um, 5um and 3 um particles. (Right) Fully-automated LUCAS characterization results for the same field of view are illustrated. Note that the decision algorithm is robust in characterizing high density regions as well as particles with low signal to noise ratio such as the 3um beads.
Figure 3: The LUCAS custom interface is illustrated. Java based LUCAS software allows inputs for various experimental conditions such as the sensor pixel size or the wavelength of light. Selection of a specific field of view on the image can also be made and the target cell patterns can be defined by the user to build a statistical cell shadow library. The acquired LUCAS image can then be characterized based on this training data (i.e., the cell shadow library) and the marked (counted) image is displayed to the user. Statistics of the count results are also stored as an XML file for further analysis.
We have illustrated that the LUCAS platform can accurately count and identify various micro-objects/cells on a chip based on their holographic signatures, and provides a promising tool for point-of-care medical diagnostics and high-throughput cell-biology. In order to accurately process the recorded holographic patterns, we implemented a custom-developed LUCAS decision software. This algorithm, which uses a statistical diffraction image database created by training of LUCAS images, identifies various features of cells within a heterogeneous solution; classifies the type and the relative position of individual cells and counts the desired cell type after applying thresholding to discard unwanted particle/cell patterns [1-3].
In summary, the LUCAS platform should provide a cost-effective and compact solution for point-of-care cytometry and medical diagnostics. For this end, LUCAS will especially be useful for monitoring of HIV patients in resource limited settings as well as for other global health related problems such as malaria and tuberculosis.
|Charged couple device (CCD)||KODAK||KAI-11002|
|Charged couple device (CCD)||KODAK||KAF-39000|
|Complementary Metal-Oxide-Semiconductor (CMOS)||Micron||MT9P031|
|Xenon Lamp||Newport Corp.||Cornerstone T260|
|Vacuum pen||Edmund Scientific||NT57-636|
|5, 10, and 20 μm Microbeads||Thermo Fisher Scientific, Inc.||4000 Series|
|Pure Eosin Y||Acros Organics||MW=691.85|
|New Methylene Blue(NMB) Dye||Acros Organics||MW=347.90|
|Potassium Oxalate Monohydrate||Acros Organics||99.0% Reagent ACS|