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Blood Analysis With a Cell Phone
Blood cells or bacteria: the mobile
of the future might be able to tell
them apart; © SXC
Researchers have advanced a novel lens-free, high-throughput imaging technique for potential use in medical diagnostics. The research outlines improvements to a technique called Lensless Ultra-wide-field Cell monitoring Array platform based on Shadow imaging (LUCAS).
First published in 2007, the technique demonstrated a lens-free method for counting targeted cell types in a homogenous cell solution. Removing the lens from the imaging process allows LUCAS to be scaled down to the point that it can eventually be integrated into a usual wireless cell phone. Samples could one day be loaded into a specially equipped phone using a disposable microfluidic chip. The read-out with the identified cells could be sent wirelessly to a hospital.
LUCAS functions as an imaging scheme in which the shadow of each cell in an entire sample volume is detected in less than a second. Various cell types or other microparticles exhibit uniquely different shadow patterns. The acquired shadow image is then digitally processed using a custom-developed "decision algorithm" to enable both the identification of the cell and bacteria location in 3-D and the classification of each microparticle type within the sample volume.
The researchers have now improved the technique to the point that it can classify a significantly larger sample volume - up to five milliliters, from an earlier volume of less than 0.1 milliliters. The new study also demonstrates that the use of narrowband, short-wavelength illumination significantly improves the detection of cell shadow images. Furthermore, by varying the wavelength, the two-dimensional pattern of the recorded cell signatures can be tuned to enable automated identification and counting of a target cell type within a mixed cell solution.
Another improvement is the creation of a hybrid imaging scheme that combines two different wavelengths to further improve the digital quality of shadow images. As the team illustrated, further improvement in image quality can also be achieved through the use of adaptive digital filtering. As result of these upgrades, the volume of the sample solution that can be imaged has, as mentioned, been increased.
MEDICA.de; Source: University of California - Los Angeles