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Scattered light detects misshapen red blood cells

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Ashley N. Paddock,

A new technique has been developed to ascertain the healthy shape of red blood cells in just a few seconds by analyzing the light scattered off hundreds of them at a time and applying a specific mathematical rule to calculate a healthy cell scattering signature.

A light-scattering technique helps differentiate between healthy red blood cells (top row) and abnormal cells (bottom row). a = dimple depth; b = diameter (in “flattop” Gaussian function); σ = dimple width; h = cell thickness; D = diameter. Courtesy of Biomedical Optics Express.

Misshapen red blood cells are a sign of serious illness, such as sickle-cell anemia or malaria. Previously, the only way to assess whether a person’s red blood cells were the correct shape was to look at them individually under a microscope – a time-consuming feat for pathologists. Now, however, a new technique from researchers at the University of Illinois at Urbana-Champaign will allow doctors to determine whether cells are in a healthy shape in a matter of seconds.

A healthy cell looks much like a disc with a depression, called a dimple, in the top and bottom. Stressed, unhealthy cells have deeper dimples, giving them a deflated look; others may have shallow dimples or none at all. The researchers deduced that if a light was shone onto a sample of blood, they could analyze the light scattering off the sample and get a pattern – a sort of signature produced by the way light interacts with itself in a 3-D space – that would be different from blood containing mostly misshapen cells.

(a) Large-area scan of a healthy red blood cell sample obtained by stitching several fields of view together. (b) Detail of area outlined by white box in (a) to demonstrate the resolution of the system. Inset shows a surface projection of a red blood cell. Colors correspond to the optical path length at each pixel. Courtesy of Mustafa Mir, University of Illinois at Urbana-Champaign.

“We believe that it is very important to be able to test for blood diseases at the single-cell level,” said Gabriel Popescu, an assistant professor at the university. “Light scattering is a very powerful method to accomplish this because it is sensitive to subtle morphology changes of individual cells. However, due to their irregular shapes, doughnut-shape, or discocytes, it is difficult to model the scattering from red blood cells.”

The researchers found that light-cell interactions were too complicated to analyze, so they used the Born approximation – a mathematical rule that can be used when the object of interest is small and transparent – to calculate what a scattering signature for healthy cells should be.

Surface map projection of a spatial light interference microscopy image of healthy red blood cells. Courtesy of Mustafa Mir.

By running Fourier transform light scattering on individual red blood cells, the scientists found that the pattern changed significantly with the diameter and dimple width of the cells. Using this information, they applied the Born approximation and determined the appropriate scattering signature for healthy cells. They used this “healthy cell signature” to identify the correct morphology of cells in a blood smear.

A collage of spatial light interference microscopy images of various types of deformed red blood cells. Courtesy of Mustafa Mir.

“We anticipate that our studies will provide a new, highly sensitive approach to blood testing, capable of revealing abnormalities earlier and with higher accuracy than currently possible,” Popescu said. “We are currently targeting several high-impact applications, sickle-cell anemia and deterioration of blood properties in blood banks.”

The findings appeared online in the open-access journal Biomedical Optics Express (

Jan 2012
AmericasBiophotonicsBioScanblood cell depressionblood disease detectionBorn approximationFourier transform light scatteringFTLSGabriel Popescuhealthy cell scattering signatureIllinoislight-cell interactionmalaria detectionMicroscopymisshapen red blood cellsNewsopticsRBCsred blood cellssickle cell anemia detectionTest & MeasurementUIUCUniversity of Illinois

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