The current gold standard for malaria diagnosis, Giemsa-stained blood smears, use optical microscopy to identify different species of the malaria parasite, Plasmodium, in blood samples. The technique requires skilled medical professionals who are trained to identify the tell tale signs of the parasite throughout its life cycle and its population density in the bloodstream.
New Optical Technique Promises Rapid and Accurate Malaria Diagnosis
Correctly and quickly diagnosing malaria infection is essential for effective and life-saving treatment to be administered. Rapid detection, particularly in remote areas, is not always possible because current methods are time-consuming and require precise instrumentation and highly skilled microscopic analysis.
The Optical Society (OSA) has published a paper in its open-access journal Biomedical Optics Express, which describes a promising new optical imaging system that could make the diagnosis of malaria easier, faster, and more accurate.
The new system, developed by an international team of researchers, uses “speckle imaging,” an optical sensing technique that measures the differences in how laser light bounces off the membranes of healthy and infected red blood cells. By comparing the apparently random scattering (speckling) of light as it builds up from multiple images, a clear statistical pattern emerges that identifies cells that harbor the parasite responsible for malaria. The team presents its preliminary results involving 25 cell samples (12 healthy, 13 infected) in the Biomedical Optics Express paper.
"A new diagnostic tool is urgently needed," notes Dan Cojoc, Ph.D., lead author of the study and a researcher at the Materials Technology Institute, National Research Council in Trieste, Italy. “With a fast, portable, low-cost, and accurate diagnostic tool, physicians can confidently and quickly administer the correct therapy.”
While these preliminary results are encouraging, the investigators note that further study is needed to validate the results and further refine the technique. If the positive outcomes hold up, field studies or clinical trials of the new method might be deployed as early as 2013.
Image Caption - Secondary Speckle Sensing Microscopy (S3M). The difference between an infected red blood cell (top) and a healthy cell (bottom) is revealed by S3M, in part, by considering the dynamics of the correlation value (CV). CV indicates the similarity between two patterns. 1,000 CVs are calculated from pairs of consecutive speckles acquired in 1 second. As shown in the chart at right, the CV oscillation range for the infected cell (top, 0.36) is almost three times larger than that of the healthy red blood cell (bottom, 0.13). In the top left image of the infected cell a parasitic life-cycle stage of malaria, called “trophozoite,” can be seen (arrow). Credit: Dan Cojoc, Materials Technology Institute, National Research Council, Italy.
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