Optical Technique Promises Rapid and Accurate Diagnosis of Malaria

An international team of scientists led by those at Materials Technology Institute, (Trieste, Italy) compared the apparently random scattering, called 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 has preliminary results involving 25 cell samples of which 12 were healthy and 13 infected with malaria.

The specific technique the scientists used is called Secondary Speckle Sensing Microscopy. By applying this imaging technique to an automated high-throughput system, the scientists were able to deliver results in as little as 30 minutes. They did so with a high rate of accuracy and without the need for highly trained technicians and a well-equipped hospital laboratory. The current time to diagnosis in most African medical centers is typically between 8-10 hours.

Secondary Speckle Sensing Microscopy consists of a custom inverted microscope in which the sample of red blood cells is illuminated by a tilted laser beam (Laser Physics; Milton Green, UK). This produces a time-varied speckle pattern field based on the cells' thermal vibration and the movement of their membranes, traits that differ in healthy and diseased states. The speckle patterns are inspected under the microscope and recorded on a camera at a high frame rate. Using two automated analytical methods called fuzzy logic and principal component analysis; scientists scour a set of speckle parameters to extract statistical information about changes in red blood cells' membranes and their flickering movements. Scientists then make a diagnosis based on statistical correlations in speckle patterns between healthy and diseased cells.

Dan Cojoc, PhD, lead author of the study, said, "A new diagnostic tool is urgently needed. With a fast, portable, low-cost, and accurate diagnostic tool, physicians can confidently and quickly administer the correct therapy." The current diagnostic gold standard for malaria is a Giemsa-stained blood smear, which uses optical microscopy to identify different species of the malaria parasite, Plasmodium, in blood samples. This technique requires skilled medical professionals trained to identify the telltale signs of the parasite throughout its life cycle and its population density in the bloodstream. The study was published in the April 2012 issue of Biomedical Optics Express.

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Materials Technology Institute
Laser Physics