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Anal Chem. 2019 Feb 5;91(3):2216-2223. doi: 10.1021/acs.analchem.8b04791. Epub 2019 Jan 15.

Malaria Detection by Third-Harmonic Generation Image Scanning Cytometry.

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Department of Chemistry , McGill University , 801 Sherbrooke Street West , Montreal , Quebec H3A 0B8 , Canada.
Institute of Parasitology , McGill University , Sainte Anne de Bellevue , Quebec H9X 3 V9 , Canada.
ANDI Centre of Excellence for Malaria Diagnosis, College of Medicine , University of Lagos , Idi-Araba, Lagos 100254 , Nigeria.
Department of Physics , McGill University , 3600 University Street , Montreal , Quebec H3A 2T8 , Canada.


Despite global efforts aimed at its elimination, malaria is still a significant health concern in many countries across the world. The disease is caused by blood-borne parasites, Plasmodium species, and is transmitted by female Anopheles mosquitoes and presents with generic febrile symptoms that are challenging to diagnose clinically. To adequately tackle this issue, an effective detection method is required for screening potential malaria patients for infection. To this day, the gold standard for malaria detection remains basic light microscopy of Giemsa-stained patient blood smears to first enable detection and manual counting to determine the parasite density by a microscopist. While effective at detecting parasites, this method requires both significant time and skilled personnel. As an alternate approach, we propose a new malaria detection method that we call third-harmonic generation image scanning cytometry (THGISC) based on the combination of third-harmonic generation imaging, high-speed motorized scanning, and automated software processing. Third-harmonic generation (THG) is a nonlinear optical process in which the frequency of incident photons is tripled within the sample material. We have previously demonstrated that hemozoin, a metabolic byproduct of the malaria parasite, presents a significant THG signal. We now present a practical approach that uses the selectivity of this contrast mechanism to perform label-free image scanning cytometry of patient blood smears for automated malaria detection. In this work, we applied this technique to lab-cultured parasites and parasites in whole blood obtained from malaria patients. We also compared its effectiveness to parasite counts obtained by classical methods. The ability to easily and rapidly determine parasitemia by THG offers potential not only for the easy confirmation of malaria diagnoses following symptoms, but also the tracking of treatment progress in existing patients, potentially allowing physicians to adjust medication and dosage for each individual.

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