Deshmukh SS, Byaruhanga O, Tumwebaze P, Akin D, Greenhouse B, Egan ES, Demirci U. Automated Recognition of Plasmodium falciparum Parasites from Portable Blood Levitation Imaging.
ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022;
9:e2105396. [PMID:
35957519 PMCID:
PMC9534981 DOI:
10.1002/advs.202105396]
[Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 05/03/2022] [Indexed: 06/15/2023]
Abstract
In many malaria-endemic regions, current detection tools are inadequate in diagnostic accuracy and accessibility. To meet the need for direct, phenotypic, and automated malaria parasite detection in field settings, a portable platform to process, image, and analyze whole blood to detect Plasmodium falciparum parasites, is developed. The liberated parasites from lysed red blood cells suspended in a magnetic field are accurately detected using this cellphone-interfaced, battery-operated imaging platform. A validation study is conducted at Ugandan clinics, processing 45 malaria-negative and 36 malaria-positive clinical samples without external infrastructure. Texture and morphology features are extracted from the sample images, and a random forest classifier is trained to assess infection status, achieving 100% sensitivity and 91% specificity against gold-standard measurements (microscopy and polymerase chain reaction), and limit of detection of 31 parasites per µL. This rapid and user-friendly platform enables portable parasite detection and can support malaria diagnostics, surveillance, and research in resource-constrained environments.
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