Parasites, Hosts and Diseases

The Korea Society for Parasitology and Tropical Medicine (대한기생충학·열대의학회)
권호 표지
DOI QR코드

DOI QR Code

Performance Evaluation of Biozentech Malaria Scanner in Plasmodium knowlesi and P. falciparum as a New Diagnostic Tool

  • Firdaus, Egy Rahman (Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University) ;
  • Park, Ji-Hoon (Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University) ;
  • Muh, Fauzi (Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University) ;
  • Lee, Seong-Kyun (Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University) ;
  • Han, Jin-Hee (Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University) ;
  • Lim, Chae-Seung (Department of Laboratory Medicine, Korea University College of Medicine) ;
  • Na, Sung-Hun (Department of Obstetrics and Gynecology, Kangwon National University Hospital, Kangwon National University School of Medicine) ;
  • Park, Won Sun (Department of Physiology, School of Medicine, Kangwon National University) ;
  • Park, Jeong-Hyun (Department of Anatomy and Cell Biology, School of Medicine, Kangwon National University) ;
  • Han, Eun-Taek (Department of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University)
  • Received : 2021.02.17
  • Accepted : 2021.03.11
  • Published : 2021.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

The computer vision diagnostic approach currently generates several malaria diagnostic tools. It enhances the accessible and straightforward diagnostics that necessary for clinics and health centers in malaria-endemic areas. A new computer malaria diagnostics tool called the malaria scanner was used to investigate living malaria parasites with easy sample preparation, fast and user-friendly. The cultured Plasmodium parasites were used to confirm the sensitivity of this technique then compared to fluorescence-activated cell sorting (FACS) analysis and light microscopic examination. The measured percentage of parasitemia by the malaria scanner revealed higher precision than microscopy and was similar to FACS. The coefficients of variation of this technique were 1.2-6.7% for Plasmodium knowlesi and 0.3-4.8% for P. falciparum. It allowed determining parasitemia levels of 0.1% or higher, with coefficient of variation smaller than 10%. In terms of the precision range of parasitemia, both high and low ranges showed similar precision results. Pearson's correlation test was used to evaluate the correlation data coming from all methods. A strong correlation of measured parasitemia (r2=0.99, P<0.05) was observed between each method. The parasitemia analysis using this new diagnostic tool needs technical improvement, particularly in the differentiation of malaria species.

Keywords

Acknowledgement

The authors are grateful to Robert W. Moon Department of Immunology and Infection, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom for providing the P. knowlesi A1-H.1 strain. This study was supported by a grant from the Korea Association of Health Promotion (2019-02), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2017R1A2A2A05069562), by Basic Science Research Programmed through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2015R1A4A1038666). The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

References

  1. Pigott DM, Howes RE, Wiebe A, Battle KE, Golding N, Gething PW, Dowell SF, Farag TH, Garcia AJ, Kimball AM. Prioritising infectious disease mapping. PLoS Negl Trop Dis 2015; 9: e0003756. https://doi.org/10.1371/journal.pntd.0003756
  2. Parselia E, Kontoes C, Tsouni A, Hadjichristodoulou C, Kioutsioukis I, Magiorkinis G, Stilianakis NI. Satellite earth observation data in epidemiological modeling of malaria, dengue and West Nile virus: a scoping review. Remote Sens 2019; 11: 1862. https://doi.org/10.3390/rs11161862
  3. Ramasamy R. Zoonotic malaria-global overview and research and policy needs. Front Public Health 2014; 2: 123. https://doi.org/10.3389/fpubh.2014.00123
  4. Ortiz-Ruiz A, Postigo M, Gil-Casanova S, Cuadrado D, Bautista JM, Rubio JM, Luengo-Oroz M, Linares M. Plasmodium species differentiation by non-expert on-line volunteers for remote malaria field diagnosis. Malar J 2018; 17: 54. https://doi.org/10.1186/s12936-018-2194-8
  5. Wiese L, Bruun B, Baek L, Friis-Moller A, Gahrn-Hansen B, Hansen J, Heltberg O, Hojbjerg T, Kathrine Hornstrup M, Kvinesdal B. Bedside diagnosis of imported malaria using the Binax Now malaria antigen detection test. Scand J Infect Dis 2006; 38: 1063-1068. https://doi.org/10.1080/00365540600818011
  6. Alvar J, Alves F, Bucheton B, Burrows L, Buscher P, Carrillo E, Felger I, Hubner MP, Moreno J, Pinazo M-J, Ribeiro I, Estani-SS, Specht S, Tarral A, Wourgaft NS, Bilbe G. Implications of asymptomatic infection for the natural history of selected parasitic tropical diseases. Semin Immunopathol 2020; 42: 231-246. https://doi.org/10.1007/s00281-020-00796-y
  7. Bronzan RN, McMorrow ML, Kachur SP. Diagnosis of malaria: challenges for clinicians in endemic and non-endemic regions. Mol Diagn Ther 2008; 12: 299-306. https://doi.org/10.1007/BF03256295
  8. Peeling RW, Holmes KK, Mabey D, Ronald A. Rapid tests for sexually transmitted infections (STIs): the way forward. Sex Transm Infect 2006; 82 (suppl): 1-6. http://dx.doi.org/10.1136/sti.2006.024265
  9. Kosack CS, Page AL, Klatser PR. A guide to aid the selection of diagnostic tests. Bull World Health Organ 2017; 95: 639-645. https://doi.org/10.2471/BLT.16.187468
  10. Zaw MT, Lin Z. Human Plasmodium knowlesi infections in South-East Asian countries. J Microbiol Immunol Infect 2019; 52: 679-684. https://doi.org/10.1016/j.jmii.2019.05.012
  11. Singh B, Daneshvar C. Human infections and detection of Plasmodium knowlesi. Clin Microbiol Rev 2013; 26: 165-184. https://doi.org/10.1128/cmr.00079-12
  12. Cox-Singh J, Hiu J, Lucas SB, Divis PC, Zulkarnaen M, Chandran P, Wong KT, Adem P, Zaki SR, Singh B. Severe malaria-a case of fatal Plasmodium knowlesi infection with post-mortem findings: a case report. Malar J 2010; 9: 10. https://doi.org/10.1186/1475-2875-9-10
  13. Mahende C, Ngasala B, Lusingu J, Yong T-S, Lushino P, Lemnge M, Mmbando B, Premji Z. Performance of rapid diagnostic test, blood-film microscopy and PCR for the diagnosis of malaria infection among febrile children from Korogwe District, Tanzania. Malar J 2016; 15: 391. https://doi.org/10.1186/s12936-016-1450-z
  14. Spencer HC, Collins WE, Warren M, Jeffery GM, Mason J, Huong AY, Stanfill PS, Skinner JC. The enzyme-linked immunosorbent assay (ELISA) for malaria. Am J Trop Med Hyg 1981; 30: 747-750. https://doi.org/10.4269/ajtmh.1981.30.747
  15. She RC, Rawlins ML, Mohl R, Perkins SL, Hill HR, Litwin CM. Comparison of immunofluorescence antibody testing and two enzyme immunoassays in the serologic diagnosis of malaria. J Travel Med 2007; 14: 105-111. https://doi.org/10.1111/j.1708-8305.2006.00087.x
  16. Cutts T, Cook B, Poliquin G, Strong J, Theriault S. Inactivating Zaire Ebolavirus in whole-blood thin smears used for malaria diagnosis. J Clin Microbiol 2016; 54: 1157-1159. http://dx.doi.org/10.1128/JCM.02960-15
  17. Fernando SD, Ihalamulla RL, Wickremasinghe R, de Silva NL, Thilakarathne JH, Wijeyaratne P, Premaratne RG. Effects of modifying the World Health Organization standard operating procedures for malaria microscopy to improve surveillance in resource poor settings. Malar J 2014; 13: 98. https://doi.org/10.1186/1475-2875-13-98
  18. Pollak JJ, Houri-Yafin A, Salpeter SJ. Computer vision malaria diagnostic systems-progress and prospects. Front Public Health 2017; 5: 219. https://doi.org/10.3389/fpubh.2017.00219
  19. Moon RW, Hall J, Rangkuti F, Ho YS, Almond N, Mitchell GH, Pain A, Holder AA, Blackman MJ. Adaptation of the genetically tractable malaria pathogen Plasmodium knowlesi to continuous culture in human erythrocytes. Proc Natl Acad Sci USA 2013; 110: 531-536. https://doi.org/10.1073/pnas.1216457110
  20. Chen CH. An introduction to computer vision in medical imaging. In Chen CH ed, Computer Vision in Medical Imaging. Toh Tuck Link, Singapore. World scientific. 2014, pp 1-16.
  21. Prescott WR, Jordan RG, Grobusch MP, Chinchilli VM, Kleinschmidt I, Borovsky J, Plaskow M, Torrez M, Mico M, Schwabe C. Performance of a malaria microscopy image analysis slide reading device. Malar J 2012; 11: 155. https://doi.org/10.1186/1475-2875-11-155
  22. Delahunt CB, Mehanian C, Hu L, McGuire SK, Champlin CR, Horning MP, Wilson BK, Thompon CM. Automated microscopy and machine learning for expert-level malaria field diagnosis. IEEE. 2015: 393-399. https://doi.org/10.1109/GHTC.2015.7344002
  23. Eshel Y, Houri-Yafin A, Benkuzari H, Lezmy N, Soni M, Charles M, Swaminathan J, Solomon H, Sampathkumar P, Premji Z. Evaluation of the Parasight platform for malaria diagnosis. J Clin Microbiol 2017; 55: 768-775. https://doi.org/10.1128/JCM.02155-16
  24. Vink J, Laubscher M, Vlutters R, Silamut K, Maude R, Hasan M, De Haan G. An automatic vision-based malaria diagnosis system. J Microsc 2013; 250: 166-178. https://doi.org/10.1111/jmi.12032
  25. Martens-Habbena W, Sass H. Sensitive determination of microbial growth by nucleic acid staining in aqueous suspension. Appl Environ Microbiol 2006; 72: 87-95. https://doi.org/10.1128/aem.72.1.87-95.2006
  26. Grimberg BT. Methodology and application of flow cytometry for investigation of human malaria parasites. J Immunol Methods 2011; 367: 1-16. https://doi.org/10.1016/j.jim.2011.01.015
  27. Watson OJ, Sumner KM, Janko M, Goel V, Winskill P, Slater HC, Ghani A, Meshnick SR, Parr JB. False-negative malaria rapid diagnostic test results and their impact on community-based malaria surveys in sub-Saharan Africa. BMJ Glob Health 2019; 4: e001582. http://dx.doi.org/10.1136/bmjgh-2019-001582
  28. Gallagher PG. Disorders of erythrocyte hydration. Blood 2017; 130: 2699-2708. https://doi.org/10.1182/blood-2017-04-590810
  29. Yoon J, Kwon JA, Yoon SY, Jang WS, Yang DJ, Nam J, Lim CS. Diagnostic performance of CellaVision DM96 for Plasmodium vivax and Plasmodium falciparum screening in peripheral blood smears. Acta Trop 2019; 193: 7-11. https://doi.org/10.1016/j.actatropica.2019.02.009