Browsing by Author "Ken Lilley"

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    Performance of a fully‐automated system on a WHO malaria microscopy evaluation slide set
    (2021-12-01) Matthew P. Horning; Charles B. Delahunt; Christine M. Bachman; Jennifer Luchavez; Christian Luna; Liming Hu; Mayoore S. Jaiswal; Clay M. Thompson; Sourabh Kulhare; Samantha Janko; Benjamin K. Wilson; Travis Ostbye; Martha Mehanian; Roman Gebrehiwot; Grace Yun; David Bell; Stephane Proux; Jane Y. Carter; Wellington Oyibo; Dionicia Gamboa; Mehul Dhorda; Ranitha Vongpromek; Peter L. Chiodini; Bernhards Ogutu; Earl G. Long; Kyaw Tun; Thomas R. Burkot; Ken Lilley; Courosh Mehanian; Mahidol Oxford Tropical Medicine Research Unit; Gokila; Universidad Peruana Cayetano Heredia; Kenya Medical Research Institute; Amref Health Africa; London School of Hygiene & Tropical Medicine; Centers for Disease Control and Prevention; James Cook University; University of Washington; Mahidol University; University of Lagos; Arizona State University; Australian Defence Force Malaria and Infectious Disease Institute; Independent Consultant; Asia Regional Centre; Defence Services Medical Academy; Creative Creek, LLC; Intellectual Ventures Global Good Fund; Intellectual Ventures
    Background: Manual microscopy remains a widely-used tool for malaria diagnosis and clinical studies, but it has inconsistent quality in the field due to variability in training and field practices. Automated diagnostic systems based on machine learning hold promise to improve quality and reproducibility of field microscopy. The World Health Organization (WHO) has designed a 55-slide set (WHO 55) for their External Competence Assessment of Malaria Microscopists (ECAMM) programme, which can also serve as a valuable benchmark for automated systems. The performance of a fully-automated malaria diagnostic system, EasyScan GO, on a WHO 55 slide set was evaluated. Methods: The WHO 55 slide set is designed to evaluate microscopist competence in three areas of malaria diagnosis using Giemsa-stained blood films, focused on crucial field needs: malaria parasite detection, malaria parasite species identification (ID), and malaria parasite quantitation. The EasyScan GO is a fully-automated system that combines scanning of Giemsa-stained blood films with assessment algorithms to deliver malaria diagnoses. This system was tested on a WHO 55 slide set. Results: The EasyScan GO achieved 94.3 % detection accuracy, 82.9 % species ID accuracy, and 50 % quantitation accuracy, corresponding to WHO microscopy competence Levels 1, 2, and 1, respectively. This is, to our knowledge, the best performance of a fully-automated system on a WHO 55 set. Conclusions: EasyScan GO’s expert ratings in detection and quantitation on the WHO 55 slide set point towards its potential value in drug efficacy use-cases, as well as in some case management situations with less stringent species ID needs. Improved runtime may enable use in general case management settings.
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    Towards harmonization of microscopy methods for malaria clinical research studies
    (2020-09-04) Mehul Dhorda; El Hadji Ba; J. Kevin Baird; John Barnwell; David Bell; Jane Y. Carter; Arjen Dondorp; Lenny Ekawati; Michelle Gatton; Iveth González; Philippe J. Guérin; Sandra Incardona; Ken Lilley; Didier Menard; François Nosten; Peter Obare; Bernhards Ogutu; Piero L. Olliaro; Ric N. Price; Stéphane Proux; Andrew R. Ramsay; John C. Reeder; Kamolrat Silamut; Cheikh Sokhna; Oxford University Clinical Research Unit; Institut Pasteur du Cambodge; Institut de Recherche pour le Développement Dakar; Kenya Medical Research Institute; Amref Health Africa; Shoklo Malaria Research Unit; Menzies School of Health Research; Centers for Disease Control and Prevention; Mahidol University; Queensland University of Technology QUT; School of Medicine; Nuffield Department of Medicine; UNICEF; Terre des Hommes Foundation; Independent Consultant; FIND; Australian Defence Force Malaria and Infectious Disease Institute; WorldWide Antimalarial Resistance Network; Worldwide Antimalarial Resistance Network
    © 2020 The Author(s). Microscopy performed on stained films of peripheral blood for detection, identification and quantification of malaria parasites is an essential reference standard for clinical trials of drugs, vaccines and diagnostic tests for malaria. The value of data from such research is greatly enhanced if this reference standard is consistent across time and geography. Adherence to common standards and practices is a prerequisite to achieve this. The rationale for proposed research standards and procedures for the preparation, staining and microscopic examination of blood films for malaria parasites is presented here with the aim of improving the consistency and reliability of malaria microscopy performed in such studies. These standards constitute the core of a quality management system for clinical research studies employing microscopy as a reference standard. They can be used as the basis for the design of training and proficiency testing programmes as well as for procedures and quality assurance of malaria microscopy in clinical research.