Abstract

BackgroundManual 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.MethodsThe 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.ResultsThe 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.ConclusionsEasyScan 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.

Highlights

  • 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

  • One strong candidate for such a benchmark is the slide set used for the World Health Organization (WHO) External Competence Assessment of Malaria Microscopists (ECAMM) programme

  • This paper reports performance of a fully-automated end-to-end malaria diagnostic system, the Motic EasyScan GO [17], on an ECAMM slide set

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Summary

Introduction

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. 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 serve as a valuable benchmark for automated systems. One strong candidate for such a benchmark is the slide set used for the World Health Organization (WHO) External Competence Assessment of Malaria Microscopists (ECAMM) programme. These slide sets consist of 55–56 carefully specified Giemsa-stained blood films, used to evaluate microscopists in detection, species ID, and quantitation of malaria parasites as part of the WHO Quality Assurance programmes [15, 16]. A system that hopes to deploy through existing field infrastructure, clinicians, and protocols needs to operate successfully on standard Giemsa-stained blood films as currently prepared and processed in the field by microscopists

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