Evaluation of a Digital Microscope for Malaria

NCT ID: NCT03512678

Last Updated: 2020-09-03

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 2250 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2018-06-25
• Study Completion Date: 2020-06-30

Brief Summary

Light microscopy, which is based on century-old technology, remains a key indicator in drug efficacy testing performed in the context of clinical trials for monitoring existing antimalarial drugs or in the context of regulatory clinical trials for registration of new drugs. It is one of the main diagnostic methods for malaria diagnosis in general, as in an ideal setting it can provide low-cost accurate diagnosis, determine the density of parasites in the blood, and accurately differentiate between different malaria parasite species, characteristics vital to the implementation of global plans for drug efficacy monitoring. Malaria rapid tests (RDTs), while useful for rapid diagnosis and case management, do not provide information on the parasite density nor the species differentiation necessary for research and drug efficacy assessment. Microscopy therefore retains key advantages over a number of newer technologies, but its reliability is severely impeded by dependence on high technical competence of the human operators as well as availability of high quality equipment and reagents. Recent studies have demonstrated frequent poor specificity and sensitivity associated with manual microscopy diagnostics in operational conditions. These drawbacks constitute a major limiting factor to effective monitoring and preservation of vital anti-malarial medicines.

Advances in digital microscopy performance and affordability have now opened the door to potentially significant improvements in the performance of malaria microscopy, overcoming serious deficiencies in current drug efficacy assessment, and more broadly in malaria diagnosis and management. Global Good (GG)/Intellectual Ventures Laboratory (IVL) sponsored by the Global Good Fund, has developed a microscope prototype consisting of low cost components to scan and capture images from Giemsa-stained thick blood films on slides. The captured images are analyzed with custom image analysis software developed at GG/IVL, using algorithms that are designed for automatic malaria diagnosis, without user input. Versions of a prototype of the device were first tested in field settings in Thailand in 2014-2015 at clinics operated by the Shoklo Malaria Research Unit (SMRU) and then again in 2016-2017. When compared to expert microscopy at SMRU, the performance of the device with respect to diagnostic sensitivity (87.8%), species identification (85.6% species correctly identified) and parasite density estimation (44% of estimates within +/-25% of reference microscopy result) corresponded to WHO Competence Level 2. The device and the accompanying image analysis algorithms have since been further developed and a new, third version of the prototype is now available for testing in diverse settings with varying malaria prevalence and user expertise.

Detailed Description

The primary purpose of this evaluation is to quantify the diagnostic performance of the EasyScan Go prototype in various field settings. The performance of the EasyScan Go prototype will be assessed by scanning of negative and positive slides with the EasyScan Go and comparing the results with expert microscopy. Plasmodium genus- and species-specific PCR will also be performed on samples collected at some sites as an additional confirmatory test for the detection of malaria parasites and their species if present. Testing by microscopy and EasyScan Go will be performed in field clinic settings on Giemsa-stained slides prepared from febrile patient blood collected from a finger-prick. Further work will be undertaken at the WWARN laboratory in Bangkok for data analyses and for quality assurance.

Funder: Intellectual Ventures Lab/Global Good (2018) Sponser: University of Oxford Grant refernce number:The Global Good Fund I, LLC PA No.5

Conditions

Malaria

Study Design

• Observational Model Type: CASE_ONLY
• Study Time Perspective: PROSPECTIVE

Eligibility Criteria

Inclusion Criteria

• Male or female subjects, age ≥ 6 months to 75 years
• Febrile at presentation or history of fever in the past 48 hours (≥ 37.5 ºC) and no other obvious diagnosis or cause for fever, warranting malaria investigation under routine clinical practice.
• Individual informed assent/consent obtained

Exclusion Criteria

• Signs of severe malaria as defined by WHO

• Minimum Eligible Age: 6 Months
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University of Oxford

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Shoklo Malaria Research Unit

Mae Sot, Changwat Tak, Thailand

Countries

Thailand

References

Das D, Vongpromek R, Assawariyathipat T, Srinamon K, Kennon K, Stepniewska K, Ghose A, Sayeed AA, Faiz MA, Netto RLA, Siqueira A, Yerbanga SR, Ouedraogo JB, Callery JJ, Peto TJ, Tripura R, Koukouikila-Koussounda F, Ntoumi F, Ong'echa JM, Ogutu B, Ghimire P, Marfurt J, Ley B, Seck A, Ndiaye M, Moodley B, Sun LM, Archasuksan L, Proux S, Nsobya SL, Rosenthal PJ, Horning MP, McGuire SK, Mehanian C, Burkot S, Delahunt CB, Bachman C, Price RN, Dondorp AM, Chappuis F, Guerin PJ, Dhorda M. Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning. Malar J. 2022 Apr 12;21(1):122. doi: 10.1186/s12936-022-04146-1.

Reference Type: DERIVED

PMID: 35413904 (View on PubMed)

Other Identifiers

MAL18002

Identifier Type: -

Identifier Source: org_study_id