Field Evaluation of a Device for Automated Malaria Microscopy (Autoscope Version 2)
Autoscope
1 other identifier
observational
793
0 countries
N/A
Brief Summary
Microscopy remains a key indicator in drug efficacy testing performed in the context of clinical trials for monitoring existing antimalarials 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 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 the frequent poor specificity and sensitivity associated with manual microscopy diagnostics in operational conditions , , . Advances in digital microscopy performance and affordability have now opened the door to potentially significant improvements in the performance of malaria diagnostic microscopy, overcoming serious deficiencies in current drug efficacy assessment, and more broadly in malaria diagnosis and management. Intellectual Ventures Laboratory (IVL), in collaboration with Global Good Fund (GG), has developed an initial microscope prototype to support its research into dark field imaging of unstained malaria slides. The system consists of low cost electromechanical components for scanning a standard slide, an optical train with a high numerical aperture objective, and an image capture system. 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. Additionally, image processing algorithms have been built around detection of Giemsa-stained malaria slides which is the current standard for malaria microscopy. Initial results show excellent potential for sensitivity and specificity which exceeds that of typical manual microscopists in the field. Based on the positive market and needs assessment in January, 2013, given by stakeholders in the malaria diagnostics community, GG/IVL are pursuing improvement and integration of this algorithm into a portable microscope platform with characteristics similar to the prototype microscope already developed at GG/IVL for dark field imaging. The prototype Autoscope was first tested in field settings in Thailand in Nov 2014 - Jan 2015 at clinics operated by the Shoklo Malaria Research Unit (SMRU). The goal of the first field evaluation was to assess the Autoscope in with respect to its diagnostic performance and also its suitability for harsh conditions typically encountered in field clinics. Further, user feedback on the design and functionality was sought. The Autoscope and the accompanying image analysis algorithms have since been further developed and a new version is now available for testing.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Nov 2016
Shorter than P25 for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
October 11, 2016
CompletedFirst Posted
Study publicly available on registry
October 13, 2016
CompletedStudy Start
First participant enrolled
November 10, 2016
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 19, 2017
CompletedStudy Completion
Last participant's last visit for all outcomes
July 19, 2017
CompletedSeptember 17, 2020
September 1, 2019
8 months
October 11, 2016
September 15, 2020
Conditions
Outcome Measures
Primary Outcomes (2)
Diagnostic sensitivity for malaria parasite detection
6 months
Diagnostic specificity for malaria parasite detection
6 months
Secondary Outcomes (2)
kappa statistic for parasite species detection
6 months
Bland-Altman plots for parasite density estimation
6 months
Eligibility Criteria
Eighty slide-confirmed malaria cases (P. falciparum, P. vivax) will be recruited in the study per study site. Accordingly, * At EOCRU, with an estimated malaria prevalence of 30% in febrile patients, up to 270 patients will be recruited * At SMRU, with an estimated malaria prevalence of 10% in febrile patients, up to 800 patients will be recruited I.e., a total of 1070 subjects with up to 160 malaria positive cases across study sites.
You may qualify if:
- Male or female subjects, age ≥ 6 months to 75 years
- Febrile at presentation or reported within the last 48 hours (\>37.5 ºC) and no other obvious diagnosis cause for fever, warranting malaria investigation under routine clinical practice.
- Individual informed assent/consent obtained
You may not qualify if:
- Signs of severe malaria as defined by WHO
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Biospecimen
Blood collection from finger-prick (maximum 150-200 µL), which will be used to prepare slides.
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- CASE ONLY
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
October 11, 2016
First Posted
October 13, 2016
Study Start
November 10, 2016
Primary Completion
July 19, 2017
Study Completion
July 19, 2017
Last Updated
September 17, 2020
Record last verified: 2019-09
Data Sharing
- IPD Sharing
- Will not share