Evaluating the diagnostic performance of miLab™ for detection of malaria parasites using nPCR as reference standard

Malaria remains a leading health threat in sub-Saharan Africa, causing over 600,000 deaths annually. Ghana, ranked among the top 15 in malaria burden in Africa, relies heavily on microscopy for diagnosis due to its affordability and established use. However, limitations in sensitivity, turnaround time, and availability of skilled personnel despite ongoing national training efforts stress the need for improved diagnostics. This study evaluated miLab<sup>™</sup>, an AI-assisted automated malaria detection platform, using nested PCR (nPCR) as the reference standard. We conducted a hospital-based cross-sectional study from August 2024 to June 2025 in three malaria-endemic communities in Kumasi, Ashanti region and enrolled 300 suspected malaria patients (168 females, 132 males; aged 1-87 years, median 24). Blood samples were analyzed independently by miLab<sup>™</sup>, two independent mid-level microscopists, and nPCR. Discrepancies between the two microscopists were resolved by a WHO expert microscopist (adjudicated microscopy) to establish a microscopy reference standard. Diagnostic accuracy, correlation and measurement agreement were determined using GraphPad Prism Version 8. Parasite densities estimated by miLab<sup>™</sup> ranged from 0.95 to 5.34 log parasites/µL (median 3.52, IQR 2.93-3.91). For mid-level microscopist 1, densities ranged from 2.02 to 5.43, (median 4.02, IQR: 3.22-4.50), while Mid-level microscopist 2 measured densities between 1.98 and 5.22, (median 3.78, IQR: 3.15-4.23). When compared to nPCR, miLab<sup>™</sup> demonstrated a sensitivity of 94.23%, specificity of 98.98%, and accuracy of 97.33%, while adjudicated microscopy showed a sensitivity of 85.58%, specificity of 97.96%, and accuracy of 93.67%. These findings indicate that miLab<sup>™</sup> has better performance compared to microscopy for detection of malaria parasites. miLab™ could offer a reliable, rapid diagnostic alternative suitable for malaria-endemic, resource-limited settings where timely and accurate diagnosis is critical for effective case management and control.

Authors

Institutions

Publication Details

Journal
Malaria Journal
Published
2026-02-12
DOI
https://doi.org/10.1186/s12936-026-05801-7
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating the diagnostic performance of miLab™ for detection of malaria parasites using nPCR as reference standard

Ebenezer Kojo Addae, Richard Owusu Ansah, Benedict Sackey, Franklin Asiedu Bekoe et al.
Malaria Journal
Malaria Research and Control
article

Evaluating the diagnostic performance of miLab™ for detection of malaria parasites using nPCR as reference standard

Ebenezer Kojo Addae, Richard Owusu Ansah, Benedict Sackey, Franklin Asiedu Bekoe, James Opoku Frimpong, Nana Kwame Ayisi‐Boateng, Richard Larbi, M. D. Owusu Owusu, Kinako Denis Elia Dazangapai, Thelma Owusuaa Ofori Amoako, Alexander Asamoah, Theophilus Awortwe-Quaicoe, Bernard Nkrumah
article en

Abstract

Malaria remains a leading health threat in sub-Saharan Africa, causing over 600,000 deaths annually. Ghana, ranked among the top 15 in malaria burden in Africa, relies heavily on microscopy for diagnosis due to its affordability and established use. However, limitations in sensitivity, turnaround time, and availability of skilled personnel despite ongoing national training efforts stress the need for improved diagnostics. This study evaluated miLab<sup>™</sup>, an AI-assisted automated malaria detection platform, using nested PCR (nPCR) as the reference standard. We conducted a hospital-based cross-sectional study from August 2024 to June 2025 in three malaria-endemic communities in Kumasi, Ashanti region and enrolled 300 suspected malaria patients (168 females, 132 males; aged 1-87 years, median 24). Blood samples were analyzed independently by miLab<sup>™</sup>, two independent mid-level microscopists, and nPCR. Discrepancies between the two microscopists were resolved by a WHO expert microscopist (adjudicated microscopy) to establish a microscopy reference standard. Diagnostic accuracy, correlation and measurement agreement were determined using GraphPad Prism Version 8. Parasite densities estimated by miLab<sup>™</sup> ranged from 0.95 to 5.34 log parasites/µL (median 3.52, IQR 2.93-3.91). For mid-level microscopist 1, densities ranged from 2.02 to 5.43, (median 4.02, IQR: 3.22-4.50), while Mid-level microscopist 2 measured densities between 1.98 and 5.22, (median 3.78, IQR: 3.15-4.23). When compared to nPCR, miLab<sup>™</sup> demonstrated a sensitivity of 94.23%, specificity of 98.98%, and accuracy of 97.33%, while adjudicated microscopy showed a sensitivity of 85.58%, specificity of 97.96%, and accuracy of 93.67%. These findings indicate that miLab<sup>™</sup> has better performance compared to microscopy for detection of malaria parasites. miLab™ could offer a reliable, rapid diagnostic alternative suitable for malaria-endemic, resource-limited settings where timely and accurate diagnosis is critical for effective case management and control.

Malaria JournalVol. 25(1)
Kwame Nkrumah University of Science and Technology (GH), Kumasi Centre for Collaborative Research in Tropical Medicine (GH), Ghana Health Service (GH)
Openalex Percentile: Top 60%
Malaria Research and Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.