Validation of artificial intelligence-based digital microscopy for automated detection of Schistosoma haematobium eggs in urine in Gabon
PLoS neglected tropical diseases, vol. 18, pp. e0011967
Abstract
INTRODUCTION: Schistosomiasis is a significant public health concern, especially in Sub-Saharan Africa. Conventional microscopy is the standard diagnostic method in resource-limited settings, but with limitations, such as the need for expert microscopists. An automated digital microscope with artificial intelligence (Schistoscope), offers a potential solution. This field study aimed to validate the diagnostic performance of the Schistoscope for detecting and quantifying Schistosoma haematobium eggs in urine compared to conventional microscopy and to a composite reference standard (CRS) consisting of real-time PCR and the up-converting particle (UCP) lateral flow (LF) test for the detection of schistosome circulating anodic antigen (CAA). METHODS: Based on a non-inferiority concept, the Schistoscope was evaluated in two parts: study A, consisting of 339 freshly collected urine samples and study B, consisting of 798 fresh urine samples that were also banked as slides for analysis with the Schistoscope. In both studies, the Schistoscope, conventional microscopy, real-time PCR and UCP-LF CAA were performed and samples with all the diagnostic test results were included in the analysis. All diagnostic procedures were performed in a laboratory located in a rural area of Gabon, endemic for S. haematobium. RESULTS: In study A and B, the Schistoscope demonstrated a sensitivity of 83.1% and 96.3% compared to conventional microscopy, and 62.9% and 78.0% compared to the CRS. The sensitivity of conventional microscopy in study A and B compared to the CRS was 61.9% and 75.2%, respectively, comparable to the Schistoscope. The specificity of the Schistoscope in study A (78.8%) was significantly lower than that of conventional microscopy (96.4%) based on the CRS but comparable in study B (90.9% and 98.0%, respectively). CONCLUSION: Overall, the performance of the Schistoscope was non-inferior to conventional microscopy with a comparable sensitivity, although the specificity varied. The Schistoscope shows promising diagnostic accuracy, particularly for samples with moderate to higher infection intensities as well as for banked sample slides, highlighting the potential for retrospective analysis in resource-limited settings. TRIAL REGISTRATION: NCT04505046 ClinicalTrials.gov.
Authors 14
-
Leiden University · Leiden University Medical Center · Centre de Recherche Médicales de Lambaréné
Affiliation as printed
Centre de Recherches Médicales des Lambaréné, CERMEL, Lambaréné, Gabon
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, The Netherlands
-
Prosper Oyibo corresponding
Delft University of Technology
Affiliation as printed
Mechanical, Maritime and Material Engineering, Delft University of Technology, Delft, The Netherlands
-
Leiden University · Leiden University Medical Center
Affiliation as printed
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, The Netherlands
-
Paul Alvyn Nguema Moure corresponding
Centre de Recherche Médicales de Lambaréné
Affiliation as printed
Centre de Recherches Médicales des Lambaréné, CERMEL, Lambaréné, Gabon
Ecole doctorale régionale d'Afrique centrale en infectiologie tropicale de Franceville, Gabon
-
Moustapha Nzamba Maloum corresponding
Centre de Recherche Médicales de Lambaréné
Affiliation as printed
Centre de Recherches Médicales des Lambaréné, CERMEL, Lambaréné, Gabon
-
Romeo Aime Laclong-Lontchi corresponding
Centre de Recherche Médicales de Lambaréné
Affiliation as printed
Centre de Recherches Médicales des Lambaréné, CERMEL, Lambaréné, Gabon
-
Leiden University · Leiden University Medical Center · Centre de Recherche Médicales de Lambaréné
Affiliation as printed
Centre de Recherches Médicales des Lambaréné, CERMEL, Lambaréné, Gabon
Fondation pour la Recherche Scientifique, Cotonou, Benin
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, The Netherlands
-
Leiden University · Leiden University Medical Center
Affiliation as printed
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, The Netherlands
-
Leiden University · Leiden University Medical Center
Affiliation as printed
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, The Netherlands
-
Leiden University Medical Center
Affiliation as printed
Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands
-
Temitope Agbana corresponding
Delft University of Technology
Affiliation as printed
Mechanical, Maritime and Material Engineering, Delft University of Technology, Delft, The Netherlands
-
Jan Carel Diehl corresponding
Delft University of Technology
Affiliation as printed
Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands
-
Leiden University · Leiden University Medical Center · Centre de Recherche Médicales de Lambaréné · University of Tübingen
Affiliation as printed
Centre de Recherches Médicales des Lambaréné, CERMEL, Lambaréné, Gabon
Ecole doctorale régionale d'Afrique centrale en infectiologie tropicale de Franceville, Gabon
Fondation pour la Recherche Scientifique, Cotonou, Benin
Institut fur Tropenmedizin, Universitat Tubingen, Tubingen, Germany
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, The Netherlands
-
Leiden University · Leiden University Medical Center
Affiliation as printed
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, Leiden, The Netherlands
Cited by 21 stored of 21
No patents citing this paper on Lens.org (checked 2026-10-11).