Enhanced serodiagnosis of opisthorchiasis using a multi-epitope dot-ELISA: comparative evaluation of visual and imageJ-assisted analysis of IgG and IgM responses.

backgroundOpisthorchiasis remains an important public health problem in Southeast Asia and is strongly associated with cholangiocarcinoma. Although stool-based diagnosis is widely used, its sensitivity is limited in light infections, highlighting the need for alternative diagnostic approaches. This study developed and evaluated a dot-enzyme-linked immunosorbent assay (dot-ELISA) based on a multi-epitope recombinant antigen (OvCB_OvAEP_OvCF) for the serological detection of Opisthorchis viverrini, and compared conventional visual interpretation with ImageJ-assisted digital analysis for IgG and IgM antibody detection.

methodsThe assay was optimised using pooled positive and negative sera, and cut-off values for ImageJ-based interpretation were determined by receiver operating characteristic (ROC) analysis. Diagnostic performance was evaluated using 70 serum samples, including sera from patients with confirmed opisthorchiasis, other parasitic infections, and negative controls. Diagnostic performance parameters were calculated. Agreement between methods was assessed using Cohen's kappa, while paired differences were evaluated using McNemar's test and the Wilcoxon signed-rank test. Logistic regression analysis was performed to identify predictors of infection. The stability of antigen-coated nitrocellulose membranes was assessed under different storage conditions.

resultsVisual interpretation of the optimised dot-ELISA yielded high sensitivity for both IgG (93.33%) and IgM (100%) detection, although specificity was limited, particularly because of cross-reactivity with other parasitic infections. ImageJ-assisted analysis improved specificity for IgG (76.36%) and IgM (45.45%) detection and increased diagnostic accuracy for both IgG (74.29%) and IgM (55.71%). ROC analysis showed moderate discriminatory ability for IgM detection (AUC = 0.797, P < 0.001), whereas IgG detection showed limited discrimination (AUC = 0.578, P = 0.458). Agreement analysis showed substantial concordance for IgM detection and moderate agreement for IgG detection. Paired statistical analyses revealed significant differences between visual and ImageJ-based interpretations, indicating that digital quantification altered classification outcomes and improved discrimination between antibody responses. Logistic regression identified IgM detection as the strongest predictor of infection. The recombinant antigen remained stable on nitrocellulose membranes for up to three months for IgG detection and up to two months for IgM detection under all tested storage conditions.

conclusionsThe developed dot-ELISA platform showed promising potential as a serological screening tool for opisthorchiasis, particularly for IgM antibody detection. ImageJ-assisted analysis improved the objectivity, reproducibility and diagnostic discrimination by reducing observer bias. Furthermore, the stability of the antigen-coated membranes supports the feasibility of field-based application. Although specificity requires further improvement, this platform may provide a practical and scalable approach for screening and surveillance of opisthorchiasis in endemic and resource-limited settings.