Performance Assessment of the Concepta Automated ANA Detection System in Routine Clinical Samples

Aim: Indirect immunofluorescence (IIF) on HEp-2 cells is the standard method for detecting anti-nuclear antibodies (ANA) due to its high sensitivity. Recently, several artificial intelligence-supported automated immunofluorescence systems have been developed to improve standardization and efficiency in ANA detection using the IIF method. This study aimed to evaluate the performance of the Concepta automated immunofluorescence system in routine clinical settings for ANA testing using the IIF method. Material and Methods: A total of 1000 patient serum samples were analyzed using the Concepta automated system after preparation with the iPRO processor. The results were compared to manual evaluations conducted by two expert clinicians to assess the system's agreement, sensitivity, specificity, and accuracy in pattern recognition. Results: The Concepta system demonstrated an overall agreement of 98.11% with manual evaluations for positive and negative discrimination, corresponding to a κ value of 0.958. The sensitivity and specificity were found to be 99.08% and 97.61%, respectively, with positive and negative predictive values of 87.96% and 99.83%. High concordance rates were observed for homogeneous (95.7%), centromere (92.3%), and nucleolar (92.1%) patterns, while lower rates were noted for speckled (60%) and cytoplasmic (44.4%) patterns. Conclusion: The Concepta automated system demonstrated very high accuracy in ANA positive and negative discrimination, comparable to other automated systems. Despite some limitations in recognizing dense fine speckled and mixed patterns, it proved particularly effective in distinguishing between positive and negative results. These findings suggest that the Concepta system is a promising new alternative in the field of ANA testing.