Automated antinuclear immunofluorescence antibody analysis is a reliable approach in routine clinical laboratories

Abstract

Background: Indirect immunofluorescence (IIF) assays are recommended as the gold standard method for the detection of antinuclear antibodies (ANAs). This study aimed to investigate the reliability of an automated system. Methods: We compared 3745 serum samples using NOVA View archived images with manual analysis via microscopy. A custom cutoff value was established to distinguish ANA titers and was validated in two clinical laboratories. The automatic ANA pattern recognition system was evaluated, and all ANA-positive sera were subjected to two commercial ANA IIF kits to compare the consistency of the pattern interpretation results. For inconsistent patterns, a third ANA IIF testing kit was utilized. Results: Agreement of the interpretation of the ANA IIF test using the platform of NOVA View and manual microscopy was 96.9%. The local cutoff value to discriminate ANA titers in four main ANA patterns was calculated based on 1390 serum samples. In our laboratory, the titer prediction accuracy was superior to the preset cutoff in NOVA View (p < 0.01); the performance was similar in another laboratory (p = 0.11). The automatic pattern recognition accuracies of speckled, homogeneous, centromere, nucleolar and nuclear dot patterns were 62.7%, 57.4%, 92.6%, 30.5% and 27.3%, respectively. The consistency of the pattern interpretation results between INOVA and MBL kits was 95.3%. Conclusions: It is necessary to establish a custom valueadded ANA report. However, confirmation of the digital immunofluorescence images by expert technicians was essential, and suspect results of an ANA pattern should be reconfirmed by another commercial ANA IIF kit to achieve more reliable results.

Recent Approaches To Optimize Laboratory Assessment of Antinuclear Antibodies

“…Although the overall performance for positive or negative results was acceptable, the accuracy of pattern recognition, restricted to the most common patterns reported (homogeneous, speckled, nucleolar, centromere, multiple nuclear dots, and cytoplasmic patterns), was limited, ranging from 52% to 79%, with significant challenges in interpreting samples with more than one pattern (mixed patterns). Those findings appear to be consistent with others that report misinterpretation difficulties for the common and mixed patterns, in addition to false-negative results for cytoplasmic, nuclear dots, and nuclear membrane patterns (50)(51)(52)(53)(54)(55)(56)(57)(58). For the available ANA IFA automated readers, the final result is provided by the operator.…”

“…Automation of both ends of ANA testing (front-end processing and digital reading) significantly minimizes the manual and analytical challenges of ANA IFA testing. There are a number of commercially available systems for automated reading of ANA IFA results (Table 2) based on the principles outlined above, with some variations (13,(49)(50)(51)(52)(53)(54)(55)(56)(57)(58). These systems differ from each other with respect to the use of DNA-binding counterstains (4=,6-diamidino-2-phenylindole [DAPI], propidium iodide, or none), the cell substrate used (HEp-2 versus HEp-2000, with restriction to the manufacturer's slides), throughput (samples per hour), the number of patterns that can be identified, titer prediction, front-end automation (slide processors), and other software features (49,50).…”

Performance analysis of automated evaluation of antinuclear antibody indirect immunofluorescent tests in a routine setting

“…Several studies on automatic ANA pattern recognition have already been published [ 8 , 9 , 29 – 31 ]. Some of these studies, however, compared two different assays using different substrates and different screening dilutions, making it difficult to evaluate the automatically generated ANA results [ 29 , 32 ].…”

Variation in antinuclear antibody detection: need for clear expectations and additional studies

“…Unfortunately, only two sites were compared and limited data were presented in the paper. Consequently, little conclusion can be drawn from this study 4. Lastly, ANA testing is also part of quality and proficiency programmes such as CAP and UK NEQAS, which also show variability.…”