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Introduction Indirect immunofluorescence (IIF) employing ethanol-fixed neutrophils (ethN) is still the method of choice for assessing antineutrophil cytoplasmic antibodies (ANCA) in ANCA-associated vasculitides (AAV). However, conventional fluorescence microscopy is subjective and prone to high variability. The objective of this study was to evaluate novel pattern recognition algorithms for the standardized automated interpretation of ANCA patterns. Methods Seventy ANCA-positive samples (20 antimyeloperoxidase ANCA, 50 antiproteinase3 ANCA) and 100 controls from healthy individuals analyzed on ethN and formalin-fixed neutrophils (formN) by IIF were used as a 'training set' for the development of pattern recognition algorithms. Sera from 342 patients ('test set') with AAV and other systemic rheumatic and infectious diseases were tested for ANCA patterns using the novel pattern recognition algorithms and conventional fluorescence microscopy. Results Interpretation software employing pattern recognition algorithms was developed enabling positive/negative discrimination and classification of cytoplasmic ANCA (C-ANCA) and perinuclear ANCA (P-ANCA). Comparison of visual reading of the 'test set' samples with automated interpretation revealed Cohen's kappa (κ) values of 0.955 on ethN and 0.929 on formN for positive/negative discrimination. Analysis of the 'test set' with regard to the discrimination between C-ANCA and P-ANCA patterns showed a high agreement for ethN (κ = 0.746) and formN (κ = 0.847). There was no significant difference between visual and automated interpretation regarding positive/negative discrimination on ethN and formN, as well as ANCA pattern recognition (P > 0.05, respectively). Conclusions Pattern recognition algorithms can assist in the automated interpretation of ANCA IIF. Automated reading of ethN and formN IIF patterns demonstrated high consistency with visual ANCA assessment.

Introduction Diagnosis of antiphospholipid syndrome (APS) still remains a laboratory challenge due to the great diversity of antiphospholipid antibodies (aPL) and their significance regarding APS-diagnostic criteria. Methods A multi-line dot assay (MLDA) employing phosphatidylserine (PS), phosphatidylinositol (PI), cardiolipin (CL), and beta2-glycoprotein I (β2 GPI) was used to detect aPL, immunoglobulin G (IgG) and immunoglobulin M (IgM) in 85 APS patients, 65 disease controls, and 79 blood donors. For comparison, anti-CL and anti-β2 GPI IgG and IgM were detected by enzyme-linked immunosorbent assay (ELISA). Results The level of agreement of both methods was good for anti-CL IgG, moderate for anti-CL IgM, very good for anti-β2 GPI IgG, and moderate for anti-β2 GPI IgM (kappa = 0.641, 0.507, 0.803 and 0.506, respectively). The frequency of observed discrepancies for anti-CL IgG (1.75%), anti-CL IgM (3.93%), anti-β2 GPI IgG (1.75%), and anti-β2 GPI IgM (0.87%) was low (McNemar test, P < 0.05, not-significant, respectively). Sensitivity, specificity, positive (+LR) and negative (-LR) likelihood ratios for at least one positive aPL antibody assessed by ELISA were 58.8%, 95.8%, 14.1, and 0.4, respectively, and for at least three positive aPl IgM and/or one positive aPL IgG by MLDA were 67.1%, 96.5%, 19.3, and 0.3, respectively. The frequency of IgM to PI, PS and CL, and combination of three or more aPL IgM detected by MLDA was significantly higher in APS patients with cerebral transient ischemia (P < 0.05, respectively). Conclusions The novel MLDA is a readily available, single-step, sensitive diagnostic tool for the multiplex detection of aPL antibodies in APS and a potential alternative for single aPL antibody testing by ELISA.