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Updated: Aug 29, 2026
Simultaneous Distinction of Monospecific and Mixed DFS70 Patterns During ANA Screening with a Novel HEp-2 ELITE/DFS70 Knockout Substrate
Published on: January 17, 2018
Development and temporal validation of AI-enhanced HEp-2 indirect immunofluorescence image analysis for specific
Patrick Vanderboom1, Surendra Dasari2, Marlon J Sandino-Bermúdez3
1Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Objective:
ANA indirect immunofluorescence (IIF) is the reference standard but depends on subjective pattern interpretation. We tested whether artificial intelligence (AI) applied to ANA IIF images could identify specific autoantibodies.
Methods:
We assembled a cohort of ANA-positive patients (HEp-2 IIF titer ≥1:80) with anti-dsDNA, Sm, RNP, SSA, SSB, Scl-70, or centromere antibody (CMA) testing within 90 days. The development cohort (Dec 12, 2016-Dec 31, 2022) included the first ANA test per patient. Two AI architectures were trained for each autoantibody. Performance was assessed using area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and accuracy; comparisons with IIF patterns were summarized as pattern-antibody agreement. A prospective cohort (Jan 1, 2023-Aug 20, 2024), including a dsDNA assay transition, provided temporal validation.
Results:
Among 512,959 patients, 47,890 met inclusion criteria (mean age 55 [SD 17.6], 78% female). Models for CMA, dsDNA, Sm, SSA, and SSB achieved AUROC ≥0.80 (CMA highest: AUROC 0.95, accuracy 94.2%, specificity 95.3%). Compared with associated IIF patterns, dsDNA and Sm models more often classified antibody-negative cases as negative (dsDNA 88.2% vs 54.7%; Sm 82.6% vs 60.3%), while similarly classifying antibody-positive cases. Performance for RNP (AUROC 0.68) and Scl-70 (AUROC 0.59) was lower. In the prospective cohort (n=21,427), performance was similar; dsDNA discrimination remained stable across assays (AUROC ~0.85).
Conclusions:
AI applied to ANA IIF images identified specific autoantibodies and often improved classification of antibody-negative cases versus simplified pattern-based comparators. These findings support its potential to standardize ANA interpretation and triage or reduce confirmatory testing.
