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Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.

ABSTRACT: Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image) with a total accuracy of about 94.62%.

SUBMITTER: Li J

PROVIDER: S-EPMC4256175 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.

Li Jiaqian J Tseng Kuo-Kun KK Hsieh Zu Yi ZY Yang Ching Wen CW Huang Huang-Nan HN

PloS one 20141204 12

Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and ...[more]

PMID: 25474260

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Project description:BackgroundTo evaluate the interpretation and reporting of antinuclear antibodies (ANA) by indirect immunofluorescence assay (IFA) using HEp-2 substrates based on common practice and guidance by the International Consensus on ANA patterns (ICAP).MethodParticipants included two groups [16 clinical laboratories (CL) and 8 in vitro diagnostic manufacturers (IVD)] recruited via an email sent to the Association of Medical Laboratory Immunologists (AMLI) membership. Twelve (n = 12) pre-qualified specimens were distributed to participants for testing, interpretation and reporting HEp-2 IFA. Results obtained were analyzed for accuracy with the intended and consensus response for three main categorical patterns (nuclear, cytoplasmic and mitotic), common patterns and ICAP report nomenclatures. The distributions of antibody titers of specimens were also compared.ResultsLaboratories differed in the categorical patterns reported; 8 reporting all patterns, 3 reporting only nuclear patterns and 5 reporting nuclear patterns with various combinations of other patterns. For all participants, accuracy with the intended response for the categorical nuclear pattern was excellent at 99% [95% confidence interval (CI): 97-100%] compared to 78% [95% CI 67-88%] for the cytoplasmic, and 93% [95% CI 86%-100%] for mitotic patterns. The accuracy was 13% greater for the common nomenclature [87%, 95% CI 82-90%] compared to the ICAP nomenclature [74%, 95% CI 68-79%] for all participants. Participants reporting all three main categories demonstrated better performances compared to those reporting 2 or less categorical patterns. The average accuracies varied between participant groups, however, with the lowest and most variable performances for cytoplasmic pattern specimens. The reported titers for all specimens varied, with the least variability for nuclear patterns and most titer variability associated with cytoplasmic patterns.ConclusionsOur study demonstrated significant accuracy for all participants in identifying the categorical nuclear staining as well as traditional pattern assignments for nuclear patterns. However, there was less consistency in reporting cytoplasmic and mitotic patterns, with implications for assigning competencies and training for clinical laboratory personnel.

Project description:Indirect immunofluorescence assay (IFA) using HEp-2 cells as a substrate is the gold standard for detecting antinuclear antibodies (ANA) in patient serum. However, the ANA IFA has labor-intensive nature of the procedure and lacks adequate standardization. To overcome these drawbacks, the automation has been developed and implemented to the clinical laboratory. The purposes of this study were to evaluate the analytical performance of a fully automated Helios ANA IFA analyzer in a real-life laboratory setting, and to compare the time and the cost of ANA IFA testing before and after adopting the Helios system. A total of 3,276 consecutive serum samples were analyzed for ANA using the Helios system from May to August 2019. The positive/negative results, staining patterns, and endpoint titers were compared between Helios and visual readings. Furthermore, the turnaround time and the number of wells used were compared before and after the introduction of Helios system. Of the 3,276 samples tested, 748 were positive and 2,528 were negative based on visual readings. Using visual reading as the reference standard, the overall relative sensitivity, relative specificity, and concordance of Helios reading were 73.3, 99.4, and 93.4% (κ = 0.80), respectively. For pattern recognition, the overall agreement was 70.1% (298/425) for single patterns, and 72.4% (89/123) for mixed patterns. For titration, there was an agreement of 75.9% (211/278) between automated and classical endpoint titers by regarding within ± one titer difference as acceptable. Helios significantly shortened the median turnaround time from 100.6 to 55.7 h (P < 0.0001). Furthermore, routine use of the system reduced the average number of wells used per test from 4 to 1.5. Helios shows good agreement in distinguishing between positive and negative results. However, it still has limitations in positive/negative discrimination, pattern recognition, and endpoint titer prediction, requiring additional validation of results by human observers. Helios provides significant advantages in routine laboratory ANA IFA work in terms of labor, time, and cost savings. We hope that upgrading and developing softwares with more reliable capabilities will allow automated ANA IFA analyzers to be fully integrated into the routine operations of the clinical laboratory.

Dataset Information

Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.

Publications

Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.

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