Dataset Information

Evaluation of a Fully Automated Antinuclear Antibody Indirect Immunofluorescence Assay in Routine Use.

ABSTRACT: 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% (? = 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.

SUBMITTER: Choi HW

PROVIDER: S-EPMC7746920 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Evaluation of a Fully Automated Antinuclear Antibody Indirect Immunofluorescence Assay in Routine Use.

Choi Hyun-Woo HW Kwon Yong Jun YJ Park Ju-Heon JH Lee Seung-Yeob SY Chun Sejong S Won Eun Jeong EJ Lee Jun Hyung JH Choi Hyun-Jung HJ Kim Soo Hyun SH Shin Myung-Geun MG Shin Jong-Hee JH Kee Seung-Jung SJ

Frontiers in immunology 20201204

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 labora ...[more]

PMID: 33343581

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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:BackgroundManual interpretation of echocardiographic data is time-consuming and operator-dependent. With the advent of artificial intelligence (AI), there is a growing interest in its potential to streamline echocardiographic interpretation and reduce variability. This study aimed to compare the time taken for measurements by AI to that by human experts after converting the acquired dynamic images into DICOM data.MethodsTwenty-three consecutive patients were examined by a single operator, with varying image quality and different medical conditions. Echocardiographic parameters were independently evaluated by human expert using the manual method and the fully automated US2.ai software. The automated processes facilitated by the US2.ai software encompass real-time processing of 2D and Doppler data, measurement of clinically important variables (such as LV function and geometry), automated parameter assessment, and report generation with findings and comments aligned with guidelines. We assessed the duration required for echocardiographic measurements and report creation.ResultsThe AI significantly reduced the measurement time compared to the manual method (159 ± 66 vs. 325 ± 94 s, p < 0.01). In the report creation step, AI was also significantly faster compared to the manual method (71 ± 39 vs. 429 ± 128 s, p < 0.01). The incorporation of AI into echocardiographic analysis led to a 70% reduction in measurement and report creation time compared to manual methods. In cases with fair or poor image quality, AI required more corrections and extended measurement time than in cases of good image quality. Report creation time was longer in cases with increased report complexity due to human confirmation of AI-generated findings.ConclusionsThis fully automated software has the potential to serve as an efficient tool for echocardiographic analysis, offering results that enhance clinical workflow by providing rapid, zero-click reports, thereby adding significant value.

Dataset Information

Evaluation of a Fully Automated Antinuclear Antibody Indirect Immunofluorescence Assay in Routine Use.

Publications

Evaluation of a Fully Automated Antinuclear Antibody Indirect Immunofluorescence Assay in Routine Use.

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