Literature DB >> 36121216

Evaluation of MetaSystems Automated Fluorescent Microscopy System for the Machine-Assisted Detection of Acid-Fast Bacilli in Clinical Samples.

Gianna Tomasello1, Farnaz Foroughi1, Danielle Padron1, Angel Moreno2, Niaz Banaei1,2,3.   

Abstract

Manual reading of fluorescent acid-fast bacilli (AFB) microscopy slides is time-intensive and technically demanding. The aim of this study was to evaluate the accuracy of MetaSystems' automated fluorescent AFB slide scanner and analyzer. Auramine O-stained slides corresponding to 133 culture-positive and 363 culture-negative respiratory (n = 284), tissue (n = 120), body fluid (n = 81), and other (n = 11) sources were evaluated with the MetaSystems Mycobacteria Scanner running the NEON Metafer AFB Module. The sensitivity and specificity of the MetaSystems platform was measured as a standalone diagnostic and as an assistant to technologists to review positive images. Culture results were used as the reference method. The MetaSystems platform failed to scan 57 (11.5%) slides. The MetaSystems platform used as a standalone had a sensitivity of 97.0% (129/133; 95% CI 92.5 to 99.2) and specificity of 12.7% (46/363; 95% CI 9.4 to 16.5). When positive scans were used to assist technologists, the MetaSystems platform had a sensitivity of 70.7% (94/133; 95% CI 62.2 to 78.3) and specificity of 89.0% (323/363; 95% CI 85.3 to 92.0). The manual microscopy method had a sensitivity of 79.7% (106/133; 95% CI 71.9 to 86.2) and specificity of 98.6% (358/363; 95% CI 96.8 to 99.6). The sensitivity of the MetaSystems platform was not impacted by smear grade or mycobacterial species. The majority (70.3%) of false positive smears had ≥2+ smear results with the MetaSystems platform. Further performance improvements are needed before the MetaSystems' automated fluorescent AFB slide reader can be used to assist microscopist in the clinical laboratory.

Entities:  

Keywords:  acid-fast bacilli; automated; digital pathology; microscopy

Mesh:

Substances:

Year:  2022        PMID: 36121216      PMCID: PMC9580351          DOI: 10.1128/jcm.01131-22

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   11.677


  11 in total

Review 1.  Diagnostic Standards and Classification of Tuberculosis in Adults and Children. This official statement of the American Thoracic Society and the Centers for Disease Control and Prevention was adopted by the ATS Board of Directors, July 1999. This statement was endorsed by the Council of the Infectious Disease Society of America, September 1999.

Authors: 
Journal:  Am J Respir Crit Care Med       Date:  2000-04       Impact factor: 21.405

2.  The automated clinical microbiology laboratory: fact or fantasy?

Authors:  Nathan A Ledeboer; Steven D Dallas
Journal:  J Clin Microbiol       Date:  2014-03-19       Impact factor: 5.948

3.  Automated high-throughput digital fluorescence microscopy for TB diagnosis.

Authors:  D Chesov; V Lesanu; N Ciobanu; A Codreanu; V Crudu; L E Cuevas; D Kiss; N Czoboly; A Somoskovi
Journal:  Int J Tuberc Lung Dis       Date:  2020-10-01       Impact factor: 2.373

4.  Machine-assisted interpretation of auramine stains substantially increases through-put and sensitivity of microscopic tuberculosis diagnosis.

Authors:  L Horvath; S Hänselmann; H Mannsperger; S Degenhardt; K Last; S Zimmermann; I Burckhardt
Journal:  Tuberculosis (Edinb)       Date:  2020-09-19       Impact factor: 3.131

Review 5.  Image analysis and artificial intelligence in infectious disease diagnostics.

Authors:  K P Smith; J E Kirby
Journal:  Clin Microbiol Infect       Date:  2020-03-22       Impact factor: 8.067

6.  Performance of a Novel Algorithm Using Automated Digital Microscopy for Diagnosing Tuberculosis.

Authors:  Nazir A Ismail; Shaheed V Omar; James J Lewis; David W Dowdy; Andries W Dreyer; Hermina van der Meulen; George Nconjana; David A Clark; Gavin J Churchyard
Journal:  Am J Respir Crit Care Med       Date:  2015-06-15       Impact factor: 21.405

7.  Low cost automated whole smear microscopy screening system for detection of acid fast bacilli.

Authors:  Yan Nei Law; Hanbin Jian; Norman W S Lo; Margaret Ip; Mia Mei Yuk Chan; Kai Man Kam; Xiaohua Wu
Journal:  PLoS One       Date:  2018-01-22       Impact factor: 3.240

8.  Feasibility of the TBDx automated digital microscopy system for the diagnosis of pulmonary tuberculosis.

Authors:  Pamela Nabeta; Joshua Havumaki; Dang Thi Minh Ha; Tatiana Caceres; Pham Thu Hang; Jimena Collantes; Nguyen Thi Ngoc Lan; Eduardo Gotuzzo; Claudia M Denkinger
Journal:  PLoS One       Date:  2017-03-02       Impact factor: 3.240

9.  Automatic microscopic detection of mycobacteria in sputum: a proof-of-concept.

Authors:  D Zingue; P Weber; F Soltani; D Raoult; M Drancourt
Journal:  Sci Rep       Date:  2018-07-27       Impact factor: 4.379

Review 10.  Developing image analysis methods for digital pathology.

Authors:  Peter Bankhead
Journal:  J Pathol       Date:  2022-05-23       Impact factor: 9.883

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