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Randomized Controlled Trial
. 2022 Jul:135:102212.
doi: 10.1016/j.tube.2022.102212. Epub 2022 May 18.

Novel TB smear microscopy automation system in detecting acid-fast bacilli for tuberculosis - A multi-center double blind study

Hsiao-Chuan Huang  1 , King-Lung Kuo  2 , Mei-Hsin Lo  1 , Hsiao-Yun Chou  1 , Yusen E Lin  3
Affiliations
Randomized Controlled Trial

Novel TB smear microscopy automation system in detecting acid-fast bacilli for tuberculosis - A multi-center double blind study

Hsiao-Chuan Huang et al. Tuberculosis (Edinb). 2022 Jul.

Abstract

Due to COVID-19 pandemic, there is a large global drop in the number of newly diagnosed cases with tuberculosis (TB) worldwide. Actions to mitigate and reverse the impact of the COVID-19 pandemic on TB are urgently needed. Recent development of TB smear microscopy automation systems using artificial intelligence may increase the sensitivity of TB smear microscopy. The objective is to evaluate the performance of an automation system (μ-Scan 2.0, Wellgen Medical) over manual smear microscopy in a multi-center, double-blind trial. Total of 1726 smears were enrolled. Referee medical technician and culture served as primary and secondary gold standards for result discrepancy. Results showed that, compared to manual microscopy, the μ-Scan 2.0's performance of accuracy, sensitivity and specificity were 95.7% (1651/1726), 87.7% (57/65), and 96.0% (1594/1661), respectively. The negative predictive value was 97.8% at prevalence of 8.2%. Manual smear microscopy remains the primary diagnosis of pulmonary tuberculosis (TB). Use of automation system could achieve higher TB smear sensitivity and laboratory efficiency. It can also serve as a screening tool that complements molecular methods to reduce the total cost for TB diagnosis and control. Furthermore, such automation system is capable of remote access by internet connection and can be deployed in area with limited medical resources.

Keywords: Artificial intelligence; Automated microscope; TB Smears.

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Conflict of interest statement

This study was financially sponsored by Department of Health, Taipei City Government. The authors rented and used μ-Scan 2.0 smear microscopy automation system (Wellgen Medical, Kaohsiung) for the study.

Figures

Fig. 1
Fig. 1
Study flow for comparison of performance between manual smear microscopy and automation system.
Fig. 2
Fig. 2
The automated microscope system in operation.
Figs. 3–1
Figs. 3–1
Examples of Tagged AFBs by the AI software.
Figs. 3–2
Figs. 3–2
Examples of Tagged AFBs by the AI software.
See this image and copyright information in PMC

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