2021
DOI: 10.1016/j.tube.2020.102025
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Detection of mycobacteria in paraffin-embedded Ziehl–Neelsen-Stained tissues using digital pathology

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Cited by 4 publications
(2 citation statements)
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“…It should be noted that most of our cases (75%) were positive, which is higher than the findings of previous reports, but this is related to the fact that Ziehl–Neelsen positivity was one of the inclusion criteria of our study. The sensitivity of Ziehl–Neelsen staining for the detection of MT in histological specimens is variable, ranging from 0 to 60% [ 2 , 7 , 32 , 33 ]. The difficulty to detect mycobacterium can be explained by its paucibacillary nature [ 5 ], the CDC points out that “there must be between 5000–10000 bacilli per milliliter of specimen to allow the detection of bacteria in stained smears” [ 34 ], and for each slide at least 10 [ 4 ] bacilli [ 7 , 30 ].…”
Section: Discussionmentioning
confidence: 99%
“…It should be noted that most of our cases (75%) were positive, which is higher than the findings of previous reports, but this is related to the fact that Ziehl–Neelsen positivity was one of the inclusion criteria of our study. The sensitivity of Ziehl–Neelsen staining for the detection of MT in histological specimens is variable, ranging from 0 to 60% [ 2 , 7 , 32 , 33 ]. The difficulty to detect mycobacterium can be explained by its paucibacillary nature [ 5 ], the CDC points out that “there must be between 5000–10000 bacilli per milliliter of specimen to allow the detection of bacteria in stained smears” [ 34 ], and for each slide at least 10 [ 4 ] bacilli [ 7 , 30 ].…”
Section: Discussionmentioning
confidence: 99%
“…The specific fluorescent antibody labeling with laser confocal microscopy has been developed to improve the efficiency of M. tuberculosis detection in lung tissue samples, especially when these bacteria have weak ZN staining ( Erokhina et al, 2019 ). The Pat-Scan program constructed using digital pathology has been developed to detect and quantify the bacteria in the paraffin-embedded ZN-stained tissue, thus being helpful in reducing the diagnostic time ( Sua et al, 2021 ). It is worth noting that SSM can neither distinguish dead and live bacteria, nor distinguish M. tuberculosis from nontuberculosis mycobacteria.…”
Section: Improvement and Optimization Of Current Diagnostic Techniquesmentioning
confidence: 99%