Literature DB >> 27037849

The clinical diagnostic value of target biopsy using narrow-band imaging endoscopy and accurate laryngeal carcinoma pathologic specimen acquisition.

Y Yang1, J Liu1, F Song1, S Zhang2.   

Abstract

OBJECTIVE: To estimate the clinical significance of target biopsy for clinical diagnosis and determine accurate laryngeal lesion pathologic specimen acquisition via narrow-band imaging (NBI) endoscopy.
METHODS: A total of 138 samples from patients with laryngeal lesions (carcinoma, 118; hyperplasia, 3; mild dysplasia, 2; moderate dysplasia, 5; severe dysplasia, 5; vocal cord polyp, 1; and inflammatory lesion, 4) were collected from the Department of Otolaryngology Head and Neck Surgery of Tianjin Union Medical Center from 1 January 2013 to 1 February 2015. All patients were divided into the regular biopsy and NBI target biopsy groups; the imaging data were recorded and patient samples were biopsied. Pathologic diagnoses were used to evaluate the accuracies of regular and target biopsy.
RESULTS: Based on the pathologic diagnosis, NBI target pathology yielded an accurate laryngeal lesion pathologic specimen acquisition rate of 95.6% (65/68), significantly higher than that yielded by regular biopsy (75.7%, 53/70; χ2 = 10.99, P = 0.001). In the NBI target pathology group, the correct accurate pathologic specimen acquisition rates at laryngeal cancer diagnostic stages 0 (Tis), I and II were 100%, 100% and 85.71%, respectively, which were higher than the corresponding rates in the regular biopsy group (0%, χ2 = 10.000, P = 0.002; 25%, χ2 = 5.625, P = 0.018; and 38.46%, χ2 = 6.454, P = 0.011, respectively).
CONCLUSIONS: In cases of laryngeal carcinoma, NBI endoscopy plays an important role in clinical diagnosis and accurate pathologic specimen acquisition and could be a regular clinical method for laryngeal lesion detection.
© 2016 John Wiley & Sons Ltd.

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Year:  2016        PMID: 27037849     DOI: 10.1111/coa.12654

Source DB:  PubMed          Journal:  Clin Otolaryngol        ISSN: 1749-4478            Impact factor:   2.597


  2 in total

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2.  Computer-aided diagnosis of laryngeal cancer via deep learning based on laryngoscopic images.

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  2 in total

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