Diagnostic Value of Narrow Band Imaging in Visualization of Pathological Lesions in Larynx and Hypopharynx

Šatanková, Jana; Staníková, Lucia; Švejdová, Anna; Černý, Michal; Laco, Ján; Chrobok, Viktor

doi:10.14712/18059694.2021.4

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…In the early meta-analysis of Zhou et al from 2018 [ 32 ] summarizing eight studies in the field of laryngeal lesions, the sensitivity and specificity in the diagnosis of malignant lesions in NBI was 0.91 (95% CI: 0.885–0.931) and 0.915 (95% CI: 0.893–0.934), respectively. Later studies supported only the evidence with the values of sensitivity and specificity ranging from 0.84 to 0.985 and from 0.889 to, 0.985, respectively [ 33 , 34 , 35 , 36 , 37 ]. It must be emphasized that in that research, the parameters of diagnostic accuracy were obtained based on evaluation by at least two specialists experienced with the method.…”

Section: Discussionmentioning

confidence: 98%

Artificial Intelligence in Laryngeal Endoscopy: Systematic Review and Meta-Analysis

Žůrek

Jasak

Niemczyk

et al. 2022

JCM

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Background: Early diagnosis of laryngeal lesions is necessary to begin treatment of patients as soon as possible to preserve optimal organ functions. Imaging examinations are often aided by artificial intelligence (AI) to improve quality and facilitate appropriate diagnosis. The aim of this study is to investigate diagnostic utility of AI in laryngeal endoscopy. Methods: Five databases were searched for studies implementing artificial intelligence (AI) enhanced models assessing images of laryngeal lesions taken during laryngeal endoscopy. Outcomes were analyzed in terms of accuracy, sensitivity, and specificity. Results: All 11 studies included presented an overall low risk of bias. The overall accuracy of AI models was very high (from 0.806 to 0.997). The accuracy was significantly higher in studies using a larger database. The pooled sensitivity and specificity for identification of healthy laryngeal tissue were 0.91 and 0.97, respectively. The same values for differentiation between benign and malignant lesions were 0.91 and 0.94, respectively. The comparison of the effectiveness of AI models assessing narrow band imaging and white light endoscopy images revealed no statistically significant differences (p = 0.409 and 0.914). Conclusion: In assessing images of laryngeal lesions, AI demonstrates extraordinarily high accuracy, sensitivity, and specificity.

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Section: Discussionmentioning

confidence: 98%

Artificial Intelligence in Laryngeal Endoscopy: Systematic Review and Meta-Analysis

Žůrek

Jasak

Niemczyk

et al. 2022

JCM

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Artificial Intelligence in laryngeal endoscopy: Systematic Review and Meta-Analysis

Žůrek

Rzepakowska

Jasak

et al. 2022

Preprint

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Background: Early and proper diagnosis of laryngeal lesions is necessary to begin treatment of the patient as soon as possible with the possibility of preserve organ functions. Imaging examinations are oft aided by artificial intelligence (AI) to improve quality and facilitate appropriate diagnosis. The aim of the study is to investigate of the diagnostic utility of AI in laryngeal endoscopy. Methods: Five electronic databases (PubMed, Embase, Cochrane, Scopus, Web of Science) were searched for studies published before October 15, 2021 implementing artificial intelligence (AI) enhanced models assessing images of laryngeal lesions taken during laryngeal endoscopy. Outcomes were analyzed in terms of accuracy, sensitivity and specificity. Results: All 13 included studies presented overall low risk of bias. The overall accuracy of AI models was very high (from 0.806 to 0.997) and the number of images used to build and evaluate the models ranged from 120 to 24,667. The accuracy was significantly higher in studies using larger database. The pooled sensitivity and specificity for identification of healthy laryngeal tissue (8 studies) was 0.91 (95% CI: 0.83-0.98) and 0.97 (95% CI: 0.96-0.99), respectively. The same values for differentiation between benign and malignant lesions (7 studies) were 0.91 (95% CI: 0.86-0.96) and 0.95 (95% CI: 0.90-0.99), respectively. The analysis was extended to a comparison of sensitivity and specificity of AI models assessing Narrow Band Imaging (3 studies) and white light endoscopy images (4 studies). The results were similar for both methods, no subgroup effect was revealed (p = 0.406 for sensitivity and p = 0.817 for specificity). Conclusions: In assessing images of laryngeal lesions, AI demonstrates extraordinarily high accuracy, sensitivity, and specificity. AI enhanced diagnostic tools should be introduced into everyday clinical work. The performance of AI diagnoses increases efficacy with the size of the image database when using similar standards for evaluating images. The multicentre cooperation should concentrate on creation of huge database of laryngeal lesions images and implement their sharing, which allows building AI modes with the best performance, based on vast amount of images for learning and testing.

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The importance of preoperative and perioperative Narrow Band Imaging endoscopy in the diagnosis of pre-tumor and tumor lesions of the larynx

Filipovský,

Kalfeřt,

Lukavcová

et al. 2023

J Appl Biomed

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Introduction: Narrow band imaging (NBI) is an endoscopic imaging method intended for the diagnosis of mucosal lesions of the larynx that are not visible in white-light endoscopy, but are typical of pre-tumor and tumor lesions of the larynx. The purpose of the study: To compare preoperative/perioperative white light endoscopy and NBI endoscopy with the results of histopathological examinations in pre-tumor and tumor lesions of the larynx. Methods: A prospective study, over a period of five years (5/2018-5/2023), included 87 patients with laryngeal lesions aged 24-80 years. We evaluated preoperative/ perioperative white light and NBI endoscopy, established a working prehistological diagnosis, and compared this with the definitive histopathological results of laryngeal biopsies. Results: In relation to the definitive histology score, a statistically significant correlation was found between the evaluation of the finding and the definitive histology for preoperative and perioperative white light endoscopy and NBI endoscopy (p < 0.001). Both methods showed higher precision when used perioperatively. Conclusion: NBI endoscopy is an optical method that allows us to improve the diagnosis of laryngeal lesions, perform a controlled perioperative biopsy, and refine the surgical scope. The NBI endoscopy is a suitable method for the diagnosis of early cancerous lesions of the larynx. The use of preoperative/perioperative NBI endoscopy allowed us to achieve a high level of agreement correlation (p < 0.001) between the prehistological working diagnosis and the final histopathological result. The NBI method proves its application in the diagnosis of pre-tumor and tumor lesions of the larynx.

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Diagnostic Value of Narrow Band Imaging in Visualization of Pathological Lesions in Larynx and Hypopharynx

Cited by 4 publications

References 22 publications

Artificial Intelligence in Laryngeal Endoscopy: Systematic Review and Meta-Analysis

Artificial Intelligence in Laryngeal Endoscopy: Systematic Review and Meta-Analysis

Artificial Intelligence in laryngeal endoscopy: Systematic Review and Meta-Analysis

The importance of preoperative and perioperative Narrow Band Imaging endoscopy in the diagnosis of pre-tumor and tumor lesions of the larynx

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