Wang yeyu1,Chang wei2*, Li jun2Corresponding Author: Chang wei(Email: cw262@163.com)

Corresponding author: chang wei, cw262@163.com

DOI: 10.12201/bmr.202408.00023

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  Abstract: Objective: The purpose is to select the most accurate classification in White Light Imaging (WLI) and Narrow Band Imaging (NBI) for diagnosing the pathological result of vocal cord leukoplakia and the proposed cut-off point,which can improve the accuracy of non-invasive prediction of the pathological result of vocal cord leukoplakia and can provide basis for whether the vocal cord leukoplakia patients need surgery and the timing of surgical intervention.Methods:96 vocal cord leukoplakia(VCL) patients(122 lesions) were included in the study from October 2021 to December 2022. Before surgery, images were collected in WLI and NBI respectively.According to two classifications (Chen classification in WLI and Ni classification in NBI) ,lesions were evaluated. By comparing Youden’s index,the proposed cut-off point for classification more than two degrees can be assessed.By comparing the area under curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value of four clinical classifications per the purposed cut-off point, the diagnostic performance of different clinical classifications on the pathological results of vocal cord leukoplakia was assessed, the most accurate classification and the purposed cut-off point were obtained. Results: 1、Chen classification in WLI was correlated with pathological tissue results(rs=0.609, P＜0.001).Ni classification in NBI was correlated with pathological tissue results(rs=0.763, P＜0.001).2、In WLI,the purposed cut-off point of Chen classification is 3(flat and smooth type is bengin,elecated and smooth type and rough type are maligant)；in NBI,the purposed cut-off point of Ni classification is 5(I~IV tpye are bengin, V and VI type are maligant).3、The AUC of two clinical classifications’ model(Chen classification in WLI and Ni classification in NBI) were 0.815,0.875.The accuracy,sensitivity,specificity,PPV and NPV of the two clinical classifications (purposed cut-off point) were79.51%,84.62%,75.71%,72.13%,86.89%；85.25%,76.92%,91.42%,86.96%,84.21%.Conclusions: Ni classification in NBI (cut-off point 5) and Chen classification(cut-off point 3) both perform well. The diagnostic performance of Ni classification in NBI (cut-off point 5) in WLI is better than Chen classification(cut-off point 3).

  Key words: Vocal; cord leukoplakia, Narrow; band imaging,White; lighting imaging,diagnosis

  Submit time: 12 August 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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