Novel quantitative analysis of autofluorescence images for oral cancer screening
Novel quantitative analysis of autofluorescence images for oral cancer screening
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DOI：
10.1016/j.oraloncology.2017.03.003
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发表时间：
2017-05-01
期刊：
影响因子：
4.8
通讯作者：
Chung, Pau-Choo
中科院分区：
文献类型：
--
作者：
Huang, Tze-Ta;Huang, Jehn-Shyun;Chung, Pau-Choo
目的：开发 VELscope (R) 用于检查口腔粘膜自发荧光。然而，其准确性在很大程度上取决于检查医生的经验。本研究旨在开发一种用于口腔癌筛查的新型自发荧光图像定量分析。材料和方法：患有口腔癌或癌前病变的患者以及具有正常口腔粘膜的对照组参加了本研究。使用数码相机拍摄病变的白光图像和 VELscope (R) 自发荧光图像。选择图像中的病变作为感兴趣区域（ROI）。计算 ROI 的平均强度和异质性。利用二次判别分析 (QDA) 来计算基于敏感性和特异性的边界。结果：分析了 47 个口腔癌病变、54 个癌前病变和 39 个正常口腔粘膜对照。口腔癌病变与正常口腔粘膜之间的特异性边界为 0.923，敏感性边界为 0.979。口腔癌及癌前病变也可与正常口腔粘膜区分开来，特异性为0.923，敏感性为0.970。结论：本研究中使用的VELscope（R）自发荧光图像强度和异质性的新颖定量分析与QDA分类器相结合，可用于区分口腔癌及癌前病变与正常口腔粘膜。 (C) 2017 Elsevier Ltd. 保留所有权利。
Objectives: VELscope (R) was developed to inspect oral mucosa autofluorescence. However, its accuracy is heavily dependent on the examining physician's experience. This study was aimed toward the development of a novel quantitative analysis of autofluorescence images for oral cancer screening.Materials and methods: Patients with either oral cancer or precancerous lesions and a control group with normal oral mucosa were enrolled in this study. White light images and VELscope (R) autofluorescence images of the lesions were taken with a digital camera. The lesion in the image was chosen as the region of interest (ROI). The average intensity and heterogeneity of the ROI were calculated. A quadratic discriminant analysis (QDA) was utilized to compute boundaries based on sensitivity and specificity.Results: 47 oral cancer lesions, 54 precancerous lesions, and 39 normal oral mucosae controls were analyzed. A boundary of specificity of 0.923 and a sensitivity of 0.979 between the oral cancer lesions and normal oral mucosae were validated. The oral cancer and precancerous lesions could also be differentiated from normal oral mucosae with a specificity of 0.923 and a sensitivity of 0.970.Conclusion: The novel quantitative analysis of the intensity and heterogeneity of VELscope (R) autofluorescence images used in this study in combination with a QDA classifier can be used to differentiate oral cancer and precancerous lesions from normal oral mucosae. (C) 2017 Elsevier Ltd. All rights reserved.