Objective detection and delineation of oral neoplasia using autofluorescence imaging.
Objective detection and delineation of oral neoplasia using autofluorescence imaging.
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DOI：
10.1158/1940-6207.capr-08-0229
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发表时间：
2009-05
期刊：
影响因子：
--
通讯作者：
Richards-Kortum R
中科院分区：
文献类型：
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作者：
Roblyer D;Kurachi C;Stepanek V;Williams MD;El-Naggar AK;Lee JJ;Gillenwater AM;Richards-Kortum R
虽然口腔很容易检查，但口腔癌患者往往出现在晚期，导致高发病率和死亡率。自体荧光成像已经成为一种很有前途的技术，可以帮助临床医生筛查口腔肿瘤并辅助切除，但目前的方法依赖于主观解释。我们提出了一种利用自体荧光显像客观描绘口腔肿瘤粘膜的新方法。对56例口腔病变患者和11例正常志愿者进行了自体荧光成像。从这些图像中，确定了159个独特感兴趣区域（ROI）对应的正常和确诊肿瘤区域的276个测量值。利用前46名受试者的roi数据，开发了一种基于红绿荧光比例的简单分类算法；然后使用最后21个受试者的roi数据验证该算法的性能。将该算法应用于患者图像，在整个视场中创建视觉疾病概率图。切除组织的组织学切片用于验证疾病概率图。在405 nm激发下，肿瘤区与非肿瘤区区分效果最好；正常组织与非典型增生和浸润性癌的区分在训练集中灵敏度为95.9%，特异性为96.2%，在验证集中灵敏度为100%，特异性为91.4%。疾病概率图在质量上与临床印象和组织学一致。自体荧光成像结合客观图像分析为口腔肿瘤的检测提供了一种灵敏、无创的工具。
Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects was used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease-probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease-probability maps. The best discrimination between neoplastic and non-neoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and non-invasive tool for the detection oral neoplasia.