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首页> 美国卫生研究院文献>other >Prospective Evaluation of Multi-modal Optical Imaging with Automated Image Analysis to Detect Oral Neoplasia In Vivo
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Prospective Evaluation of Multi-modal Optical Imaging with Automated Image Analysis to Detect Oral Neoplasia In Vivo

机译：具有自动图像分析功能的多模态光学成像在体内检测口腔肿瘤的前瞻性评估

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The five-year survival rate for patients with oral cancer remains low, in part because diagnosis often occurs at a late stage. Early and accurate identification of oral high-grade dysplasia and cancer can help improve patient outcomes. Multi-modal optical imaging is an adjunctive diagnostic technique in which autofluorescence imaging is used to identify high-risk regions within the oral cavity, followed by high resolution microendoscopy to confirm or rule out the presence of neoplasia. Multi-modal optical images were obtained from 206 sites in 100 patients. Histologic diagnosis, either from a punch biopsy or an excised surgical specimen, was used as the gold standard for all sites. Histopathologic diagnoses of moderate dysplasia or worse were considered neoplastic. Images from 92 sites in the first 30 patients were used as a training set to develop automated image analysis methods for identification of neoplasia. Diagnostic performance was evaluated prospectively using images from 114 sites in the remaining 70 patients as a test set. In the training set, multi-modal optical imaging with automated image analysis correctly classified 95% of non-neoplastic sites and 94% of neoplastic sites. Among the 56 sites in the test set that were biopsied, multi-modal optical imaging correctly classified 100% of non-neoplastic sites and 85% of neoplastic sites. Among the 58 sites in the test set that corresponded to a surgical specimen, multi-modal imaging correctly classified 100% of non-neoplastic sites and 61% of neoplastic sites. These findings support the potential of multi-modal optical imaging to aid in the early detection of oral cancer.
机译：口腔癌患者的五年生存率仍然很低，部分原因是诊断通常发生在晚期。尽早而准确地识别口腔严重增生和癌症可以帮助改善患者预后。多模态光学成像是一种辅助诊断技术，其中自体荧光成像用于识别口腔内的高危区域，然后进行高分辨率显微内窥镜检查以确认或排除肿瘤的形成。从100位患者的206个部位获得了多模态光学图像。组织学诊断，无论是打孔活检还是切除的手术标本，都被用作所有部位的黄金标准。中度不典型增生或更严重的组织病理学诊断被认为是肿瘤。前30名患者中92个部位的图像用作训练集，以开发用于鉴定赘生物的自动化图像分析方法。使用剩余70名患者中114个部位的图像作为测试集，对诊断性能进行了前瞻性评估。在训练集中，具有自动图像分析功能的多模式光学成像正确地将95％的非肿瘤部位和94％的肿瘤部位分类。在活检的56个部位中，多模态光学成像正确地将100％的非肿瘤部位和85％的肿瘤部位正确分类。在对应于外科标本的测试集中的58个部位中，多模式成像正确地将100％的非肿瘤部位和61％的肿瘤部位正确分类。这些发现支持了多模态光学成像技术在口腔癌早期发现方面的潜力。

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