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共焦荧光显微镜实时评估新鲜人乳腺组织肿瘤的可行性。

Feasibility of confocal fluorescence microscopy for real-time evaluation of neoplasia in fresh human breast tissue.

机构信息

Rice University, Department of Bioengineering, 6500 Main Street, BRC 502, Houston, Texas 77030.

出版信息

J Biomed Opt. 2013 Oct;18(10):106016. doi: 10.1117/1.JBO.18.10.106016.

Abstract

Breast cancer management could be improved by developing real-time imaging tools to assess tissue architecture without extensive processing. We sought to determine whether confocal fluorescence microscopy (CFM) provides sufficient information to identify neoplasia in breast tissue. Breast tissue specimens were imaged following proflavine application. Regions of interest (ROIs) were selected in histologic slides and in the corresponding region on confocal images, and then divided into sets for training and validation. Readers reviewed images in the training set and evaluated images in the validation set for the presence of neoplasia. Accuracy was assessed using histologic diagnosis as the gold standard. Seventy tissue specimens from 31 patients were imaged; 235 ROIs were identified and diagnosed as neoplastic or non-neoplastic. A training set was assembled using 23 matched ROIs; 49 matched ROIs were assembled into a validation set. Neoplasia was identified in histologic images: 93% sensitivity, 97% specificity [area under the curve (AUC=0.987)] and in confocal images: 93% sensitivity 93% specificity (AUC=0.957). CFM produced images of architectural features in breast tissue comparable with conventional histology, while requiring little processing. Potential applications include assessment of excised tissue margins and evaluation of tissue adequacy for bio-banking and genomic studies.

摘要

通过开发实时成像工具来评估组织架构,而无需进行广泛的处理,可以改善乳腺癌的管理。我们旨在确定共聚焦荧光显微镜(CFM)是否提供了足够的信息来识别乳腺组织中的肿瘤。在应用普魯卡因后对乳腺组织标本进行成像。在组织学幻灯片和共聚焦图像的相应区域中选择感兴趣区域(ROI),然后将其分为训练集和验证集。读者在训练集中查看图像,并在验证集中评估图像是否存在肿瘤。使用组织学诊断作为金标准来评估准确性。对 31 名患者的 70 个组织标本进行了成像;确定了 235 个 ROI,并将其诊断为肿瘤或非肿瘤。使用 23 个匹配的 ROI 构建了一个训练集;将 49 个匹配的 ROI 构建成验证集。在组织学图像中识别出肿瘤:敏感性为 93%,特异性为 97%[曲线下面积(AUC=0.987)],在共聚焦图像中为 93%敏感性 93%特异性(AUC=0.957)。CFM 生成的乳腺组织结构特征图像与传统组织学相当,而所需的处理很少。潜在的应用包括评估切除组织边缘以及评估生物库和基因组研究的组织充足性。

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