Phung Michael C, Rouse Andrew R, Pangilinan Jayce, Bell Robert C, Bracamonte Erika R, Mashi Sharfuddeen, Gmitro Arthur F, Lee Benjamin R
Department of Urology, University of Arizona College of Medicine, Arizona, USA.
Department of Medical Imaging, University of Arizona College of Medicine, Arizona, USA.
Asian J Urol. 2020 Oct;7(4):363-368. doi: 10.1016/j.ajur.2019.12.008. Epub 2019 Dec 24.
Novel optical imaging modalities are under development with the goal of obtaining an "optical biopsy" to efficiently provide pathologic details. One such modality is confocal microscopy which allows visualization of cells within a layer of tissue and imaging of cellular-level structures. The goal of this study is to validate the ability of confocal microscopy to quickly and accurately differentiate between normal renal tissue and cancer.
Specimens were obtained from patients who underwent robotic partial nephrectomy for renal mass. Samples of suspected normal and tumor tissue were extracted from the excised portion of the kidney and stained with acridine orange. The stained samples were imaged on a Nikon E600 C1 Confocal Microscope. The samples were then submitted for hematoxylin and eosin processing and read by an expert pathologist to provide a gold-standard diagnosis that can later be compared to the confocal images.
This study included 11 patients, 17 tissue samples, and 118 confocal images. Of the 17 tissue samples, 10 had a gold-standard diagnosis of cancer and seven were benign. Of 118 confocal images, 66 had a gold-standard diagnosis of cancer and 52 were benign. Six confocal images were used as a training set to train eight observers. The observers were asked to rate the test images on a six point scale and the results were analyzed using a web based receiver operating characteristic curve calculator. The average accuracy, sensitivity, specificity, and area under the empirical receiver operating characteristic curve for this study were 91%, 98%, 81%, and 0.94 respectively.
This preliminary study suggest that confocal microscopy can be used to distinguish cancer from normal tissue with high sensitivity and specificity. The observers in this study were trained quickly and on only six images. We expect even higher performance as observers become more familiar with the confocal images.
新型光学成像模式正在研发中，目标是获得“光学活检”以有效提供病理细节。共聚焦显微镜就是这样一种模式，它能够可视化组织层内的细胞并对细胞水平的结构进行成像。本研究的目的是验证共聚焦显微镜快速、准确区分正常肾组织和癌组织的能力。
从因肾肿物接受机器人辅助部分肾切除术的患者身上获取标本。从切除的肾脏部分提取疑似正常组织和肿瘤组织样本，并用吖啶橙染色。将染色后的样本在尼康E600 C1共聚焦显微镜下成像。然后将样本送去进行苏木精和伊红染色处理，并由专业病理学家进行解读，以提供金标准诊断，随后可与共聚焦图像进行比较。
本研究纳入了11名患者、17个组织样本和118张共聚焦图像。在17个组织样本中，10个的金标准诊断为癌，7个为良性。在118张共聚焦图像中，66个的金标准诊断为癌，52个为良性。6张共聚焦图像用作训练集来培训8名观察者。要求观察者对测试图像进行六点评分，并使用基于网络的受试者工作特征曲线计算器对结果进行分析。本研究的平均准确率、敏感性、特异性和经验受试者工作特征曲线下面积分别为91%、98%、81%和0.94。
这项初步研究表明，共聚焦显微镜可用于以高敏感性和特异性区分癌组织与正常组织。本研究中的观察者接受培训的速度很快，且仅使用了6张图像。我们预计随着观察者对共聚焦图像更加熟悉，性能会更高。
