Investigation of confocal microscopy for differentiation of renal cell carcinoma versus benign tissue. Can an optical biopsy be performed?
Michael C. Phung, Andrew R. Rouse, Jayce Pangilinan, Robert Bell, Erika Bracamonte, Sharfuddeen Abbas Mashi, Arthur F. Gmitro, Benjamin R. Lee
- 发表年份
- 2019
- 引用次数
- 4
摘要
OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
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