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• W2912136660 abstract "Confocal laser endomicroscopy (CLE) is a fluorescence-based fiber-optic imaging technique with the potential for intraoperative grading of upper tract urothelial carcinoma (UTUC). This study aims to (1) investigate the prevalence of the previously proposed CLE criteria for bladder cancer in papillary UTUC, (2) estimate the diagnostic value of CLE for UTUC grading and (3) propose a scoring system for a more quantifiable approach of CLE-based grading of UTUC. Ureteroscopic CLE was performed in patients with UTUC. Following CLE imaging, co-localized biopsies were taken for histopathologic comparison. Postoperatively, two blinded raters assessed the CLE images. Fifty-three papillary UTUCs (34 low grade and 19 high grade) were imaged with CLE in 36 patients. All the previously described CLE criteria were identifiable in varying proportions. After excluding 10 non-diagnostic recordings (5 low grade and 5 high grade) due to insufficient image quality, the histopathologic grade was correctly identified with CLE in 26 low-grade UTUCs (90%) and in 12 high-grade UTUCs (86%). The most prevalent CLE criteria with the highest diagnostic potential were cellular organization, morphology and cohesiveness of cells. A scoring system was proposed with these criteria, which yielded similar diagnostic accuracies. Based on the previously proposed criteria, CLE enables accurate grading of papillary UTUC at a non-diagnostic rate of 19%. The most prevalent CLE criteria with the highest diagnostic potential for grading of papillary UTUC are cellular organization, morphology and cohesiveness of cells. The proposed scoring system may simplify the assessment of CLE images for UTUC grading but external validation is required." @default.
• W2912136660 created "2019-02-21" @default.
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• W2912136660 date "2019-01-25" @default.
• W2912136660 modified "2023-10-10" @default.
• W2912136660 title "Confocal laser endomicroscopy for upper tract urothelial carcinoma: validation of the proposed criteria and proposal of a scoring system for real-time tumor grading" @default.
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• W2912136660 doi "https://doi.org/10.1007/s00345-019-02646-5" @default.
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