Literature DB >> 23442199

Indocyanine green cannot predict malignancy in partial nephrectomy: histopathologic correlation with fluorescence pattern in 100 patients.

Ted B Manny1, L Spencer Krane, Ashok K Hemal.   

Abstract

INTRODUCTION: Indocyanine green (ICG) is emerging as a potential adjunct to robot-assisted partial nephrectomy by its ability to aid in the real-time identification of renal vasculature, renal masses, and the renal mass-parenchymal margin. The fluorescence patterns of renal masses have not been adequately described according to histology, and it remains unknown if fluorescence pattern can reliably predict histology or malignancy. We therefore describe the ICG fluorescence pattern of our first 100 robot-assisted partial nephrectomies (RAPN) and correlate with histology.
MATERIALS AND METHODS: We reviewed our prospective RAPN database and categorized fluorescence pattern as isofluorescent (same as surrounding parenchyma), hypofluorescent (less than surrounding parenchyma, but with uptake), or afluorescent (no visible uptake of dye). Descriptive statistics were applied.
RESULTS: All 14 cystic lesions were afluorescent and comprised 9 malignant and 5 benign masses. Eighty-six lesions were solid, of which 3 were isofluorescent including two clear-cell and one translocation tumor. The remaining 83 solid lesions were hypofluorescent and included 65 malignant and 18 benign lesions. Clear-cell was the most common histology of which 96% were hypofluorescent and 4% isofluorescent. In determining malignant vs benign lesions, hypofluorescence had a positive predictive value of 87%, negative predictive value of 52%, sensitivity of 84%, and specificity of 57%.
CONCLUSIONS: A three-grade classification of renal mass ICG fluorescence pattern is correlated with some histologic findings but unable to reliably predict malignant vs benign lesions.

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Year:  2013        PMID: 23442199      PMCID: PMC3704115          DOI: 10.1089/end.2012.0756

Source DB:  PubMed          Journal:  J Endourol        ISSN: 0892-7790            Impact factor:   2.942


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