Literature DB >> 22215306

Indocyanine green (ICG)-based fluorescence navigation system for discrimination of kidney cancer from normal parenchyma: application during partial nephrectomy.

Yozo Mitsui1, Hiroaki Shiina, Naoko Arichi, Takeo Hiraoka, Shogo Inoue, Masahiro Sumura, Satoshi Honda, Hiroaki Yasumoto, Mikio Igawa.   

Abstract

PURPOSE: To determine the definite border between normal and tumor kidney tissues during partial nephrectomy (PN) procedures using intraoperative indocyanine green (ICG)-based fluorescence imaging.
METHODS: Sixteen potential candidates for PN with organ-confined, small renal masses treated between July 2008 and June 2011 at Shimane University Hospital were enrolled. An ICG-based fluorescence navigation (FN) system was used to evaluate the border between the tumor and normal kidney parenchyma (step 1), the cavity following tumor excision (step 2), and the negative surgical margin of resected tissues (step 3). The R.E.N.A.L nephrometry score (RNS) was applied to evaluate the correlation between tumor anatomy and ICG-based fluorescence imaging.
RESULTS: In step 1, in vivo probing revealed 14 tumors with a mean RNS of 7 points that showed quite low ICG fluorescence signals in the tumor mass as compared with normal kidney parenchyma. In step 2, in vivo probing around the bed revealed highly fluorescent signals with no remnant tumor residing in 10 cases with a mean RNS of 6 points. In step 3, ex vivo probing revealed cancer tissues involving normal parenchyma that were completely excised with minimum amounts of normal parenchyma in all 16 resected specimens.
CONCLUSIONS: ICG-based FN system was very helpful for confirming negative margin status in even the most complex cases. Further evaluations may open the door for widespread use of this ICG-based FN system as a feasible and attractive alternative during a PN procedure.

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Year:  2012        PMID: 22215306     DOI: 10.1007/s11255-011-0120-x

Source DB:  PubMed          Journal:  Int Urol Nephrol        ISSN: 0301-1623            Impact factor:   2.370


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