Roughness of the renal tumor surface could predict the surgical difficulty of robot‐assisted partial nephrectomy

Introduction Preoperative prediction of surgical difficulty of partial nephrectomy (PN) is essential to minimize the perioperative complications and to achieve a good surgical outcome. Recently, various scoring systems have been used to evaluate the difficulty of PN including R.E.N.A.L (Radius, Exop...

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Veröffentlicht in:Asian journal of endoscopic surgery 2022-07, Vol.15 (3), p.591-598
Hauptverfasser: Tatenuma, Tomoyuki, Ito, Hiroki, Muraoka, Kentaro, Ito, Yusuke, Hasumi, Hisashi, Hayashi, Narihiko, Kondo, Keiichi, Nakaigawa, Noboru, Makiyama, Kazuhide
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Sprache:eng
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Zusammenfassung:Introduction Preoperative prediction of surgical difficulty of partial nephrectomy (PN) is essential to minimize the perioperative complications and to achieve a good surgical outcome. Recently, various scoring systems have been used to evaluate the difficulty of PN including R.E.N.A.L (Radius, Exophytic/Endophytic, Nearness, Anterior/Posterior, Location) nephrometry score. There were no scoring systems evaluating the roughness of the renal tumor surface and we hypothesized that the roughness of the renal tumor surface might affect the surgical difficulty of robot‐assisted partial nephrectomy (RAPN). This study aimed to evaluate the impact of roughness of the renal tumor surface on the surgical outcome of RAPN. Methods Overall, 161 patients underwent RAPN performed by the same surgeon between May 2016 and April 2019. We divided those tumors into two groups, like “roughness positive (tumor with roughness of tumor surface)” and “roughness negative (tumor without roughness of tumor surface)” according to the roughness of the endophytic region on preoperative computed tomography images. Clinical and pathological outcomes were compared between the two groups. Results Eighty‐five and 78 tumors were identified roughness negative and positive, respectively. Cases with roughness positive showed a significantly longer operative time, console time, and ischemia time and had greater blood loss than those with roughness negative. Significant and independent predictors of ischemia time and estimated glomerular filtration rate (eGFR) decrease were roughness of tumor surface, tumor size (not for eGFR decrease), and N score of the R.E.N.A.L nephrometry score. Conclusion Roughness of renal tumor surface was significantly and positively associated with ischemia time and the eGFR decrease rate.
ISSN:1758-5902
1758-5910
DOI:10.1111/ases.13058