Poster, Podium & Video Sessions
Presentation Authors: Shuji Isotani*, Tokyo, Japan, Michael Stifelman, Hackensack, NJ, Shigeo Horie, Tokyo, Japan
Introduction: Current paradigms in partial nephrectomy (PN) for localized renal tumor support a minimally-margin size with limited ischemia where possible, even in the most complex of cases. However, there is as yet no standardized assessment or planning procedure for Robotic partial nephrectomy (RPN).
Methods: Here we present our technique for Robotic Partial Nephrectomy Precision Surgery. This technique combines patient-specific imaging assessment by Virtual PN and surgical navigation intra-operatively with cognitive fusion.
Results: Case1: The 49-year-old woman, with right non-functional kidney was referred by the 5.2cm left renal tumor located in the renal hilum and tumor thrombus in the renal vein in a functional solitary kidney. The tumor biopsy revealed the clear cell carcinoma. After administration of molecular targeted medicine for 6 months with tumor shrinkage to 4.7cm, R.E.N.A.L. nephrometry score 10a, RPN was conducted. Preoperative Virtual PN revealed that the selecting clamping was not appropriate for this case, and provided the case specific margin size (1-2mm) and anatomical visualization of the intrarenal structures, tumor, renal arteries, veins, tumor thrombus, and renal pelvis, and their location in color-coded manner. RPN was performed with intra-operational image guidance in 19 min warm ischemia time (WIT), 50ml estimated blood loss (EBL), and negative surgical margin. Post-operative creatinine level was same as pre-operative level 0.89, and the dialysis was not required. Case 2: 56-year-old woman with totally endophytic renal tumor sized in 2.5cm and the nephrometry score was 8a was underwent RPN. Prior the operation, the 3rd arterial branch was identified for the point of selective clamping by the Virtual PN. RPN was performed with intra-operational image guidance of the targeted artery, with WIT being 18 min, with EBL being 100ml and with negative surgical margin. Pre-operative creatinine was 0.59 and post-operative creatinine was 0.58. There were no complications in either case.
Conclusions: Robotic Partial Nephrectomy combined with 3D navigation, Virtual PN, and intra-op surgical navigation may allow "Precision Surgery" to preserve renal function by minimizing the excision margin and limiting ischemic area.
Source Of Funding: None
Juntendo University, Graduate School of Medicine
Shuji Isotani, M.D., Ph.D. Associate Professor Department of Urology, Juntendo University, Graduate School of Medicine
Dr.Shuji Isotani is the Associate Professor of Division of Urology in Juntendo University, Tokyo, Japan. Dr. Shuji obtained his M.D. degree from Toyama University the in 1998 and Ph.D degree from Kobe University in 2002. His interest in urology includes the technological development of urology and minimum invasive surgery including endurology. In 2015, Dr. Shuji developed a novel computational imaging method, to simulate the partial nephrectomy both in functionally and visually, and named it as “Virtual Partial Nephrectomy (PN)”. Currently, with using his method as the surgical navigation, precise planned robotic PN have conducted.
Friday, May 12
3:30 PM – 3:30 PM