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      Utility of patient-specific silicone renal models for planning and rehearsal of complex tumour resections prior to robot-assisted laparoscopic partial nephrectomy

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          Abstract

          Objective

          To describe our experience using patient-specific tissue-like kidney models created with advanced three-dimensional (3D)-printing technology for preoperative planning and surgical rehearsal prior to robot-assisted laparoscopic partial nephrectomy (RALPN).

          Patients and Methods

          A feasibility study of 10 patients with solid renal masses who underwent RALPN after preoperative rehearsal using 3D-print kidney models. A single surgeon performed all surgical rehearsals and procedures. Using standard preoperative imaging and 3D reconstruction, we generated pre-surgical models using a silicone-based material. All surgical rehearsals were performed using the da Vinci ® robotic system (Intuitive Surgical Inc., Sunnyvale, CA, USA) before the actual procedure. To determine construct validity, we compared resection times between the model and actual tumour in a patient-specific manner. Using 3D laser scanning in the operating room, we quantified and compared the shape and tumour volume resected for each model and patient tumour.

          Results

          We generated patient-specific models for 10 patients with complex tumour anatomy. R.E.N.A.L. nephrometry scores were between 7 and 11, with a mean maximal tumour diameter of 40.6 mm. The mean resection times between model and patient (6:58 vs 8:22 min, P = 0.162) and tumour volumes between the computer model, excised model, and excised tumour (38.88 vs 38.50 vs 41.79 mm 3, P = 0.98) were not significantly different.

          Conclusions

          We have developed a patient-specific pre-surgical simulation protocol for RALPN. We demonstrated construct validity and provided accurate representation of enucleation time and resected tissue volume. This simulation platform can assist in surgical decision-making, provide preoperative rehearsals, and improve surgical training.

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          Author and article information

          Journal
          100886721
          21363
          BJU Int
          BJU Int.
          BJU international
          1464-4096
          1464-410X
          10 September 2018
          10 December 2016
          April 2017
          24 September 2018
          : 119
          : 4
          : 598-604
          Affiliations
          [1 ]Scott Department of Urology, Baylor College of Medicine, Houston, TX, USA
          [2 ]Department of Urology, Jena University Hospital, Friedrich-Schiller University, Jena, Germany
          [3 ]Translational Biology and Molecular Medicine, Baylor College of Medicine, Houston, TX, USA
          [4 ]Center for Reproductive Medicine, Baylor College of Medicine, Houston, TX, USA
          [5 ]Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
          [6 ]Lazarus 3D LLC, Houston, TX, USA
          [7 ]Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
          Author notes
          Correspondence: Richard E. Link, Carlton-Smith Endowed Chair in Urologic Education, Associate Professor of Urology, Director, Division of Endourology and Minimally Invasive Surgery, Director, Comprehensive Kidney Program, Scott Department of Urology, 7200 Cambridge, 10th Floor, Suite B, Houston, TX 77030, USA. link@ 123456bcm.edu
          Article
          PMC6152819 PMC6152819 6152819 nihpa913881
          10.1111/bju.13712
          6152819
          27862866
          a571effb-7034-4159-b332-dcc26100fbb5
          History
          Categories
          Article

          #KidneyCancer,#KCSM,robotic partial nephrectomy,RALPN,surgical simulation,3D printing

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