Nicole Wake1, Marc A Bjurlin2, Pooya Rostami2, Hersh Chandarana3, William C Huang2. 1. Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI(2)R), New York, NY; Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY. Electronic address: nicole.wake@nyumc.org. 2. Division of Urologic Oncology, Department of Urology, New York University Langone Medical Center, New York, NY. 3. Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI(2)R), New York, NY; Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY.
Abstract
OBJECTIVE: To describe novel 3-dimensional (3D) printing and augmented reality (AR) methods of image data visualization to facilitate anatomic understanding and to assist with surgical planning and decision-making during robotic partial nephrectomy. MATERIALS AND METHODS: We created a video of the workflow for creating 3D printed and AR kidney models along with their application to robotic partial nephrectomy. Key steps in their development are (1) radiology examination (magnetic resonance imaging and computed tomography), (2) image segmentation, (3) preparing for 3D printing or AR, and (4) printing the model or deploying the model to the AR device. RESULTS: We demonstrate the workflow and utility of 3D printing and AR kidney models applied to a case of a 70-year-old woman with a 3.4 cm renal mass on her left pelvic kidney. A 3D printed kidney model was created using multicolor PolyJet technology (Stratasys J750), allowing a transparent kidney with coloring of the renal tumor, artery, vein, and ureter. An AR kidney model was created using Unity 3D software and deployed to a Microsoft HoloLens. The 3D printed and AR models were used preoperatively and intraoperatively to assist in robotic partial nephrectomy. To date, we have created 15 3D printed and AR kidney models to use for robotic partial nephrectomy planning and intraoperative guidance. The application of 3D printed and AR models is safe and feasible and can influence surgical decisions. CONCLUSION: Our video highlights the workflow and novel application of 3D printed and AR kidney models to provide preoperative guidance for robotic partial nephrectomy. The insights gained from advanced visualization can influence surgical planning decisions.
OBJECTIVE: To describe novel 3-dimensional (3D) printing and augmented reality (AR) methods of image data visualization to facilitate anatomic understanding and to assist with surgical planning and decision-making during robotic partial nephrectomy. MATERIALS AND METHODS: We created a video of the workflow for creating 3D printed and AR kidney models along with their application to robotic partial nephrectomy. Key steps in their development are (1) radiology examination (magnetic resonance imaging and computed tomography), (2) image segmentation, (3) preparing for 3D printing or AR, and (4) printing the model or deploying the model to the AR device. RESULTS: We demonstrate the workflow and utility of 3D printing and AR kidney models applied to a case of a 70-year-old woman with a 3.4 cm renal mass on her left pelvic kidney. A 3D printed kidney model was created using multicolor PolyJet technology (Stratasys J750), allowing a transparent kidney with coloring of the renal tumor, artery, vein, and ureter. An AR kidney model was created using Unity 3D software and deployed to a Microsoft HoloLens. The 3D printed and AR models were used preoperatively and intraoperatively to assist in robotic partial nephrectomy. To date, we have created 15 3D printed and AR kidney models to use for robotic partial nephrectomy planning and intraoperative guidance. The application of 3D printed and AR models is safe and feasible and can influence surgical decisions. CONCLUSION: Our video highlights the workflow and novel application of 3D printed and AR kidney models to provide preoperative guidance for robotic partial nephrectomy. The insights gained from advanced visualization can influence surgical planning decisions.
Authors: Nicole Wake; Amy E Alexander; Andy M Christensen; Peter C Liacouras; Maureen Schickel; Todd Pietila; Jane Matsumoto Journal: 3D Print Med Date: 2019-12-30
Authors: Jan Witowski; Szymon Darocha; Łukasz Kownacki; Arkadiusz Pietrasik; Radosław Pietura; Marta Banaszkiewicz; Jakub Kamiński; Andrzej Biederman; Adam Torbicki; Marcin Kurzyna Journal: Quant Imaging Med Surg Date: 2019-01
Authors: Lianne M Wellens; Jene Meulstee; Cornelis P van de Ven; C E J Terwisscha van Scheltinga; Annemieke S Littooij; Marry M van den Heuvel-Eibrink; Marta Fiocco; Anne C Rios; Thomas Maal; Marc H W A Wijnen Journal: JAMA Netw Open Date: 2019-04-05
Authors: Joseph D Shirk; David D Thiel; Eric M Wallen; Jennifer M Linehan; Wesley M White; Ketan K Badani; James R Porter Journal: JAMA Netw Open Date: 2019-09-04